Reviewer #4 (Public Review):

Summary:

Although previous research suggested that noradrenergic glutamatergic signaling could influence respiratory control, the work performed by Chang and colleagues reveals that excitatory (specifically Vglut2) neurons is dynamically and widely expressed throughout the central noradrenergic system, but it is not significantly crucial to change baseline breathing as well the hypercapnia and hypoxia ventilatory responses. The central point that will make a significant change in the field is how NA-glutamate transmission may influence breathing control and the dysfunction of NA neurons in respiratory disorders.

Strengths:

There are several strengths such as the comprehensive analysis of Vglut1, Vglut2, and Vglut3 expression in the central noradrenergic system and the combined measurements of breathing parameters in conscious unrestrained mice.

Other considerations :

These results strongly suggest that glutamate may not be necessary for modulating breathing under normal conditions or even when faced with high levels of carbon dioxide (hypercapnia) or low oxygen levels (hypoxia). This finding is unexpected, considering many studies have underscored glutamate's vital role in respiratory regulation, more so than catecholamines. This leads us to question the significance of catecholamines in controlling respiration. Moreover, if glutamate is not essential for this function, we need to explore its role in other physiological processes such as sympathetic nerve activity (SNA), thermoregulation, and sensory physiology.

Reviewer #3 (Public Review):

Summary:

ISR contributes to the pathogenesis of multiple neurodegenerative diseases, such as ALS, FTD, VWMD, etc. Targeting ISR is a promising avenue for therapeutic intervention. However, all previously identified ways to target ISR have problems. PERK inhibitors suppress ISR by inhibiting eIF2alpha phosphorylation and cause pancreatic toxicity in mice. In order to bypass eIF2alpha, previous studies have identified ISR suppressors that target eIF2B, such as ISRIB and 2BAct. These molecules suppress neurodegeneration but do not cause detrimental effects in mouse models. However, ISRIB is water-insoluble, and 2BAct causes cardiovascular complications in dogs, preventing their use in clinics. Here, the authors showed that DNL343, a new ISR inhibitor targeting eIF2B, suppresses features that can be related to neurodegeneration in mouse models. Combined with their previous results of a clinical phase I trial showing the safety of DNL343, these findings suggest the promise of DNL343 as a potential drug for neurodegenerative diseases in which ISR contributes to pathogenesis.

Strengths:

The finding is important and has disease implications.

Weakness:

The authors did not provide evidence that DNL343 suppresses the demise of nervous systems in their VWMD model.

Reviewer #3 (Public Review):

Gil et al provide novel evidence that the chromatin regulator KDM6B is important for establishing and maintaining the neural stem cell (NSC) pool within the dentate gyrus in development and adulthood. They show compelling evidence that loss of KDM6B promotes precocious neuronal differentiation, resulting in a failure to establish and maintain the dentate gyrus NSC pool. The strongest evidence they provide is their immunohistochemistry analysis, in which they observed precocious expression of later differentiation markers from cells marked by BrdU. However, given that KDM6B is ubiquitously expressed, it is difficult to ascertain if their dysregulation is due to a direct loss of KDM6B within NSCs or caused by dysregulation of other glial cells impacted by KDM6B loss through the hGFAP-Cre. Characterization of mature glia would strengthen the work.

They additionally provide evidence of precocious differentiation through scRNA-seq by highlighting key genes that are dysregulated with KDM6B loss. It appears the clustering analysis into cell types was done with WT and KDM6b-depleted cells together. The evidence for precocious differentiation would be greatly strengthened if they instead determined cell-type specific clusters using their WT samples and then observed if fewer cells are characterized as NSCs and more cells align to later developmental stage clusters with KDM6B depletion.

Gil et al propose that KDM6B loss leads to hippocampus-specific impairments in learning and memory. While KDM6B-depleted mice do show a significant decrease in freezing time in contextual fear conditioning, Figure 2 Supplement 1 shows KDM6B-depleted mice are hyperactive compared to WT in the open field test. Thus, the reduction in freezing could be due to hyperactivity. Plotting freezing time in short bins throughout the duration of the test can help clarify this. It would be additionally helpful to plot the training baseline and the test on the same graph and compare their freezing from baseline to clarify if they completely fail to freeze or show a reduction in freezing compared to the wild-type.

Reviewer #3 (Public Review):

Summary:

The goal of this study was to carry out an in-depth granular and unbiased phenotyping of peripheral blood circulating Tfh specific to two malaria vaccine candidates, PfSEA-1A and PfGARP, and correlate these with age (children vs adults) and protection from malaria (antibody titers against Plasmodium antigens.). The authors further attempted to identify any specific differences in the Tfh responses to these two distinct malaria antigens.

Strengths:

The authors had access to peripheral blood samples from children and adults living in a malaria-endemic region of Kenya. The authors studied these samples using in vitro restimulation in the presence of specific malaria antigens. The authors generated a very rich data set from these valuable samples using cutting-edge spectral flow cytometry and a 21-plex panel that included a variety of surface markers, cytokines, and transcription factors.

Weaknesses:

- Quantifying antigen-specific T cells by flow cytometry requires the use of either 1- tetramers or 2- in vitro restimulation with specific antigens followed by identification of TCR-activated cells based on de-novo expression of activation markers (e.g. intracellular cytokine staining and/or surface marker staining). Although authors use an in vitro restimulation strategy, they do not focus their study on cells de-novo expressing activation markers as a result of restimulation; therefore, their study is not really on antigen-specific cTfh. Moreover, the authors report no changes in the expression of activation markers commonly used to identify antigen-specific T cells upon in vitro restimulation (including IFNg and CD40L); therefore, it is not clear if their in vitro restimulation with malaria antigens actually worked.

- CXCR5+CD4+ memory T cells have been shown to present multi-potency and plasticity, capable of differentiating to non-Tfh subsets upon re-challenge. Although authors included in their flow panel a good number of markers commonly used in combination to identify Tfh (CXCR5, PD-1, ICOS, Bcl-6, IL-21), they only used one single marker (CXCR5) as their basis to define Tfh, thus providing a weak definition for Tfh cells and follow up downstream analysis.

- Previous works have used FACS-sorting and in vitro assays for cytokine production and B cell help to study the functional capacity of different cTfh subsets in blood from Plasmodium-infected individuals. In this study, authors do not carry out any such assays to isolate and evaluate the functional capacity of the different Tfh subsets identified. Thus, all the suggestions for the role that these different cTfh subsets may have in vivo in the context of malaria remain highly hypothetical.

- The authors have not included malaria unexposed control groups in their study, and experimental groups are relatively small (n=13).

Reviewer #3 (Public Review):

Summary:

In the submitted manuscript by Go et al, the authors evaluated the tumor microenvironment in pancreatic ductal adenocarcinoma (PDAC) and made a number of interesting observations, including the following: 1) CCL5 expression within the tumor microenvironment negatively correlated with clinical outcomes in human patients with PDAC; 2) there were both positive and negative correlations between CCL5 expression and the expression of specific genes (e.g. those encoding CD56 and CD16, respectively) included among gene signature lists for Treg, MDSC, TAM, and NK cells; 3) CCR5 inhibition with the inhibitor, maraviroc, reduced Treg infiltration but not that of other immune cell types in an orthotopic murine model of PDAC; 4) CCR5 inhibition augmented anti-PD1 immunotherapy when combined with ionizing radiation (IR) therapy in the murine model; 5) the above therapy resulted in increased infiltration of CD8+ cytotoxic T cells as well as of a subset of NKG2D-negative, tissue-residency (tr) marker expressing NK cells (deemed Cluster 1 NK in their data sets) that inversely correlated with the number of E-cadherin+ cells (i.e. tumor cells) and showed predicted interactions with cDC1 dendritic cells (including XCL1/XCL2 expressed by the NK and XCR1 expressed by the cDC1); 6) the authors identified a number of putative signals stemming from the trNK (e.g. IL-16, TNFSF14, FASLG, CSF, MIF) as well as incoming from cDC1s to NK (e.g. BAG6-NKp30); 7) these trNK cells positively correlated with good outcomes and with CD8+ T cell infiltrations in human PDAC as well as in many other solid tumor types; and 8) importantly, the benefit of IR therapy was specific to the subset of PDAC patients (represented in the TCGA dataset) that were predicted to have low amounts of trNK cells. The authors used murine experimental models, multi-plexed imaging analyses, and a number of publicly available sequencing data sets from human tumor samples to perform their investigations. Based on their findings, the authors proposed that combining IR with CCR5 inhibition and anti-PD1 immunotherapy is a promising strategy to treat solid cancers.

Strengths:

Overall, the collective analyses and conclusions appear to be novel and could be of high and rapid impact on the field, particularly in terms of directing clinical trials to incorporate IR with CCR5 inhibition and immunotherapy. The manuscript is well written; the figures are for the most part clear; and the Discussion is very thoughtful.

Weaknesses:

In the revised manuscript, the authors addressed my original concerns. I have no new major concerns with the study. One of the limitations is that the authors did not perform functional in vivo or ex vivo assays to address some of the major hypotheses that arose from the descriptive, correlative data; but overall, this does not detract from the enthusiasm for the work or the potential significance and impact of the study.

Reviewer #3 (Public Review):

Summary:

Das et al. discovered a maternal role for Caspar (Casp), the Drosophila orthologue of human Fas-associated factor-1 (FAF1), in embryonic development and germ cell formation. They find that Casp interacts with Transitional endoplasmic reticulum 94 (TER94). Loss of Casp or TER94 leads to partial embryonic lethality, correlated with aberrant centrosome behavior and cytoskeletal abnormalities. This suggests that Casp, along with TER94, promotes embryonic development through a still unidentified mechanism. They also find that Casp regulates germ cell number by controlling a key determinant of germ cell formation, Oskar, through its negative regulator, Smaug.

Strengths:

Overall, the experiments are well-conducted, and the conclusions of this paper are mostly well-supported by data.

Weaknesses:

Some additional controls could be included, and the language could be clarified for accuracy.

Reviewer #3 (Public Review):

Drougard et al. explore microglial detection of a switch to high-fat diet and a subsequent metabolic response that benefits memory. The findings are both surprising and novel in the context of acute high-fat intake, with convincing evidence of increased CSF palmitate after 3 days of HFD. While the authors demonstrate compelling signs of microglial activation in multiple brain regions and unique metabolite release in tracing studies, they should address the following areas.

Major Points:

(1) It appears that the authors perform key metabolic assays in vitro/ex vivo using primary microglia from either neonatal or adult mice, which should be more clearly delineated especially for the 13C-palmitate tracing. In the case of experiments using primary microglia derived from mixed glial cultures stimulated with M-CSF, this system relies on neonatal mice. This is understandable given the greater potential yield from neonatal mice, but the metabolic state and energetic demands of neonatal and adult microglia differ as their functional roles change across the lifespan. The authors should either show that the metabolic pathways they implicate in neonatal microglia are also representative of adult microglia or perform additional experiments using microglia pooled from adult mice, especially because they link metabolites derived from neonatal microglia (presumably not under the effects of acute HFD) to improved performance in behavioral assays that utilize adult mice.

(2) The authors demonstrate that 3 days of HFD increases circulating palmitate by CSF metabolomics and that microglia can readily metabolize palmitate, but the causal link between palmitate metabolism specifically by microglia and improved performance in behavioral paradigms remains unclear. A previous body of research, alluded to by the authors, suggests that astrocyte shuttling of lactate to neurons improves long-term and spatial memory. The authors should account for palmitate that also could be derived from astrocyte secretion into CSF, and the relative contribution compared to microglia-derived palmitate. Specifically, although microglia can metabolize the palmitate in circulation, there is no direct evidence that the palmitate from the HFD is directly shuttled to microglia and not, for example, to astrocytes (which also express CX3CR1). Thus, the Barnes Maze results could be attributed to multiple cell types. Furthermore, the evidence provided in Figure 5J is insufficient to claim a microglia-dependent mechanism without showing data from mice on HFD with and without microglia depletion (analogous to the third and fourth bars in panel K).

(3) Given the emphasis on improved cognitive function, there is minimal discussion of the actual behavioral outcomes in both the results and discussion sections. The data that HFD-treated animals outperform controls should be presented in more detail both in the figure and in the text. For example, data from all days/trials of the Barnes Maze should be shown, including the day(s) HFD mice outperform controls. Furthermore, the authors should either cite additional literature or provide experimental evidence supporting the notion that microglia release of TCA-associated substrates into the extracellular milieu after HFD specifically benefits neuronal function cellularly or regionally in the brain, which could translate to improved performance in classical behavioral paradigms. The single reference included is a bit obscure, given the study found that increased lactate enhances fear memory which is a neural circuit not studied in the current manuscript. Are there no additional studies on more relevant metabolites (e.g., itaconate, succinate)?

Reviewer #3 (Public Review):

Summary:

In this manuscript, Nagarajan et al. study the impact of early damage to the anterior cingulate cortex (ACC) on the vocal development of marmoset monkeys. AAC lesions were performed on neonatal marmosets and their vocal patterns and the spectrotemporal features of their calls were analyzed compared to control groups during the first six weeks of life. While the vocal repertoire was not significantly affected by ACC lesions, the authors described notable differences in the social contact call, the phee call. Marmosets with ACC damage made fewer social contact calls, and when they did, these calls were shorter, louder, and monotonic. Additionally, the study revealed that ACC damage in infancy led to permanent alterations in downstream brain areas involved in social vocalizations, such as the amygdala and periaqueductal gray.

Strengths:

This study suggests that the ACC plays a crucial role in the normal development of social vocal behavior in infant marmosets. Studying vocal behavior in marmosets can provide insights into the neural mechanisms underlying human speech and communication disorders due to their similarity in brain structure and social behavior.

The methods are robust and reliable with precise localization of the lesions with neuroimaging and histological examination.

Weaknesses:

It is striking to find that the vocal repertoire of infant marmosets was not significantly affected by ACC lesions. During development, the neural circuits are still maturing and the role of different brain regions may evolve over time. While the ACC likely contributes to vocalizations across the lifespan, its relative importance may vary depending on the developmental stage. In neonates, vocalizations may be more reflexive or driven by physiological needs. At this stage, the ACC may play a role in basic socioemotional regulation but may not be as critical for vocal production. Since the animals lived for two years, further analysis might be helpful to elucidate the precise role of ACC in the vocal behavior of marmosets.

- Figure 3D. According to the Introduction "...infant ACC lesions abolish the characteristic cries that infants normally issue when separated from its mother". Are the present results in marmosets showing the opposite effect? Please discuss.

- Figure 3E and Discussion. Phees are mature contact calls and cries immature contact calls (Zhang et al, 2019, Nat Commun). Therefore, I would rather say that the proportion of immature (cries) contact calls increases vs the mature (phee, trill, twitters) contact calls in the ACC group. Cries are also "isolated-induced contact calls" to attract the attention of the caregivers.

- Figure 4D. Animal location and head direction within the recording incubator can have significant effects on the perceived amplitude of a call. Were these factors taken into account?

- Figure 4E. When a phee call has a higher amplitude, as is the case for the ACC group (Figure 4D), the energy of the signal will be concentrated more strongly at the phee call frequency ~8KHz. This concentration of the energy reduces the variability in the frequency distribution, leading to lower entropy. The interpretation of the results should be reconsidered. A faint call (control group) can exhibit more variability in the frequency content since the energy is distributed across a wider range of frequencies contributing to higher entropy. It can still be "fixed, regular, and stereotyped" if the behavior is consistent or predictable with little variation. Also, to define ACC calls as "monotonic" I would rather search for the lack of frequency modulation, amplitude variation, or narrower bandwidth.

- Apart from the changes in the vocal behavior, did the AAC lesions manifest in any other observable cognitive, emotional, or social behavior? ACC plays a role in processing pain and modulating pain perception. Could that be the reason for the observed increase in the proportion of cries in the ACC group and the increase in the phee call amplitude? Did the cries in the ACC group also display a higher amplitude than the cries in the control group?

- Discussion. Louder calls have the potential to travel longer distances compared to fainter calls, possess higher energy levels, and can propagate through the environment more effectively. If the ACC group produced louder phee syllables, how could be the message conveyed over long distances "deficient, limited, and/or indiscriminate"?

Reviewer #3 (Public Review):

Petty and Bruno ask whether activity in secondary thalamic nuclei depends on the behavioral relevance of stimulus modality. They recorded from POm and LP, but the weight of the paper is skewed toward POm. They use two cohorts of mice (N=11 and 12), recorded in both nuclei using multi-electrode arrays, while being trained to lick to either a tactile stimulus (air puff against whiskers, first cohort) or a visual stimulus (drifting grating, second cohort), and ignore the respective other. They find that both nuclei, while primarily responsive to their 'home' modality, are more responsive to the relevant modality (i.e. the modality predicting reward).

Strengths:

The paper asks an important question, it is timely and is very well executed. The behavioral method using a delayed lick index (excluding impulsive responses) is well worked out. Electrophysiology methods are state-of-the-art with information about spike quality in Figure S1. The main result is novel and important, convincingly conveying the point that encoding of secondary thalamic nuclei is flexible and clearly includes aspects of the behavioral relevance of a stimulus. The paper explores the mapping of responses within POm, pointing to a complex functional structure, something that has been reported/suggested in earlier studies.

Weaknesses:

Coding: It does not become clear to which aspect of the task POm/LP is responding. There is a motor-related response (whisking, licking, pupil), which, however, after regressing it out leaves a remaining response that the authors speculate could be sensory.

Learning: The paper talks a lot about 'learning', although it is only indirectly addressed. The authors use two differently (over-)trained mice cohorts rather than studying e.g. a rule switch in one and the same mouse, which would allow us to directly assess whether it is the same neurons that undergo rule-dependent encoding.

Mapping: The authors treat and interpret the two nuclei very much in the same vein, although there are clear differences. I would think these differences are mentioned in passing but could be discussed in more depth. Mapping using responses on electrode tracks is done in POm but not LP.

Reviewer #3 (Public Review):

Summary:

This paper uses a new chemogenetic tool to investigate the role of cerebellar Purkinje cells in postural control. Using a high-throughput behavioral assay, they show that activation or ablation of Purkinje cells affects various aspects of postural control in zebrafish larvae during spontaneous swimming and that the effects are more pronounced at later developmental time points, where the Purkinje cell number is much greater. Using a sophisticated imaging assay, they record Purkinje cell activity in response to the tilt of the fish and show that some Purkinje cells are tuned to tilt direction and that the direction can even be decoded from untuned neurons.

Strengths:

Overall the study is nice, using a range of tools to address a fundamental question about the role of the cerebellum in postural control in fish.

Weaknesses:

(1) The data in Figure 1 that establishes the method seems to be based on a very small number of experiments and lacks some statistical analysis.

(2) The choice and presentation of the statistical and analysis methods used in Figures 2-5 could be improved.

Reviewer #3 (Public Review):

Summary:

Li et al. describe an audiovisual temporal recalibration experiment in which participants perform baseline sessions of ternary order judgments about audiovisual stimulus pairs with various stimulus-onset asynchronies (SOAs). These are followed by adaptation at several adapting SOAs (each on a different day), followed by post-adaptation sessions to assess changes in psychometric functions. The key novelty is the formal specification and application/fit of a causal-inference model for the perception of relative timing, providing simulated predictions for the complete set of psychometric functions both pre and post-adaptation.

Strengths:

(1) Formal models are preferable to vague theoretical statements about a process, and prior to this work, certain accounts of temporal recalibration (specifically those that do not rely on a population code) had only qualitative theoretical statements to explain how/why the magnitude of recalibration changes non-linearly with the stimulus-onset asynchrony of the adaptor.

(2) The experiment is appropriate, the methods are well described, and the average model prediction is a fairly good match to the average data (Figure 4). Conclusions may be overstated slightly, but seem to be essentially supported by the data and modelling.

(3) The work should be impactful. There seems a good chance that this will become the go-to modelling framework for those exploring non-population-code accounts of temporal recalibration (or comparing them with population-code accounts).

(4) A key issue for the generality of the model, specifically in terms of recalibration asymmetries reported by other authors that are inconsistent with those reported here, is properly acknowledged in the discussion.

Weaknesses:

(1) The evidence for the model comes in two forms. First, two trends in the data (non-linearity and asymmetry) are illustrated, and the model is shown to be capable of delivering patterns like these. Second, the model is compared, via AIC, to three other models. However, the main comparison models are clearly not going to fit the data very well, so the fact that the new model fits better does not seem all that compelling. I would suggest that the authors consider a comparison with the atheoretical model they use to first illustrate the data (in Figure 2). This model fits all sessions but with complete freedom to move the bias around (whereas the new model constrains the way bias changes via a principled account). The atheoretical model will obviously fit better, but will have many more free parameters, so a comparison via AIC/BIC or similar should be informative.

(2) It does not appear that some key comparisons have been subjected to appropriate inferential statistical tests. Specifically, lines 196-207 - presumably this is the mean (and SD or SE) change in AIC between models across the group of 9 observers. So are these differences actually significant, for example via t-test?

(3) The manuscript tends to gloss over the population-code account of temporal recalibration, which can already provide a quantitative account of how the magnitude of recalibration varies with adaptor SOA. This could be better acknowledged, and the features a population code may struggle with (asymmetry?) are considered.

(4) The engagement with relevant past literature seems a little thin. Firstly, papers that have applied causal inference modelling to judgments of relative timing are overlooked (see references below). There should be greater clarity regarding how the modelling here builds on or differs from these previous papers (most obviously in terms of additionally modelling the recalibration process, but other details may vary too). Secondly, there is no discussion of previous findings like that in Fujisaki et al.'s seminal work on recalibration, where the spatial overlap of the audio and visual events didn't seem to matter (although admittedly this was an N = 2 control experiment). This kind of finding would seem relevant to a causal inference account.

References:<br /> Magnotti JF, Ma WJ and Beauchamp MS (2013) Causal inference of asynchronous audiovisual speech. Front. Psychol. 4:798. doi: 10.3389/fpsyg.2013.00798<br /> Sato, Y. (2021). Comparing Bayesian models for simultaneity judgement with different causal assumptions. J. Math. Psychol., 102, 102521.

(5) As a minor point, the model relies on simulation, which may limit its take-up/application by others in the field.

(6) There is little in the way of reassurance regarding the model's identifiability and recoverability. The authors might for example consider some parameter recovery simulations or similar.

(7) I don't recall any statements about open science and the availability of code and data.

Reviewer #3 (Public Review):

Summary:

The burst fraction neural code has conceptual interest but has been little examined in vivo. This study examines and compares the burst fraction, the standard firing rate (firing rate) code, and the related event fraction (event rate) code using published data from an experiment where rats learned to lick after detecting electrical microstimulation in the somatosensory (barrel) cortex. Analyzing single-neuron spiking responses, the study reports that the burst fraction identifies more and different neurons showing the effects of training than the firing rate. The study further claims that the burst fraction (1) most promptly responded to false-negative detection errors, (2) during further training of trained animals (from 80% to 90% accuracy, over five days), correlates with behavioral accuracy, and (3) by shifting earlier to align with the (relatively constant) event rate modulation, leads to the observed sharpened firing rate response during this further training. The study concludes that 'a fine-grained separation of spike timing patterns [into burst fraction, firing rate, and event rate] reveals two signals,' an error signal and a sharpening signal.

Strengths:

The burst fraction is shown to discern more (and somewhat different) cells showing significant responses in trained animals and also to reveal a larger absolute difference in the fraction of responsive cells between naïve and trained animals. The Poisson model analysis particularly convincingly shows that the firing rate alone cannot explain either the spiking pattern or the prevalence of burst fraction-ON cells, thereby furnishing strong evidence that the burst fraction conveys independent information from the firing rate. The demonstration of error signals on miss trials in all three neural codes (burst fraction, firing rate, event rate) is interesting. It is also interesting to see that neural responses broadly shift earlier for animals even during further training in an already 'expert' stage and that the burst fraction correlates with further accuracy increases.

Weaknesses:

The evidence is inadequate for the burst fraction as responding more promptly to missed trials.

This key claim seems to rest solely on the timing of the first bins in Figure 3B showing statistically significant differences. This reasoning implicitly draws inferences from the lack of statistical differences, which cannot support a positive claim in general. Specifically, here, the burst fraction is calculated with a division, which can magnify small differences and impact the power of statistical tests. If I trace back from the first bin showing significant differences to the first bin the signal starts rising, the timing seems to be comparable for all three neural codes (~1.6 s).

Pertinently, what is the statistical test used in Figure 3B? A parametric test may be inappropriate for the burst fraction, a ratio that like does not fulfill the normality assumption. An inappropriate test would compound the problem of concluding from the lack of (early) significant differences.

The evidence that burst fraction is responsible for sharpening is opaque due to insufficient statistical reporting. Specifically, it seems there is a correlation between firing rate and accuracy that is reported as non-significant.

Changes in the reaction times (or other movement parameters) over-training may confound the correlation of the burst fraction to the accuracy and firing rate sharpening during further training. Lack of control for changes in movement over training weakens the results.

The claim of independence of burst fraction and event rate/firing rate information is too strong. The authors show a significant negative correlation between burst fraction and firing rate (2D).

The claim that there is no 'functional reorganization' beyond day two is too strong. Although this claim is not a core one to the study, it derives from an absence of statistical significance, especially problematic here as the effect sizes are large. For example, the Spearman correlation is 0.67/0.87 for the analyses with burst fraction. With only five data points, even strong effects may not achieve statistical significance, making negative conclusions problematic. Further, how are the p-values calculated (if using a parametric test, are the assumptions met), and why should these analyses use Spearman's correlation when analogous analyses in Figure 4E, F use Pearson's r?

Does the burst fraction correlate with accuracy in cross-training?

If the burst fraction correlates with accuracy, it should be expected to do so also when the animals progress from the naïve to the trained stage. Moreover, the correlation in Figure 4E can benefit from strengthening as it is now supported by only five points, is driven by only three 'clusters,' and only represents a narrow range of accuracies. If the data is available for this analysis, it should be done to test and potentially strengthen the main claim of the study.

The text and figures contain numerous ambiguities that need to be clarified. These do not include obvious typos, only elements that affect conceptual understanding.

- Some key terms in the main claims are never defined. For example, in the title, it is unclear what 'fast' and 'transients' mean. The abstract uses, but the main text never defines, 'demultiplexing,' 'a *conjunctive* burst code,' 'sparse and succinct [sic],' and 'correlated more *globally*.'

- Some paper components are un(der)explained and, sometimes, apparently internally inconsistent. For example, in Figure 1I, the fraction of firing rate-ON cells does not look like the 6% shown in Figure 1J, left. In Figure 2E-G, what is the total cell number, 279, in Figure 2G legend, why is it different from the 153 total cells in Figure 2E legend, and what is the 'n = 5' within Figure 2G? All n numbers should be explained in general; more examples include the 245 in Figure 3C and the 49 in Figure 3B. In Figure 3C, what is the top horizontal bar (I assume significant differences)? About catch trials, the Figure 3D legend says rewards are given on licks, but the text says licking was not rewarded; which is the case? Figure 4B legend says 'firing rate (left), burst fraction (middle) and event rate (right),' but the plot colors imply a different order.

- The abstract states, 'The alignment of bursting and event rate modulation [...] was strongly associated [sic] behavioral accuracy.' It seems to me it is not the alignment of burst fraction and event rate but rather burst fraction per se that correlates with behavioral accuracy (Figure 4E right). At least, the latter correlation is the only one tested.

Reviewer #3 (Public Review):

Summary:

The authors aimed to determine the mechanism by which seizures emerge in Developmental and Epileptic Encephalopathies caused by variants in the gene FGF13. Loss of FGF13 in excitatory neurons had no effect on seizure phenotype as compared to the loss of FGF13 in GABAergic interneurons, which in contrast caused a dramatic proseizure phenotype and early death in these animals. They were able to show that Fgf13 ablation and consequent loss of FGF13-S and FGF13-VY reduced overall inhibitory input from Fgf13-expressing interneurons onto hippocampal pyramidal neurons. This was shown to occur not via disruption to voltage-gated sodium channels but rather by reducing potassium currents and action potential repolarisation in these interneurons.

Strengths:

The authors employed multiple well-validated, novel mouse lines with FGF13 knocked out in specific cell types including all neurons, all excitatory cells, all GABAergic interneurons, or a subset of MGE-derived interneurons, including axo-axonic chandelier cells. The phenotypes of each of these four mouse lines were carefully characterised to reveal clear differences with the most fundamental being that Interneuron-targeted deletion of FGF13 led to perinatal mortality associated with extensive seizures and impaired the hippocampal inhibitory/excitatory balance while deletion of FGF13 in excitatory neurons caused no detectable seizures and no survival deficits.

The authors made excellent use of western blotting and in situ hybridisation of the different FGF13 isoforms to determine which isoforms are expressed in which cell types, with FGF3-S predominantly in excitatory neurons and FGF13-VY and FGF13-V predominantly in GABAergic neurons.

The authors performed a highly detailed electrophysiological analysis of excitatory neurons and GABAergic interneurons with FGF13 deficits using whole-cell patch clamp. This enabled them to show that FGF13 removal did not affect voltage-gated sodium channels in interneurons, but rather reduced the action of potassium channels, with the resultant effect of making it more likely that interneurons enter depolarisation block. These findings were strengthened by the demonstration that viral re-expression of different Fgf13 splice isoforms could partially rescue deficits in interneuron action potential output and restore K+ channel current size.

Additionally, the discussion was nuanced and demonstrated how the current findings resolved previous apparent contradictions in the field involving the function of FGF13.

These findings will have a significant impact on our understanding of how FGF13 causes seizures and death in DEEs, and the action of different FGF13 isoforms within different neuronal cell types, particularly GABAergic interneurons.

Reviewer #3 (Public Review):

Summary:

This study presented a valuable inventory of scoring a neuropsychological test, ROCFT, with constructing an artificial intelligence model.

Strengths:

They constructed huge samples collected among multi-center international researchers and tested the model precisely using internet data.<br /> The model scored the test with excellent ability, surpassing even experts. The product can run an application on a tablet, which helps clinicians and patients.<br /> Their method of building the model of deep learning and testing will apply to tests in all fields, not just the psychological field.

Weaknesses:

The considerable effort and cost to make the model only for an existing neuropsychological test.

Reviewer #3 (Public Review):

Summary:

In this manuscript, Last and colleagues describe Ais, an open-source software package for the semi-automated segmentation of cryo-electron tomography (cryo-ET) maps. Specifically, Ais provides a graphical user interface (GUI) for the manual segmentation and annotation of specific features of interest. These manual annotations are then used as input ground-truth data for training a convolutional neural network (CNN) model, which can then be used for automatic segmentation. Ais provides the option of several CNNs so that users can compare their performance on their structures of interest in order to determine the CNN that best suits their needs. Additionally, pre-trained models can be uploaded and shared to an online database.

Algorithms are also provided to characterize "model interactions" which allows users to define heuristic rules on how the different segmentations interact. For instance, a membrane-adjacent protein can have rules where it must colocalize a certain distance away from a membrane segmentation. Such rules can help reduce false positives; as in the case above, false negatives predicted away from membranes are eliminated.

The authors then show how Ais can be used for particle picking and subsequent subtomogram averaging and for the segmentation of cellular tomograms for visual analysis. For subtomogram averaging, they used a previously published dataset and compared the averages of their automated picking with the published manual picking. Analysis of cellular tomogram segmentation was primarily visual.

Strengths:

CNN-based segmentation of cryo-ET data is a rapidly developing area of research, as it promises substantially faster results than manual segmentation as well as the possibility for higher accuracy. However, this field is still very much in the development and the overall performance of these approaches, even across different algorithms, still leaves much to be desired. In this context, I think Ais is an interesting package, as it aims to provide both new and experienced users with streamlined approaches for manual annotation, access to a number of CNNs, and methods to refine the outputs of CNN models against each other. I think this can be quite useful for users, particularly as these methods develop.

Weaknesses:

Whilst overall I am enthusiastic about this manuscript, I still have a number of comments:

On page 5, paragraph 1, there is a discussion on human judgement of these results. I think a more detailed discussion is required here, as from looking at the figures, I don't know that I agree with the authors' statement that Pix2pix is better. I acknowledge that this is extremely subjective, which is the problem. I think that a manual segmentation should also be shown in a figure so that the reader has a better way to gauge the performance of the automated segmentation.

On page 7, the authors mention terms such as "emit" and "absorb" but never properly define them, such that I feel like I'm guessing at their meaning. Precise definitions of these terms should be provided.

For Figure 3, it's unclear if the parent models shown (particularly the carbon model) are binary or not. The figure looks to be grey values, which would imply that it's the visualization of some prediction score. If so, how is this thresholded? This can also be made clearer in the text.

Figure 3D was produced in ChimeraX using the hide dust function. I think some discussion on the nature of this "dust" is in order, e.g. how much is there and how large does it need to be to be considered dust? Given that these segmentations can be used for particle picking, this seems like it may be a major contributor to false positives.

Page 9 contains the following sentence: "After selecting these values, we then launched a batch particle picking process to determine lists of particle coordinates based on the segmented volumes." Given how important this is, I feel like this requires significant description, e.g. how are densities thresholded, how are centers determined, and what if there are overlapping segmentations?

The FSC shown in Figure S6 for the auto-picked maps is concerning. First, a horizontal line at FSC = 0 should be added. It seems that starting at a frequency of ~0.045, the FSC of the autopicked map increases above zero and stays there. Since this is not present in the FSC of the manually picked averages, this suggests the automatic approach is also finding some sort of consistent features. This needs to be discussed.

Page 11 contains the statement "the segmented volumes found no immediately apparent false positive predictions of these pores". This is quite subjective and I don't know that I agree with this assessment. Unless the authors decide to quantify this through subtomogram classification, I don't think this statement is appropriate.

In the methods, the authors note that particle picking is explained in detail in the online documentation. Given that this is a key feature of this software, such an explanation should be in the manuscript.

Reviewer #3 (Public Review):

Summary:

Using protein degradation approach, Eaton et al show that INST11 can terminate the sense and anti-sense transcription but higher activity of CDK9 in sense direction protects it from INS11-dependent termination. They developed sPOINT-seq that detects nascent 5'-capped RNA. The technique allowed them to reveal robust transcription initiation of sense-RNA as compared to anti-sense.

Strengths:

The strength of paper is acute degradation of proteins, eliminating the off-target effects. Further, the paper uses elegant approaches such as POINT and sPOINT-seq to measure nascent RNA and 5'-capped short RNA. Together, the combination of these three allowed the authors to make clean interpretations of data.

Weaknesses:

While manuscript is well written, the details on panel is not sufficient. The methods can be more elaborate for better understanding. Additional discussion on how authors findings contradict the existing model of anti-sense transcription termination should be added.

in the revised manuscript, authors have added details on panels and elaborated method and other sections for better understanding.

Reviewer #3 (Public Review):

Summary

The high heterogeneity nature of α-synuclein (α-syn) fibrils posed significant challenges in structural reconstruction of the ex vivo conformation. A deeper understanding of the factors influencing the formation of various α-syn polymorphs remains elusive. The manuscript by Frey et al. provides a comprehensive exploration of how pH variations (ranging from 5.8 to 7.4) affect the selection of α-syn polymorphs (specifically, Type1, 2 and 3) in vitro by using cryo-electron microscopy (cryo-EM) and helical reconstruction techniques. Crucially, the authors identify two novel polymorphs at pH 7.0 in PBS. These polymorphs bear resemblance to the structure of patient-derived juvenile-onset synucleinopathy (JOS) polymorph and diseased tissue amplified α-syn fibrils. The revised manuscript more strongly supports the notion that seeding is a non-polymorph-specific in the context of secondary nucleation-dominated aggregation, underscoring the irreplaceable role of pH in polymorph formation.

Strengths

This study systematically investigates the effects of environmental conditions and seeding on the structure of α-syn fibrils. It emphasizes the significant influence of environmental factors, especially pH, in determining the selection of α-syn polymorphs. The high-resolution structures obtained through cryo-EM enable a clear characterization of the composition and proportion of each polymorph in the sample. Collectively, this work provides a strong support for the pronounced sensitivity of α-syn fibril structures to the environmental conditions, and systematically categorizes previously reported α-syn fibril structures. Furthermore, the identification of JOS-like polymorph also demonstrates the possibility of in vitro reconstruction of brain-derived α-syn fibril structures.

Weaknesses

There are two minor points I recommend the authors to address:

(1) In the response to Weakness 1, point (3), the authors state that "the Type 5 represented only 10-20% of the fibrils in the sample." However, this information is not labeled in the corresponding Figure 4. I suggest the authors verify and label all relevant percentages in the figures to prevent misunderstandings.

(2) While the authors have detailed the helical reconstruction procedure in the Methods section, it is necessary to indicate the scale bar or box size in the figure legend of the 2D representative classes to ensure clarity and reproducibility.

Comments on the revised manuscript:

The authors have responded adequately to these critiques in the revised version of the manuscript.

Reviewer #3 (Public Review):

This study presents a detailed examination of the molecular and cellular organization of the mouse VNO, unveiling new cell types, receptor co-expression patterns, lineage specification regulation, and potential associations between transcription factors, guidance molecules, and receptor types crucial for vomeronasal circuitry wiring specificity. The study identifies a novel type of VSN molecularly different from classic VSNs, which may serve as an accessory to other VSNs by secreting olfactory binding proteins and mucins in response to VNO activation. They also describe a previously undetected co-expression of multiple VRs in individual VSNs, providing an interesting view of the ongoing discussion on how receptor choice occurs in VSNs, either stochastic or deterministic. Finally, the study correlates the expression of axon guidance molecules associated with individual VRs, providing a putative molecular mechanism that specifies VSN axon projections and their connection with postsynaptic cells in the accessory olfactory bulb.

The conclusions of this paper are well supported by data, but some aspects of data analysis and acquisition need to be clarified and extended.

(1) The authors claim that they have identified two new classes of sensory neurons, one being a class of canonical olfactory sensory neurons (OSNs) within the VNO. This classification as canonical OSNs is based on expression data of neurons lacking the V1R or V2R markers but instead expressing ORs and signal transduction molecules, such as Gnal and Cnga2. Since OR-expressing neurons in the VNO have been previously described in many studies, it remains unclear to me why these OR-expressing cells are considered here a "new class of OSNs." Moreover, morphological features, including the presence of cilia, and functional data demonstrating the recognition of chemosignals by these neurons, are still lacking to classify these cells as OSNs akin to those present in the MOE. While these cells do express canonical markers of OSNs, they also appear to express other VSN-typical markers, such as Gnao1 and Gnai2 (Figure 2B), which are less commonly expressed by OSNs in the MOE. Therefore, it would be more precise to characterize this population as atypical VSNs that express ORs, rather than canonical OSNs.

(2) The second new class of sensory neurons identified corresponds to a group of VSNs expressing prototypical VSN markers (including V1Rs, V2Rs, and ORs), but exhibiting lower ribosomal gene expression. Clustering analysis reveals that this cell group is relatively isolated from V1R- and V2R-expressing clusters, particularly those comprising immature VSNs. The question then arises: where do these cells originate? Considering their fewer overall genes and lower total counts compared to mature VSNs, I wonder if these cells might represent regular VSNs in a later developmental stage, i.e., senescent VSNs. While the secretory cell hypothesis is compelling and supported by solid data, it could also align with a late developmental stage scenario. Further data supporting or excluding these hypotheses would aid in understanding the nature of this new cell cluster, with a comparison between juvenile and adult subjects appearing particularly relevant in this context.

(3) The authors' decision not to segregate the samples according to sex is understandable, especially considering previous bulk transcriptomic and functional studies supporting this approach. However, many of the highly expressed VR genes identified have been implicated in detecting sex-specific pheromones and triggering dimorphic behavior. It would be intriguing to investigate whether this lack of sex differences in VR expression persists at the single-cell level. Regardless of the outcome, understanding the presence or absence of major dimorphic changes would hold broad interest in the chemosensory field, offering insights into the regulation of dimorphic pheromone-induced behavior. Additionally, it could provide further support for proposed mechanisms of VR receptor choice in VSNs.

(4) The expression analysis of VRs and ORs seems to have been restricted to the cell clusters associated with the neuronal lineage. Are VRs/ORs expressed in other cell types, i.e. sustentacular, HBC, or other cells?

Reviewer #3 (Public Review):

Summary:

The authors harnessed the potential of mammalian endogenous virus-like proteins to encapsulate virus-like particles (VLPs), enabling the precise delivery of tumor neoantigens. Through meticulous optimization of the VLP component ratios, they achieved remarkable stability and efficiency in delivering these crucial payloads. Moreover, the incorporation of CpG-ODN further heightened the targeted delivery efficiency and immunogenicity of the VLPs, solidifying their role as a potent tumor vaccine. In a diverse array of tumor mouse models, this novel tumor vaccine, termed ePAC, exhibited profound efficacy in activating the murine immune system. This activation manifested through the stimulation of dendritic cells in lymph nodes, the generation of effector memory T cells within the spleen, and the infiltration of neoantigen-specific T cells into tumors, resulting in robust anti-tumor responses.

Strengths:

This study delivered tumor neoantigens using VLPs, pioneering a new method for neoantigen delivery. Additionally, the gag protein of VLP is derived from mammalian endogenous virus-like protein, which offers greater safety compared to virus-derived gag proteins, thereby presenting a strong potential for clinical translation. The study also utilized a humanized mouse model to further validate the vaccine's efficacy and safety. Therefore, the anti-tumor vaccine designed in this study possesses both innovation and practicality.

Weaknesses:

(1) CpG-ODN is an FDA-approved adjuvant with various sequence structures. Why was CpG-ODN 1826 directly chosen in this study instead of other types of CpG-ODN? Additionally, how does DEC-205 recognize CpG-ODN 1826, and can DEC-205 recognize other types of CpG-ODN?

(2) Why was it necessary to treat DCs with virus-like particles three times during the in vitro activation of T cells? Can this in vitro activation method effectively obtain neoantigen-responsive T cells?

(3) In the humanized mouse model, the authors used Hepa1-6 cells to construct the tumor model. To achieve the vaccine's anti-tumor function, these Hepa1-6 cells were additionally engineered to express HLA-A0201. However, in the in vitro experiments, the authors used the HepG2 cell line, which naturally expresses HLA-A0201. Why did the authors not continue to use HepG2 cells to construct the tumor model, instead of Hepa1-6 cells?

(4) The advantages of low immunogenicity viruses as vaccines compared with conventional adenovirus and lentivirus, etc. should be discussed.

(5) In Figure 6B, the authors should provide statistical results.

(6.) The entire article demonstrates a clear logical structure and substantial content in its writing. However, there are still some minor errors, such as the misspelling of "Spleenic" in Figure 3B, and the sentence from line 234 should be revised.

(7) The authors demonstrated the efficiency of CpG-ODN membrane modification by varying the concentration of DBCO, ultimately determining the optimal modification scheme for eVLP as 3.5 nmol of DBCO. However, in Figure 2B, the author did not provide the modification efficiency when the DBCO concentration is lower than 3.5 nmol. These results should be provided.

(8) In Figure 3, the authors presented a series of data demonstrating that ePAC can activate mouse DC2.4 cells and BMDCs in vitro. However, in Figure 7, there is no evidence showing whether human DC cells can be activated by ePAC in vitro. This data should be provided.

Reviewer #3 (Public Review):

Summary:

The authors investigate the kinase activity of IKK2, a crucial regulator of inflammatory cell signaling. They describe a novel tyrosine kinase activity of this well-studied enzyme and a highly unusual phosphotransfer from phosphorylated IKK2 onto substrate proteins in the absence of ATP as a substrate.

Strengths:

The authors provide an extensive biochemical characterization of the processes with recombinant protein, western blot, autoradiography, and protein engineering.

Weaknesses:

The identity and purity of the used proteins is not clear. Since the findings are so unexpected and potentially of wide-reaching interest - this is a weakness. Similar specific detection of phospho-Ser/Thr vs phospho-Tyr relies largely on antibodies which can have varying degrees of specificity.

Reviewer #3 (Public Review):

In this manuscript, Park and colleagues describe a series of experiments that investigate the role of R-loops in HIV-1 genome integration. The authors show that during HIV-1 infection, R-loops levels on the host genome accumulate. Using a synthetic R-loop prone gene construct, they show that HIV-1 integration sites target sites with high R-loop levels. They further show that integration sites on the endogenous host genome are correlated with sites prone to R-loops. Using biochemical approaches, as well as in vivo co-IP and proximity ligation experiments, the authors show that HIV-1 integrase physically interacts with R-loop structures.

My primary concern with the paper is with the interpretations the authors make about their genome-wide analyses. I think that including some additional analyses of the genome-wide data, as well as some textual changes can help make these interpretations more congruent with what the data demonstrate. Here are a few specific comments and questions:

(1) I think Figure 1 makes a good case for the conclusion that R-loops are more easily detected HIV-1 infected cells by multiple approaches (all using the S9.6 antibody). The authors show that their signals are RNase H sensitive, which is a critical control. For the DRIPc-Seq, I think including an analysis of biological replicates would greatly strengthen the manuscript. The authors state in the methods that the DRIPc pulldown experiments were done in biological replicates for each condition. Are the increases in DRIPc peaks similar across biological replicates? Are genomic locations of HIV-1-dependent peaks similar across biological replicates? Measuring and reporting the biological variation between replicate experiments is crucial for making conclusions about increases in R-loop peak frequency. This is partially alleviated by the locus-specific data in Figure S3A. However, a better understanding of how the genome-wide data varies across biological replicates will greatly enhance the quality of Figure 1.

(2) I think that the conclusion that R-loops "accumulate" in infected cells is acceptable, given the data presented. However, in line 134 the authors state that "HIV-1 infection induced host genomic R-loop formation". I suggest being very specific about the observation. Accumulation can happen by (a) inducing a higher frequency of the occurrence of individual R-loops and/or (b) stabilizing existing R-loops. I'm not convinced the authors present enough evidence to claim one over the other. It is altogether possible that HIV-1 infection stabilizes R-loops such that they are more persistent (perhaps by interactions with integrase?), and therefore more easily detected. I think rephrasing the conclusions to include this possibility would alleviate my concerns.

(3) A technical problem with using the S9.6 antibody for the detection of R-loops via microscopy is that it cross-reacts with double-stranded RNA. This has been addressed by the work of Chedin and colleagues (as well as others). It is absolutely essential to treat these samples with an RNA:RNA hybrid-specific RNase, which the authors did not include, as far as their methods section states. Therefore, it is difficult to interpret all of the immunofluorescence experiments that depend on S9.6 binding.

(4) Given that there is no clear correlation between expression levels and R-loop peak detection, combined with the data that show increased detection of R-loop frequency in non-genic regions, I think it will be important to show that the R-loop forming regions are indeed transcribed above background levels. This will help alleviate possible concerns that there are technical errors in R-loop peak detection.

(5) In Figures 4C and D the hashed lines are not defined. It is also interesting that the integration sites do not line up with R-loop peaks. This does not necessarily directly refute the conclusions (especially given the scale of the genomic region displayed), but should be addressed in the manuscript. Additionally, it would greatly improve Figure 4 to have some idea about the biological variation across replicates of the data presented 4A.

(6) The authors do not adequately describe the Integrase mutant that they use in their biochemical experiments in Figure 5A. Could this impact the activity of the protein in such a way that interferes with the interpretation of the experiment? The mutant is not used in subsequent experiments for Figure 5 and so even though the data are consistent with each other (and the conclusion that Integrase interacts with R-loops) a more thorough explanation of why that mutant was used and how it impacts the biochemical activity of the protein will help the interpretation of the data presented in Figure 5.

Reviewer #3 (Public Review):

Summary:

In this manuscript, the authors explore the contribution of metabolism to the response of two subpopulations of macrophages to bacterial pathogens commonly encountered in the human lung, as well as the influence of priming signals typically produced at a site of inflammation. The two subpopulations are resident airway macrophages (AM) isolated via bronchoalveolar lavage and monocyte-derived macrophages (MDM) isolated from human blood and differentiated using human serum. The two cell types were primed using IFNγ and Il-4, which are produced at sites of inflammation as part of initiation and resolution of inflammation respectively, followed by stimulation with either irradiated Mycobacterium tuberculosis (Mtb) or LPS to simulate interaction with a bacterial pathogen. The authors use human cells for this work, which makes use of widely reported and thoroughly described priming signals, as well as model antigens. This makes the observations on the functional response of these two subpopulations relevant to human health and disease. To examine the relationship between metabolism and functional response, the authors measure rates of oxidative phosphorylation and glycolysis under baseline conditions, primed using IFNγ or IL-4, and primed and stimulated with Mtb or LPS.

Strengths:

• The data indicate that both populations of macrophages increase metabolic rates when primed, but MDMs decrease their rates of oxidative phosphorylation after IL-4 priming and bacterial exposure while AMs do not.<br /> • It is demonstrated that glycolysis rates are directly linked to the expression of surface molecules involved in T-cell stimulation and while secretion of TNFα in AM is dependent on glycolysis, in MDM this is not the case. IL-1β is regulated by glycolysis only after IFN-γ priming in both MDM and AM populations. It is also demonstrated that Mtb and LPS stimulation produces responses that are not metabolically consistent across the two macrophage populations. The Mtb-induced response in MDMs differed from the LPS response, in that it relies on glycolysis, while this relationship is reversed in AMs. The difference in metabolic contributions to functional outcomes between these two macrophage populations is significant, despite acknowledgement of the reductive nature of the system by the authors.<br /> • The observations that AM and MDM rely on glycolysis for the production of cytokines during a response to bacterial pathogens in the lung, but that only MDM shift to Warburg Metabolism, though this shift is blocked following exposure to IL-4, are supported by the data and a significant contribution the study of the innate immune response.

Weaknesses:

• It is unclear whether changes in glycolysis and oxidative phosphorylation in primed cells are due to priming or subsequent treatments. ECAR and OCR analyses were therefore difficult to interpret.<br /> • The data may not support a claim that AM has greater "functional plasticity" without a direct comparison of antigen presentation. Moreover, MDM secrete more IL-1β than AM. The claim that AM "have increased ability to produce all cytokines assayed in response to Mtb stimulation" does not appear to be supported by the data.<br /> • The claim that AM are better for "innate training" via IFNγ may not be consistent with increased IL-1β and a later claim that MDM have increased production and are "associated with optimal training."<br /> • Statistical analyses may not appropriately support some of the conclusions.<br /> • AM populations would benefit from further definition-presumably this is a heterogenous, mixed population.<br /> • The term "functional plasticity" could also be more stringently defined for the purposes of this study.

Conclusion:

Overall, the authors succeed in their goals of investigating how inflammatory and anti-inflammatory cytokine priming contributes to the metabolic reprogramming of AM and MDM populations. Their conclusions regarding the relationship between cytokine secretion and inflammatory molecule expression in response to bacterial stimuli are supported by the data. The involvement of metabolism in innate immune cell function is relevant when devising treatment strategies that target the innate immune response during infection. The data presented in this paper further our understanding of that relationship and advance the field of innate immune cell biology.

Reviewer #3 (Public Review):

Summary:

In this manuscript, Krause and colleagues identify miR-182 as diabetes-associated microRNA: miR-182 is increased in bariatric surgery patients with versus without T2D; miR-182 was the only microRNA associated with three metabolic traits; miR-182 levels were associated with increased body weight in mice under different dietary manipulations; overexpression in Hep-G2 led to a decrease in LRP6; and overexpression in HFD fed mice led to increased insulin and liver TG. The manuscript provides a potentially useful resource of microRNA expression in human livers, though the functional importance of miR-182 remains unclear.

Strengths:

The use of human tissues and good sample sizes is strong.

Weaknesses:

The study remains primarily correlative; the in vivo overexpression is non-physiological; and the mechanisms by which miR-182 exerts its effects are not rigorously tested.

Reviewer #3 (Public Review):

Bing et al. attempt to address fundamental mechanisms of TAD formation in Drosophila by analyzing gene expression and 3D conformation within the vicinity of the eve TAD after insertion of a transgene harboring a Homie insulator sequence 142 kb away in different orientations. These transgenes along with spatial gene expression analysis were previously published in Fujioka et al. 2016, and the underlying interpretations regarding resulting DNA configuration in this genomic region were also previously published. This manuscript repeats the expression analysis using smFISH probes in order to achieve more quantitative analysis, but the main results are the same as previously published. The only new data are the Micro-C and an additional modeling/analysis of what they refer to as the 'Z3' orientation of the transgenes. The rest of the manuscript merely synthesizes further interpretation with the goal of addressing whether loop extrusion may be occurring or if boundary:boundary pairing without loop extrusion is responsible for TAD formation. The authors conclude that their results are more consistent with boundary:boundary pairing and not loop extrusion; however, most of this imaging data seems to support both loop extrusion and the boundary:boundary models. This manuscript lacks support, especially new data, for its conclusions. Furthermore, there are many parts of the manuscript that are difficult to follow. There are some minor errors in the labelling of the figures that if fixed would help elevate understanding. Lastly, there are several major points that if elaborated on, would potentially be helpful for the clarity of the manuscript.

Major Points:

(1) The authors suggest and attempt to visualize in the supplemental figures, that loop extrusion mechanisms would appear during crosslinking and show as vertical stripes in the micro-C data. In order to see stripes, a majority of the nuclei would need to undergo loop extrusion at the same rate, starting from exactly the same spots, and the loops would also have to be released and restarted at the same rate. If these patterns truly result from loop extrusion, the authors should provide experimental evidence from another organism undergoing loop extrusion.<br /> (2) On lines 311-314, the authors discuss that stem-loops generated by cohesin extrusion would possibly be expected to have more next-next-door neighbor contacts than next-door neighbor contacts and site their models in Figure 1. Based on the boundary:boundary pairing models in the same figure would the stem-loops created by head-to-tail pairing also have the same phenotype? Making possible enrichment of next-next-door neighbor contacts possible in both situations? The concepts in the text are not clear, and the diagrams are not well-labeled relative to the two models.<br /> (3) The authors appear to cite Chen et al., 2018 as a reference for the location of these transgenes being 700nM away in a majority of the nuclei. However, the exact transgenes in this manuscript do not appear to have been measured for distance. The authors could do this experiment and include expression measurements.<br /> (4) The authors discuss the possible importance of CTCF orientation in forming the roadblock to cohesin extrusion and discuss that Homie orientation in the transgene may impact Homie function as an effective roadblock. However, the Homie region inserted in the transgene does not contain the CTCF motif. Can the authors elaborate on why they feel the orientation of Homie is important in its ability to function as a roadblock if the CTCF motif is not present? Trans-acting factors responsible for Homie function have not been identified and this point is not discussed in the manuscript.<br /> (5) The imaging results seem to be consistent with both boundary:boundary interaction and loop extrusion stem looping.<br /> (6) The authors suggest that the eveMa TAD could only be formed by extrusion after the breakthrough of Nhomie and several other roadblocks. Additionally, the overall long-range interactions with Nhomie appear to be less than the interactions with endogenous Homie (Figures 7, 8, and supplemental 5). Is it possible that in some cases boundary:boundary pairing is occurring between only the transgenic Homie and endogenous Homie and not including Nhomie?<br /> (7) In Figure 4E, the GFP hebe expression shown in the LhomieG Z5 transgenic embryo does not appear in the same locations as the LlambdaG Z5 control. Is this actually hebe expression or just a background signal?<br /> (8) Figure 6- The LhomieG Z3 late-stage embryo appears to be showing the ventral orientation of the embryo rather than the lateral side of the embryo as was shown in the previous figure. Is this for a reason? Additionally, there are no statistics shown for the Z3 transgenic images. Were these images analyzed in the same way as the Z5 line images?<br /> (9) Do the Micro-C data align with the developmental time points used in the smFISH probe assays?

Reviewer #3 (Public Review):

In this study, Prochera, et al. identify PLP1+ cells as the glia that most closely interact with the gut epithelium and show that genetic depletion of these PLP1+ glia in mice does not have major effects on the intestinal transcriptome or the cellular composition of the epithelium. Enteric glial loss, however, causes dysregulation of Paneth cell gene expression that is associated with morphological disruption of Paneth cells, diminished lysozyme secretion, and altered gut microbial composition. Overall, the authors need to first prove whether the Plp1CreER Rosa26DTA/+ mice system is viable. Also, most experimental systems have been evaluated by immunohistochemistry, scRNAseq, and electron microscopy, but need quantitative statistical processing. In addition, the value of the paper would be enhanced if the significance of why the phenotype appeared in the large intestine rather than the small intestine when PLP1 is deficient for Paneth cells is clarified.

Weaknesses:

Major:

(1) Supplementary Figure 2; Cannot be evaluated without quantification.

(2) Figure 2A; Is Plp1CreER Rosa26DTA/+ mice system established correctly? S100B immunohistology picture is not clear. A similar study is needed for female Plp1CreER Rosa26DTA/+ mice. What is the justification for setting 5 dpt, 11 dpt? Any consideration of changes to organs other than the intestine? Wouldn't it be clearer to introduce Organoid technology?

3) Figure 2B; Need an explanation for the 5 genes that were altered in the colon. Five genes should be evaluated by RT-qPCR. Why was there a lack of change in the duodenum and ileum?

(4) Supplementary Figure 3; Top 3 genes should be evaluated by RT-qPCR.

(5) Supplementary Figure 4B, C, and D; Why not show analysis in the small intestine?

(6) Supplementary Figure 4D; Cannot be evaluated without quantification.

(7) Figure 3D; Cannot be evaluated without quantification.

(8) Supplementary Figure 5B and C; Top 3 genes should be evaluated by RT-qPCR.

(9) Supplementary Figure 6; Top 3 genes should be evaluated by RT-qPCR.

(10) Figure 4A; Cannot be evaluated without quantification.

(11) Figure 4D; Cannot be evaluated without quantification.

(12) Additional experiments on in vivo infection systems comparing Plp1CreER Rosa26DTA/+ mice and controls would be great.

Reviewer #3 (Public Review):

In this manuscript, Wu et al. investigate active H3K27ac and H3K4me1 marks in term pregnant nonlabor myometrial biopsies, linking putative-enhancers and super-enhancers to gene expression levels. Through their findings, they reveal the PGR-dependent regulation of the PLCL2 gene in human myometrial cells via a cis-acting element located 35-kilobases upstream of the PLCL2 gene. By targeting this region using a CRISPR activation system, they were able to elevate the endogenous PLCL2 mRNA levels in immortalized human myometrial cells.

This research offers novel insights into the molecular mechanisms governing gene expression in myometrial tissues, advancing our understanding of pregnancy-related processes.

Major comments:

(1) A more comprehensive analysis of the epigenetic and transcriptomic data would have strengthened the paper, moving beyond basic association studies. Currently, it is challenging to assess the quality and significance of the data as much of the information is lacking.

(2) The rationale for and connections between experiments, as well as results, could be bolstered to underscore the significance of this research.

Strengths:

- The combination of ChIP-Seq, RNA-Seq, and CRISPRa Perturb-Seq approaches to investigate gene regulation and expression in myometrial cells.

- The use of CRISPR activation system to specifically target cis-acting elements.

Weaknesses:

- The manuscript would strongly benefit from a deeper analysis of the Omic datasets. Furthermore, expanding figures/graphs to effectively contextualize these datasets would be greatly beneficial and would add more value to this research. Currently, it is difficult for us to assess and appreciate the quality of these data sets across the manuscript, which is mostly correlative.

- Limited sample size, coupled with variability in results and overall lack of details, compromises the robustness of result interpretation.

- For most parts of the results section, a better description is needed, including rationale, approach, and presentation of data. As it stands, it is challenging to assess the quality of the data and appreciate the results.

- Additional efforts are needed to dissect the proposed regulatory mechanisms.

- While the discussion provided helpful context for understanding some of the experiments performed, it lacked interpretation of the results in relation to the existing literature.

Reviewer #3 (Public Review):

During meiosis in sexually reproducing organisms, double-strand breaks are induced by a topoisomerase-related enzyme, Spo11, which is essential for homologous recombination, which in turn is required for accurate chromosome segregation. Additional factors control the number and genome-wide distribution of breaks, but the mechanisms that determine both the frequency and preferred location of meiotic DSBs remain only partially understood in any organism.

The manuscript presents a variety of different analyses that include variable subsets of putative DSB factors. It would be much easier to follow if the analyses had been more systematically applied. It is perplexing that several factors known to be essential for DSB formation (e.g., cohesins, HORMA proteins) are excluded from this analysis, while it includes several others that probably do not directly contribute to DSB formation (XND-1, HIM-17, CEP-1, and PARG-1). The strongest claims seem to be that "HIM-5 is the determinant of X-chromosome-specific crossovers" and "HIM-5 coordinates the actions of the different accessory factors sub-groups." Prior work had already shown that mutations in him-5 preferentially reduce meiotic DSBs on the X chromosome. While it is possible that HIM-5 plays a direct role in DSB induction on the X chromosome, the evidence presented here does not strongly support this conclusion. It is also difficult to reconcile this idea with evidence from prior studies that him-5 mutations predominantly prevent DSB formation on the sex chromosomes, while the protein localizes to autosomes. The one experiment that seems to elicit the conclusion that HIM-5 expression is sufficient for breaks on the X chromosome is flawed (see below). The conclusion that HIM-5 "coordinates the activities of the different accessory sub-groups" is not supported by data presented here or elsewhere.

Like most other studies that have examined DSB formation in C. elegans, this work relies on indirect assays, here limited to the cytological appearance of RAD-51 foci and bivalent chromosomes, as evidence of break formation or lack thereof. Unfortunately, neither of these assays has the power to reveal the genome-wide distribution or number of breaks. These assays have additional caveats, due to the fact that RAD-51 association with recombination intermediates and successful crossover formation both require multiple steps downstream of DSB induction, some of which are likely impaired in some of the mutants analyzed here. This severely limits the conclusions that can be drawn. Given that the goal of the work is to understand the effects of individual factors on DSB induction, direct physical assays for DSBs should be applied; many such assays have been developed and used successfully in other organisms.

Throughout the manuscript, the writing conflates the roles played by different factors that affect DSB formation in very different ways. XND-1 and HIM-17 have previously been shown to be transcription factors that promote the expression of many germline genes, including genes encoding proteins that directly promote DSBs. Mutations in either xnd-1 or him-17 result in dysregulation of germline gene expression and pleiotropic defects in meiosis and fertility, including changes in chromatin structure, dysregulation of meiotic progression, and (for xnd-1) progressive loss of germline immortality. It is thus misleading to refer to HIM-17 and XND-1 as DSB "accessory factors" or to lump their activities with those of other proteins that are likely to play more direct roles in DSB induction. For example, statements such as the following sentence in the Introduction should be omitted or explained more clearly: "xnd-1 is also unique among the accessory factors in influencing the timing of DSBs; in the absence of xnd-1, there is precocious and rapid accumulation of DSBs as monitored by the accumulation of the HR strand-exchange protein RAD-51." The evidence that HIM-17 promotes the expression of him-5 presented here corroborates data from other publications, notably the recent work of Carelli et al. (2022), but this conclusion should not be presented as novel here. The other factors also fall into several different functional classes, some of which are relatively well understood, based largely on studies in other organisms. The roles of RAD-50 and MRE-11 in DSB induction have been investigated in yeast and other organisms as well as in several prior studies in C. elegans. DSB-1, DSB-2, and DSB-3 are homologs of relatively well-studied meiotic proteins in other organisms (Rec114 and Mei4) that directly promote the activity of Spo11, although the mechanism by which they do so is still unclear. Mutations in PARG-1 (a Poly-ADP ribose glycohydrolase) likely affect the regulation of poly-ADP-ribose addition and removal at sites of DSBs, which in turn are thought to regulate chromatin structure and recruitment of repair factors; however, there is no convincing evidence that PARG-1 directly affects break formation. CEP-1 is a homolog of p53 and is involved in the DNA damage response in the germline, but again is unlikely to directly contribute to DSB induction. HIM-5 and REC-1 do not have apparent homologs in other organisms and play poorly understood roles in promoting DSB induction. A mechanistic understanding of their functions would be of value to the field, but the current work does not shed light on this. A previous paper (Chung et al. G&D 2015) concluded that HIM-5 and REC-1 are paralogs arising from a recent gene duplication, based on genetic evidence for a partially overlapping role in DSB induction, as well as an argument based on the genomic location of these genes in different species; however, these proteins lack any detectable sequence homology and their predicted structures are also dissimilar (both are largely unstructured but REC-1 contains a predicted helical bundle lacking in HIM-5). Moreover, the data presented here do not reveal overlapping sets of genetic or physical interactions for the two genes/proteins. Thus, this earlier conclusion was likely incorrect, and this idea should not be restated uncritically here or used as a basis to interpret phenotypes.

DSB-1 was previously reported to be strictly required for all DSB and CO formation in C. elegans. Here the authors test whether the expression of HIM-5 from the pie-1 promoter can rescue DSB formation in dsb-1 mutants, and claim to see some rescue, based on an increase in the number of nuclei with one apparent bivalent (Figure 2C). This result seems to be the basis for the claim that HIM-5 coordinates the activities of other DSB proteins. However, this assay is not informative, and the conclusion is almost certainly incorrect. Notably, a substantial number of nuclei in the dsb-1 mutant (without Ppie-1::him-5) are reported as displaying a single bivalent (11 DAPI staining bodies) despite prior evidence that DSBs are absent in dsb-1 mutants; this suggests that the way the assay was performed resulted in false positives (bivalents that are not actually bivalents), likely due to inclusion of nuclei in which univalents could not be unambiguously resolved in the microscope. A slightly higher level of nuclei with a single unresolved pair of chromosomes in the dsb-1; Ppie-1::him-5 strain is thus not convincing evidence for rescue of DSBs/CO formation, and no evidence is presented that these putative COs are X-specific. The authors should provide additional experimental evidence - e.g., detection of RAD-51 and/or COSA-1 foci or genetic evidence of recombination - or remove this claim. The evidence that expression of Ppie-1::him-5 may partially rescue DSB abundance in dsb-2 mutants is hard to interpret since it is currently unknown why C. elegans expresses 2 paralogs of Rec114 (DSB-1 and DSB-2), and the age-dependent reduction of DSBs in dsb-2 mutants is not understood.

Several of the factors analyzed here, including XND-1, HIM-17, HIM-5, DSB-1, DSB-2, and DSB-3, have been shown to localize broadly to chromatin in meiotic cells. Co-immunoprecipitation of pairs of these factors, even following benzonase digestion, is not strong evidence to support a direct physical interaction between proteins. Similarly, the super-resolution analysis of XND-1 and HIM-17 (Figure 1EF) does not reveal whether these proteins physically interact with each other, and does not add to our understanding of these proteins' functions, since they are already known to bind to many of the same promoters. Promoters are also likely to be located in chromatin loops away from the chromosome axis, so in this respect, the localization data are also confirmatory rather than novel.

The phenotypic analysis of double mutant combinations does not seem informative. A major problem is that these different strains were only assayed for bivalent formation, which (as mentioned above) requires several steps downstream of DSB induction. Additionally, the basis for many of the single mutant phenotypes is not well understood, making it particularly challenging to interpret the effects of double mutants. Further, some of the interactions described as "synergistic" appear to be additive, not synergistic. While additive effects can be used as evidence that two genes work in different pathways, this can also be very misleading, especially when the function of individual proteins is unknown. I find that the classification of genes into "epistastasis groups" based on this analysis does not shed light on their functions and indeed seems in some cases to contradict what is known about their functions.

The yeast two-hybrid (Y2H) data are only presented as a single colony. While it is understandable to use a 'representative' colony, it is ideal to include a dilution series for the various interactions, which is how Y2H data are typically shown.

Additional (relatively minor) concerns about these data:

(1) Several interactions reported here seem to be detected in only one direction - e.g., MRE-11-AD/HIM-5-BD, REC-1-AD/XND-1-BD, and XND-1-AD/HIM-17-BD - while no interactions are seen with the reciprocal pairs of fusion proteins. I'm not sure if some of this is due to pasting "positive" colony images into the wrong position in the grid, but this should be addressed.

(2) DSB-3 was only assayed in pairwise combinations with a subset of other proteins; this should be explained; it is also unclear why the interaction grids are not symmetrical about the diagonal.

(3) I don't understand why the graphic summaries of Y2H data are split among 3 different figures (1, 2, and 3).

Reviewer #3 (Public Review):

This is a very ordinary research paper. The horizontal of endosymbionts, including Wolbachia, Rickettsia etc. has been reported in detail in the last 10 years, and parasitoid vectored as well as plant vectored horizontal transmission is the mainstream of research. For example, Ahmed et al. 2013 PLoS One, 2015 PLoS Pathogens, Chiel et al. 2014 Enviromental Entomology, Ahmed et al. 2016 BMC Evolution Biology, Qi et al. 2019 JEE, Liu et al. 2023 Frontiers in Cellular and Infection Microbiology, all of these reported the parasitoid vectored horizontal transmission of endosymbiont. While Caspi-Fluger et al. 2012 Proc Roy Soc B, Chrostek et al. 2017 Frontiers in Microbiology, Li et al. 2017 ISME Journal, Li et al. 2017 FEMS, Shi et al. 2024 mBio, all of these reported the plant vectored horizontal transmission of endosymbiont. For the effects of endosymbiont on the biology of the host, Ahmed et al. 2015 PLoS Pathogens explained the effects in detail.

Weaknesses:

In the current study, the authors downloaded the MLST or wsp genes from a public database and analyzed the data using other methods, and I think the authors may not be familiar with the research progress in the field of insect symbiont transmission, and the current stage of this manuscript lacking sufficient novelty.

Reviewer #3 (Public Review):

The paper by Le Roy and colleagues seeks to ask whether wing morphology or wing kinematics enable miniaturization in an interesting clade of agile flying insects. Isometry argues that insects cannot maintain both the same kinematics and the same wing morphology as body size changes. This raises a long-standing question of which varies allometrically. The authors do a deep dive into the morphology and kinematics of eight specific species across the hoverfly phylogeny. They show broadly that wing kinematics do not scale strongly with body size, but several parameters of wing morphology do in a manner different from isometry leading to the conclusion that these species have changed wing shape and size more than kinematics. The authors find no phylogenetic signal in the specific traits they analyze and conclude that they can therefore ignore phylogeny in the later analyses. They use both a quasi-steady simplification of flight aerodynamics and a series of CFD analyses to attribute specific components of wing shape and size to the variation in body size observed. However, the link to specific correlated evolution, and especially the suggestion of enabling or promoting miniaturization, is fraught and not as strongly supported by the available evidence.

The aerodynamic and morphological data collection, modeling, and interpretation are very strong. The authors do an excellent job combining a highly interpretable quasi-steady model with CFD and geometric morphometrics. This allows them to directly parse out the effects of size, shape, and kinematics.

Despite the lack of a relationship between wing kinematics and size, there is a large amount of kinematic variation across the species and individual wing strokes. The absolute differences in Figure 3F - I could have a very large impact on force production but they do indeed not seem to change with body size. This is quite interesting and is supported by aerodynamic analyses.

The authors switch between analyzing their data based on individuals and based on species. This creates some pseudoreplication concerns in Figures 4 and S2 and it is confusing why the analysis approach is not consistent between Figures 4 and 5. In general, the trends appear to be robust to this, although the presence of one much larger species weighs the regressions heavily. Care should be taken in interpreting the statistical results that mix intra- and inter-specific variation in the same trend.

The authors based much of their analyses on the lack of a statistically significant phylogenetic signal. The statistical power for detecting such a signal is likely very weak with 8 species. Even if there is no phylogenetic signal in specific traits, that does not necessarily mean that there is no phylogenetic impact on the covariation between traits. Many comparative methods can test the association of two traits across a phylogeny (e.g. a phylogenetic GLM) and a phylogenetic PCA would test if the patterns of variation in shape are robust to phylogeny.

The analysis of miniaturization on the broader phylogeny is incomplete. The conclusion that hoverflies tend towards smaller sizes is based on an ancestral state reconstruction. This is difficult to assess because of some important missing information. Specifically, such reconstructions depend on branch lengths and the model of evolution used, which were not specified. It was unclear how the tree was time-calibrated. Most often ancestral state reconstructions utilize a maximum likelihood estimate based on a Brownian motion model of evolution but this would be at odds with the hypothesis that the clade is miniaturizing over time. Indeed such an analysis will be biased to look like it produces a lot of changes towards smaller body size if there is one very large taxa because this will heavily weight the internal nodes. Even within this analysis, there is little quantitative support for the conclusion of miniaturization, and the discussion is restricted to a general statement about more recently diverged species. Such analyses are better supported by phylogenetic tests of directedness in the trait over time, such as fitting a model with an adaptive peak or others.

Setting aside whether the clade as a whole tends towards smaller size, there is a further concern about the correlation of variation in wing morphology and changes in size (and the corresponding conclusion about lack of co-evolution in wing kinematics). Showing that there is a trend towards smaller size and a change in wing morphology does not test explicitly that these two are correlated with the phylogeny. Moreover, the subsample of species considered does not appear to recapitulate the miniaturization result of the larger ancestral state reconstruction.

Given the limitations of the phylogenetic comparative methods presented, the authors did not fully support the general conclusion that changes in wing morphology, rather than kinematics, correlate with or enable miniaturization. The aerodynamic analysis across the 8 species does however hold significant value and the data support the conclusion as far as it extends to these 8 species. This is suggestive but not conclusive that the analysis of consistent kinematics and allometric morphology will extend across the group and extend to miniaturization. Nonetheless, hoverflies face many shared ecological pressures on performance and the authors summarize these well. The conclusions of morphological allometry and conserved kinematics are supported in this subset and point to a clade-wide pattern without having to support an explicit hypothesis about miniaturization.

The data and analyses on these 8 species provide an important piece of work on a group of insects that are receiving growing attention for their interesting behaviors, accessibility, and ecologies. The conclusions about morphology vs. kinematics provide an important piece to a growing discussion of the different ways in which insects fly. Sometimes morphology varies, and sometimes kinematics depending on the clade, but it is clear that morphology plays a large role in this group. The discussion also relates to similar themes being investigated in other flying organisms. Given the limitations of the miniaturization analyses, the impact of this study will be limited to the general question of what promotes or at least correlates with evolutionary trends towards smaller body size and at what phylogenetic scale body size is systematically decreasing.

In general, there is an important place for work that combines broad phylogenetic comparison of traits with more detailed mechanistic studies on a subset of species, but a lot of care has to be taken about how the conclusions generalize. In this case, since the miniaturization trend does not extend to the 8 species subsample of the phylogeny and is only minimally supported in the broader phylogeny, the paper warrants a narrower conclusion about the connection between conserved kinematics and shared life history/ecology.

Reviewer #3 (Public Review):

Summary:

In their manuscript titled "Multiplexed Assays of Human Disease‐relevant Mutations Reveal UTR Dinucleotide Composition as a Major Determinant of RNA Stability" the authors aim to investigate the effect of sequence variations in 3'UTR and 5'UTRs on the stability of mRNAs in two different human cell lines.

To do so, the authors use a massively parallel reporter assay (MPRA). They transfect cells with a set of mRNA reporters that contain sequence variants in their 3' or 5' UTRs, which were previously reported in human diseases. They follow their clearance from cells over time relative to the matching non-variant sequence. To analyze their results, they define a set of factors (RBP and miRNA binding sites, sequence features, secondary structure etc.) and test their association with differences in mRNA stability. For features with a significant association, they use clustering to select a subset of factors for LASSO regression and identify factors that affect mRNA stability.<br /> They conclude that the TA dinucleotide content of UTRs is the strongest destabilizing sequence feature. Within that context, elevated GC content and protein binding can protect susceptible mRNAs from degradation. They also show that TA dinucleotide content of UTRs affects native mRNA stability, and that it is associated with specific functional groups. Finally, they link disease associated sequence variants with differences in mRNA stability of reporters.

Strengths:

(1) This work introduces a different MPRA approach to analyze the effect of genetic variants. While previous works in tissue culture use DNA transfections that require normalization for transcription efficiency, here the mRNA is directly introduced into cells at fixed amounts, allowing a more direct view of the mRNA regulation.

(2) The authors also introduce a unique analysis approach, which takes into account multiple factors that might affect mRNA stability. This approach allows them to identify general sequence features that affect mRNA stability beyond specific genetic variants, and reach important insights on mRNA stability regulation. Indeed, while the conclusions to genetic variants identified in this work are interesting, the main strength of the work involve general effect of sequence features rather than specific variants.

(3) The authors provide adequate supports for their claims, and validate their analysis using both their reporter data and native genes. For the main feature identified, TA di-nucleotides, they perform follow-up experiments with modified reporters that further strengthen their claims, and also validate the effect on native cellular transcripts (beyond reporters), demonstrating its validity also within native scenarios.

(4) The work provides a broad analysis of mRNA stability, across two mRNA regulatory segments (3'UTR and 5'UTR) and is performed in two separate cell-types. Comparison between two different cell-types is adequate, and the results demonstrate, as expected, the dependence of mRNA stability on the cellular context. Analysis of 3'UTR and 5'UTR regulatory effects also shows interesting differences and similarities between these two regulatory regions.

Weaknesses:

(1) The authors fail to acknowledge several possible confounding factors of their MPRA approach in the discussion.<br /> First, while transfection of mRNA directly into cells allows to avoid the need to normalize for differences in transcription, the introduction of naked mRNA molecules is different than native cellular mRNAs and could introduce biases due to differences in mRNA modifications, protein associations etc. that may occur co-transcriptionally.<br /> Second, along those lines, the authors also use in-vitro polyadenylation. The length of the polyA tail of the transfected transcripts could potentially be very different than that of native mRNAs and also affect stability.

(2) The analysis approach used in this work for identifying regulatory features in UTRs was not previously used. As such, lack of in-depth details of the methodology, and possibly also more general validation of the approach, is a drawback in convincing the reader in the validity of this approach and its results.<br /> In particular, a main point that is not addressed is how the authors decide on the set of "factors" used in their analysis? As choosing different sets of factors might affect the results of the analysis. For example, the choice to use 7-mer sequences within the factors set is not explained, particularly when almost all motifs that are eventually identified (Figure 3B-E) are shorter.<br /> In addition, the authors do not perform validations to demonstrate the validity of their approach on simulated data or well-established control datasets. Such analysis would be helpful to further convince the reader in the usefulness and robustness of the analysis.

(3) The analysis and regression models built in this work are not thoroughly investigated relative to native genes within cells. The effect of sequence "factors" on native cellular transcripts' stability is not investigated beyond TA di-nucleotides, and it is unclear to what degree do other predicted factors also affect native transcripts.

Reviewer #3 (Public Review):

Summary:

In this manuscript, Bimbard and colleagues describe a new implant apparatus called "Apollo Implant", which should facilitate recording in freely moving rodents (mice and rats) using Neuropixels probes. The authors collected data from both mice and rats, they used 3 different versions of Neuropixels, multiple labs have already adopted this method, which is impressive. They openly share their CAD designs and surgery protocol to further facilitate the adaptation of their method.

Strengths:

Overall, the "Apollo Implant" is easy to use and adapt, as it has been used in other laboratories successfully and custom modifications are already available. The device is reproducible using common 3D printing services and can be easily modified thanks to its CAD design (the video explaining this is extremely helpful). The weight and price are amazing compared to other systems for rigid silicon probes allowing a wide range of use of the "Apollo Implant".

Weaknesses:

The "Apollo Implant" can only handle Neuropixels probes. It cannot hold other widely used and commercially available silicon probes. Certain angles and distances are not possible in their current form (distance between probes 1.8 to 4mm, implantation depth 2-6.5 mm, or angle of insertion up to 20 degrees).

Reviewer #3 (Public Review):

Summary:

Heterochromatin is characterized by low transcription activity and late replication timing, both dependent on the NAD-dependent protein deacetylase Sir2, the founding member of the sirtuins. This manuscript addresses the mechanism by which Sir2 delays replication timing at the rDNA in budding yeast. Previous work from the same laboratory (Foss et al. PLoS Genetics 15, e1008138) showed that Sir2 represses transcription-dependent displacement of the Mcm helicase in the rDNA. In this manuscript, the authors show convincingly that the repositioned Mcms fire earlier and that this early firing partly depends on the ATPase activity of the nucleosome remodeler Fun30. Using read-depth analysis of sorted G1/S cells, fun30 was the only chromatin remodeler mutant that somewhat delayed replication timing in sir2 mutants, while nhp10, chd1, isw1, htl1, swr1, isw2, and irc5 had not effect. The conclusion was corroborated with orthogonal assays including two-dimensional gel electrophoresis and analysis of EdU incorporation at early origins. Using an insightful analysis with an Mcm-MNase fusion (Mcm-ChEC), the authors show that the repositioned Mcms in sir2 mutants fire earlier than the Mcm at the normal position in wild type. This early firing at the repositioned Mcms is partially suppressed by Fun30. In addition, the authors show Fun30 affects nucleosome occupancy at the sites of the repositioned Mcm, providing a plausible mechanism for the effect of Fun30 on Mcm firing at that position. However, the results from the MNAse-seq and ChEC-seq assays are not fully congruent for the fun30 single mutant. Overall, the results support the conclusions providing a much better mechanistic understanding how Sir2 affects replication timing at rDNA,

Strengths

(1) The data clearly show that the repositioned Mcm helicase fires earlier than the Mcm in the wild type position.<br /> (2) The study identifies a specific role for Fun30 in replication timing and an effect on nucleosome occupancy around the newly positioned Mcm helicase in sir2 cells.

Weaknesses

(1) It is unclear which strains were used in each experiment.<br /> (2) The relevance of the fun30 phospho-site mutant (S20AS28A) is unclear.<br /> (3) For some experiments (Figs. 3, 4, 6) it is unclear whether the data are reproducible and the differences significant. Information about the number of independent experiments and quantitation is lacking. This affects the interpretation, as fun30 seems to affect the +3 nucleosome much more than let on in the description.

Reviewer #3 (Public Review):

Summary: Boffi and colleagues sought to quantify the single-trial, azimuthal information in the dorsal cortex of the inferior colliculus (DCIC), a relatively understudied subnucleus of the auditory midbrain. They used two complementary recording methods while mice passively listened to sounds at different locations: a large volume but slow sampling calcium-imaging method, and a smaller volume but temporally precise electrophysiology method. They found that neurons in the DCIC were variable in their activity, unreliably responding to sound presentation and responding during inter-sound intervals. Boffi and colleagues used a naïve Bayesian decoder to determine if the DCIC population encoded sound location on a single trial. The decoder failed to classify sound location better than chance when using the raw single-trial population response but performed significantly better than chance when using intermediate principal components of the population response. In line with this, when the most azimuth dependent neurons were used to decode azimuthal position, the decoder performed equivalently to the azimuthal localization abilities of mice. The top azimuthal units were not clustered in the DCIC, possessed a contralateral bias in response, and were correlated in their variability (e.g., positive noise correlations). Interestingly, when these noise correlations were perturbed by inter-trial shuffling decoding performance decreased. Although Boffi and colleagues display that azimuthal information can be extracted from DCIC responses, it remains unclear to what degree this information is used and what role noise correlations play in azimuthal encoding.

Strengths: The authors should be commended for collection of this dataset. When done in isolation (which is typical), calcium imaging and linear array recordings have intrinsic weaknesses. However, those weaknesses are alleviated when done in conjunction with one another - especially when the data largely recapitulates the findings of the other recording methodology. In addition to the video of the head during the calcium imaging, this data set is extremely rich and will be of use to those interested in the information available in the DCIC, an understudied but likely important subnucleus in the auditory midbrain.

The DCIC neural responses are complex; the units unreliably respond to sound onset, and at the very least respond to some unknown input or internal state (e.g., large inter-sound interval responses). The authors do a decent job in wrangling these complex responses: using interpretable decoders to extract information available from population responses.

Weaknesses:<br /> The authors observe that neurons with the most azimuthal sensitivity within the DCIC are positively correlated, but they use a Naïve Bayesian decoder which assume independence between units. Although this is a bit strange given their observation that some of the recorded units are correlated, it is unlikely to be a critical flaw. At one point the authors reduce the dimensionality of their data through PCA and use the loadings onto these components in their decoder. PCA incorporates the correlational structure when finding the principal components and constrains these components to be orthogonal and uncorrelated. This should alleviate some of the concern regarding the use of the naïve Bayesian decoder because the projections onto the different components are independent. Nevertheless, the decoding results are a bit strange, likely because there is not much linearly decodable azimuth information in the DCIC responses. Raw population responses failed to provide sufficient information concerning azimuth for the decoder to perform better than chance. Additionally, it only performed better than chance when certain principal components or top ranked units contributed to the decoder but not as more components or units were added. So, although there does appear to be some azimuthal information in the recoded DCIC populations - it is somewhat difficult to extract and likely not an 'effective' encoding of sound localization as their title suggests.

Although this is quite a worthwhile dataset, the authors present relatively little about the characteristics of the units they've recorded. This may be due to the high variance in responses seen in their population. Nevertheless, the authors note that units do not respond on every trial but do not report what percent of trials that fail to evoke a response. Is it that neurons are noisy because they do not respond on every trial or is it also that when they do respond they have variable response distributions? It would be nice to gain some insight into the heterogeneity of the responses. Additionally, is there any clustering at all in response profiles or is each neuron they recorded in the DCIC unique? They also only report the noise correlations for their top ranked units, but it is possible that the noise correlations in the rest of the population are different. It would also be worth digging into the noise correlations more - are units positively correlated because they respond together (e.g., if unit x responds on trial 1 so does unit y) or are they also modulated around their mean rates on similar trials (e.g., unit x and y respond and both are responding more than their mean response rate). A large portion of trial with no response can occlude noise correlations. More transparency around the response properties of these populations would be welcome.

It is largely unclear what the DCIC is encoding. Although the authors are interested in azimuth, sound location seems to be only a small part of DCIC responses. The authors report responses during inter-sound interval and unreliable sound-evoked responses. Although they have video of the head during recording, we only see a correlation to snout and ear movements (which are peculiar since in the example shown it seems the head movements predict the sound presentation). Additional correlates could be eye movements or pupil size. Eye movement are of particular interest due to their known interaction with IC responses - especially if the DCIC encodes sound location in relation to eye position instead of head position (though much of eye-position-IC work was done in primates and not rodent). Alternatively, much of the population may only encode sound location if an animal is engaged in a localization task. Ideally, the authors could perform more substantive analyses to determine if this population is truly noisy or if the DCIC is integrating un-analyzed signals.

Although this critique is ubiquitous among decoding papers in the absence of behavioral or causal perturbations, it is unclear what - if any - role the decoded information may play in neuronal computations. The interpretation of the decoder means that there is some extractable information concerning sound azimuth - but not if it is functional. This information may just be epiphenomenal, leaking in from inputs, and not used in computation or relayed to downstream structures. This should be kept in mind when the authors suggest their findings implicate the DCIC functionally in sound localization.

It is unclear why positive noise correlations amongst similarly tuned neurons would improve decoding. A toy model exploring how positive noise correlations in conjunction with unreliable units that inconsistently respond may anchor these findings in an interpretable way. It seems plausible that inconsistent responses would benefit from strong noise correlations, simply by units responding together. This would predict that shuffling would impair performance because you would then be sampling from trials in which some units respond, and trials in which some units do not respond - and may predict a bimodal performance distribution in which some trials decode well (when the units respond) and poor performance (when the units do not respond).

Significance: Boffi and colleagues set out to parse the azimuthal information available in the DCIC on a single trial. They largely accomplish this goal and are able to extract this information when allowing the units that contain more information about sound location to contribute to their decoding (e.g., through PCA or decoding on top unit activity specifically). The dataset will be of value to those interested in the DCIC and also to anyone interested in the role of noise correlations in population coding. Although this work is first step into parsing the information available in the DCIC, it remains difficult to interpret if/how this azimuthal information is used in localization behaviors of engaged mice.

Reviewer #3 (Public Review):

In this manuscript, Pierre Ferrer and colleagues explore the exciting possibility that, in the male germ line, the composition and function of deeply conserved chromatin remodeling complexes is fine-tuned by the addition of testis-specific actin-related proteins (ARPs). In this regard, the Authors aim to extend previously reported non-canonical (transcriptional) roles of ARPs in somatic cells to the unique developmental context of the germ line. The manuscript is focused on the potential regulatory role in post-meiotic transcription of two ARPs: ACTL7A and ACTL7B (particularly the latter). The canonical function of both testis-specific ARPs in spermatogenesis is well established, as they have been previously shown to be required for the extensive cellular morphogenesis program driving post-meiotic development (spermiogenesis). Disentangling the actual functions of ACTL7A and ACTL7B as transcriptional regulators from their canonical role in the profound morphological reshaping of post-meiotic cells (a process that also deeply impacts nuclear architecture and regulation) represents a key challenge in terms of interpreting the reported findings (see below).

The authors begin by documenting, via fluorescence microscopy, the intranuclear localization of ACTL7B. This ARP is convincingly shown to accumulate in the nucleus of spermatocytes and spermatids. Using a series of elegant reporter-based experiments in a somatic cell line, the authors map the driver of this nuclear accumulation to a potential NLS sequence in the ACTL7B actin-like body domain. Ferrer and colleagues then performed a testicular RNA-seq analysis in ACTL7B KO mice to define the putative role of ACTL7B in male germ cell transcription. They report substantial changes to the testicular transcriptome - particularly the upregulation of several classes of genes - in ACTL7B KO mice. However, wild-type testes were used as controls for this experiment, thus introducing a clear confounding effect to the analysis (ACTL7B KO testes have extensive post-meiotic defects due to the canonical role of ACTL7B in spermatid development). Then, the authors employ cutting-edge AI-driven approaches to predict that both ACTL7A and ACTL7B are likely to bind to four key chromatin remodeling complexes. Although these predictions are based on a robust methodology, they would certainly benefit from experimental validation. Finally, the authors associate the loss of ACTL7B with decreased lysine acetylation and lower levels of the HDAC1 and HDAC3 chromatin remodelers in the nucleus of developing spermatids.

Globally, these data may provide important insight into the unique processes male germ cells employ to sustain their extraordinarily complex transcriptional program. Furthermore, the concept that (comparably younger) testis-specific proteins can be incorporated into ancient chromatin remodeling complexes to modulate their function in the germ line is timely and exciting.

It is my opinion that the manuscript would benefit from additional experimental validation to better support the authors' conclusions. In particular, I believe that addressing two critical points would substantially strengthen the message of the manuscript:

(1) The proposed role of ACTL7B in post-meiotic transcriptional regulation temporally overlaps with the protein's previously reported canonical functions in spermiogenesis (PMID: 36617158 and 37800308). Indeed, the canonical functions of ACTL7B have been shown to have a profound effect at the level of spermatid morphology and to impact nuclear organization. This potentially renders the observed transcriptional deregulation in ACTL7B KO testes an indirect consequence of spermatid morphology defects. I acknowledge that it is experimentally difficult to disentangle the proposed intranuclear roles of ACTL7B from the protein's well-documented cytoplasmic function. Perhaps the generation of a NLS-scrambled ACTL7B variant could offer some insight. In light of the substantial investment this approach would represent, I would suggest, as an alternative, that instead of using wild-type testes as controls for the transcriptome and chromatin localization assays, the authors consider the possibility of using testicular tissue from a mutant with similarly abnormal spermiogenesis but due to transcription-independent defects. This would, in my opinion, offer a more suitable baseline to compare ACTL7B KO testes with.

(2) The manuscript would greatly benefit if experimental validation of the AI-driven predictions were to be provided (in terms of the binding capacity of ACTL7A and ACTL7B to key chromatin remodeling complexes). More so it seems that the authors have the technical expertise / available mass spectrometry data required for this purpose (lines 664-665). Still on this topic, given the predicted interactions of ACTL7A and ACTL7B with the SRCAP, EP400, SMARCA2 and SMARCA4 complexes (Figure 7), it is rather counter-intuitive that the Authors chose for their immunofluorescence assays, in ACTL7B KO testes, to determine the chromatin localization of HDAC1 and HDAC3, rather than that of any of above four complexes.

Reviewer #3 (Public Review):

(2.1) Summary

In this paper, the authors model motor adaptation as a Bayesian process that combines visual uncertainty about the error feedback, uncertainty about proprioceptive sense of hand position, and uncertainty of predicted (=planned) hand movement with a learning and retention rate as used in state space models. The model is built with results from several experiments presented in the paper and is compared with the PReMo model (Tsay, Kim et al., 2022) as well as a cue combination model (Wei & Körding, 2009). The model and experiments demonstrate the role of visual uncertainty about error feedback in implicit adaptation.

In the introduction, the authors notice that implicit adaptation (as measured in error-clamp based paradigms) does not saturate at larger perturbations, but decreases again (e.g. Moorehead et al., 2017 shows no adaptation at 135{degree sign} and 175{degree sign} perturbations). They hypothesized that visual uncertainty about cursor position increases with larger perturbations since the cursor is further from the fixated target. This could decrease importance assigned to visual feedback which could explain lower asymptotes.

The authors characterize visual uncertainty for 3 rotation sizes in a first experiment, and while this experiment could be improved, it is probably sufficient for the current purposes. Then the authors present a second experiment where adaptation to 7 clamped errors are tested in different groups of participants. The models' visual uncertainty is set using a linear fit to the results from experiment 1, and the remaining 4 parameters are then fit to this second data set. The 4 parameters are 1) proprioceptive uncertainty, 2) uncertainty about the predicted hand position, 3) a learning rate and 4) a retention rate. The authors' Perceptual Error Adaptation model ("PEA") predicts asymptotic levels of implicit adaptation much better than both the PReMo model (Tsay, Kim et al., 2022), which predicts saturated asymptotes, or a causal inference model (Wei & Körding, 2007) which predicts no adaptation for larger rotations. In a third experiment, the authors test their model's predictions about proprioceptive recalibration, but unfortunately compare their data with an unsuitable other data set (Tsay et al. 2020, instead of Tsay et al. 2021). Finally, the authors conduct a fourth experiment where they put their model to the test. They measure implicit adaptation with increased visual uncertainty, by adding blur to the cursor, and the results are again better in line with their model (predicting overall lower adaptation), than with the PReMo model (predicting equal saturation but at larger perturbations) or a causal inference model (predicting equal peak adaptation, but shifted to larger rotations). In particular the model fits for experiment 2 and the results from experiment 4 show that the core idea of the model has merit: increased visual uncertainty about errors dampens implicit adaptation.

(2.2) Strengths

In this study the authors propose a Perceptual Error Adaptation model ("PEA") and the work combines various ideas from the field of cue combination, Bayesian methods and new data sets, collected in four experiments using various techniques that test very different components of the model. The central component of visual uncertainty is assessed in a first experiment. The model uses 4 other parameters to explain implicit adaptation. These parameters are: 1) a learning and 2) a retention rate, as used in popular state space models and the uncertainty (variance) of 3) predicted and 4) proprioceptive hand position. In particular, the authors observe that asymptotes for implicit learning do not saturate, as claimed before, but decrease again when rotations are very large and that this may have to do with visual uncertainty (e.g. Tsay et al., 2021, J Neurophysiol 125, 12-22). The final experiment confirms predictions of the fitted model about what happens when visual uncertainty is increased (overall decrease of adaptation). By incorporating visual uncertainty depending on retinal eccentricity, the predictions of the PEA model for very large perturbations are notably different from, and better than, the predictions of the two other models it is compared to. That is, the paper provides strong support for the idea that visual uncertainty of errors matters for implicit adaptation.

(2.3) Weaknesses

Although the authors don't say this, the "concave" function that shows that adaptation does not saturate for larger rotations has been shown before, including in papers cited in this manuscript.

The first experiment, measuring visual uncertainty for several rotation sizes in error-clamped paradigms has several shortcomings, but these might not be so large as to invalidate the model or the findings in the rest of the manuscript. There are two main issues we highlight here. First, the data is not presented in units that allow comparison with vision science literature. Second, the 1 second delay between movement endpoint and disappearance of the cursor, and the presentation of the reference marker, may have led to substantial degradation of the visual memory of the cursor endpoint. That is, the experiment could be overestimating the visual uncertainty during implicit adaptation.

The paper's third experiment relies to a large degree on reproducing patterns found in one particular paper, where the reported hand positions - as a measure of proprioceptive sense of hand position - are given and plotted relative to an ever present visual target, rather than relative to the actual hand position. That is, 1) since participants actively move to a visual target, the reported hand positions do not reflect proprioception, but mostly the remembered position of the target participants were trying to move to, and 2) if the reports are converted to a difference between the real and reported hand position (rather than the difference between the target and the report), those would be on the order of ~20{degree sign} which is roughly two times larger than any previously reported proprioceptive recalibration, and an order of magnitude larger than what the authors themselves find (1-2{degree sign}) and what their model predicts. Experiment 3 is perhaps not crucial to the paper, but it nicely provides support for the idea that proprioceptive recalibration can occur with error-clamped feedback.

Perhaps the largest caveat to the study is that it assumes that people do not look at the only error feedback available to them (and can explicitly suppress learning from it). This was probably true in the experiments used in the manuscript, but unlikely to be the case in most of the cited literature. Ignoring errors and suppressing adaptation would also be a disastrous strategy to use in the real world, such that our brains may not be very good at this. So the question remains to what degree - if any - the ideas behind the model generalize to experiments without fixation control, and more importantly, to real life situations.

Reviewer #3 (Public Review):

Summary

In this manuscript, Weng et al. identify the neuron specific transcriptome that impacts age dependent cognitive decline. The authors design a pipeline to profile neurons from wild type and long-lived insulin receptor/IGF-1 mutants using timepoints when memory functions are declining. They discover signatures unique to neurons which validates their approach. The authors identify that genes related to neuronal identity are lost with age in wild type worms. For example, old neurons reduce the expression of genes linked to synaptic function and neuropeptide signaling and increase the expression of chromatin regulators, insulin peptides and glycoproteins. Depletion of selected genes which are upregulated in old neurons (utx-1, ins-19 and nmgp-1) leads to improved short memory function. This indicates that some genes that increase with age have detrimental effects on learning and memory. The pipeline is then used to test neuronal profiles of long-lived insulin/IGF-1 daf-2 mutants. Genes related to stress response pathways are upregulated in long lived daf-2 mutants (e.g. dod-24, F08H9.4) and those genes are required for improved neuron function.

Strengths

The manuscript is well written, and the experiments are well described. The authors take great care to explain their reasoning for performing experiments in a specific way and guide the reader through the interpretation of the results, which makes this manuscript an enjoyable and interesting read. The authors discover novel regulators of learning and memory using neuron-specific transcriptomic analysis in aged animals, which underlines the importance of cell specific deep sequencing. The timepoints of the transcriptomic profiling are elegantly chosen, as they coincide with the loss of memory and can be used to specifically reveal gene expression profiles related to neuron function. The authors discuss on the dod-24 example how powerful this approach is. In daf-2 mutants whole-body dod-24 expression differs from neuron specific profiles, which underlines the importance of precise cell specific approaches. This dataset provides a very useful resource for the C. elegans and aging community as it complements existing datasets with additional time points and neuron specific deep profiling.

Reviewer #3 (Public Review):

Summary:

In this study, Schweibenz et al., identify the transcriptional coactivator, Taiman (Tai), as a factor that determines the fitness level of epithelial cells by regulating Wingless (Wg), which is an important determinant of cellular fitness. Taiman determines cellular fitness level by regulating levels of cell-surface glypican Dally-like protein (Dlp), which regulates extracellular Wingless (Wg) distribution. Thus, by affecting levels of Wg via glypican regulation, Tai participates in determining cellular fitness, and cells with low Tai levels are eliminated as they are deprived of adequate Wg levels.

Strengths:

(1) The authors make a strong case for the effect of tai on Dlp and Wg levels in experiments where a relatively large group of cells have reduced tai levels.<br /> (2) The claim that tai-low clones are competitively eliminated is supported by experiments that show cell death in them, and their elimination at different time points.<br /> (3) The manuscript is well written.

Weaknesses:

(1) The study has relatively weak evidence for the mechanism of cell competition mediated by Dlp and Wg.

(2) More evidence is required to support the claim that dlp transcription or endocytosis is affected in tai clones.

Other comments:

(1) The authors put the study in the context of cell competition, and the first figure indeed is convincing in this regard. However, most of the rest of the study is not in the clonal context, and mainly relies on RNAi KD of tai in the posterior compartment, which is a relatively large group of cells. I understand why the authors chose a different approach to investigate the role of tai in cell competition. However because ubiquitous loss of tai results in smaller organs, it is important to determine to what extent reducing levels of tai in the entire posterior compartment compares with clonal elimination i.e. cell competition. This is important in order to determine to what extent the paradigm of Tai-mediated regulation of Dlp levels and by extension, Wg availability, can be extended as a general mechanism underlying competitive elimination of tai-low clones. If the authors want to make a case for mechanisms involved in the competitive elimination of tai clones, then they need to show that the KD of tai in the posterior compartment shows hallmarks of cell competition. Is there cell death along the A/P boundary? Or is the compartment smaller because those cells are growing slower? Are the levels of Myc/DIAP1, proteins required for fitness, affected in en>tai RNAi cells?

2) The authors do not have direct/strong evidence of changes in dlp mRNA levels or intracellular trafficking. To back these claims, the authors should look for dlp mRNA levels and provide more evidence for Dlp endocytosis like an antibody uptake assay or at the very least, a higher resolution image analysis showing a change in the number of intracellular Dlp positive punctae. Also, do the authors think that loss of tai increases Dlp endocytosis, making it less available on the cell surface for maintaining adequate extracellular Wg levels?

3) The data shown in the last figure is at odds with the model (I think) the authors are trying to establish: When cells have lower Tai levels, this reduces Dlp levels (S2) presumably either by reducing dlp transcription and/or increasing (?) Dlp endocytosis. This in turn reduces Wg (availability) in cells away from source cells (Figure 6). The reduced Wg availability makes them less fit, targeting them for competitive elimination. But in tai clones, I do not see any change in cell-surface Dlp (9B) (I would have expected them to be down based on the proposed model). The authors also see more total Dlp (9A) (which is at odds with S2 assuming data in S2 were done under permeabilizing conditions.).

As a side note, because Dlp is GPI-anchored, the authors should consider the possibility that the 'total' Dlp staining observed in 9A may not be actually total Dlp (and possibly mostly intracellular Dlp, since the permeabilizing membranes with detergent will cause some (most?) Dlp molecules to be lost, and how this might be affecting the interpretation of the data. I think one way to address this would be to process the permeabilized and non-permeabilized samples simultaneously and then image them at the same settings and compare what membrane staining in these two conditions looks like. If membrane staining in the permeabilized condition is decreased compared to non-permeabilized conditions, and the signal intensity of Dlp in permeabilized conditions remains high, then the authors will have evidence to support increased endocytosis in tai clones. Of course, these data will still need to be reconciled with what is shown in S2.

Reviewer #3 (Public Review):

Summary:

The hippocampal CA3 region is generally considered to be the primary site of initiation of sharp wave ripples-highly synchronous population events involved in learning and memory although the precise mechanism remains elusive. A recent study revealed that CA3 comprises two distinct pyramidal cell populations: thorny cells that receive mossy fiber input from the dentate gyrus, and athorny cells that do not. That study also showed that it is athorny cells in particular that play a key role in sharp wave initiation. In the present work, Sammons, Masserini, and colleagues expand on this by examining the connectivity probabilities among and between thorny and athorny cells. First, using whole-cell patch clamp recordings, they find an asymmetrical connectivity pattern, with athorny cells receiving the most synaptic connections from both athorny and thorny cells, and thorny cells receiving fewer. They then demonstrate in spiking neural network simulations how this asymmetrical connectivity may underlie the preferential role of athorny cells in sharp wave initiation.

Strengths:

The authors provide independent validation of some of the findings by Hunt et al. (2018) concerning the distinction between thorny and athorny pyramidal cells in CA3 and advance our understanding of their differential integration in CA3 microcircuits. The properties of excitatory connections among and between thorny and athorny cells described by the authors will be key in understanding CA3 functions including, but not limited to, sharp wave initiation.

As stated in the paper, the modeling results lend support to the idea that the increased excitatory connectivity towards athorny cells plays a key role in causing them to fire before thorny cells in sharp waves. More generally, the model adds to an expanding pool of models of sharp wave ripples which should prove useful in guiding and interpreting experimental research.

Weaknesses:

The mechanism by which athorny cells initiate sharp waves in the model is somewhat confusingly described. As far as I understood, random fluctuations in the activities of A and B neurons provide windows of opportunity for pyramidal cells to fire if they have additionally recovered from adaptive currents. Thorny and athorny pyramidal cells are then set in a winner-takes-all competition which is quickly won by the athorny cells. The main thesis of the paper seems to be that athorny cells win this competition because they receive more inputs both from themselves and from thorny cells, hence, the connectivity "underlies the sequential activation". However, it is also stated that athorny cells activate first due to their lower rheobase and steeper f-I curve, and it is also indicated in the methods that athorny (but not thorny) cells fire in bursts. It seems that it is primarily these features that make them fire first, something which apparently happens even when the A to A connectivity is set to 0-albeit with a very small lag. Perhaps the authors could further clarify the differential role of single cell and network parameters in determining the sequential activation of athorny and thorny cells. Is the role of asymmetric excitatory connectivity only to enhance the initial intrinsic advantage of athorny cells? If so, could this advantage also be enhanced in other ways?

Although a clear effort has been made to constrain the model with biological data, too many degrees of freedom remain that allow the modeler to make arbitrary decisions. This is not a problem in itself, but perhaps the authors could explain more of their reasoning and expand upon the differences between their modeling choices and those of others. For example, what are the conceptual or practical advantages of using adaptation in pyramidal neurons as opposed to short-term synaptic plasticity as in the model by Hunt et al.? Relatedly, what experimental observations could validate or falsify the proposed mechanisms?

In the data by Hunt et al., thorny cells have a higher baseline (non-SPW) firing rate, and it is claimed that it is actually stochastic correlations in their firing that are amplified by athorny cells to initiate sharp waves. However, in the current model, the firing of both types of pyramidal cells outside of ripples appears to be essentially zero. Can the model handle more realistic firing rates as described by Hunt et al., or as produced by e.g., walking around an environment tiled with place cells, or would that trigger SPWs continuously?

Reviewer #3 (Public Review):

Summary:

Lichtinger et al. have used an extensive set of molecular dynamics (MD) simulations to study the conformational dynamics and transport cycle of an important member of the proton-coupled oligopeptide transporters (POTs), namely SLC15A2 or PepT2. This protein is one of the most well-studied mammalian POT transporters that provides a good model with enough insight and structural information to be studied computationally using advanced enhanced sampling methods employed in this work. The authors have used microsecond-level MD simulations, constant-PH MD, and alchemical binding free energy calculations along with cell-based transport assay measurements; however, the most important part of this work is the use of enhanced sampling techniques to study the conformational dynamics of PepT2 under different conditions.

The study attempts to identify links between conformational dynamics and chemical events such as proton binding, ligand-protein interactions, and intramolecular interactions. The ultimate goal is of course to understand the proton-coupled peptide and drug transport by PepT2 and homologous transporters in the solute carrier family.

Some of the key results include (1) Protonation of H87 and D342 initiate the occluded (Occ) to the outward-facing (OF) state transition; (2) In the OF state, through engaging R57, substrate entry increases the pKa value of E56 and thermodynamically facilitates the movement of protons further down; (3) E622 is not only essential for peptide recognition but also its protonation facilitates substrate release and contributes to the intracellular gate opening. In addition, cell-based transport assays show that mutation of residues such as H87 and<br /> D342 significantly decrease transport activity as expected from simulations.

Strengths:

(1) This is an extensive MD based study of PepT2, which is beyond the typical MD studies both in terms of the sheer volume of simulations as well as the advanced methodology used. The authors have not limited themselves to one approach and have appropriately combined equilibrium MD with alchemical free energy calculations, constant-pH MD and geometry-based free energy calculations. Each of these 4 methods provides a unique insight regarding the transport mechanism of PepT2.

(2) The authors have not limited themselves to computational work and has performed experiments as well. The cell-based transport assays clearly establish the importance of the residues that have been identified as significant contributors to the transport mechanism using simulations.

(3) The conclusions made based on the simulations are mostly convincing and provide useful information regarding the proton pathway and the role of important residues in proton binding, protein-ligand interaction, and conformational changes.

Weaknesses:

There are inherent limitations with the methodology used such as the MEMENTO and constant pH MD that have been briefly noted in the manuscript.

Reviewer #3 (Public Review):

Summary:

In this study, Wang et al. have demonstrated that TMC7, a testis-enriched multipass transmembrane protein, is essential for male reproduction in mice. Tmc7 KO male mice are sterile due to reduced sperm count and abnormal sperm morphology. TMC7 co-localizes with GM130, a cis-Golgi marker, in round spermatids. The absence of TMC7 results in reduced levels of Golgi proteins, elevated abundance of ER stress markers, as well as changes of Ca2+ and pH levels in the KO testis. However, further confirmation is required because the analyses were performed with whole testis samples in spite of the differences in the germ cell composition in WT and KO testis. In addition, the causal relationships between the reported anomalies await thorough interrogation

Strengths:

By using PD21 testes, the revised assays have consolidated that depletion of TMC7 leads to a reduced level of Ca2+ and an elevated level of ROS in the male germ cells. The immunohistochemistry analyses have clearly indicated the reduced abundance of GM130, P115, and GRASP65 in the knockout testis.

Weaknesses:

The Discussion section contains sentences reiterating the Introduction and Results of this manuscript (e.g., Lines 79-85 and 231-236; Lines 175-179 and 259-263). Those read repetitive and can be removed.

Future studies are required to decipher how TMC7 stabilizes Golgi structure, coordinates vesicle transport, and maintains the germ cell homeostasis.

Reviewer #3 (Public Review):

The superfamily I 3'-5' DNA helicase Srs2 is well known for its role as an anti-recombinase, stripping Rad51 from ssDNA, as well as an anti-crossover factor, dissociating extended D-loops and favoring non-crossover outcome during recombination. In addition, Srs2 plays a key role in ribonucleotide excision repair. Besides DNA repair defects, srs2 mutants also show a reduced recovery after DNA damage that is related to its role in downregulating the DNA damage signaling or checkpoint response. Recent work from the Zhao laboratory (PMID: 33602817) identified a role of Srs2 in downregulating the DNA damage signaling response by removing RPA from ssDNA. This manuscript reports further mechanistic insights into the signaling downregulation function of Srs2.

Using the genetic interaction with mutations in RPA1, mainly rfa1-zm2, the authors test a panel of mutations in Srs2 that affect CDK sites (srs2-7AV), potential Mec1 sites (srs2-2SA), known sumoylation sites (srs2-3KR), Rad51 binding (delta 875-902), PCNA interaction (delta 1159-1163), and SUMO interaction (srs2-SIMmut). All mutants were generated by genomic replacement and the expression level of the mutant proteins was found to be unchanged. This alleviates some concern about the use of deletion mutants compared to point mutations. The double mutant analysis identified that PCNA interaction and SUMO sites were required for the Srs2 checkpoint dampening function, at least in the context of the rfa1-zm2 mutant. There was no effect of these mutants in a RFA1 wild-type background. This latter result is likely explained by the activity of the parallel pathway of checkpoint dampening mediated by Slx4, and genetic data with an Slx4 point mutation affecting Rtt107 interaction and checkpoint downregulation support this notion. Further analysis of Srs2 sumoylation showed that Srs2 sumoylation depended on PCNA interaction, suggesting sequential events of Srs2 recruitment by PCNA and subsequent sumoylation. Kinetic analysis showed that sumoylation peaks after maximal Mec1 induction by DNA damage (using the Top1 poison camptothecin (CPT)) and depended on Mec1. These data are consistent with a model that Mec1 hyperactivation is ultimately leading to signaling downregulation by Srs2 through Srs2 sumoylation. Mec1-S1964 phosphorylation, a marker for Mec1 hyperactivation and a site found to be needed for checkpoint downregulation after DSB induction did not appear to be involved in checkpoint downregulation after CPT damage. The data are in support of the model that Mec1 hyperactivation when targeted to RPA-covered ssDNA by its Ddc2 (human ATRIP) targeting factor, favors Srs2 sumoylation after Srs2 recruitment to PCNA to disrupt the RPA-Ddc2-Mec1 signaling complex. Presumably, this allows gap filling and disappearance of long-lived ssDNA as the initiator of checkpoint signaling, although the study does not extend to this step.

Strengths

(1) The manuscript focuses on the novel function of Srs2 to downregulate the DNA damage signaling response and provide new mechanistic insights.

(2) The conclusions that PCNA interaction and ensuing Srs2-sumoylation are involved in checkpoint downregulation are well supported by the data.

Weaknesses

(1) Additional mutants of interest could have been tested, such as the recently reported Pin mutant, srs2-Y775A (PMID: 38065943), and the Rad51 interaction point mutant, srs2-F891A (PMID: 31142613).

(2) The use of deletion mutants for PCNA and RAD51 interaction is inferior to using specific point mutants, as done for the SUMO interaction and the sites for post-translational modifications.

(3) Figure 4D and Figure 5A report data with standard deviations, which is unusual for n=2. Maybe the individual data points could be plotted with a color for each independent experiment to allow the reader to evaluate the reproducibility of the results.

Reviewer #3 (Public Review):

Summary:

The authors elucidated the role of USP8 in the endocytic pathway. Using C. elegans epithelial cells as a model, they observed that when USP8 function is lost, the cells have a decreased number and size in lysosomes. Since USP8 was already known to be a protein linked to ESCRT components, they looked into what role USP8 might play in connecting lysosomes and multivesicular bodies (MVB). They observed fewer ESCRT-associated vesicles but an increased number of "abnormal" enlarged vesicles when USP8 function was lost. Then they observed that the abnormally enlarged vesicles, marked by the PI3P biosensor YFP-2xFYVE, are bigger but in the same number in USP8 (-) compared to wild-type animals, suggesting homotypic fusion. They confirmed this result by knocking down USP8 in a human cell line, and they observed enlarged vesicles marked by YFP-2xFYVE as well. They finally propose that USP8 dissociates Rabx-5 from early endosomes facilitating endosome maturation.

Strengths:

The authors have created significant, multifaceted tools for investigating systems involved in endosome dynamics control in both worm and human cells, which will help many members of the cell biology community. The study discovered an intriguing relationship between USP8 and the Rab5 guanine nucleotide exchange factor Rabx5, expanding USP8's targets and modes of action. The results provide significant contributions to our knowledge of how endosomal maturation works.

Weaknesses:

The rationales could have been stated clearer to help the readers.

Reviewer #3 (Public Review):

Summary:

This manuscript reveals an important mechanism of KCNQ1/IKs channel gating such that the open state of the pore is unstable and undergoes intermittent closed and open conformations. PUFA enhances the maximum open probability of IKs by binding to a crevice adjacent to the pore and stabilize the open conformation. This mechanism is supported by convincing single channel recordings that show empty and open channel traces and the ratio of such traces is affected by PUFA. In addition, mutations of the pore residues alter PUFA effects, convincingly supporting that PUFA alters the interactions among these pore residues.

Strengths:

The data are of high quality and the description is clear.

Reviewer #3 (Public Review):

Summary:

Mimura et al describe the discovery of the orphan transporter SLC35G1 as a citrate transporter in the small intestine. Using a combination of cellular transport assays, they show that SLC35G1 can mediate citrate transport in small intestinal cell lines. Furthermore, they investigate its expression and localization in both human tissue and cell lines. Limited evidence exists to date on both SLC35G1 and citrate uptake in the small intestine, therefore this study is an important contribution to both fields. However, the main claims by the authors are only partially supported by experimental evidence.

Strengths:

The authors convincingly show that SLC35G1 mediates uptake of citrate which is dependent on pH and chloride concentration. Putting their initial findings in a physiological context, they present human tissue expression data of SLC35G. Their Transwell assay indicates that SLC35G1 is a citrate exporter at the basolateral membrane.

Weaknesses:

Further confirmation and clarification are required to claim that the SLC indeed exports citrate at the basolateral membrane as concluded by the authors. Most experiments measure citrate uptake, but the authors state that SLC35G1 is an exporter, mostly based on the lack of uptake at physiological conditions faced at the basolateral side. The Transwell assay in Figure 1L is the only evidence that it indeed is an exporter. However, in this experiment, the applied chloride concentration was not according to the proposed model (120mM at the basolateral side). The Transwell assay, or a similar assay measuring export instead of import, should be carried out in knockdown cells to prove that the export indeed occurs through SLC35G1 and not through an indirect effect. Related to the mentioned chloride sensitivity, it is unclear how the proposed model works if the SLC faces high chloride conditions under physiological conditions though it is inhibited by chloride.

Reviewer #3 (Public Review):

Summary:

Overall, this is an interesting series of experiments which have identified a putative inhibitor of the Plasmodium M1 alanyl aminopeptidases, PfA-M1 and PvA-M1. The weaknesses include the lack of additional analysis of additional targets identified in the chemoproteomic approaches.

Strengths:

The main strengths include the synthesis of MIPS2673 which is selectively active against the enzyme and in whole cell assay.

Weaknesses:

The authors have addressed the previously identified weaknesses and have now provided additional data and explanations. They have modified their conclusions to indicate the limitations of their work.

Reviewer #3 (Public Review):

Summary:

This study profiled the single-cell transcriptome of human spermatogenesis and provided many potential molecular markers for developing testicular puncture-specific marker kits for NOA patients.

Strengths:

Perform single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) on testicular tissues from two OA patients and three NOA patients.

Weaknesses:

Most results are analytical and lack specific experiments to support these analytical results and hypotheses.

Reviewer #3 (Public Review):

Summary:

This manuscript by Beardslee and Schmitz reports discoveries made from a genetic screen to identify C-terminal degrons that cause the efficient depletion of a potent toxin, which allowed for a deep assessment of amino acid patterns that promote protein turnover.

Strengths:

The key findings are that SsrA-like C termini are a dominant class of efficient degrons and that ClpP (X/A) mediates the turnover in most cases. Moreover, the data provides insight into the importance of residues situated farther into the degron and reveals aspects of the ClpX engagement and processivity process. The manuscript is clearly written and there is ample supporting data for the conclusions drawn. The figures are also informative.

Weaknesses:

There are only a few minor suggestions on data interpretation.

(1) Page 6: It is stated that "We plated cells on media containing 0 - 1% arabinose inducer, and observed that stronger induction of untagged VapC indeed correlates with smaller colony size; ... We conclude that VapC levels have a titratable effect on growth rate."

In E. coli with intact arabinose import/response systems, sub-saturating levels of arabinose do not generally lower the induction level of the PBAD promoter in each cell; rather, a sub-population of cells becomes induced [PMID: 9223333]. The bulk observation is a reduced expression level, and, in this case, slowed growth, but it seems more likely that the slow growth observed is from the induced cohort dying off as the cultures and colonies develop.

(2) Page 8: "At 6-hours post-induction,..."

Because these experiments were enrichments from initial pools of clones, the number of cell divisions is more informative than the hours of outgrowth or culture densities at harvest. It would be helpful if the authors could indicate, or at least estimate, the number of cell divisions. this could then be included in the results or methods section.

(3) Page 12: "It is possible that these sequences compromise VapC folding and solubility, or mimic inhibitory interactions made by hydrophobic segments of the VapB antitoxin that block VapC activity (43, 59)."

Later in the manuscript, Lon is presented as a minor player in the overall story, but Lon prefers hydrophobic degrons. Could that hydrophobic class be Lon substrates? (Possibly presented as an additional mechanism here or in the discussion of this class of tags.)

(4) Page 13: "Arg in the 2nd position was also associated with proteolysis, yet Arg is virtually absent from proteobacterial ssrA sequences."

The nucleic acid changes required for evolutionary drift from the predominant amino acid codons at this position in proteobacteria to Arg may require moving through several codons that notably impair the performance of the degron. Such a constraint may also be responsible, in part, for the observed conservation.

Reviewer #3 (Public Review):

I very much enjoyed reading Lingxiu Xu et al.'s paper "Temporally controlled nervous system-to-gut signaling bidirectionally regulates longevity in C. elegans," where they investigate the mechanisms by which motor neurons regulate lifespan in C. elegans worms. In this paper, they first discover that interfering with synaptic release in cholinergic motor neurons affects lifespan. Using mutants and gene knockdowns they show that these effects are due to the neurotransmitter acetylcholine. They show that the effects of these motor neurons on lifespan are opposite, depending on timed genetic interventions promoting synaptic release. If these interventions occur during development, the lifespan is shortened, but if they occur starting on day 7 of adulthood, then lifespan is lengthened. They then show that the transcription factor daf-16 is required for the former effect, while the transcription factor hsf-1 is required for the latter one. In addition, these early and late effects, they find, required the acetylcholine receptors acr-6 and gar-3, respectively, and intestinal expression of these genes rescues the respective phenotypes. Interestingly, tagging the endogenous acr-6 and gar-3 genes with mCherry, they find that the ACR-6 and GAR-3 proteins are expressed in the intestine, ACR-6 during development, and GAR-3 during adulthood. Based on these findings they propose a model where acetylcholine from motor neurons regulates lifespan by modulating different receptors expressed at different times. These receptors, in turn, affect lifespan in opposing ways via different transcription factors.

Reviewer #3 (Public Review):

Summary:

The authors presented a data-centric ML approach for virtual ligand screening. They used BRAF as an example to demonstrate the predictive power of their approach.

Strengths:

The performance of predictive models in this study is superior (nearly perfect) with respect to exiting methods.

Weaknesses:

I feel the training and testing datasets may not be rigorously constructed. If that is the case, the results would be significantly affected.

I have 3 major comments:

(1) The authors identified ~4100 BRAF actives, then randomly selected 3600 BRAF actives to be part of the training dataset with the remaining 500 actives becoming a part of the hold-out test set. The problem is that, the authors did not evaluate the chemical similarity between the 3600 actives in the training, and the 500 actives in the testing set. If some of them were similar, the testing results would be very good but partially due to information leakage. The authors should carefully examine the chemical similarity between any pairs of their training and testing datasets, before any conclusion is made.

(2) The authors tried to explore the role of dataset size in the performance, in particular, what would happen when the number of actives are reduced. However the minimal number of actives used is 500 while the number of inactives ranges from 500 to 3600. This is quite different from real applications where the number of expected actives in the screening library would be at most 1-2% of the whole database. The authors should further reduced the number of actives (e.g. 125, 25, 5, 1), and evaluate their model's performance.

(3) The authors chose BRAF as example in this study. BRAF is a well studied drug target with thousands of known actives. In real applications, the target may only have a handful of known actives. The authors should try to apply their approach, to a couple other targets that have less known actives than BRAF, to evaluate their method's transferability.

DOI: 10.1038/s41467-023-42626-3

Resource: Bloomington Drosophila Stock Center (RRID:SCR_006457)

Curator: @maulamb

SciCrunch record: RRID:SCR_006457

What is this?

Reviewer #3 (Public Review):

The study presents strong evidence for allosteric activation of plant receptor kinases, which enhances our understanding of the non-catalytic mechanisms employed by this large family of receptors.

Plant receptor kinases (RKs) play a critical role in transducing extracellular signals. The activation of RKs involves homo- or heterodimerization of the RKs, and it is believed that mutual phosphorylation of their intracellular kinase domains initiates downstream signaling. However, this model faces a challenge in cases where the kinase domain exhibits pseudokinase characteristics. In their recent study, Mühlenbeck et al. reveal the non-catalytic activation mechanisms of the EFR-BAK1 complex in plant receptor kinase signaling. Specifically, they aimed to determine that the EFR kinase domain activates BAK1 not through its kinase activity, but rather by utilizing a "conformational toggle" mechanism to enter an active-like state, enabling allosteric trans-activation of BAK1. The study sought to elucidate the structural elements and mutations of EFR that affect this conformational switch, as well as explore the implications for immune signaling in plants. To investigate the activation mechanisms of the EFR-BAK1 complex, the research team employed a combination of mutational analysis, structural studies, and hydrogen-deuterium exchange mass spectrometry (HDX-MS) analysis. For instance, through HDX-MS analysis, Mühlenbeck et al. discovered that the EFR (Y836F) mutation impairs the accessibility of the active-like conformation. On the other hand, they identified the EFR (F761H) mutation as a potent intragenic suppressor capable of stabilizing the active-like conformation, highlighting the pivotal role of allosteric regulation in BAK1 kinase activation. The data obtained from this methodology strengthens their major conclusion. Moreover, the researchers propose that the allosteric activation mechanism may extend beyond the EFR-BAK1 complex, as it may also be partially conserved in the Arabidopsis LRR-RK XIIa kinases. This suggests a broader role for non-catalytic mechanisms in plant RK signaling.

The allosteric activation mechanism was demonstrated for receptor tyrosine kinases (RTKs) many years ago. A similar mechanism has been suggested for the activation of plant RKs, but experimental evidence for this conclusion is lacking. Data in this study represent a significant advancement in our understanding of non-catalytic mechanisms in plant RK signaling. By shedding light on the allosteric regulation of BAK1, the study provides a new paradigm for future research in this area.

Reviewer #3 (Public Review):

Summary:

The authors report a new version of the iSuRe-Cre approach, which was originally developed by Rui Benedito's group in Spain (https://doi.org/10.1038/s41467-019-10239-4). Shi et al claim that their approach shows reduced leakiness compared to the iSuRe-Cre line. Shi et al elaborate strongly about the leakiness of iSuRe-Cre mice, although leakiness is rather minor according to the original publication and the senior author of the study wrote in a review a few years ago that there is no leakiness (https://doi.org/10.1016/j.jbc.2021.100509). Furthermore, a new R26-roxCre-tdT mouse line was established after extensive testing, which enables efficient expression of the Cre recombinase after activation of the Dre recombinase.

Strengths:

The authors carefully evaluated the efficiency and leakiness of the new strains and demonstrated the applicability by marking peri-central hepatocytes in an intersectional genetics approach, amongst others. I can only find very few weaknesses in the paper, which represents the result of an enormous effort. Carefully conducted technical studies have considerable value. However, I would have preferred to see a study, which uses the wonderful new tools to address a major biological question, rather than a primarily technical report, which describes the ongoing efforts to further improve Cre and Dre recombinase-mediated recombination.

Weaknesses:

Very high levels of Cre expression may cause toxic effects as previously reported for the hearts of Myh6-Cre mice. Thus, it seems sensible to test for unspecific toxic effects, which may be done by bulk RNA-seq analysis, cell viability, and cell proliferation assays. It should also be analyzed whether the combination of R26-roxCre-tdT with the Tnni3-Dre allele causes cardiac dysfunction, although such dysfunctions should be apparent from potential changes in gene expression.

The R26-GFP or R26-tdT reporters, Alb-roxCre1-tdT, Cdh5-roxCre4-tdT, Alb-roxCre7-GFP, and Cdh5-roxCre10-GFP demonstrate no leakiness without Dre-rox recombination (Figure S1-S2). Is there any leakiness when the inducible DreER allele is introduced but no tamoxifen treatment is applied? This should be documented. The same also applies to loxCre mice.

The enhanced efficiency of loxCre and roxCre systems holds promise for reducing the necessary tamoxifen dosage, potentially reducing toxicity and side effects. In Figure 6, the author demonstrates an enhanced recombination efficiency of loxCre mice, which makes it possible to achieve efficient deletion of Ctnnb1 with a single dose of tamoxifen, whereas a conventional driver (Alb-CreER) requires five dosages. It would be very helpful to include a dose-response curve for determining the minimum dosage required in Alb-CreER; R26-loxCre-tdT; Ctnnb1flox/flox mice for efficient recombination.

In the liver panel of Figure 4F, tdT signals do not seem to colocalize with the VE-cad signals, which is odd. Is there any compelling explanation?

The authors claim that "virtually all tdT+ endothelial cells simultaneously expressed YFP/mCFP" (right panel of Figure 5D). Well, it seems that the abundance of tdT is much lower compared to YFP/mCFP. If the recombination of R26-Confetti was mainly triggered by R26-loxCre-tdT, the expression of tdT and YFP/mCFP should be comparable. This should be clarified.

In several cases, the authors seem to have mixed up "R26-roxCre-tdT" with "R26-loxCre-tdT". There are errors in #251 and #256. Furthermore, in the passage from line #278 to #301. In the lines #297 and #300 it should probably read "Alb-CreER; R26-loxCre-tdT;Ctnnb1flox/flox"" rather than "Alb-CreER;R26-tdT2;Ctnnb1flox/flox".

Reviewer #3 (Public Review):

Summary:

This manuscript looks at the single-cell spike signatures taken from in vivo cerebellar nuclear neurons from awake mice suffering from 3 distinct diseases and uses a sophisticated classifier model to predict disease based on a number of different parameters about the spiking patterns, rather than just one or two. Single read-outs of spike firing patterns did not show significant differences between all 4 groups meaning that you need to analyze multiple parameters of the spike trains to get this information. The results are really satisfying and intriguing, with some diseases separating very well, and others having more overlap. It also represents a significant advancement for the rigor and creativity used for analyzing cerebellar output spike patterns. I really like this paper, it's a clever idea and has been done very well.

The authors examine multiple distinct forms of different diseases, including different types of ataxia, dystonia, and tremor. While some of the interpretation of this work remains unclear to this reviewer (in particular Fig. 2, with ataxia models), I applaud the rigor, and sharing complex data that is not always straightforward to understand.

Strengths:

The work is technically impressive and the analysis pushes the envelope of how cerebellar dysfunction is classified, which makes it an important paper for the field.<br /> It's well written. The approach it is taking is clever. The analysis is thorough, and the authors examine a wide array of different disease models, which is time-consuming, costly, and very challenging to do. It's a very strong manuscript.

Reviewer #3 (Public Review):

Summary:

The authors investigated that learning processes relied on distinct reward or punishment outcomes in probabilistic instrumental learning tasks were involved in functional interactions of two different cortico-cortical gamma-band modulations, suggesting that learning signals like reward or punishment prediction errors can be processed by two dominated interactions, such as areas lOFC-vmPFC and areas aINS-dlPFC, and later on integrated together in support of switching conditions between reward and punishment learning. By performing the well-known analyses of mutual information, interaction information, and transfer entropy, the conclusion was accomplished by identifying directional task information flow between redundancy-dominated and synergy-dominated interactions. Also, this integral concept provided a unifying view to explain how functional distributed reward and/or punishment information were segregated and integrated across cortical areas.

Strengths:

The dataset used in this manuscript may come from previously published works (Gueguen et al., 2021) or from the same grant project due to the methods. Previous works have shown strong evidence about why gamma-band activities and those 4 areas are important. For further analyses, the current manuscript moved the ideas forward to examine how reward/punishment information transfer between recorded areas corresponding to the task conditions. The standard measurements such mutual information, interaction information, and transfer entropy showed time-series activities in the millisecond level and allowed us to learn the directional information flow during a certain window. In addition, the diagram in Figure 6 summarized the results and proposed an integral concept with functional heterogeneities in cortical areas. These findings in this manuscript will support the ideas from human fMRI studies and add a new insight to electrophysiological studies with the non-human primates.

Comments on revised version:

Thank you authors for all efforts to answer questions from previous comments. I appreciated that authors clarified the terminology and added a paragraph to discuss the current limitations of functional connectivity and anatomical connections. This provided clear and fair explanations to readers who are not familiar with methods in systems neuroscience.

Reviewer #3 (Public Review):

Summary:

There is a growing body of literature on the clustering of co-active synapses in adult mice, which has important implications for understanding dendritic integration and sensory processing more broadly. However, it has been unclear when this spatial organization of co-active synapses arises during development. In this manuscript, Leighton et al. investigate the emergence of spatially organized, co-active synapses on pyramidal dendrites in the mouse visual cortex before eye opening. They find that some dendrite segments contain highly active synapses that are co-active with their neighbors as early as postnatal day (P) 8-10, and that these domains of co-active synapses increase their coverage of the dendritic arbor by P12-13. Interestingly, Leighton et al. demonstrate that synapses co-active with their neighbors are more likely to increase their activity across a single recording session, compared to synapses that are not co-active with their neighbors, suggesting local plasticity driven by coincident activity before eye opening.

The current manuscript includes some replication of earlier results from the same research group (Winnubst et al., 2015), including the presence of clustered, co-active synapses in the visual cortex of mouse pups, and the finding that synapses co-active with their neighbors show an increase in transmission frequency during a recording session. The main novelty in the current study compared to Winnubst et al. (2015) is the inclusion of younger animals (P8-13 in the current study compared to P10-15 in Winnubst et al., 2015). The current manuscript is the first demonstration that active synapses are clustered on specific dendrite segments as early as P8-10 in the mouse visual cortex, and the first to show the progression in active synapse distribution along the dendrite during the 2nd postnatal week. These results from visual cortex may help inform our understanding of sensory development more broadly.

Strengths:

The authors ask a novel question about the emergence of synaptic spatial organization, and they use well-chosen techniques that directly address their questions despite the challenging nature of these techniques. To capture both structural and functional information from dendrites simultaneously, the authors performed whole-cell voltage clamp to record synaptic currents arriving at the soma while imaging calcium influx at individual synaptic sites on dendrites. The simultaneous voltage clamp and calcium imaging allowed the authors to isolate individual synaptic inputs without their occlusion by widespread calcium influx from back-propagating action potentials. Achieving in vivo dendrite imaging in live mice that are as young as P8 is challenging, and the resulting data provides a unique view of synaptic activity along individual dendrites in the visual cortex at an early stage in development that is otherwise difficult to assess.<br /> The authors provide convincing evidence that synapses are more likely to be co-active with their neighbors compared to synapses located farther away (Fig. 6F-H), and that synapses co-active with their neighbors increase their transmission frequency during a recording session (Fig. 7C). These findings are particularly interesting given that the recordings occur before eye opening, suggesting a relationship between co-activity and local synaptic plasticity even before the onset of detailed visual input. These results replicate previously published findings from P10-15 pups (Winnubst et al., 2015), increasing confidence in the reproducibility of the data.<br /> The authors also provide novel data documenting for the first time spatially organized, co-active synapses in pups as young as P8. Comparing the younger (P8-10) and older (P12-13) pups, provides insight into how clusters of co-active synapses might emerge during development.

Weaknesses:

The P8-10 vs P12-13 age comparisons are the primary novel finding in this manuscript, and it is therefore critical to avoid systematic age differences in the methods and analysis whenever possible. In their rebuttal and revised manuscript the authors have acceptably addressed prior concerns regarding this important point, as well as most of the other methodological issues raised.<br /> One point addressed in the rebuttal, but not corrected in the manuscript relates to the reliable localization of cells to visual cortex.

Reviewer #3 (Public Review):

Summary:

In this article, the authors combine a well-established choice-response time (RT) model (the Linear Ballistic Accumulator) with a CNN model of visual processing to model image-based decisions (referred to as the Visual Accumulator Model - VAM). While this is not the first effort to combine these modeling frameworks, it uses this combination of approaches uniquely. Specifically, the authors attempt to better understand the structure of human information representations by fitting this model to behavioral (choice-RT) data from a classic flanker task. This objective is made possible by using a very large (by psychological modeling standards) industry data set to jointly fit both components of this VAM model to individual-level data. Using this approach, they illustrate (among other results) (1) how the interaction between target and flanker representations influence the presence and strength of congruency effects, (2) how the structure of representations changes (distributed versus more localized) with depth in the CNN model component, and (3) how different model training paradigms change the nature of information representations. This work contributes to the ML literature by demonstrating the value of training models with richer behavioral data. It also contributes to cognitive science by demonstrating how ML approaches can be integrated into cognitive modeling. Finally, it contributes to the literature on conflict modeling by illustrating how information representations may lead to some of the classic effects observed in this area of research.

Strengths:

(1) The data set used for this analysis is unique and is made publicly available as part of this article. Specifically, they have access to data for 75 participants with >25,000 trials per participant. This scale of data/individual is unusual and is the foundation on which this research rests.

(2) This is the first time, to my knowledge, that a model combining a CNN with a choice-RT model has been jointly fit to choice-RT data at the level of individual people. This type of model combination has been used before but in a more restricted context. This joint fitting, and in particular, learning a CNN through the choice-RT modeling framework, allows the authors to probe the structure of human information representations learned directly from behavioral data.

(3) The analysis approaches used in this article are state-of-the-art. The training of these models is straightforward given the data available. The interesting part of this article (opinion of course) is the way in which they probe what CNN has learned once trained. I find their analysis of how distractor and target information interfere with each other particularly compelling as well as their demonstration that training on behavioral data changes the structure of information representations when compared to training models on standard task-optimized data.

Weaknesses:

(1) Just as the data in this article is a major strength, it is also a weakness. This type of modeling would be difficult, if not impossible to do with standard laboratory data. I don't know what the data floor would be, but collecting tens of thousands of decisions for a single person is impractical in most contexts. Thus this type of work may live in the realm of industry. I do want to re-iterate that the data for this study was made publicly available though!

2) While this article uses choice-RT data it doesn't fully leverage the richness of the RT data itself. As the authors point out, this modeling framework, the LBA component in particular, does not account for some of the more nuanced but well-established RT effects in this data. This is not a big concern given the already nice contributions of this article and it leads to an opportunity for ongoing investigation.

Reviewer #3 (Public Review):

Summary:

Pyruvate kinase M2 (PKM2) is a rate-limiting enzyme in glycolysis and its translocation to the nucleus in astrocytes in various nervous system pathologies has been associated with a metabolic switch to glycolysis which is a sign of reactive astrogliosis. The authors investigated whether this occurs in experimental autoimmune encephalomyelitis (EAA), an animal model of multiple sclerosis (MS). They show that in EAA, PKM2 is ubiquitinated by TRIM21 and transferred to the nucleus in astrocytes. Inhibition of TRIM21-PKM2 axis efficiently blocks reactive gliosis and partially alleviates symptoms of EAA. Authors conclude that this axis can be a potential new therapeutic target in the treatment of MS.

Strengths:

The study is well-designed, controls are appropriate and a comprehensive battery of experiments has been successfully performed. Results of in vitro assays, single-cell RNA sequencing, immunoprecipitation, RNA interference, molecular docking, and in vivo modeling etc. complement and support each other.

Weaknesses:

Though EAA is a valid model of MS, a proposed new therapeutic strategy based on this study needs to have support from human studies.

Reviewer #3 (Public Review):

Summary:

This is a proposal for a new theory for the geometry of insect eyes. The novel cost-benefit function combines the cost of the optical portion with the photoreceptor portion of the eye. These quantities are put on the same footing using a specific (normalized) volume measure, plus an energy factor for the photoreceptor compartment. An optimal information transmission rate then specifies each parameter and resource allocation ratio for a variable total cost. The elegant treatment allows for comparison across a wide range of species and eye types. Simple eyes are found to be several times more efficient across a range of eye parameters than neural superposition eyes. Some trends in eye parameters can be explained by optimal allocation of resources between the optics and photoreceptors compartments of the eye.

Strengths:

Data from a variety of species roughly align with rough trends in the cost analysis, e.g. as a function of expanding the length of the photoreceptor compartment.

New data could be added to the framework once collected, and many species can be compared.

Eyes of different shapes are compared.

Weaknesses:

Detailed quantitative conclusions are not possible given the approximations and simplifying assumptions in the models and poor accounting for trends in the data across eye types.

Reviewer #3 (Public Review):

Summary:

In this manuscript, Mehrhof and Nord study a large dataset of participants collected online (n=958 after exclusions) who performed a simple effort-based choice task. They report that the level of effort and reward influence choices in a way that is expected from prior work. They then relate choice preferences to neuropsychiatric syndromes and, in a smaller sample (n<200), to people's circadian preferences, i.e., whether they are a morning-preferring or evening-preferring chronotype. They find relationships between the choice bias (a model parameter capturing the likelihood to accept effort-reward challenges, like an intercept) and anhedonia and apathy, as well as chronotype. People with higher anhedonia and apathy and an evening chronotype are less likely to accept challenges (more negative choice bias). People with an evening chronotype are also more reward sensitive and more likely to accept challenges in the evening, compared to the morning.

Strengths:

This is an interesting and well-written manuscript which replicates some known results and introduces a new consideration related to potential chronotype relationships which have not been explored before. It uses a large sample size and includes analyses related to transdiagnostic as well as diagnostic criteria. I have some suggestions for improvements.

Weaknesses:

(1) The novel findings in this manuscript are those pertaining to transdiagnostic and circadian phenotypes. The authors report two separate but "overlapping" effects: individuals high on anhedonia/apathy are less willing to accept offers in the task, and similarly, individuals tested off their chronotype are less willing to accept offers in the task. The authors claim that the latter has implications for studying the former. In other words, because individuals high on anhedonia/apathy predominantly have a late chronotype (but might be tested early in the day), they might accept less offers, which could spuriously look like a link between anhedonia/apathy and choices but might in fact be an effect of the interaction between chronotype and time-of-testing. The authors therefore argue that chronotype needs to be accounted for when studying links between depression and effort tasks.<br /> The authors argue that, if X is associated with Y and Z is associated with Y, X and Z might confound each other. That is possible, but not necessarily true. It would need to be tested explicitly by having X (anhedonia/apathy) and Z (chronotype) in the same regression model. Does the effect of anhedonia/apathy on choices disappear when accounting for chronotype (and time-of-testing)? Similarly, when adding the interaction between anhedonia/apathy, chronotype, and time-of-testing, within the subsample of people tested off their chronotype, is there a residual effect of anhedonia/apathy on choices or not?<br /> If the effect of anhedonia/apathy disappeared (or got weaker) while accounting for chronotype, this result would suggest that chronotype mediates the effect of anhedonia/apathy on effort choices. However, I am not sure it renders the direct effect of anhedonia/apathy on choices entirely spurious. Late chronotype might be a feature (induced by other symptoms) of depression (such as fatigue and insomnia), and the association between anhedonia/apathy and effort choices might be a true and meaningful one. For example, if the effect of anhedonia/apathy on effort choices was mediated by altered connectivity of the dorsal ACC, we would not say that ACC connectivity renders the link between depression and effort choices "spurious", but we would speak of a mechanism that explains this effect. The authors should discuss in a more nuanced way what a significant mediation by the chronotype/time-of-testing congruency means for interpreting effects of depression in computational psychiatry.

(2) It seems that all key results relate to the choice bias in the model (as opposed to reward or effort sensitivity). It would therefore be helpful to understand what fundamental process the choice bias is really capturing in this task. This is not discussed, and the direction of effects is not discussed either, but potentially quite important. It seems that the choice bias captures how many effortful reward challenges are accepted overall which maybe captures general motivation or task engagement. Maybe it is then quite expected that this could be linked with questionnaires measuring general motivation/pleasure/task engagement. Formally, the choice bias is the constant term or intercept in the model for p(accept), but the authors never comment on what its sign means. If I'm not mistaken, people with higher anhedonia but also higher apathy are less likely to accept challenges and thus engage in the task (more negative choice bias). I could not find any discussion or even mention of what these results mean. This similarly pertains to the results on chronotype. In general, "choice bias" may not be the most intuitive term and the authors may want to consider renaming it. Also, given the sign of what the choice bias means could be flipped with a simple sign flip in the model equation (i.e., equating to accepting more vs accepting less offers), it would be helpful to show some basic plots to illustrate the identified differences (e.g., plotting the % accepted for people in the upper and lower tertile for the SHAPS score etc).

(3) None of the key effects relate to effort or reward sensitivity which is somewhat surprising given the previous literature and also means that it is hard to know if choice bias results would be equally found in tasks without any effort component. (The only analysis related to effort sensitivity is exploratory and in a subsample of N=56 per group looking at people meeting criteria for MDD vs matched controls.) Were stimuli constructed such that effort and reward sensitivity could be separated (i.e., are uncorrelated/orthogonal)? Maybe it would be worth looking at the % accepted in the largest or two largest effort value bins in an exploratory analysis. It seems the lowest and 2nd lowest effort level generally lead to accepting the challenge pretty much all the time, so including those effort levels might not be sensitive to individual difference analyses?

(4) The abstract and discussion seem overstated (implications for the school system and statements on circadian rhythms which were not measured here). They should be toned down to reflect conclusions supported by the data.

Reviewer #3 (Public Review):

Summary:

The authors provide compelling evidence for the causal role of the subthalamic nucleus (STN) in perceptual decision-making. By recording from a large number of STN neurons and using microstimulation, they demonstrate the STN's involvement in setting decision bounds, scaling evidence accumulation, and modulating non-decision time.

Strengths:

The study tested three hypotheses about the STN's function and identified distinct STN subpopulations whose activity patterns support predictions from previous computational models. The experiments are well-designed, the analyses are rigorous, and the results significantly advance our understanding of the STN's multi-faceted role in decision formation.

Weaknesses:

While the study provides valuable insights into the STN's role in decision-making, there are a few areas that could be improved. First, the interpretation of the neural subpopulations' activity patterns in relation to the computational models should be clarified, as the observed patterns may not directly correspond to the specific signals predicted by the models. Second, the authors could consider using a supervised learning method to more explicitly model the pattern correlations between the three profiles. Third, a neural population model could be employed to better understand how the STN population jointly contributes to decision-making dynamics. Finally, the added value of the microstimulation experiments should be more directly addressed in the Results section, as the changes in firing patterns compared to the original patterns are not clearly evident.

Reviewer #3 (Public Review):

Summary:

Understanding the central neural circuits regulating body temperature is critical for improving health outcomes in many disease conditions and in combating heat stress in an ever-warming environment. The authors present important and detailed new data that characterizes a specific population of POA neurons with a relationship to thermoregulation. The new insights provided in this manuscript are exactly what is needed to assemble a neural network model of the central thermoregulatory circuitry that will contribute significantly to our understanding of regulating the critical homeostatic variable of body temperature. These experiments were conducted with the expertise of an investigator with career-long experience in intracellular recordings from POA neurons. They were interpreted conservatively in the appropriate context of current literature.

The Introduction begins with "Homeotherms, including mammals, maintain core body temperature (CBT) within a narrow range", but this ignores the frequent hypothermic episodes of torpor that mice undergo triggered by cold exposure. Although the author does mention torpor briefly in the Discussion, since these experiments were carried out exclusively in mice, greater consideration (albeit speculative) of the potential for a role of MPO Nts neurons in torpor initiation or recovery is warranted. This is especially the case since some 'torpor neurons' have been characterized as PACAP-expressing and a population of PACAP neurons represent the target of MPO Nts neurons.

Reviewer #3 (Public Review):

Summary:

In this manuscript, Yip and colleagues incorporated the pipette cleaning technique into their existing dual-patch robotic system, "the PatcherBot", to allow sequential patching of more cells for synaptic connection detection in living brain slices. During dual-patching, instead of retracting all two electrodes after each recording attempt, the system cleaned just one of the electrodes and reused it to obtain another recording while maintaining the other. With one new patch clamp recording attempt, new connections can be probed. By placing one pipette in front of the other in this way, one can "walk" across the tissue, termed "patch-walking." This application could allow for probing additional neurons to test the connectivity using the same pipette in the same preparation.

Strengths:

Compared to regular dual-patch recordings, this new approach could allow for probing more possible connections in brain slices with dual-patch recordings, thus having the potential to improve the efficiency of identifying synaptic connections

Weaknesses:

While this new approach offers the potential to increase efficiency, it has several limitations that could curtail its widespread use.

Loss of Morphological Information: Unlike traditional multi-patch recording, this approach likely loses all detailed morphology of each recorded neuron. This loss is significant because morphology can be crucial for cell type verification and understanding connectivity patterns by morphological cell type.

Spatial Restrictions: The robotic system appears primarily suited to probing connections between neurons with greater spatial separation (~100µm ISD). This means it may not reliably detect connections between neurons in close proximity, a potential drawback given that the connectivity is much higher between spatially close neurons. This limitation could help explain the low connectivity rate (5%) reported in the study.

Limited Applicability: While the approach might be valuable in specific research contexts, its overall applicability seems limited. It's important to consider scenarios where the trade-off between efficiency and specific questions that are asked.

Scalability Challenges: Scaling this method beyond a two-pipette setup may be difficult. Additional pipettes would introduce significant technical and logistical complexities.

Reviewer #3 (Public Review):

Summary:

The authors set out to devise a system for the neural and behavioral study of socially cooperative behaviors in nonhuman primates (common marmosets). They describe instrumentation to allow for a "cooperative pulling" paradigm, the training process, and how both behavioral and neural data can be collected and analyzed. This is a valuable approach to an important topic, as the marmoset stands as a great platform to study primate social cognition. Given that the goals of such a methods paper are to (a) describe the approach and instrumentation, (b) show the feasibility of use, and (c) quantitatively compare to related approaches, the work is easily able to meet those criteria. My specific feedback on both strengths and weaknesses is therefore relatively limited in scope and depth.

Strengths:

The device is well-described, and the authors should be commended for their efforts in both designing this system but also in "writing it up" so that others can benefit from their R&D.

The device appears to generate more repetitions of key behavior than other approaches used in prior work (with other species).

The device allows for quantitative control and adjustment to control behavior.

The approach also supports the integration of markerless behavioral analysis as well as neurophysiological data.

Weaknesses:

A few ambiguities in the descriptions are flagged below in the "Recommendations for authors".

The system is well-suited to marmosets, but it is less clear whether it could be generalized for use in other species (in which similar behaviors have been studied with far less elegant approaches). If the system could impact work in other species, the scope of impact would be significantly increased, and would also allow for more direct cross-species comparisons. Regardless, the future work that this system will allow in the marmoset will itself be novel, unique, and likely to support major insights into primate social cognition.

Reviewer #3 (Public Review):

Summary:

In this manuscript, Koh, Stratiievska, and their colleagues investigate the mechanism by which TRPV1 channels are delivered to the plasma membrane following the activation of receptor tyrosine kinases, specifically focusing on the NGF receptor. They demonstrate that the activation of the NGF receptor's PI3K pathway alone is sufficient to increase the levels of TRPV1 at the plasma membrane.

Strengths:

The authors employ cutting-edge optogenetic, imaging, and chemical-biology techniques to achieve their research goals. They ingeniously use optogenetics to selectively activate the PI3K pathway without affecting other NGF pathways. Additionally, they develop a novel, membrane-impermeable fluorescent probe for labeling cell-surface proteins through click-chemistry.

Comment on revised version:

We commend the authors on the significant improvements made to the manuscript. They have adequately addressed our comments. Notably, the new control experiments shown in Figure 4E and Figure 5 Fig. Supp 1 convincingly demonstrate the specificity of the NGF and 650 nm light stimuli, respectively. The addition of quantitative analyses strengthens the findings significantly. Furthermore, the manuscript is now presented in a much linear manner, enhancing its clarity and impact.

Reviewer #3 (Public Review):

Summary:

The manuscript of Nick and colleagues addresses the intriguing question of how brain connectivity evolves during reward-based motor learning. The concept of quantifying connectivity through changes in extraction and contraction across lower-dimensional manifolds is both novel and interesting and the presented results are clear and well-presented. Overall, the manuscript is a valuable addition to the field.

Strengths:

This manuscript is written in a clear and comprehensible way. It introduces a rather novel technique of assessing connectivity across lower-dimensional manifold which has hitherto not been applied in this way to the question of reward-based motor learning. Thus, this presents a unique viewpoint on understanding how the brain changes with motor learning. I particularly enjoyed the combination of connectivity-based, followed by further scrutiny of seed-based connectivity analyses, thus providing a more comprehensive viewpoint. Now it also has added a more comprehensive report on the behavioural changes of learning, and the added statistical quantification, which is useful.

Weaknesses:

The main weakness of the manuscript is the lack of direct connection between the reported neural changes and behavioural learning. Namely, most of the results could also be explained by changes in attention allocation during the session, or changes in movement speed (independent of learning). The authors acknowledge some of these potential confounds and argue that factors like attention are important for learning. While this is true, it is nonetheless very limiting if one cannot ascertain whether the observed effects are due to attention (independent of learning) or attention allocated in the pursuit of learning. The only direct analysis linking behavioural changes to neural changes is based on individual differences in learning performance, where the DAN-A shows the opposite trend than group level effects, which they interpret as differences given the used higher-resolution parcellation. However, it could be that these learning effects are indeed much smaller and subtler compared to more dominant group-level attention effects during the task. The lack of a control condition in the task limits the interpretability of results as learning-related.

Reviewer #3 (Public Review):

The manuscript of Nick and colleagues addresses the intriguing question of how brain connectivity evolves during reward-based motor learning. The concept of quantifying connectivity through changes in extraction and contraction across lower-dimensional manifolds is both novel and interesting and the presented results are clear and well-presented. Overall, the manuscript is a valuable addition to the field. The evidence supporting the presented findings is strong, though at times lacking rigorous statistical quantification. Nevertheless, there are several issues that require attention and clarification.

Reviewer #3 (Public Review):

Summary:

Drosophila melanogaster of North America overwinters in a state of reproductive diapause. The authors aimed to measure 'successful' D. melanogaster reproductive diapause and reveal loci that impact this quantitative trait. In practice, the authors quantified the number of eggs produced by a female after she exited 35 days of diapause. The authors claim that genes involved with olfaction in part contribute to some of the variation in this trait.

Strengths:

The work used the power platform of the fly DRGP/GWAS. The work tried to verify some of the candidate loci with targeted gene manipulations.

Weaknesses:

Some context is needed. Previous work from 2001 established that D. melanogaster reproductive diapause in the laboratory suspends adult aging but reduces post-diapause fecundity. The work from 2001 showed the extent fecundity is reduced is proportional to diapause duration. As well, the 2001 data showed short diapause periods used in the current submission reduce fecundity only in the first days following diapause termination; after this time fecundity is greater in the post-diapause females than in the non-diapause controls.

In this context, the submission fails to offer a meaningful concept for what constitutes 'successful diapause'. There is no biological rationale or relationship to the known patterns of post-diapause fecundity. The phenotype is biologically ambiguous.

I have a serious concern about the antenna-removal design. These flies were placed on cool/short days two weeks after surgery. Adults at this time will not enter diapause, which must be induced soon after eclosion. Two-week-old adults will respond to cool temperatures by 'slowing down', but they will continue to age on a time scale of day-degrees. This is why the control group shows age-dependent mortality, which would not be seen in truly diapaused adults. Loss of antennae increases the age-dependent mortality of these cold adults, but this result does not reflect an impact on diapause.

• Appraisal of whether the authors achieved their aims, and whether the results support their conclusions.

The work falls well short of its aim because the concept of 'successful diapause' is not biologically established. The paper studies post-diapause fecundity, and we don't know what that means. The loci identified in this analysis segregate for a minimally constructed phenotype. The results and conclusions are orthogonal.

• The likely impact of the work on the field, and the utility of the methods and data to the community.

The work will have little likely impact. Its phenotype and operational methods are weakly developed. It lacks insight based on the primary literature on post-diapause. The community of insect diapause investigators are not likely to use the data or conclusions to understand beneficial or pest insects, or the impact of a changing climate on how they over-winter.

Reviewer #3 (Public Review):

The role of neural variability in various cognitive functions is one of the focal contentions in systems and computational neuroscience. In this study, the authors used a large-scale cohort dataset to investigate the relationship between neural variability measured by fMRI and several factors, including stimulus complexity, GABA levels, aging, and visual performance. Such investigations are valuable because neural variability, as an important topic, is by far mostly studied within animal neurophysiology. There is little evidence in humans. Also, the conclusions are built on a large-scale cohort dataset that includes multi-model data. Such a dataset per se is a big advantage. Pharmacological manipulations and MRS acquisitions are rare in this line of research. Overall, I think this study is well-designed, and the manuscript reads well. I listed my comments below and hope my suggestions can further improve the paper.

Strength:<br /> (1) The study design is astonishingly rich. The authors used task-based fMRI, MRS technique, population contrast (aging vs. control), and psychophysical testing. I appreciate the motivation and efforts for collecting such a rich dataset.<br /> (2) The MRS part is good. I am not an expert in MRS so cannot comment on MRS data acquisition and analyses. But I think linking neural variability to GABA in humans is in general a good idea. There has been a long interest in the cause of neural variability, and inhibition of local neural circuits has been hypothesized as one of the key factors.<br /> (3) The pharmacological manipulation is particularly interesting as it provides at least evidence for the causal effects of GABA and deltaSDBOLD. I think this is quite novel.

Weakness:<br /> (1) I am concerned about the definition of neural variability. In electrophysiological studies, neural variability can be defined as Poisson-like spike count variability. In the fMRI world, however, there is no consensus on what neural variability is. There are at least three definitions. One is the variability (e.g., std) of the voxel response time series as used here and in the resting fMRI world. The second is to regress out the stimulus-evoked activation and only calculate the std of residuals (e.g., background variability). The third is to calculate variability of trial-by-trial variability of beta estimates of general linear modeling. It currently remains unclear the relations between these three types of variability with other factors. It also remains unclear the links between neuronal variability and voxel variability. I don't think the computational principles discovered in neuronal variability also apply to voxel responses. I hope the authors can acknowledge their differences and discuss their differences.<br /> (2) If I understand it correctly, the positive relationship between stimulus complexity and voxel variability has been found in the author's previous work. Thus, the claims in the abstract in lines 14-15, and section 1 in results are exaggerated. The results simply replicate the findings in the previous work. This should be clearly stated.<br /> (3) It is difficult for me to comprehend the U-shaped account of baseline GABA and shift in deltaSDBOLD. If deltaSDBOLD per se is good, as evidenced by the positive relationship between brainscore and visual sensitivity as shown in Fig. 5b and the discussion in lines 432-440, why the brain should decrease deltaSDBOLD ?? or did I miss something? I understand that "average is good, outliers are bad". But a more detailed theory is needed to account for such effects.<br /> (4) Related to the 3rd question, can you should the relationship between the shift of deltaSDBOLD (i.e., the delta of deltaSDBOLD) and visual performance?<br /> (5) Are the dataset openly available ?? I didn't find the data availability statement.

Reviewer #3 (Public Review):

This is an interesting and carefully carried out theoretical analysis of potential explanations for hexadirectional modulation of neural population activity that has been reported in the human entorhinal cortex and some other cortical regions. The previously reported hexadirectional modulation is of considerable interest as it has been proposed to be a proxy for the activation of grid cell networks. However, the extent to which this proposal is consistent with the known firing properties of grids hasn't received the attention it perhaps deserves. By comparing the predictions of three different models this study imposes constraints on possible mechanisms and generates predictions that can be tested through future experimentation.

Overall, while the conclusions of the study are convincing, I think the usefulness to the field would be increased if null hypotheses were more carefully considered and if the authors' new metric for hexadirectional modulation (H) could be directly contrasted with previously used metrics. For example, if the effect sizes for hexadirectional modulation in the previous fMRI and EEG data could be more directly compared with those of the models here, then this could help in establishing the extent to which the experimental hexadirectional modulation stands out from path hexasymmetry and how close it comes to the striking modulation observed with the conjunctive models. It could also be helpful to consider scenarios in which hexadirectional modulation is independent of grid firing, for example perhaps with appropriate coordination of head direction cell firing.

Reviewer #3 (Public Review):

In this manuscript, Notartomaso, Antenucci et al. use two different light-sensitive metabotropic glutamate receptor negative allosteric modulators (NAMs) to determine how mGlu5 receptor signaling in distinct brain regions of mice influences mechanical sensitivity in chronic constriction injury (CCI) model of neuropathic pain. This is an extension of their previous work using photocaged mGlu5 negative allosteric modulators and incorporates a systemically active NAM that can be locally photoswitched off and on with violet and green light, respectively. The authors found that NAM signaling in the thalamus and prefrontal cortical regions consistently reduced mechanical hypersensitivity. However, they observed divergent effects on these measures in the basolateral amygdala. The authors attempted to solve the discrepancy in behavioral measurements between mGlu5 signaling in the basolateral amygdala by determining how NAMs modulate synaptic transmission or in vivo firing and found that these effects were projection-dependent.

Strengths:

This study demonstrates the importance of local signaling by mGlu5 receptors across multiple pain-processing circuits in the brain, and the use of optical activation and inactivation strategies is very intriguing.

Weaknesses:

One major limitation is the lack of sham surgery groups and vehicle/light-only controls in behavior and physiology experiments, though the authors did test mechanical sensitivity in the contralateral paw. The reliance on a single behavioral measure in these groups is also problematic. Many of these brain regions are known to influence distinct aspects of somatosensory processing or other behaviors entirely, which may be interpreted as hypersensitivity (e.g. fear or anxiety-like behaviors in the basolateral amygdala). Details on the light intensities used is also absent, and it is important to test whether violet light had any unintended effects on these cells/mice.

While the effort to provide some mechanistic understanding using slice physiology and in vivo recordings is appreciated, they ignore any effects that these NAMs have directly on the excitability of the recorded output neuron. In the models, mGlu5 is proposed to exist on some upstream inhibitory (mPFC) or excitatory (BLA) projection, but no evidence of a direct effect on these synaptic inputs was observed. Given the widespread distribution of mGlu5 in these brain regions, the proposed model seems unlikely. Perhaps CCI induces changes in functional coupling of mGlu5 in different cell types, and this could be revealed with appropriate control experiments.

Overall the broad profiling taken here across multiple brain regions lacks controls and some cohesion, making it challenging to conclude how mGlu5 signaling is acutely impacting these circuits and/or specific cell types.

Reviewer #3 (Public Review):

The authors of this study aimed to enhance the prognostic assessment of endometrial cancer (EC) by identifying and validating a set of serum tumor markers (CA125, CEA, and AFP) that could reliably predict progression-free survival (PFS) and overall survival (OS) in patients. By employing a robust methodology that included the use of LASSO Cox regression analysis to construct a predictive model, the study sought to provide a more nuanced tool for clinical decision-making in the management of EC.

Major Strengths:

Methodological Rigor: The study's use of advanced statistical methods to analyze a large dataset of EC patients stands out. The inclusion of a validation cohort enhances the credibility of the prognostic model developed.<br /> Clinical Relevance: The identification of CA125, CEA, and AFP as independent prognostic factors and the creation of a risk score based on these markers offer valuable tools for clinicians. The predictive accuracy of this model could significantly impact patient management and treatment planning.<br /> Weaknesses:

Generalizability: The study is based on a cohort from a single institution, which may limit the applicability of the findings across different populations and healthcare settings.<br /> Loss to Follow-Up: As acknowledged by the authors, the loss to follow-up of some patients introduces a potential source of bias, possibly affecting the study's conclusions.<br /> Achievement of Aims and Support for Conclusions:

The study successfully achieves its aim of developing a prognostic model for EC that integrates serum levels of CA125, CEA, and AFP. The evidence presented supports the authors' conclusions that this model is a robust tool for predicting patient outcomes, evidenced by its performance in both the training and validation cohorts.

Impact and Utility:

This work is poised to make a significant contribution to the field of gynecological oncology, particularly in the management of endometrial cancer. The study's findings provide a practical approach to stratifying patients based on their risk, which could be instrumental in tailoring individualized treatment plans. Moreover, the model's ability to predict PFS and OS with considerable accuracy offers a promising avenue for further research and application in clinical settings.

Additional Context:

Understanding the role of tumor markers in cancer prognosis is a rapidly evolving area of oncology research. This study's focus on combining multiple serum markers into a comprehensive risk score model represents a significant step forward in the quest for more personalized cancer care. Future studies could expand on this work by exploring the integration of such markers with other clinical and molecular data to further refine prognostic models.

Reviewer #3 (Public Review):

In this study, Roumelioti et al demonstrate the role of miR-221/222 in synovial fibroblasts (SFs) in inflammatory arthritis, applying a plethora of methods in three transgenic mouse models (huTNFtg, TgColVI-miR-221/222, huTNFtg;TgColVI-miR-221/222). miR-221/222 is upregulated in SFs, upon stimulation with TNF, both in early and established disease, while its gene is activated, as shown by scATAC-seq data. Using RNA sequencing and KEGG pathway analysis, authors showed that overexpression of miR-221 and miR-222 exacerbates arthritis, mainly due to SFs proliferation, driven by cell cycling inhibition and extracellular matrix remodeling. Although the authors suggest the potential utility of miR-221/222 targeting in inflammatory arthritis treatment, this was only examined through miR-221/222 -/- mice generation and not by direct silencing of miR-221/222 by administering a miR-221/222 antagonist.

Reviewer #3 (Public Review):

The main goal of this study was to test how and why the intake of two important macronutrients ‒protein and carbon‒ often changes with ontogeny and body size. To do this, authors examined protein and carbon intake in a locusts lab population, across each instar and adult stages. Then, authors examined how the optimal balance of carbon and protein intake in a wild locusts population corresponded to that observed in the laboratory population. Results of these experiments showed that with ontogenic growth, locust decreased protein while increasing carbohydrate intake. Authors concluded that such decrease in the protein: carbohydrate intake may result from reductions in specific growth rates (growth within each instar). The protein: carbohydrate intake in the lab population appeared to be consistent with that observed in a wild locust population. Finally, authors combined their data with that from the literature to examine how protein intake scales with body mass throughout development, within and across different species.

Strengths:<br /> To determine how locusts balance protein: carbohydrate intake, authors applied the Geometric Framework (GF) of nutrition, which is a powerful approach for studying effects of nutrition and understanding the rules of compromise associated with balancing dietary unbalances.

Captivity can change behavior and physiology of most organisms, making it difficult to establish the relevance of laboratory experiments to what happens in the real world. A strength of this paper is that it compares behavior/physiology of lab vs. wild locusts. Finally, this study takes a step further by proposing a new scaling rule based on this study's results and data from the literature on various species.

Weaknesses:<br /> Although the paper has strengths, there seems to be several methodological issues that obscure the interpretation/conclusions presented in the manuscript.<br /> It appears that authors are not actually estimating "Intake Targets", as stated throughout the manuscript. According to the geometric framework, the intake target (IT) is estimated as the point in the nutritional landscape under which performance/fitness is optimized. The geometric framework also predicts that animals can reach their intake targets by feeding selectivity when given a choice of diets that differ in nutrient amounts, which is what authors did here. However, because the relationship between fitness/performance with diet was not established, in the choice experiments authors seem to be assuming (but not testing) that locusts are reaching their intake target.

You estimated a mass-specific protein intake for each instar. It is not clear why mass-specific intake and not just intake of protein was used for analysis. While mass (or size) of an individual may influence food consumption, it seems like authors calculated mass-specific consumption using each instar's final mass, which would make mass a result of protein consumption (and not the opposite). Importantly, the comparison between mass-specific protein consumption and specific growth rate may be problematic, as both variables seem to be estimated using final mass.

Reviewer #3 (Public Review):

Summary:

The manuscript by Marshall et al. investigates the role mGluR5 in modulating the coactivity of d1 spiny projection neurons (dSPN) in the dorsolateral striatum through calcium imaging and pharmacological i.p. injections or targeted deletion of mGluR5 in dSPNs. They show a bidirectional modulation by negative and positive allosteric modulators respectively (mainly at rest) on dSPN coactivity, the increase in coactivity by the negative modulator showed qualitative similar effects on coactivity as the deletion of mGluR5 in dSPNs.

Strengths:

Overall the study is well written and easy to read, with the data supporting (most of the time) the conclusion. It brings a new perspective on the role of mGluR5 in the modulation of dSPNs coactivity and its correlation with movement.

Weaknesses:

Some of the experiments would strengthen the solidness of the study providing further information and verifying the claims of the main text with the statistics on the figure legends.

Reviewer #3 (Public Review):

The development of an automated Barnes maze allows for more naturalistic and uninterrupted behavior, facilitating the study of spatial learning and memory, as well as the analysis of the brain's neural networks during behavior when combined with neurophysiological techniques. The system's design has been thoughtfully considered, encompassing numerous intricate details. These details include the incorporation of flexible options for selecting start, goal, and proximal landmark positions, the inclusion of a rotating platform to prevent the accumulation of olfactory cues, and careful attention given to atomization, taking into account specific considerations such as the rotation of the maze without causing wire shortage or breakage. When combined with neurophysiological manipulations or recordings, the system provides a powerful tool for studying spatial navigation system.

The behavioral experiment protocols, along with the analysis of animal behavior, are conducted with care, and the development of behavioral modeling to capture the animal's search strategy is thoughtfully executed. It is intriguing to observe how the integration of these innovative stochastic models can elucidate the evolution of mice's search strategy within a variant of the Barnes maze.

Reviewer #3 (Public Review):

The goal of the current manuscript is to investigate how changes in transporter substrate specificity emerge in response to a novel selective pressure. The authors investigate the APC family of amino acid transporters, a large family with many related transporters that together cover the spectrum of amino acid uptake in yeast.

The authors use a clever approach for their experimental evolutions. By deleting 10 amino acid uptake transporters in yeast, they develop a strain that relies on amino acid import by introduced APC transporters under nitrogen limiting conditions. They can thus evolve transporters towards transport of new substrates if no other nitrogen source is available. The main takeaway from the paper is that it is relatively easy for the spectrum of substrates in a particular transporter of this family to shift, as a number of single mutants are identified that modulate substrate specificity. In general, transporters evolved towards gain-of-function mutations (better or new activities) also confer transport promiscuity, expanding the range of amino acids transported.

The data in the paper support the conclusions, and the outcomes (evolution towards promiscuity) agree with the literature available for soluble enzymes. The authors do a good job in the discussion of relating the lessons of the current study to natural evolution.

Reviewer #3 (Public Review):

Summary:

Liu et al. focus on a mathematical method to quantify active hematopoietic precursors in mice using Confetti reporter mice combined with Cre-lox technology. The paper explores the hematopoietic dynamics in various scenarios, including homeostasis, myeloablation with 5-fluorouracil, Fanconi anemia (FA), and post-transplant environments. The key findings and strengths of the paper include (1) precursor quantification: The study develops a method based on the binomial distribution of fluorescent protein expression to estimate precursor numbers. This method is validated across a wide dynamic range, proving more reliable than previous approaches that suffered from limited range and high variance outside this range; (2) dynamic response analysis: The paper examines how hematopoietic precursors respond to myeloablation and transplantation; (3) application in disease models: The method is applied to the FA mouse model, revealing that these mice maintain normal precursor numbers under steady-state conditions and post-transplantation, which challenges some assumptions about FA pathology. Despite the normal precursor count, a diminished repopulation capability suggests other factors at play, possibly related to cell proliferation or other cellular dysfunctions. In addition, the FA mouse model showed a reduction in active lymphoid precursors post-transplantation, contributing to decreased repopulation capacity as the mice aged. The authors are aware of the limitation of the assumption of uniform expansion. The paper assumes a uniform expansion from active precursor to progenies for quantifying precursor numbers. This assumption may not hold in all biological scenarios, especially in disease states where hematopoietic dynamics can be significantly altered. If non-uniformity is high, this could affect the accuracy of the quantification. Overall, the study underscores the importance of precise quantification of hematopoietic precursors in understanding both normal and pathological states in hematopoiesis, presenting a robust tool that could significantly enhance research in hematopoietic disorders and therapy development. The following concerns should be addressed.

Major Points:

• The authors have shown a wide range of seeded cells (1 to 1e5) (Figure 1D) that follow the linear binomial rule. As the standard deviation converges eventually with more seeded cells, the authors need to address this limitation by seeding the number of cells at which the assumption fails.<br /> • Line 276: This suggests myelopoiesis is preferred when very few precursors are available after irradiation-mediated injury. Did the authors see more myeloid progenitors at 1 month post-transplantation with low precursor number? The authors need to show this data in a supplement.

Minor Points:

• Please cite a reference for line 40: a rare case where a single HSPC clone supports hematopoiesis.<br /> • Line 262-263: "This discrepancy may reflect uneven seeding of precursors to the BM throughout the body after transplantation and the fact that we only sampled a part of the BM (femur, tibia, and pelvis)." Consider citing this paper (https://doi.org/10.1016/j.cell.2023.09.019) that explores the HSPCs migration across different bones.<br /> • Lines 299 and 304. Misspellings of RFP.<br /> • The title is misleading as the paper's main focus is the precursor number estimator using the binomial nature of fluorescent tagging. Using a single-copy cassette of Confetti mice cannot be used to measure clonality.

Reviewer #3 (Public Review):

Summary:

This manuscript presents a series of experiments aimed at investigating orientation to polarized lunar skylight in a nocturnal ant, the first report of its kind that I am aware of.

Strengths:

The study was conducted carefully and is clearly explained here.

Weaknesses:

I have only a few comments and suggestions, that I hope will make the manuscript clearer and easier to understand.

Time compensation or periodic snapshots

In the introduction, the authors compare their discovery with that in dung beetles, which have only been observed to use lunar skylight to hold their course, not to travel to a specific location as the ants must. It is not entirely clear from the discussion whether the authors are suggesting that the ants navigate home by using a time-compensated lunar compass, or that they update their polarization compass with reference to other cues as the pattern of lunar skylight gradually shifts over the course of the night - though in the discussion they appear to lean towards the latter without addressing the former. Any clues in this direction might help us understand how ants adapted to navigate using solar skylight polarization might adapt use to lunar skylight polarization and account for its different schedule. I would guess that the waxing and waning moon data can be interpreted to this effect.

Effects of moon fullness and phase on precision

As well as the noted effect on shift magnitudes, the distributions of exit headings and reorientations also appear to differ in their precision (i.e., mean vector length) across moon phases, with somewhat shorter vectors for smaller fractions of the moon illuminated. Although these distributions are a composite of the two distributions of angles subtracted from one another to obtain these turn angles, the precision of the resulting distribution should be proportional to the original distributions. It would be interesting to know whether these differences result from poorer overall orientation precision, or more variability in reorientation, on quarter moon and crescent moon nights, and to what extent this might be attributed to sky brightness or degree of polarization.

N.B. The Watson-Williams tests for difference in mean angle are also sensitive to differences in sample variance. This can be ruled out with another variety of the test, also proposed by Watson and Williams, to check for unequal variances, for which the F statistic is = (n2-1)*(n1-R1) / (n1-1)*(n2-R2) or its inverse, whichever is >1.

Reviewer #3 (Public Review):

Summary:

This study aims to demonstrate that cortical feedback is not necessary to signal behavioral outcome to shell neurons of the inferior colliculus during a sound detection task. The demonstration is achieved in a very clear manner by the observation of the activity of cortico-recepient neurons in animals which have received lesions of the auditory cortex. The experiment shows that neither behavior performance nor neuronal responses are significantly impacted by cortical lesions except for the case of partial lesions which seem to have a disruptive effect on behavioral outcome signaling.

Strengths:

The demonstration of the main conclusions is based on state-of-the-art, carefully controlled methods and is highly convincing. There is an in depth discussion of the different effects of auditory cortical lesions on sound detection behavior.

Weaknesses:

The description of feedback signals could be more detailed although it is difficult to achieve good temporal resolution with the calcium imaging technique necessary for targeting cortico-recipient neurons.

Reviewer #3 (Public Review):

Summary:

Ribbon synapses are complex molecular assemblies responsible for synaptic vesicle trafficking in sensory cells of the eye and the inner ear. The Ca2+-dependent exocytosis occurs at the active zone (AZ), however, the molecular mechanisms orchestrating the structure and function of the AZs of ribbon synapses are not well understood. To advance in the understanding of those mechanisms, the authors present a novel and interesting experimental strategy pursuing the reconstitution of a minimal active zone of a ribbon synapse within a synapse-naïve cell line: HEK293 cells. The authors have used stably transfected HEK293 cells that express voltage-gated Ca2+ channels subunits (constitutive -CaV beta3 and CaV alpha2 beta1- and inducible CaV1.3 alpha1). They have expressed in those cells several proteins of the ribbon synapse active zone: (1) RIBEYE, (2) a modified version of Bassoon that binds to the plasma membrane through artificial palmitoylation (Palm-Bassoon) and (3) RIM-binding protein 2 (RBP2) to induce the formation of a minimal active zone that they called SyRibbons. The formation of such structures is convincing, however, the evidence of such structures having an impact enhancing Ca2+-currents, as the authors claim, is rather weak in the present version of the study.

Strengths of the study:

(1) The study is carefully carried out using a remarkable combination of (1) superresolution microscopy, to analyze the formation and subcellular distribution of molecular assemblies and (2) functional assessment of voltage-gated Ca2+ channels using patch-clamp recording of Ca2+-currents and fluorometry to correlate Ca2+ influx with the molecular assemblies formed by AZ proteins. The results are of high quality and are in general accompanied of required control experiments.<br /> (2) The method opens new opportunities to further investigate the minimal and basic properties of AZ proteins that are difficult to study using in vivo systems. The cells that operate through ribbon synapses (e.g. photoreceptors and hair cells) are particularly difficult to manipulate, so setting up and validating the use of a heterologous system more suitable for molecular manipulations is highly valuable.<br /> (3) The structures formed by RIBEYE and Palm-Bassoon in HEK293 cells identified by STED nanoscopy are strikingly similar to the AZs of ribbon synapses found in rat inner hair cells (Figure 2).

Weaknesses of the study:

(1) The results obtained in a heterologous system (HEK293 cells) need to be interpreted with caution. They will importantly speed the generation of models and hypothesis that will, however, require in vivo validation.<br /> (2) The authors analyzed the distribution of RIBEYE clusters in different membrane compartments and correctly conclude that RIBEYE clusters are not trapped in any of those compartments, but it is soluble instead. The authors, however, did not carry out a similar analysis for Palm-Bassoon. It is therefore unknown if Palm-Bassoon binds to other membrane compartments besides the plasma membrane. That could occur because in non-neuronal cells GAP43 has been described to be in internal membrane compartments. This should be investigated to document the existence of ectopic internal Synribbons beyond the plasma membrane because it might have implications for interpreting functional data in case Ca2+-channels become part of those internal Synribbons.<br /> (3) The co-expression of RBP2 and Palm-Bassoon induces a rather minor but significant increase in Ca2+-currents (Figure 5). Such an increase does not occur upon expression of (1) Palm-Bassoon alone, (2) RBP2 alone or (3) RIBEYE alone (Figure 5). Intriguingly, the concomitant expression of Palm-Bassoon, RBP2 and RIBEYE does not translate into an increase of Ca2+-currents either (Figure 7).<br /> (4) The authors claim that Ca2+-imaging reveals increased CA2+-signal intensity at synthetic ribbon-type AZs. That claim is a subject of concern because the increase is rather small and it does not correlate with an increase in Ca2+-currents.

DOI: 10.1007/978-3-030-19898-5_1

Resource: SCR_012840

Curator: @bandrow

SciCrunch record: RRID:SCR_012840

What is this?

Reviewer #3 (Public Review):

Summary:

The authors address a very important issue of going beyond a single-copy model obtained by the two principal experimental methods of structural biology, macromolecular crystallography and cryo electron microscopy (cryo-EM). Such multiconformer model is based on the fact that experimental data from both these methods represent a space- and time-average of a huge number of the molecules in a sample, or even in several samples, and that the respective distributions can be multimodal. Differently from structure prediction methods, this approach is strongly based on accurate high-resolution experimental information and requires validated single-copy high-quality models as input. In overall, the results support the authors' conclusions.

In fact, the method addresses two problems which could be considered separately:

- an automation of construction of multiple conformations when they can be identified visually;<br /> - a determination of multiple conformations when their visual identification is difficult or impossible.

The former is a known problem, when missing alternative conformations may cost a few percent in R-factors. While these conformations are relatively easy to detect and build manually, the current procedure may save significant time being quite efficient, as the test results show. It is an indisputably useful tool for such a goal. The second problem is important from the physical point of view and has been considered first thirty years ago by Burling & Brünger. The manuscript does not specify clearly how much the current tool addresses the second case. To model such maps, the authors introduced errors in structure factors, however, being independent, as in this work, such errors, even quite high, may leave the maps reasonably well interpretable. Obviously, it is impossible to model all kinds of errors and this modeling of noise is appreciated but it would helpful for understanding if the manuscript shows, for example, the worst map when the procedure was successful.

The new procedure deals with a second-order variation in the R-factors, of about 1% or less, like placing riding hydrogen atoms, modeling density deformation or variation of the bulk solvent. In such situations, it is hard to justify model improvement. Keeping Rfree values or their marginal decreasing can be considered as a sign that the model does not overfit data but hardly as a strong argument in favor of the model.

In general, global targets are less appropriate for this kind of problems and local characteristics may be better indicators. Improvement of the model geometry is a good choice. Indeed, yet Cruickshank (1956) showed that averaged density images may lead to a shortening of covalent bonds when interpreting such maps by a single model. However, a total absence of geometric outliers is not necessarily required for the structures solved at a high resolution where diffraction data should have a more freedom to place the atoms where the experiments "see" them.

The key local characteristic for multicomformer models is a closeness of the model map to the experimental one. Actually, the procedure uses a kind of such measure, the Bayesian information criteria (BIC). Unfortunately, the manuscript does not describe how sharply it identifies the best model and how much it changes between the initial and final models; in general, there is no feeling about its values. The Q-score (page 17) can be an appropriate tool for the first problem where the multiple conformations and individual atomic images are clearly separated and not for the second problem where the contributions from neighboring conformations and atoms are merged. In addition to BIC or to even more conventional global target functions such as LS or map correlation, the extreme values of the local difference maps may help to validate, or not, the model.

This described method with the results presented is a strong argument for a need in experimental data and information they contain, differently from a pure structure prediction. This tool is important to produce user-unbiased multiconformer models rapidly and automatically. At the same time, absence of strong density-based validation components may limit its impact.

Strengths:<br /> Addressing an important problem and automatisation of model construction for alternative conformations using high-resolution experimental data.

Weaknesses:<br /> An insufficient validation of the models when no discrete alternative conformations visible and insufficiency of local real-space validation indicators.

Reviewer #3 (Public Review):

Summary:

Long-lived PCs are maintained in a CXCR4-dependent manner.

Strengths:

The reporter mice for fate-mapping can clearly distinguish long-lived PCs from total PCs and greatly contribute to the identification of long-lived PCs.

Reviewer #3 (Public Review):

Summary:

In this ambitious paper, the authors develop an unparalleled community resource of insect genome regulatory annotations spanning five insect orders. They employ their previously-developed SCRMshaw method for computational cross-species enhancer prediction, drawing on available training datasets of validated enhancer sequence and expression from Drosophila melanogaster, which had been previously shown to perform well across select holometabolous insects (representing 160-345MY divergence). In this work, they expand regulatory sequence annotation to 33 insect genomes spanning Holometabola and Hemiptera, which is even more distantly related to the fly model. They perform multiple downstream analyses of sets of predicted enhancers to assess the true-positive rate of predictions; the independent comparisons of real predictions with simulated predictions and with chromatin accessibility data, as well as the functional validation through reporter gene analysis, strengthen their conclusions that their annotation pipeline achieves a high true-positive rate and can be used across long divergence times to computationally annotate regulatory genome regions, an ability that has been previously inaccessible for non-model insects and now is possible across the many newly-sequenced insect scaffold-level genomes.

Strengths:

This work fills a large gap in current methods and resources for predicting regulatory regions of the genome, a task that has long lagged behind that of coding region prediction and analysis.

Despite technical constraints in working outside of well-developed model insect systems, the authors creatively draw on existing resources to scaffold a pipeline and independently assess the likelihood of prediction validity.

The established database will be a welcome community resource in its current state, and even more so as the authors continue to expand their annotations to more insect genomes as they indicate. Their available analysis pipeline itself will be useful to the community as well for research groups that may want to undertake their own regulatory genome annotation.

Weaknesses:

The rates of predicted true positive enhancer identification vary widely across the genomes included here based on the simulations and comparison to datasets of accessible chromatin in a manner that doesn't map neatly onto phylogenetic distance. At this point, it is unclear why these patterns may arise, although this may become more clear as regulatory annotation is undertaken for more genomes.

Functional assessment of predicted enhancers was performed through reporter gene assays primarily in Drosophila melanogaster imaginal discs, a system amenable to transgenics. Unfortunately, this mode of canonical imaginal disc development is only representative of a subset of all holometabolous insects; therefore, it is difficult to interpret reporter gene expression in a fly imaginal disc as evidence of a true positive enhancer that would be active in its native species whose adult appendages develop differently through the larval stage (for example, Coleopteran and Lepidopteran legs). However, the reporter gene assays from other tissues do offer strong evidence of true positive enhancer detection, and constraints on transgenic experiments in other systems mean that this approach is the best available.

Reviewer #3 (Public Review):

Summary:

In this very important study by Dantzer et al., 'Emerging role of oncogenic b-catenin in exosome biogenesis as a driver of immune escape in hepatocellular carcinoma' the authors define a role for oncogenic b-catenin on exosome biology and explore the link between reduce exosome secretion and tumor immune cell evasion. Using transcriptional and proteomic analysis of hepatocellular carcinoma cells with either oncogenic or wildtype b-catenin the authors find that oncogenic b-catenin negatively regulates exosome biogenesis.

The authors can provide compelling evidence that oncogenic b-catenin in different hepatocellular carcinoma cells negatively regulates exosome biogenesis and secretion, by downregulation of, amongst others, SDC4 and RAB27A, two proteins involved in exosome biogenesis. The authors corroborate these results by inducing b-catenin activation using CHIR99021 in a hepatocarcinoma cell line with non-oncogenic bCatenin (Huh7 cells). The authors can further demonstrate convincingly that reduction in exosome release by hepatocarcinoma spheroids leads to a reduction in immune cell infiltration into the tumor spheroid.

Strengths:

This is a very important and well-conceived study, that appeals to a readership beyond the field of hepatocarcinoma. The authors demonstrate a compelling link between oncogenic bCatenin and exosome biogenesis. Their results are convincing and with well-designed control experiments. The authors included various complementary lines of investigation to verify their findings.

Weaknesses:

One limitation of this study is that the mechanistic relationship of exosome release and how they affect immune cells remains to be elucidated. In this context, the authors conclusions rest on the assumption that hepatocarcinoma immune evasion is based exclusively on the reduced number of exosomes. However, the authors do not analyze exosome composition between exosomes of wildtype and oncogenic background, which could be different.

Reviewer #3 (Public Review):

Summary:

By conducting QM/MM free energy simulations, the authors aimed to characterize the mechanism and transition state for the phosphoryl transfer in adenylate kinase. The qualitative reliability of the QM/MM results has been supported by several interesting experimental kinetic studies. However, the interpretation of the QM/MM results is not well supported by the current calculations.

Strengths:

The QM/MM free energy simulations have been carefully conducted. The accuracy of the semi-empirical QM/MM results was further supported by DFT/MM calculations, as well as qualitatively by several experimental studies.

Weaknesses:

(1) One key issue is the definition of the transition state ensemble. The authors appear to define this by simply considering structures that lie within a given free energy range from the barrier. However, this is not the rigorous definition of transition state ensemble, which should be defined in terms of committor distribution. This is not simply an issue of semantics, since only a rigorous definition allows a fair comparison between different cases - such as the transition state in an enzyme vs in solution, or with and without the metal ion. For a chemical reaction in a complex environment, it is also possible that many other variables (in addition to the breaking and forming P-O bonds) should be considered when one measures the diversity in the conformational ensemble.

In the revised ms, the authors included committor analysis. However, the discussion of the result is very brief. In particular, if we use the common definition of the transition state ensemble (TSE) as those featuring the committor around 0.5, the reaction coordinate of the TSE would span a much narrower range than those listed in Table 1. This point should be carefully addressed.

(2) While the experimental observation that the activation entropy differs significantly with and without the Ca2+ ion is interesting, it is difficult to connect this result with the "wide" transition state ensemble observed in the QM/MM simulations so far. Even without considering the definition of the transition state ensemble mentioned above, it is unlikely that a broader range of P-O distances would explain the substantial difference in the activation entropy measured in the experiment. Since the difference is sufficiently large, it should be possible to compute the value by repeating the free energy simulations at different temperatures, which would lead to a much more direct evaluation of the QM/MM model/result and the interpretation.

Reviewer #3 (Public Review):

The manuscript presents an intriguing explanation for why grid cell firing fields do {\em not} lie on a lattice whose axes aligned to the walls of a square arena. This observation, by itself, merits the manuscript's dissemination to the journals audience.

The presentation is quirky (but keep the quirkiness!).

But let me recast the problem presented by the authors as one of combinatorics. Given repeating, spatially separated firing fields across cells, one obtains temporal sequences of grid cells firing. Label these cells by integers from $[n]$. Any two cells firing in succession should uniquely identify one of six directions (from the hexagonal lattice) in which the agent is currently moving.

Now, take the symmetric group $\Sigma$ of cyclic permutations on $n$ elements.<br /> We ask whether there are cyclic permutations of $[n]$ such that

So, for instance, $(4,2,3,1)$ would not be counted as a valid permutation of $(1,2,3,4)$, as $(2,3)$ and $(1,4)$ are adjacent.

Furthermore, given $[n]$, are there two distinct cyclic permutations such that {\em no} adjacencies are preserved when considering any pair of permutations (among the triple of the original ordered sequence and the two permutations)? In other words, if we consider the permutation required to take the first permutation into the second, that permutation should not preserve any adjacencies.

{\bf Key question}: is there any difference between the solution to the combinatorics problem sketched above and the result in the manuscript? Specifically, the text argues that for $n=7$ there is only {\em one} solution.

Ideally, one would strive to obtain a closed-form solution for the number of such permutations as a function of $n$.

Reviewer #3 (Public Review):

This manuscript examines the impact of congenital visual deprivation on the excitatory/inhibitory (E/I) ratio in the visual cortex using Magnetic Resonance Spectroscopy (MRS) and electroencephalography (EEG) in individuals whose sight was restored. Ten individuals with reversed congenital cataracts were compared to age-matched, normally sighted controls, assessing the cortical E/I balance and its interrelationship to visual acuity. The study reveals that the Glx/GABA ratio in the visual cortex and the intercept and aperiodic signal are significantly altered in those with a history of early visual deprivation, suggesting persistent neurophysiological changes despite visual restoration.

My expertise is in EEG (particularly in the decomposition of periodic and aperiodic activity) and statistical methods. I have several major concerns in terms of methodological and statistical approaches along with the (over)interpretation of the results. These major concerns are detailed below.

(1) Variability in visual deprivation:

- The document states a large variability in the duration of visual deprivation (probably also the age at restoration), with significant implications for the sensitivity period's impact on visual circuit development. The variability and its potential effects on the outcomes need thorough exploration and discussion.

(2) Sample size:

- The small sample size is a major concern as it may not provide sufficient power to detect subtle effects and/or overestimate significant effects, which then tend not to generalize to new data. One of the biggest drivers of the replication crisis in neuroscience.

- The main problem with the correlation analyses between MRS and EEG measures is that the sample size is simply too small to conduct such an analysis. Moreover, it is unclear from the methods section that this analysis was only conducted in the patient group (which the reviewer assumed from the plots), and not explained why this was done only in the patient group. I would highly recommend removing these correlation analyses.

(3) Statistical concerns:

- The statistical analyses, particularly the correlations drawn from a small sample, may not provide reliable estimates (see https://www.sciencedirect.com/science/article/pii/S0092656613000858, which clearly describes this problem).

- Statistical analyses for the MRS: The authors should consider some additional permutation statistics, which are more suitable for small sample sizes. The current statistical model (2x2) design ANOVA is not ideal for such small sample sizes. Moreover, it is unclear why the condition (EO & EC) was chosen as a predictor and not the brain region (visual & frontal) or neurochemicals. Finally, the authors did not provide any information on the alpha level nor any information on correction for multiple comparisons (in the methods section). Finally, even if the groups are matched w.r.t. age, the time between surgery and measurement, the duration of visual deprivation, (and sex?), these should be included as covariates as it has been shown that these are highly related to the measurements of interest (especially for the EEG measurements) and the age range of the current study is large.

- EEG statistical analyses: The same critique as for the MRS statistical analyses applies to the EEG analysis. In addition: was the 2x3 ANOVA conducted for EO and EC independently? This seems to be inconsistent with the approach in the MRS analyses, in which the authors chose EO & EC as predictors in their 2x2 ANOVA.

- Figure 4: The authors report a p-value of >0.999 with a correlation coefficient of -0.42 with a sample size of 10 subjects. This can't be correct (it should be around: p = 0.22). All statistical analyses should be checked.

- Figure 2c. Eyes closed condition: The highest score of the *Glx/GABA ratio seems to be ~3.6. In subplot 2a, there seem to be 3 subjects that show a Glx/GABA ratio score > 3.6. How can this be explained? There is also a discrepancy for the eyes-closed condition.

(4) Interpretation of aperiodic signal:

- Several recent papers demonstrated that the aperiodic signal measured in EEG or ECoG is related to various important aspects such as age, skull thickness, electrode impedance, as well as cognition. Thus, currently, very little is known about the underlying effects which influence the aperiodic intercept and slope. The entire interpretation of the aperiodic slope as a proxy for E/I is based on a computational model and simulation (as described in the Gao et al. paper).

- Especially the aperiodic intercept is a very sensitive measure to many influences (e.g. skull thickness, electrode impedance...). As crucial results (correlation aperiodic intercept and MRS measures) are facing this problem, this needs to be reevaluated. It is safer to make statements on the aperiodic slope than intercept. In theory, some of the potentially confounding measures are available to the authors (e.g. skull thickness can be computed from T1w images; electrode impedances are usually acquired alongside the EEG data) and could be therefore controlled.

- The authors wrote: "Higher frequencies (such as 20-40 Hz) have been predominantly associated with local circuit activity and feedforward signaling (Bastos et al., 2018; Van Kerkoerle et al., 2014); the increased 20-40 Hz slope may therefore signal increased spontaneous spiking activity in local networks. We speculate that the steeper slope of the aperiodic activity for the lower frequency range (1-20 Hz) in CC individuals reflects the concomitant increase in inhibition." The authors confuse the interpretation of periodic and aperiodic signals. This section refers to the interpretation of the periodic signal (higher frequencies). This interpretation can not simply be translated to the aperiodic signal (slope).

- The authors further wrote: We used the slope of the aperiodic (1/f) component of the EEG spectrum as an estimate of E/I ratio (Gao et al., 2017; Medel et al., 2020; Muthukumaraswamy & Liley, 2018). This is a highly speculative interpretation with very little empirical evidence. These papers were conducted with ECoG data (mostly in animals) and mostly under anesthesia. Thus, these studies only allow an indirect interpretation by what the 1/f slope in EEG measurements is actually influenced.

(5) Problems with EEG preprocessing and analysis:

- It seems that the authors did not identify bad channels nor address the line noise issue (even a problem if a low pass filter of below-the-line noise was applied).

- What was the percentage of segments that needed to be rejected due to the 120μV criteria? This should be reported specifically for EO & EC and controls and patients.

- The authors downsampled the data to 60Hz to "to match the stimulation rate". What is the intention of this? Because the subsequent spectral analyses are conflated by this choice (see Nyquist theorem).

- "Subsequently, baseline removal was conducted by subtracting the mean activity across the length of an epoch from every data point." The actual baseline time segment should be specified.

- "We excluded the alpha range (8-14 Hz) for this fit to avoid biasing the results due to documented differences in alpha activity between CC and SC individuals (Bottari et al., 2016; Ossandón et al., 2023; Pant et al., 2023)." This does not really make sense, as the FOOOF algorithm first fits the 1/f slope, for which the alpha activity is not relevant.

- The model fits of the 1/f fitting for EO, EC, and both participant groups should be reported.

(6) Validity of GABA measurements and results:

- According the a newer study by the authors of the Gannet toolbox (https://analyticalsciencejournals.onlinelibrary.wiley.com/doi/abs/10.1002/nbm.5076), the reliability and reproducibility of the gamma-aminobutyric acid (GABA) measurement can vary significantly depending on acquisition and modeling parameter. Thus, did the author address these challenges? Furthermore, the authors wrote: "We confirmed the within-subject stability of metabolite quantification by testing a subset of the sighted controls (n=6) 2-4 weeks apart. Looking at the supplementary Figure 5 (which would be rather plotted as ICC or Blant-Altman plots), the within-subject stability compared to between-subject variability seems not to be great. Furthermore, I don't think such a small sample size qualifies for a rigorous assessment of stability.

- "Why might an enhanced inhibitory drive, as indicated by the lower Glx/GABA ratio" Is this interpretation really warranted, as the results of the group differences in the Glx/GABA ratio seem to be rather driven by a decreased Glx concentration in CC rather than an increased GABA (see Figure 2).

- Glx concentration predicted the aperiodic intercept in CC individuals' visual cortices during ambient and flickering visual stimulation. Why specifically investigate the Glx concentration, when the paper is about E/I ratio?

(7) Interpretation of the correlation between MRS measurements and EEG aperiodic signal:

- The authors wrote: "The intercept of the aperiodic activity was highly correlated with the Glx concentration during rest with eyes open and during flickering stimulation (also see Supplementary Material S11). Based on the assumption that the aperiodic intercept reflects broadband firing (Manning et al., 2009; Winawer et al., 2013), this suggests that the Glx concentration might be related to broadband firing in CC individuals during active and passive visual stimulation." These results should not be interpreted (or with very caution) for several reasons (see also problem with influences on aperiodic intercept and small sample size). This is a result of the exploratory analyses of correlating every EEG parameter with every MRS parameter. This requires well-powered replication before any interpretation can be provided. Furthermore and importantly: why should this be specifically only in CC patients, but not in the SC control group?

(8) Language and presentation:

- The manuscript requires language improvements and correction of numerous typos. Over-simplifications and unclear statements are present, which could mislead or confuse readers (see also interpretation of aperiodic signal).

- The authors state that "Together, the present results provide strong evidence for experience-dependent development of the E/I ratio in the human visual cortex, with consequences for behavior." The results of the study do not provide any strong evidence, because of the small sample size and exploratory analyses approach and not accounting for possible confounding factors.

- "Our results imply a change in neurotransmitter concentrations as a consequence of *restoring* vision following congenital blindness." This is a speculative statement to infer a causal relationship on cross-sectional data.

- In the limitation section, the authors wrote: "The sample size of the present study is relatively high for the rare population , but undoubtedly, overall, rather small." This sentence should be rewritten, as the study is plein underpowered. The further justification "We nevertheless think that our results are valid. Our findings neurochemically (Glx andGABA+ concentration), and anatomically (visual cortex) specific. The MRS parameters varied with parameters of the aperiodic EEG activity and visual acuity. The group differences for the EEG assessments corresponded to those of a larger sample of CC individuals (n=38) (Ossandón et al., 2023), and effects of chronological age were as expected from the literature." These statements do not provide any validation or justification of small samples. Furthermore, the current data set is a subset of an earlier published paper by the same authors "The EEG data sets reported here were part of data published earlier (Ossandón et al., 2023; Pant et al., 2023)." Thus, the statement "The group differences for the EEG assessments corresponded to those of a larger sample of CC individuals (n=38) " is a circular argument and should be avoided.

Reviewer #3 (Public Review):

Summary:

Using a compressed sensing-based approach applied previously by the author's group, the authors conducted an initial screen for neurons that when optogenetically down-regulated, influenced learned pathogen avoidance consisting of two component behaviors, exit from the bacterial lawn and lawn re-entry. Authors found that 4 classes of neurons AVK, SIA, AIY, and MI were inferred over a wide range of sparsity parameters, thereby indicating the importance of lawn re-entry. They found six classes of neurons required for lawn exit. The authors then went on to further analyze the neurons for the re-entry behavior, and conducted calcium imaging of those neurons in the freely behaving animals. They found that the activities of AIY and SIA neurons decreased after the animals that had been exposed to the pathogenic bacteria tried to re-enter the bacterial lawn. They also found that when those neurons of the animals that had not been exposed to pathogenic bacteria were downregulated by optogenetics, those operated animals increased the latency of the re-entry, which is a similar behavioral modification to that of the animals that had been exposed to the pathogen. Conversely, those neurons of the animals that were exposed to pathogenic bacteria were up-regulated by optogenetics, those animals showed a shortened latency of the re-entry, which is similar to the behavior observed in the animals not exposed to pathogen.

Strengths:

This is overall a very nice piece of work. Most importantly, an initial screening of neurons was conducted by a compressed sensing-based approach previously applied by the same group. It is also worth emphasizing that this compressed analysis is applicable when the behavior of interest involves a small number of neurons, as the authors pointed out in the Introduction Session. Therefore, the readers should keep in mind that the validation and significance of this work heavily depend on the justification of scarcity parameters that the authors chose. Nevertheless, this work is well justified because neurons identified by the initial screening were thoroughly analyzed by various methods including calcium imaging and optogenetic manipulation of neuronal activities and behavioral analyses using an animal-tracking system.

Weaknesses:

My only concern is that the authors should be more careful about describing their "compressed sensing-based approach". Authors often cite their previous Nature Methods paper, but should explain more because this method is critical for this manuscript. Also, this analysis is based on the hypothesis that only a small number of neurons are responsible for a given behavior. Authors should explain more about how to determine scarcity parameters, for example.

Reviewer #3 (Public Review):

Coatl et al. investigated the mechanisms of synaptic plasticity of two important hippocampal synapses, the excitatory afferents from lateral and medial perforant pathways (LPP and MPP, respectively) of the entorhinal cortex (EC) connecting to granule cells of the hippocampal dentate gyrus (DG). They find that these two different EC-DG synaptic connections in mice show a presynaptically expressed form of long-term depression (LTD) requiring postsynaptic calcium, eCB synthesis, CB1R activation, astrocyte activity, and metabotropic glutamate receptor activation. Interestingly, LTD at MPP-GC synapses requires ionotropic NMDAR activation whereas LTD at LPP-GC synapse is NMDAR independent. Thus, they discovered two novel forms of t-LTD that require astrocytes at EC-GC synapses. Although plasticity of EC-DG granule cell (GC) synapses has been studied using classical protocols, These are the first analysis of the synaptic plasticity induced by spike timing dependent protocols at these synapses. Interestingly, the data also indicate that t-LTD at each type of synapse require different group I mGluRs, with LPP-GC synapses dependent on mGluR5 and MPP-GC t-LTD requiring mGluR1.

The authors performed a detailed analysis of the coefficient of variation of the EPSP slopes, miniature responses and different approaches (failure rate, PPRs, CV, and mEPSP frequency and amplitude analysis) they demonstrate a decrease in the probability of neurotransmitter release and a presynaptic locus for these two forms of LTD at both types of synapses. By using elegant electrophysiological experiments and taking advantage of the conditional dominant-negative (dn) SNARE mice in which doxycycline administration blocks exocytosis and impairs vesicle release by astrocytes, they demonstrate that both LTD forms require the release of gliotransmitters from astrocytes. These data add in an interesting way to the ongoing discussion on whether LTD induced by STDP participates in refining synapses potentially weakening excitatory synapses under the control of different astrocytic networks. The conclusions of this paper are mostly well supported by data, but some aspects the results must be clarified and extended.

(1) It should be clarified whether present results are obtained with or without the functional inhibitory synapse activation. It is not clear if GABAergic synapses are blocked or not. If GABAergic synapses are not blocked authors must discuss whether the LTD of the EPSPs is due to a decrease in glutamatergic receptor activation or an increase in GABAergic receptor activation. Moreover, it should be recommended to analyze not only the EPSPs but also the EPSCs to address whether the decrease in synaptic transmission is caused by a decrease in the input resistance or by a decrease in the space constant (lambda).<br /> (2) Authors show that Thapsigargin loaded in the postsynaptic neuron prevents the induction of LTD at both synapses. Analyzing the effects of blocking postsynaptic IP3Rs (Heparin in the patch pipette) and Ryanodine receptors (Ruthenium red in the patch pipette) is recommended for a deeper analysis of the mechanism implicated in the induction of this novel forms of LTD in the hippocampus.<br /> (3) Authors nicely demonstrate that CB1R activation is required in these forms of LTD by blocking CB1Rs with AM251, however an interesting unanswered question is whether CB1R activation is sufficient to induce this synaptic plasticity. This reviewer suggests studying whether applying puffs of the CB1R agonist, WIN 55,212-2, could induce these forms of LTD.<br /> (4) Finally, adding a last figure with a cartoon summarizing the proposed model of action in these novel forms of LTD would add a positive value and would help the reading of the manuscript, especially in those aspects related with the discussion of the results.

The extension of these results would improve the manuscript which provides interesting results showing two novel forms of presynaptic t-LTD in the brain synapses with different action mechanisms probably implicated in the different aspects of information processing.

Couple things: Elio ties the transition between immature to mature as the acceptance of a elongated, convoluted, and contradictory identity that cannot be condensed into words. Elio also displays this immaturity through one key behaviour: His "smuggling"of as much information into the fewest possible words, indicating his desire to condense his identity. Thirdly, in the next line, what that gives him in terms of appearance, he is unconfident and that juxtaposes him with Oliver

Can this characterise Oliver as someone who doesn't believe in the constructed identities of individuals, seeing as he says to all, "Later!" without naming? Or characterise him as someone who has no respect for societal obligations and is simply true to himself in such way?

Reviewer #3 (Public Review):

Summary:

Right-sided colorectal Cancer (CRC) is very different from left-sided CRC. Therefore it is important to model this cancer in mice and find new molecular targets. A broad set of data exists on FAK (Focal Adhesion Kinase) being important in colorectal cancer. However, this has focussed on APC mutant CRC which tends to be left-sided. BRAF mutation is common in right-sided CRC (and is rarely mutated with APC). Therefore the authors have tested whether FAK is important in this context. The authors show that FAK deletion surprisingly accelerates BRAF mutant CRC. Tumours arise in the proximal colon (which recapitulates BRAF mutant right-sided CRC). There are low for Lgr5 and high for foetal programmes. Mechanistically they suggest a pathway from FAK to NEDD4 to Lgr4 may underpin this phenotype.

Strengths:

Strong genetic data from FAK revealed that there is an acceleration of tumourigenesis and mice now develop proximal colon tumours and can be viewed as a good model of right-sided CRC.<br /> The expression data between humans and mice is strong.

Weaknesses:

The functional mechanism of how FAK loss promotes tumourigenesis is still quite correlative. An alternative hypothesis is that it drives inflammation in the proximal colon that drives tumourigenesis.

We still did not know the functional role for LGR4 (loss leads to a loss of paneth cells in homeostasis) so I'm not sure you can hypothesise a stem cell role.

Reviewer #3 (Public Review):

Summary:

The manuscript by Wang et al. investigates the effects of B. velezensis HBXN2020 in alleviating S. Typhimurium-induced mouse colitis. The results showed that B. velezensis HBXN2020 could alleviate bacterial colitis by enhancing intestinal homeostasis (decreasing harmful bacteria and enhancing the abundance of Lactobacillus and Akkermansia) and gut barrier integrity and reducing inflammation.

Strengths:

B. velezensis HBXN2020 is a novel species of Bacillus that can produce a great variety of secondary metabolites and exhibit high antibacterial activity against several pathogens. B. velezensis HBXN2020 is able to form endospores and has strong anti-stress capabilities. B. velezensis HBXN2020 has a synergistic effect with other beneficial microorganisms, which can improve intestinal homeostasis.

Weaknesses:

Few studies about the clinical application of Bacillus velezensis. Thus, more studies are still needed to explore the effectiveness of Bacillus velezensis before clinical application.

Reviewer #3 (Public Review):

Summary:

The authors examined the effects of glutamate release from PMv LepR neurons in the regulation of puberty and reproduction in female mice.

Strengths:

Multiple genetic mouse models were utilized to either manipulate PMv LepR neuron activities or to delete glutamate vesicle transporters from LepR neurons. The authors have been quite rigorous in validating these models and exploring potential contaminations. Most of the data presented are solid and convincing and support the conclusion.

Comments on revised version:

The authors have addressed most of my comments.

Reviewer #3 (Public Review):

Summary:

The manuscript by Pooja Popli and co-authors tested the importance of Atg14 in the female reproductive tract by conditionally deleting Atg14 using PrCre and also Foxj1cre. The authors showed that loss of Atg14 leads to infertility due to the retention of embryos within the oviduct. The authors further concluded that the retention of embryos within the oviduct is due to pyroptosis in oviduct cells leading to defective cellular integrity. The manuscript has some interesting findings, however there are also areas that could be improved.

Strengths:

The importance of Atg14 and autophagy in the female reproductive tract is incompletely understood. The manuscript also provides partial evidence about a new mechanism linking Atg14 to pyropotosis.

Weaknesses:

(1) It is not clear why the loss of Atg14 selectively induces Pyroptosis within oviduct cells but not in other cellular compartments. The authors should demonstrate that these events are not happening in uterine cells.

(2) The manuscript never showed any effect on the autophagy upon loss of Atg14. Is there any effect on autophagy upon Atg14 loss? If so does that contribute to the observation?

(3) It is not clear what the authors meant by cellular plasticity and integrity. There is no evidence provided in that aspect that the plasticity of oviduct cells is lost. Similarly, more experimental evidence is necessary for the conclusion about cellular integrity.

(4) The mitochondrial phenotype shown in Figure 3 didn't appear as severe as it is described in the results section. The analyses should be more thorough. They should include multiple frames (in supplemental information) showing mitochondrial morphology in multiple cells. The authors should also test that aspect in uterine cells. The authors should measure Feret's diagram. Difference in membrane potential etc. for a definitive conclusion.

(5) The comment that the loss of Atg14 and pyroptosis leads to the narrowing of the lumen in the oviduct should be experimentally shown.

(6) The manuscript never showed the proper mechanism through which Atg14 loss induces pyroptosis. The authors should link the mechanism.

Reviewer #3 (Public Review):

Summary:

Buck et al., set out to characterize small DNA tumor viruses through the generation and analysis of ~100,000 public sequencing datasets from the SRA and other databases. Using a variety of powerful bioinformatic methods including alignment-based searches, statistical modelling, and structure-aware detection, the authors successfully classify novel protein sequences which support the occurrence of evolutionary gene transfer between DNA virus families. The authors propose a naming scheme to better capture viral diversity and uncover novel chimeric viruses, those containing genes from multiple established virus families. Additional analysis using the generated dataset was performed to search for DNA and RNA viruses of interest, demonstrating the utility of generated datasets for exploratory screens. The assembled sequencing datasets are publicly available, providing invaluable resources for current and future investigations within this subfield.

Strengths:

The scope of data analysis (100,000+ SRA records and additional libraries) is substantial, and the authors have contributed to further insight into the modularity of previously uncharacterized viral genomes, through computationally demanding advanced bioinformatics analyses in addition to extensive manual inspection.

The publicly available resources generated as a result of these analyses provide useful data for further experiments to inspect viral diversity and modularity. Other scanning experiments and further investigation of biologically relevant viruses using these contigs may uncover, for example, animal reservoirs or novel recombinant viruses of significance.

Novel instances of genomic modularity provide excellent starting points for understanding virus evolutionary pathways and gene transfer events.

Weaknesses:

Overall, the methods section of this paper requires more detail.

The inclusion criteria for which "SRA" datasets were or were not utilized within this study are poorly defined. This means the comprehensiveness of the study for a given search space of the SRA is not defined, and the results are ultimately not reproducible, or expandable. For example, are all vertebrate RNA-seq samples processed? Or just aquatic vertebrate RNA-seq? Were samples randomly sampled from a more comprehensive data set? What is the make-up of the search space and how much was DNA-seq or RNA-seq? This section should be expanded and explicit accounting provided for how dataset selection was performed. This would provide additional confidence in the results and conclusions, as well as allow for future analysis to be conducted.

Hallmark virus genes require further clarification, as it is unclear what genes are utilized as bait, or in the initial search process. The reported "Hallmark gene sets" are not described in a systematic way. What is the sensitivity and specificity of these gene sets? Was there a validation of the performance characteristics (ROC) for this gene set with different tools? How is this expected to be utilized? Which kinds of viruses are excluded/missed? Are viroids included?

For the Tailtomavirus, additional information is needed for sufficient confidence. Was this "chimeric" genomic arrangement detected in a single library? This raises a greater issue of how technical artifacts, which may appear as chimeric assemblies, are ruled out in the workflow. If two viral genomes share a k-mer of length greater than the assembly k, the graph may become merged. Are there read pairs that span all regions of the genome? Is there evidence for multiple homologous viruses with synteny between them that supports the combination of these genes as an evolving genome, or is this an anomalous observation? Read alignments should be included and Bandage graph visualization for all cases of chimeric assemblies and active steps to disprove the baseline hypotheses that these are technical artifacts of genome assembly.

Justification for exclusion of endogenized sequences is not included and must be described, as small DNA tumor viruses may endogenize into the host genome as part of their life cycle. How is such an integration resolved from an evolutionary "endogenization"? What's the biological justification for this step?

Additional supporting information, clear presentation, and context are needed to strengthen results and conclusions.

Basic reporting of global statistics, such as the total number of viruses found per family, should be included in the main text to better support the scope of the results. How many viruses (per family) were previously known, and therefore what is the magnitude of the expansion performed here?

Additional parameters and information should be included in bioinformatic tool outputs to provide greater clarity and interpretation of results. For example, reporting the "BLASTp E-val", as for the PolB homology (BLASTp 6E-12) is not informative, and does not tell the reader this is (we assume) an expectancy value. For each such case please report, the top database hit accession, percent identity, query coverage, and E-value. Otherwise, a judgment cannot be adequately made regarding the quality of evidence for homology. Similarly, for HHpred what does the number represent - confidence, identity, or coverage?

Some findings described in the Results section may require revision. Several of the Nidoviruses (Nidovirus takifugu, Nidovirus hypomesus, Nidovirus ambystoma, etc...) have been previously described by three groups, first by Edgar et al., (https://www.nature.com/articles/s41586-021-04332-2), then Miller et al., (https://academic.oup.com/ve/article/7/2/veab050/6290018) and then Lauber et al., (https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1012163). This is now the 4th description of the same set of viruses. These sequences are in GenBank (https://www.ncbi.nlm.nih.gov/nuccore/OV442424.1), although it is unclear why they're not returned as BLAST hits. Miller also described the Togavirus co-segment previously.

It is also uncertain what is being described with HelPol/maldviruses which was not previously described in distantly similar relatives. How many were described in the previous literature and how many are described by this work?

Co-phylogenies should be used to convey gene transfer and flow clearly to support the conclusions made in the text.

Statements such as, "The group encompasses a surprising degree of genomic diversity...", should be supported by additional information to strengthen conclusions (e.g., what the expected diversity is). What is the measurement for genomic diversity here, and why is this surprising? There is overall a lack of quantification to support the conclusions made throughout the paper.

Reviewer #3 (Public Review):

Summary:

In this manuscript the authors begin with the interesting phenotype of sub-inhibitory concentrations of the aminoglycoside tobramycin proving toxic to a knockout of the tRNA-guanine transglycosylase (Tgt) of the important human pathogen, Vibrio cholerae. Tgt is important for incorporating queuosine (Q) in place of guanosine at the wobble position of GUN codons. The authors go on to define a mechanism of action where environmental stressors control expression of tgt to control translational decoding of particularly tyrosine codons, skewing the balance from TAC towards TAT decoding in the absence of the enzyme. The authors use advanced proteomics and ribosome profiling to reveal that the loss of tgt results in increased translation of proteins like RsxA and a cohort of DNA repair factors, whose genes harbor an excess of TAT codons in many cases. These findings are bolstered by a series of molecular reporters, mass spectrometry, and tRNA overexpression strains to provide support for a model where Tgt serves as a molecular pivot point to reprogram translational output in response to stress.

Strengths:

The manuscript has many strengths. The authors use a variety of strains, assays, and advanced techniques to discover a mechanism of action for Tgt in mediating tolerance to sub-inhibitory concentrations of tobramycin. They observe a clear phenotype for a tRNA modification in facilitating reprogramming of the translational response, and the manuscript certainly has value in defining how microbes tolerate antibiotics.

Weaknesses:

The conclusions of the manuscript are mostly very well-supported by the data, but in some places control experiments or peripheral findings cloud precise conclusions. Some additional clarification, discussion, or even experimental extension could be useful in strengthening these areas.

(1) The authors have created and used a variety of relevant molecular tools. In some cases, using these tools in additional assays as controls would be helpful. For example, testing for compensation of the observed phenotypes by overexpression of the Tyrosine tRNA(GUA) in Figure 2A with the 6xTAT strain, Figure 5C with the rxsA-GFP fusion, and/or Figure 7B with UV stress would provide additional information of the ability of tRNA overexpression to compensate for the defect in these situations.<br /> (2) The authors present a clear story with a reprogramming towards TAT codons in the knockout strain, particularly regarding tobramycin treatment. The control experiments often hint at other codons also contributing to the observed phenotypes (e.g., His or Asp), yet these effects are mostly ignored in the discussion. It would be helpful to discuss these findings at a minimum in the discussion section, or possibly experimentally address the role of His or Asp by overexpression of these tRNAs together with Tyrosine tRNA(GUA) in an experiment like that of Figure 1I to see if a more "wild type" phenotype would present. In fact, the synergy of Tyr, His, and/or Asp codons likely helps to explain the effects observed with the DNA repair genes in later experiments.<br /> (3) Regarding Figure 6D, the APB northern blot feels like an afterthought. It was loaded with different amounts of RNA as input and some samples are repeated three times, but Δcrp only once. Collectively, it makes this experiment very difficult to assess.

Minor Points:<br /> (4) Fig S2B, do the authors have a hypothesis why the Asp and Phe tRNAs lead to a growth decrease in the untreated samples? It appears like Phe(GAA) partially compensates for the defect.<br /> (5) Lines 655 to 660 seem more appropriate as speculation in the discussion rather than as a conclusion in the results, where no direct experiments are performed. The authors might take advantage of the "Ideas and Speculation" section that eLife allows.

Reviewer #3 (Public Review):

Summary:

This paper presents bees with varying levels of experience with a choice task where bees have to choose to pull either a connected or unconnected string, each attached to a yellow flower containing sugar water. Bees without experience of string pulling did not choose the connected string above chance (experiment 1), but with experience of horizontal string pulling (as in the right-hand panel of Figure 4) bees did choose the connected string above chance (experiments 2-3), even when the string colour changed between training and test (experiments 4-5). Bees that were not provided with perceptual-motor feedback (i.e they could not observe that each pull of the string moved the flower) during training still learned to string pull and then chose the connected string option above chance (experiment 6). Bees with normal experience of string pulling then failed to discriminate between connected and unconnected strings when the strings were coiled or looped, rather than presented straight (experiments 7-8).

Weaknesses:

The authors have only provided video of some of the conditions where the bees succeeded. In general, I think a video explaining each condition and then showing a clip of a typical performance would make it much easier to follow the study designs for scholars. Videos of the conditions bees failed at would be highly useful in order to compare different hypotheses for how the bees are solving this problem. I also think it is highly important to code the videos for switching behaviours. When solving the connected vs unconnected string tasks, when bees were observed pulling the unconnected string, did they quickly switch to the other string? Or did they continue to pull the wrong string? This would help discriminate the use of perceptual-motor feedback from other hypotheses.

The experiments are also not described well, for my below comments I have assumed that different groups of bees were tested for experiments 1-8, and that experiment 6 was run as described in line 331, where bees were given string-pulling training without perceptual feedback rather than how it is described in Figure 4B, which describes bees as receiving string pulling training with feedback.

The authors suggest the bees' performance is best explained by what they term 'image matching'. However, experiment 6 does not seem to support this without assuming retroactive image matching after the problem is solved. The logic of experiment 6 is described as "This was to ensure that the bees could not see the familiar "lollipop shape" while pulling strings....If the bees prefer to pull the connected strings, this would indicate that bees memorize the arrangement of strings-connected flowers in this task." I disagree with this second sentence, removing perceptual feedback during training would prevent bees memorising the lollipop shape, because, while solving the task, they don't actually see a string connected to a yellow flower, due to the black barrier. At the end of the task, the string is now behind the bee, so unless the bee is turning around and encoding this object retrospectively as the image to match, it seems hard to imagine how the bee learns the lollipop shape.

Despite this, the authors go on to describe image matching as one of their main findings. For this claim, I would suggest the authors run another experiment, identical to experiment 6 but with a black panel behind the bee, such that the string the bee pulls behind itself disappears from view. There is now no image to match at any point from the bee's perspective so it should now fail the connectivity task.

Strengths:

Despite these issues, this is a fascinating dataset. Experiments 1 and 2 show that the bees are not learning to discriminate between connected and unconnected stimuli rapidly in the first trials of the test. Instead, it is clear that experience in string pulling is needed to discriminate between connected and unconnected strings. What aspect of this experience is important? Experiment 6 suggests it is not image matching (when no image is provided during problem-solving, but only afterward, bees still attend to string connectivity) and casts doubt on perceptual-motor feedback (unless from the bee's perspective, they do actually get feedback that pulling the string moves the flower, video is needed here). Experiments 7 and 8 rule out means-end understanding because if the bees are capable of imagining the effect of their actions on the string and then planning out their actions (as hypotheses such as insight, means-end understanding and string connectivity suggest), they should solve these tasks.

If the authors can compare the bees' performance in a more detailed way to other species, and run the experiment suggested, this will be a highly exciting paper

Reviewer #3 (Public Review):

Summary:

This study established a single-cell RNA sequencing atlas of pipefish embryos. The results obtained identified unique gene expression patterns for pipefish-specific characteristics, such as fgf22 in the tip of the palatoquadrate and Meckel's cartilage, broadly informing the genetic mechanisms underlying morphological novelty in teleost fishes. The data obtained are unique and novel, potentially important in understanding fish diversity. Thus, I would enthusiastically support this manuscript if the authors improve it to generate stronger and more convincing conclusions than the current forms.

Weaknesses:

Regarding the expression of sfrp1a and bmp4 dorsal to the elongating ethmoid plate and surrounding the ceratohyal: are their expression patterns spatially extended or broader compared to the pipefish ancestor? Is there a much closer species available to compare gene expression patterns with pipefish? Did the authors consider using other species closely related to pipefish for ISH? Sfrp1a and bmp4 may be expressed in the same regions of much more closely related species without face elongation. I understand that embryos of such species are not always accessible, but it is also hard to argue responsible genes for a specific phenotype by only comparing gene expression patterns between distantly related species (e.g., pipefish vs. zebrafish). Due to the same reason, I would not directly compare/argue gene expression patterns between pipefish and mice, although I should admit that mice gene expression patterns are sometimes helpful to make a hypothesis of fish evolution. Alternatively, can the authors conduct ISH in other species of pipefish? If the expression patterns of sfrp1a and bmp4 are common among fishes with face elongation, the conclusion would become more solid. If these embryos are not available, is it possible to reduce the amount of Wnt and BMP signal using Crispr/Cas, MO, or chemical inhibitor? I do think that there are several ways to test the Wnt and/or BMP hypothesis in face elongation.

for - Buddhist teachings - 3 marks of existence - birth and death

Buddhist teachings - 3 marks of existence - The 3 marks of existence - there is no unchanging self - it is characterized by impermanence and suffering - whatever comes into being must pass away - also describe that we ourselves as human INTERbeCOMings, are aspects of reality - that come into being - and must pass away

DOI: 10.7554/eLife.89516

Resource: (ZFIN Cat# ZDB-GENO-140423-3,RRID:ZFIN_ZDB-GENO-140423-3)

Curator: @scibot

SciCrunch record: RRID:ZFIN_ZDB-GENO-140423-3

What is this?

Reviewer #3 (Public Review):

Summary:

In this study, the authors analyzed data from 99 individuals with implanted electrodes who were performing a word-list recall task. Because the task involves successively encoding and then recalling 25 lists in a row, they were able to measure the similarity in neural responses for items within the same list as well as items across different lists, allowing them to test hypotheses about the impact of between-list boundaries on neural responses. They find that, in addition to slow drift in responses across items within a list and changes across lists, there is boundary-related structure in the medial parietal lobe such that early items in each list show similarity (for recalled items) and late items in each list show similarity (for not recalled items).

Strengths:

The dataset used in this paper is substantially larger than most iEEG datasets, allowing for the detection of nuanced differences between item positions and for analyses of individual differences in boundary-related responses. There are excellent visualizations of the similarity structure between items for each region, and this work connects to a growing literature on the role of event boundaries in structuring neural responses.

Weaknesses:

(1) The visualization in Fig 1B claims that the prediction of the temporal context model is that nearby items in the presented sequence should have similar representations; that is, nearby items within a list should be similar, and the end of a list should look similar to the beginning of the next list. First, it's unclear to me if this is exactly what TCM would predict for this dataset, since lists are separated by ~60 seconds of distractor and retrieval tasks, rather than simply by a brief event boundary. Second, the authors do not actually test this model of continuous similarity across lists. After examining smooth drift in the within-list analysis (Fig 2), the across-list analyses (Figs 3-5) use a model with a "list distance" regressor that predicts discrete changes between lists. The authors state that it is not possible to replace this list distance regressor with an item distance regressor (which would be a straight line in Fig 3D rather than stair-steps) because this would be too collinear with the boundary proximity regressor, but I do not understand why these regressors would be collinear at all (since the boundary proximity regressor does not systematically increase or decrease across items).

(2) There is no theoretical or quantitative justification for the specific forms of the boundary proximity models, For initial items, a model of e^(1-d) is used (with d being serial position), but it is not stated how the falloff scale of this model was selected (as opposed to e.g. e^((1-d)/2)). For final items, a different linear model of d/#items is used, which seems to have a somewhat different interpretation, since it changes at a constant rate across all items rather than only modeling items near the final boundary. Confusingly, the schematic in Fig 1B shows symmetric effects at initial and final boundaries, despite two different models being used and the authors' assertion in their response that they do not believe these processes are symmetric.

(3) It is unclear to me whether the authors believe that the observed similarity after boundaries is due to an active process in which "the medial parietal lobe uses drift-resets" to reinstate a boundary-related context, or that this similarity is simply because "the context for the first item may be the boundary itself", and therefore this effect would emerge naturally from a temporal context model that incorporates the full task structure as the "items."

Reviewer #3 (Public Review):

Summary:

The authors food-deprived male and female mice and observed a much stronger reduction of leptin levels, energy consumption in the visual cortex, and visual coding performance in males than females. This indicates a sex-specific strategy for the regulation of the energy budget in the face of low food availability.

Strengths:

This study extends a previous study demonstrating the effect of food deprivation on visual processing in males, by providing a set of clear experimental results, demonstrating the sex-specific difference. It also provides hypotheses about the strategy used by females to reduce energy budget based on the literature.

Weaknesses:

The authors do not provide evidence that females are not impacted by visually guided behaviors contrary to what was shown in males in the previous study.

Reviewer #3 (Public Review):

Summary:

Te Rietmolen et al., investigated the selectivity of cortical responses to speech and music stimuli using neurosurgical stereo EEG in humans. The authors address two basic questions: 1. Are speech and music responses localized in the brain or distributed; 2. Are these responses selective and domain specific or rather domain general and shared. To investigate this, the study proposes a nomenclature of shared responses (speech and music responses are not significantly different), domain selective (one domain is significant from baseline and the other is not), domain preferred (both are significant from baseline but one is larger than the other and significantly different from each other). The authors employ this framework using neural responses across the spectrum (rather than focusing on high gamma), providing evidence for a low level of selectivity across spectral signatures. To investigate the nature of the underlying representations they use encoding models to predict neural responses (low and high frequency) given a feature space of the stimulus envelope or peak rate (by time delay) and find stronger encoding for both in the low frequency neural responses. The top encoding electrodes are used as seeds for a pair-wise connectivity (coherence) in order to repeat the shared/selective/preferred analysis across the spectra, suggesting low selectivity. Spectral power and connectivity are also analyzed on the level of regional patient population to rule out (and depict) any effects driven by a select few patients. Across analyses the authors consistently show a paucity of domain selective responses and when evident these selective responses were not represented across the entire cortical region. The authors argue that speech and music mostly rely on shared neural resources.

Strengths:

I found this manuscript to be rigorous providing compelling and clear evidence towards shared neural signatures for speech and music. The use of intracranial recordings provides an important spatial and temporal resolution that lends itself to the power, connectivity and encoding analyses. The statistics and methods employed are rigorous and reliable, estimated based on permutation approaches and cross-validation/regularization was employed and reported properly. The analysis of measures across the entire spectra in both power, coherence and encoding models provides a comprehensive view of responses that no doubt will benefit the community as an invaluable resource. Analysis on the level of patient population (feasible with their high N) per region also supports the generalizability of the conclusions across a relatively large cohort of patients. Last but not least, I believe the framework of selective, preferred, and shared is a welcome lens through which to investigate cortical function.

Weaknesses:

I did not find methodological weaknesses in the current version of the manuscript. I do believe that it is important to highlight that the data is limited to passively listening to naturalistic speech and music. The speech and music stimuli are not completely controlled with varying key acoustic features (inherent to the different domains). Overall, I found the differences in stimulus and lack of attentional controls (passive listening) to be minor weaknesses that would not dramatically change the results or conclusions.

Reviewer #3 (Public Review):

Summary:

In this article, Gao et. al. uses single-molecule FRET (smFRET) and position-specific labelling of RNA (PLOR) to dissect the folding and behavioral ligand sensing of the Guanidine-IV riboswitch in the presence and absence of the ligand guanidine and the cation Mg2+. Results provided valuable information on the mechanistic aspects of the riboswitch, including the confirmation on the kissing loop present in the structure as essential for folding and riboswitch activity. Co-transcriptional investigations of the system provided key information on the ligand-sensing behavior and ligand-binding window of the riboswitch. A plausible folding model of the Guanidine-IV riboswitch was proposed as a final result. The evidence presented here sheds additional light into the mode of action of transcriptional riboswitches.

Strengths:

The investigations were very thorough, providing data that supports the conclusions. The use of smFRET and PLOR to investigate RNA folding has been shown to be a valuable tool to the understand of folding and behavior properties of these structured RNA molecules. The co-transcriptional analysis brought important information on how the riboswitch works, including the ligand-sensing and the binding window that promotes the structural switch. The fact that investigations were done with the aptamer domain, aptamer domain + terminator/anti-terminator region, and the full length riboswitch were essential to inform how each domain contributes to the final structural state if in the presence of the ligand and Mg2+.

Weaknesses:

The system has its own flaws when comparing to physiological conditions. The RNA polymerase used (the study uses T7 RNA polymerase) is different from the bacterial RNA polymerase, not only on complexity, but also in transcriptional speed, that can direct interfere with folding and ligand-sensing. Additionally, rNTPs concentrations were much lower than physiological concentrations during transcription, likely causing a change in the polymerase transcriptional speed. These important aspects and how they could interfere with results are important to be addressed to the broad audience. Another point of consideration to be aware is that the bulky fluorophores attached to the nucleotides can interfere with folding to some extent.

Reviewer #3 (Public Review):

Summary:

Weng and colleagues investigated the association between attention-related connectivity and substance use. They conducted a study with a sizable sample of over 1,000 participants, collecting longitudinal data at ages 14, 19, and 23. Their findings indicate that behaviors and brain connectivity linked to sustained attention at age 14 forecasted subsequent increases in cigarette and cannabis use from ages 14 to 23. However, early substance use did not predict future attention levels or attention-related connectivity strength.

Strengths:

The study's primary strength lies in its large sample size and longitudinal design spanning three time-points. A robust predictive analysis was employed, demonstrating that diminished sustained attention behavior and connectivity strength predict substance use, while early substance use does not forecast future attention-related behavior or connectivity strength.

Weaknesses:

It's questionable whether the prediction approach (i.e., CPM), even when combined with longitudinal data, can establish causality. I recommend removing the term 'consequence' in the abstract and replacing it with 'predict'. Additionally, the paper could benefit from enhanced rigor through additional analyses, such as testing various thresholds and conducting lagged effect analyses with covariate regression.