Reviewer #1 (Public Review):

This work investigated Fragile X Messenger Ribonucleoprotein (FMRP) protein impact on neuroblast tangential migration in the postnatal rostral migratory stream (RMS). Authors conducted series of live-imaging on organotypic brain slices from Fmr1-null mice. They continued their analysis silencing Fmr1 exclusively from migrating neuroblasts using electroporation-mediated RNA interference method (MiRFmr1 KD). These impressive approaches show that neuroblasts tangential migration is impaired in Fmr1-null mice RMS and these defects are mostly recapitulated in the MiRFmr1neuroblasts.This nicely supports the idea that FMRP have a cell autonomous function in tangentially migrating neuroblasts. It is an important part of this work as migrating neuroblasts are in contact with each other and surrounding glial cells while migrating towards the olfactory bulb. The authors also confirm that FMRP mRNA target Microtubule Associated Protein 1B (MAP1B) is overexpressed in the Fmr1-null mice RMS. They successfully use electroporation-mediated RNA interference method to silence Map1b in the Fmr1-null mice neuroblasts. This discreet and elaborate experiment rescues most of the migratory defects observed both in Fmr1-null and MiRFmr1neuroblasts. Altogether, these results strongly suggest that FMRP-MAP1B axis has an important role in regulation of the neuroblasts tangential migration in RMS. Neurons move forward in cyclic saltatory manner which includes repeated steps of leading process extension, migration of the cell organelles and nuclear translocation. Authors reveal by analyzing the live-imaging data that FMRP-MAP1B axis is affecting movement of centrosome and nucleus during saltatory migration. An important part of the centrosome and nucleus movement is forces mediated by microtubule dynamics. Authors propose that FMRP regulate tangential migration via microtubule dynamics regulator MAP1B. This work provides valuable new information on regulation of the neuroblasts tangential saltatory migration. These findings also increase and improve our understanding of the issues involved in Fragile X Syndrome (FXS) disorders. The conclusions of this work are mostly supported by the data. However, methods and data analysis would benefit from more careful and comprehensive scrutiny.

1.) It would be beneficial for the detail-oriented readers to have a more comprehensive section of neuronal migration analysis. It would help to understand better the details of the results and analysis. For example, percentage of pausing time. Is neuroblast migration speed and pausing time (%) separated from each other? Does this mean that migration speed is measured from time of the nucleus movement, and it excludes pausing time? Sometimes migration speed refers to the total distance that cells have moved divided by the time between images (e.g., Nam et al. 2007, J Comp Neurol 505: 190-208). This is also important as neuroblasts migration speed fluctuate during their migration in RMS (e.g., Belvindrah et al. 2017, J Cell Biol 216: 2443-2461). It could be useful, for example, to show a plot of total migration distance distribution between controls, Fmr1-null, MiRFmr1 KD and MiRMap1b KD neuroblasts.

2.) The author's claim that Fmr1 interfering RNA (MiFmr1 KD) model "recapitulates the entire migratory phenotype described in Fmr1-null mutants". This is evident from the data analysis for the migration speed, pausing time percentage and NK distance. Parallel, but slightly weaker effect is seen in, NK frequency, CK frequency and CK efficiency. However, interpretation of the directionality analysis causes some concerns.<br /> a) Sinuosity index<br /> Fmr1-null mice (ctr: 1.32{plus minus}0.04; Fmr1-null: 1.93{plus minus}0.16; Figure 2C) and MiFmr1 KD neurons (MiRNEG: 1.5{plus minus}0.12; MiRFmr1 KD 1.62 {plus minus}0.08; Figure S1C). The latter results are significant, but standard error of means (SEM) seems to overlap. In addition, there is only a minor difference between control and MiRFmr1 KD cells sinuosity index.<br /> b) Directionality radar<br /> Migration directionality radar seems to be considerably different between Fmr1-null (Figure 2D) and MiFmr1 KD results (Figure S1D).<br /> It would be beneficial for this article to fully disclose, how these analyses were performed. For example, how sinuosity index was calculated and what does it precisely measure. It would greatly help to understand better the directionality analysis. To make these results more solid authors could have used original migration trajectories in the rose and/or trajectory plots. These plots visualize better the migration directionality results and clarify the changes in the directionality during migration.

3.) Authors claim that "Overall, our results demonstrate that MAP1B is the main FMRP mRNA target involved in the regulation of neuronal migration". Results and analysis show that migration speed, pausing time percentage, NK distance and NK frequency migratory defects are all rescued in Fmr1-null mice when MiRMap1b KD was introduced to the neuroblasts (Figure 4). These results are very interesting, linking FMRP-MAP1B axis to the microtubule dynamics.

4.) Authors could refine in discussion what is known about FRMP in neuronal migration. For example, La Fata et al. 2014 found that N-cadherin protein levels were lower in Fmr1-null mice and reintroducing N-cadherin rescued embryonic radial migration defects. N-cadherin is also expressed in the RMS and its deficiency affects negatively to the neuroblast migration (e.g., Porlan et al. 2014, Nat Cell Biol (7):629-38). This relationship of FMRP and N-cadherin could be discussed and considered in the article more closely. Overall, the article will benefit from clearer writing and more comprehensive discussion.

Reviewer #1 (Public Review):

In their manuscript entitled, "Reward contingency gates selective cholinergic suppression of amygdala neurons," Kimchi and colleagues explore the engagement and consequences of acetylcholine (ACh) signaling in the basolateral amygdala (BLA) using a number of sophisticated methodological approaches.

Perhaps the most compelling new idea in this manuscript is that ACh may have different effects on network activity in the BLA, a conclusion based on the measurement of equivalent photo-stimulated ACh levels in BLA during rewarded vs. unrewarded lick bouts despite increased licking/consumption in the rewarded bouts. The authors hypothesize that, "this could suggest that reward associations may gate post-synaptic responses to photostimulation." The electrophysiological data showing that overall firing of BLA neurons during licking was higher as a result of photostimulation during unreinforced, and lower as a result of photostimulation during reinforced, sessions is intriguing in this context, as is the contrast with the overall ACh-mediated stimulation of firing in dorsomedial prefrontal cortex. The ex-vivo data presented showing that ACh depresses BLA neuron activity via muscarinic ACh receptors on glutamate neurons and nicotinic ACh receptors on GABA neurons, along with previous data in the field suggesting that ACh has divergent effects on neuronal firing rate depending on whether baseline firing is low (tonic) or high (phasic), provides intriguing hints as to the role of ACh in state-dependent modulation of BLA activity.

One of the primary questions that came up while reading this manuscript was what behavioral domains were being measured with the "windows of opportunity" task. As noted by the authors, the cholinergic system has been implicated in arousal, reward thresholds, motivation and many other behaviors that might alter performance in this task, complicating interpretation of the data presented. In addition, some additional details of the task are needed for the field to be able to replicate these experiments.

Reviewer #1 (Public Review):

The manuscript by Hage et al. presents interesting results from a foraging behavior in Marmosets that explores the interactions of saccade and lick vigor with pupil dilation and performance as well as a marginal value theory and foraging theory-inspired value-based decision-making model thereof. The results are generally robust and carefully presented and analyses, particularly of vigor, are carefully executed.

The authors constructed a model that makes two predictions: "In summary, this simple theory made two sets of predictions: in response to an increased cost of harvest, one should work longer, but move with reduced vigor. In response to an increased reward value, as in hunger, one should also work longer, but now move with increased vigor." Their behavioral data meets these predictions. It is not clear if the model was designed and tweaked in order to make those predictions and match the data, or derived from principles. Furthermore, it is not clear what other models would make similar predictions. It would help to assess what is predicted by other simple models, as well as different functional forms for the effort costs in their model.

Line 37 page 6; the link of pupil to NE/LC is tenuous. Other modulators systems and circuits may be equally important and should be mentioned (e.g. Reimer, Jacob, Matthew J. McGinley, Yang Liu, Charles Rodenkirch, Qi Wang, David A. McCormick, and Andreas S. Tolias. "Pupil fluctuations track rapid changes in adrenergic and cholinergic activity in cortex." Nature communications 7, no. 1 (2016): 13289.)<br /> Line 35 page 6-page 7 line 10 emphasizes a cognitive interpretation of the pupil dilations they is emphasized, in relation to effort costs. But there are also concomitant more vigorous movements. Could all of their pupil results be explained by motor correlates? This should be tested and ruled out before making cognitive interpretations.<br /> Page 7, line 37-42: How would the model need to be modified in order to account for this discrepancy with the data? Ideally, this would be tested.<br /> Page 9, line 2-11: In this section, it would help to also consider 'baseline' pupil size (in between trials). This would give a signal that is not 'contaminated' by movements, and may reflect control state. Relatedly, changes in control state may impact and confound the movement-related dilation magnitudes due to e.g. floor and ceiling effects on pupil size, which has a strong tendency for reversion to the mean.<br /> Page 10 line 21-32 presents a dated view of pupil that has/had little data supporting it. They should mention other neuromodulators (Reimer et al., 2016) and related interpretations.<br /> The hunger-related and reward-size related analyses are both heavily confounded since they were not manipulated directly and could co-vary with many latent factors. For example, why might a given Marmoset be lower weight on a given day? Could it affect sleep, stress, activity, or other factors during the preceding 24 hours? If so, could these other variables be driving the results that are interpreted as 'hunger?' Relatedly, since the reward size is determined by the animals behavior on each trial (how much they worked), factors (internal brain state, external noises, etc.) that alter how much they worked will influence the subsequent reward size. Therefore interpretations about reward expectancy are confounded. Both of these issues should be discussed and manipulations of them (different feeding schedules and reward size-work functions proposed, respectively.<br /> A major issue is a lack of alternative models. The authors seem to have constructed a particular model designed to capture the behavioral patterns they observed in the data. The model fails in some instances, as they point out. Even more importantly, there are no results or discussion about how other plausible models could or couldn't fit the data. The lack of model comparisons makes it difficult to interpret the conclusions or put the results in a broader context.

Reviewer #1 (Public Review):

This manuscript by He et al. explores the molecular basis of the different stinging behaviors of two related anemones. The freshwater Nematostella which only stings when a food stimulus is presented with mechanical stimulation and the saltwater Exaiptasia which stings in response to mechanical stimuli. The authors had previously shown that Nematostella stinging is calcium-dependent and mediated by a voltage-gated calcium channel (VGCC) with very pronounced voltage-dependent inactivation, which gets removed upon hyperpolarization produced by taste receptors.

In this manuscript, they show that Exaiptacia and Nematostella differing stinging behavior is near optimal, according to their ecological niche, and conforms to predictions from a Markov decision model.

It is also shown that Exaiptacia stinging is also calcium-dependent, but the calcium channel responsible is much less inactivated at resting potential and can readily induce nematocyte discharge only in the presence of mechanical stimulation. To this end, the authors record calcium currents from Exaipacia nematocysts and discover that the VGCCs in this anemone are not strongly inactivated and thus are easily activated by mechanical stimuli-induced depolarization accounting for the different stinging behavior between species. The authors further explore the role of the auxiliary beta subunit in the modulation of VGCC inactivation and show that different n-terminal splice variants in Exaiptacia produce strong and weak voltage-dependent inactivation.

The manuscript is clear and well-written and the conclusions are in general supported by the experiments and analysis. The findings are very relevant to increase our understanding of the molecular basis of non-neural behavior and its evolutionary basis. This manuscript should be of general interest to biologists as well as to more specialized fields such as ion channel biophysics and physiology.

Some findings need to be clarified and perhaps additional experiments performed.

1) The authors identify by sequencing that the Exaiptacia Cav is a P-type channel (cacna1a). However, the biophysical properties of the nematocyte channel are different from mammalian P-type channels. The cnidarian channel inactivation is exceedingly rapid and activation happens at relatively low voltages. These substantial differences should be mentioned and commented on.

2) The currents from Nematostella in Figure 3d seem to be poorly voltage-clamped. Poor voltage-clamp is also evident in the sudden increase of conductance in Figure 3C and might contribute to incorrect estimation of voltage dependence of activation and if present in inactivation experiments, also to incorrect estimation of the inactivation voltage range. This problem should be reassessed with new data.

3) While co-expression of the mouse Cav channel with the beta1 isoform from Exaiptacia indeed shifts inactivation to more negative voltages, it does not recapitulate the phenotype of the more inactivated Ca-currents in nematocytes (compare Figures 4d and 5d). It should be explained if this might be due to the use of a mammalian alpha subunit. Related to this, did the authors clone the alpha subunit from Exaiptacia? Using this to characterize the effect of beta subunits on inactivation might be more accurate.

4) The in situ shown in Figure 4b are difficult to follow for a non-expert in cnidarian anatomy. Some guidance should be provided to understand the structures. Also, for the left panels, is the larger panel the two-channel image? If so, blue would indicate co-localization of the two isoforms and there seems to be a red mark in the same nematocyte.

Reviewer #1 (Public Review):

In this manuscript, the authors explore the effects of DNA methylation on the strength of regulatory activity using massively parallel reporter assays in cell lines on a genome-wide level. This is a follow-up of their first paper from 2018 that describes this method for the first time. In addition to adding more in-depth information on sequences that are explored by many researchers using two main methods, reduced bisulfite sequencing and sites represented on the Illumina EPIC array, they now show also that DNA methylation can influence changes in regulatory activity following a specific stimulation, even in absence of baseline effects of DNA methylation on activity. In this manuscript, the authors explore the effects of DNA methylation on the response to Interferon alpha (INFA) and a glucocorticoid receptor agonist (dexamethasone). The authors validate their baseline findings using additional datasets, including RNAseq data, and show convergences across two cell lines. The authors then map the methylation x environmental challenge (IFNA and dex) sequences identified in vitro to explore whether their methylation status is also predictive of regulatory activity in vivo. This is very convincingly shown for INFA response sequences, where baseline methylation is predictive of the transcriptional response to flu infection in human macrophages, an infection that triggers the INF pathways. The extension of the functional validity of the dex-response altering sequences is less convincing. Sequences altering the response to glucocorticoids, however, were not enriched in DNA methylation sites associated with exposure to early adversity. The authors interpret that "they are not links on the causal pathway between early life disadvantage and later life health outcomes, but rather passive biomarkers". However, this approach does not seem an optimal model to explore this relationship in vivo. This is because exposure to early adversity and its consequences is not directly correlated with glucocorticoid release and changes in DNA methylation levels following early adversity could be related to many physiological mechanisms, and overall, large datasets and meta-analyses do not show robust associations of exposure to early adversity and DNA methylation changes. Here, other datasets, such as from Cushing patients may be of more interest.

Overall, the authors provide a great resource of DNA methylation-sensitive enhancers that can now be used for functional interpretation of large-scale datasets (that are widely generated in the research community), given the focus on sites included in RBSS and the Illumina EPIC array. In addition, their data lends support that differences in DNA methylation can alter responses to environmental stimuli and thus of the possibility that environmental exposures that alter DNS methylation can also alter the subsequent response to this exposure, in line with the theory of epigenetic embedding of prior stimuli/experiences. The conclusions related to the early adversity data should be reconsidered in light of the comments above.

Reviewer #1 (Public Review):

The studies by Hwangbo et al. diligently attempt to account for many of the typically neglected dietary and non-dietary factors.

Strengths:

• Work addresses many potential artifacts of dietary (e.g., dehydration stress, macronutrient ratios, and protein source) and non-dietary (e.g., leaky expression of S106-GAL4) manipulations-important factors that are too often overlooked.<br /> • Balanced and complementary behavioral, molecular, and bioinformatic experiments<br /> • Show necessity of proteostatic subunits in the fat body for DR-mediated longevity. The findings in the current manuscript lay the ground for future studies that test sufficiency of fat body prosβ3 and rpn7, or necessity of other proteostatic genes in other tissues.

Weaknesses:

• Could the lack of DR response in clock mutants across dietary concentrations be simply because the clock mutants are better at compensatory feeding adjustments to dietary dilutions? If this were the case, there are two major implications to the authors' conclusions:<br /> a) The Clk mutants are differently responding to dietary dilutions, not to dietary restriction, per se.<br /> b) Nutritional intake was unaffected by the dietary manipulations. If the changes in fat body proteostasis and lifespan were due to nourishment, it would be expected that the physiology and lifespan do not change.<br /> Accurate measurements of food consumption and the resulting protein intake could potentially clarify this critical question.

Reviewer #1 (Public Review):

Ciampa et al. investigated the role of the hypoxia-inducible factor 1 (HIF-1) pathway in placental aging. They performed transcriptomic analysis of prior data of placental gene expression over serial timepoints throughout gestation in a mouse model and identified increased expression of senescence and HIF-1 pathways and decreased expression of cell cycle and mitochondrial transcripts with advancing gestational age. These findings were confirmed by RT-PCR, Western blot, and mitochondrial assessment from mouse placental tissues from late gestation time points. Studies of human placental samples at similar late gestational ages showed similar trends in increased HIF-1 targets and decreased mitochondrial abundance with increasing gestation, but were not significantly significant due to the limited availability of uncomplicated preterm placenta samples. The authors demonstrated that stabilization of HIF-1 in vitro using primary trophoblasts and choriocarcinoma cell lines recapitulated the gene and mitochondrial dysfunction seen in the placental tissues and were consistent with senescence. Interestingly, cell-conditioned media from HIF-1 stabilized placenta cell lines induced myometrial cell contractions in vitro and correspondingly, induction of HIF-1 in pregnant mice was associated with preterm labor in vivo. These data support the role of the HIF-1 pathway in the process of placental senescence with increasing gestational age and highlight this pathway as a potentially important contributor to gestational length and a potential target for therapeutics to reduce preterm birth.

Overall, the conclusions of this study are mostly well supported by the data. The concept of placental aging has been controversial, with several prior studies with conflicting viewpoints on whether placental aging occurs at all, is a normal process during gestation, or rather only a pathologic phenomenon in abnormal pregnancies. This has been rather difficult to study given the difficulty of obtaining serial placental samples in late gestation. The authors used both a mouse model of serial placental sampling and human placental samples obtained at preterm, but non-pathologic deliveries, which is an impressive accomplishment as it provides insight into a previously poorly understood timepoint of pregnancy. The data clearly demonstrate changes in the HIF-1 pathway and cellular senescence at increasing gestational ages in the third trimester, which is consistent with the process of aging in other tissues.

Weaknesses of this study are that although the authors attribute alterations in HIF-1 pathways in advanced gestation to hypoxia, there are no experiments directly assessing whether the changes in HIF-1 pathways are due to hypoxia in either in vitro or in vivo experiments. HIF-1 has both oxygen-dependent and oxygen-independent regulation, so it is unclear which pathways contribute to placental HIF-1 activity during late gestation, especially since the third-trimester placenta is exposed to significantly higher oxygen levels compared to the early pregnancy environment. Additionally, the placenta is in close proximity to the maternal decidua, which consists of immune and stromal cells, which are also significantly affected by HIF-1. Although the in vitro experimental data in this study demonstrate that HIF-1 induction leads to a placenta senescence phenotype, it is unclear whether the in vivo treatment with HIF-1 induction acts directly on the placenta or rather on uterine myometrium or decidua, which could also contribute to the initiation of preterm labor.

For any action, habit, and belief you have, ask yourself: "Does this help toward my goals and future self or not?", if the answer is no, it is a distraction and part of the 80% you need to let go in order to reach 10X

Your future self and 10X (or 100X) vision and goals serve as a massive filter for action and belief.

Note: You should not 10X everything! Just 3 priorities.

Counterintuitively, the 10X mindset and goal setting is not about goals. It is about identifying the essential PROCESSES that lead to significant progress.

What is the game you want to play? What is the game you could play? What is a game you could go all in on and succeed at and be really good at?

This defines your pathways and strategies within your 20%

The path can change and adjust over time.

Hope = 1. Clear and Committed Goal 2. Agency Thinking 3. Pathways Thinking

This turns into definite optimism.

To achieve goals, raise the floor, FOCUS on removing bottlenecks. Also create constraints by Schwerpunkt (primary objective), contrary to common wisdom, constraint actually gives freedom, it prevents analysis paralysis.

Reviewer #1 (Public Review):

This manuscript employs a string method with swarms of trajectories to extract a free energy map of KcsA channel inactivation and its model dependence. The approach connects X-ray structures for closed, partially and fully open, and inactivated KcsA through optimisation of a string defined in a collective variable space consisting of distances involving gate size, cavity-filter and filter pinching (as defined in the proposed X-ray structure for an inactivated state). The final trajectory includes pore opening and filter collapse with water penetration behind the filter, via different intermediates depending on the force field. The authors propose a role for residue L81 in controlling water entry in the final stage of this process. The results suggest that KcsA more easily inactivates with the Charmm force field, with lower barrier and direct passage from a partially open state, whereas the pathway for Amber involves transition first to a fully open state with higher barrier, despite not being the dominant open state seen experimentally under activating conditions. The results also suggest that PG lipids help activate the channel within the Amber force field, consistent with experimental evidence. The work represents large-scale advanced MD simulation. Some questions remain, however, such as if the CV space chosen is sufficient to capture all possible slow coordinates in the inactivation process, and how the resultant free energy surfaces may potentially depend on the end structures and initial pulling procedure.

Collective variable choice:

The explanation for the choice of CVs on page 5 is not sufficient to understand the process and its likely success. How were the most important and unimportant CVs identified exactly? Table 2 on page 19 shows only gate distances, cavity-filter distances and a single variable related to filter structure itself (77 CA - 77 CA) representing a pinch. Is that pinching really the only slow variable associated with inactivation changes in the filter? Why are there no variables, say for carbonyl flipping, E71 or D80 movements or even for ion and water occupancy (although water may be sampled with control of other interactions, such as involving L81)? I understand that the X-ray structure is the one source of information used to define an inactivated structure and is one with just a pinch and no complete carbonyl flipping away from the pore, as has been identified in past studies and discussed as being involved by the authors on page 14. Key changes like carbonyl flipping surely are part of the story and may be slow variables. At the very least, if not part of the CV space, could be analysed.

On page 10 the authors discuss possible differences in Amber and Charmm involving the extent to which the 4 subunits change in respect to the L81-W67 water pathway and W67-D80 hydrogen bond, arguing the different results for force field could be to do with different numbers of subunits doing different things. If I understand, the chosen CVs are all tetramer-based distances (including across subunits) and not subunit-based CVs, so that random and incomplete changes may occur to subunits for a given point in CV space. There is thus potential for the string to converge on a local minimum pathway with partial changes to its interactions within and between subunits, and may not be a unique global solution. Can the authors please explain whether or not this is possible and what analysis has been done to check it?

X-ray endpoints and initial pathway:

The string was created from a pulling/steered MD between existing X-ray structures for the closed (5VKH), partially open (3FB5), fully open (5VK6) and finally inactivated (5VKE) states. The authors write on page 12 that "The block of conduction during inactivation appears to result from pinching at the selectivity filter...", but given the end point was forced to be the X-ray structure with pinching, wasn't this outcome predetermined? This raises a significant point of how much has choice of endpoints predetermined the final states of the string? i.e. How much is an end state actually allowed to draft away from the initial Xray structure. Was a bead placed at the very endpoint and allowed to update via swarms, or was it fixed and all beads just interpolate between those fixed end states? The reason this is important is that it is plausible the inactivated crystal structure with pinching but not other changes (such as complete V76 carbonyl flipping or outer filter splaying), may not be the actual free energy minimum structure for that state and that force field.

Another obvious concern is the possible reliance on the initial pulling procedure used before string optimisation began. Fig.2 Supp 1 shows generally that the Amber path stayed pretty close to the initial steered MD path, whereas Charmm drifted downward away from that path. One could justifiably ask, if a very different initial path was chosen, might different local minimum pathways result, including Amber sampling a path like Charmm? How does one test whether or not the final path has not been trapped in some local trough of free energy? e.g. Imagine starting the Amber string using an initial path like the more diagonal Charmm-like path, or even a more extreme unphysiological one, such as a steered trajectory that initially inactivates before opening the gate. Would the final results be the same? I appreciate the simulations are very expensive and such trials may not be possible, but what evidence is there that the final path has not been trapped away from the global minimum?

One test offered by the authors is a set of unbiased MD simulations launched from points on the string. The authors ran 200ns simulations and write on page 5 that "These simulations have the expected stability based on their starting values. This is a good quality test to check the correct estimation of the general features of the free energy surface". While this sounds reasonable, 200ns MD may only be sufficient to begin to explore locally within the solved free energy trough, much like the swarms in the iterations were able to do. My own examination of Fig2 Supp 5 is that some of these simulations linger around the expected states and some drift away within the general trough of sampling, which is a good sign. What those 200ns simulations may not be able to do is escape that trough and see evidence of other possible solutions, beyond what was sampled with the string that was tied to Xray endpoints and trapped in the solution pathway that was already formed after 100-300 iterations. Overall, the string involved 800 iterations of 10ps swarms (80ns around each bead; albeit 32 trajectories in parallel), allowing good local sampling around the beads in the free energy trough, but in terms of ability to diffuse away from that point, only being comparable in contiguous trajectory time to the unbiased MD tests. It therefore would have been interesting to see if longer simulations remain in this trough; though I understand the challenges in running so much MD. Such simulations may, however, lead to exploration beyond what was seen in the string solutions.

Force field effects and origin:

Regarding the effect of the chosen force field, the authors state that "Given that our simulations were conducted under activating conditions, we had expected the open states to be more populated than the closed ones. Simulations carried out at higher pH may be able to resolve this inconsistency". Also running at high pH would be a nice thing to do to prove the method is in fact sensitive to conditions to see a shift in the distribution of states. But the question is why were open states not more occupied under low pH and 50mM K+? From my analysis of the figures, the results show that the Charmm force field tends to allow for opening of the channel somewhat (at least with similar free energy for partially and fully open to closed) whereas Amber tends to close the channel more (with more uphill energy as the channel opens than Charmm; Fig 2). i.e. at low pH and 50 K+, isn't the Amber model incorrectly reporting fairly strong bias against opening? Moreover, regarding the free energy of the inactivated state itself, why should we not expect equilibrated channels under activating conditions to eventually fall into an inactivated state, in which case we should expect low free energy of that state (as found with Charmm and not Amber in Fig2), but with a slow rate. While much discussion in the manuscript appears to discuss limitations in Charmm (although on page 12 discussion leans either way), these factors may seem to favour Charmm over Amber.

On page 12 the authors explain the possible causes for force field dependence, although this seems limited to ion interactions, glutamate charges and dihedrals. But it would be nice to get a bit more insight into what terms may have influenced the pathway, in particular involving interactions between TM2 and the base of the selectivity filter and hydration behind the filter. Regarding ion interactions, is there a good reason to believe ions are key to the difference seen? i.e. How were ions involved differently in the state transitions involving Amber and Charmm? The authors have noted a role for ion-carbonyl interactions. It is important that the authors explain which is the two competing models has been used and why. i.e. Off-the-shelf Charmm36 force field includes strong K+-backbone carbonyl interaction, previously seen to promote high ion occupancy, similar to Amber, whereas Lennard-Jones parameters modified to match N-methyl-acetamide and water partitioning (such as early Berneche, Noskov and Roux work) reduce ion occupancy and increase water content inside the filter.

Public Review:

The primary goal of this paper is to examine microtubule detyrosination as a potential therapeutic target for axon regeneration. Using dimethylamino-parthenolide (DMAPT), this study extensively examines mechanistic links between microtubule detyrosination, hyper-interleukin-6 (hIL-6), and PTEN in neurite outgrowth in retinal ganglion cells in vitro. These findings provide convincing evidence that parthenolide has a synergistic effect on hIL-6- and PTEN-related mechanisms of neurite outgrowth in vitro. The potential efficacy of systemic DMAPT treatment to promote axon<br /> regeneration in mouse models of optic nerve crush and spinal cord injury was also examined.

Strengths:

1) The examination of synergistic activities between parthenolide, hyperIL-6, and PTEN knockout is leveraged not only for potential therapeutic value, but also to validate and delineate mechanism of action.

2) The in vitro studies utilize a multi-level approach that combines cell biology and biochemistry approaches to dissect the mechanistic link from parthenolide to microtubule dynamics.

3) The studies provide a basis for others to test the role of DMAPT in other settings, particularly in the context of other effective pro-regenerative approaches.

Weaknesses:

1) In vivo studies are limited to select outcomes of recovery and do not validate or address mechanism of action in vivo.

2) Known activities of DMAPT beyond microtubule detyrosination, such as oxidative stress, mitochondrial function and NFkB inhibition, are not considered in experimental examinations or in the interpretation of findings.

Reviewer #1 (Public Review):

Using the colon transcriptomes of 52 BXD mouse strains fed either chow or a high-fat diet (HFD), Li et al. present their findings on gene-by-environment interactions underpinning inflammation and inflammatory bowel disease (IBD). They discovered modules that are enriched for IBD-dysregulated genes using co-expression gene networks. They determined Muc4 and Epha6 to be the leading candidates causing variations in HFD-driven intestinal inflammation by using systems genetics in the mouse and integration with external human datasets. In their analysis, they concluded that their strategy "enabled the prioritization of modulators of IBD susceptibility that were generalizable to the human situation and may have clinical value." This dataset is intriguing and generates hypotheses that will be investigated in the future. However, there were no mechanistic or causation-focused investigations; the results were primarily observational and correlative.

Reviewer #1 (Public Review):

Jamge et al. sought to identify the relationships between histone variants and histone modifications in Arabidopsis by systematic genomic profiling of 13 histone variants and 12 histone modifications to define a set of "chromatin states". They find that H2A variants are key factors defining the major chromatin types (euchromatin, facultative heterochromatin, and constitutive heterochromatin) and that loss of the DDM1 chromatin remodeler leads to loss of typical constitutive heterochromatin and replacement of this state with features common to genes in euchromatin and facultative heterochromatin. This study deepens our understanding of how histone variants shape the Arabidopsis epigenome and provides a wealth of data for other researchers to explore.

Strengths:

1. The manuscript provides convincing evidence supporting the claims that: A) Arabidopsis nucleosomes are homotypic for H2A variants and heterotypic for H3 variants, B) that H3 variants are not associated with specific H2A variants, and C) H2A variants are strongly associated with specific histone post-translational modifications (PTMs) while H3 variants show no such strong associations with specific PTMs. These are important findings that contrast with previous observations in animal systems and suggest differences in plant and animal chromatin dynamics.

2. The authors also performed comprehensive epigenomic profiling of all H2A, H2B, and H3 variants and 12 histone PTMs to produce a Hidden Markov Model-based chromatin state map. These studies revealed that histone H2A variants are as important as histone PTMs in defining the various chromatin states, which is unexpected and of high significance.

3. The authors show that in ddm1 mutants, normally heterochromatic transposable element (TE) genes lose H2A.W and gain H2A.Z, along with the facultative heterochromatin and euchromatin signatures associated with H2A.Z at silent and expressed genes, respectively.

Reviewer #1 (Public Review):

In this work, Urbanska and colleagues use a machine-learning based crossing of mechanical characterisations of various cells in different states and their transcriptional profiles. Using this approach, they identify a core set of five genes that systematically vary together with the mechanical state of the cells, although not always in the same direction depending on the conditions. They show that the combined transcriptional changes in this gene set is strongly predictive of a change in the cell mechanical properties, in systems that were not used to identify the genes (a validation set). Finally, they experimentally after the expression level of one of these genes, CAV1, that codes for the caveolin 1 protein, and show that, in a variety of cellular systems and contexts, perturbations in the expression level of CAV1 also induce changes in cell mechanics, cells with lower CAV1 expression being generally softer.

Overall the approach seems accessible, sound and is well described. My personal expertise is not suited to judge its validity, novelty or relevance, so I do not make comments on that. The results it provides seem to have been thoroughly tested by the authors (using different types of mechanical characterisations of the cells) and to be robust in their predictive value. The authors also show convincingly that one of the genes they identified, CAV1, is not only correlated with the mechanical properties of cells, but also that changing its expression level affects cell mechanics. At this stage, the study appears mostly focused on the description and validation of the methodological approach, and it is hard to really understand what the results obtain really mean, the importance of the biological finding - what is this set of 5 genes doing in the context of cell mechanics? Is it really central, or is it just one of the set of knobs on which the cell plays - and it is identified by this method because it is systematically modulated but maybe, for any given context, it is not the dominant player - all these fundamental questions remain unanswered at this stage. On one hand, it means that the study might have identified an important novel module of genes in cell mechanics, but on the other hand, it also reveals that it is not yet easy to interpret the results provided by this type of novel approach.

Reviewer #1 (Public Review):

The authors have approached the study of the mechanism by which the two more antigenic proteins of the influenza A virus, hemagglutinin (HA) and neuraminidase (NA), are expressed later during the infection. For this aim, they set an experimental approach consisting of a 2-hour-long infection at a multiplicity of infection of 2 with the viral strain WSN. They used cells from the lung carcinoma cell line A549. They used the FISH technique to detect the mRNAs in situ and developed an imaging-based assay for mathematically modeling and estimating the nuclear export rate of each of the eight viral segments. They propose that the delay in the expression of HA and NA is based on the retention of their mRNA within the nucleus.

The main strength of this work is the fact that the authors have studied a long-unaddressed mechanism in influenza A virus infectious cycle, as is the late expression of HA and NA, by creating a work flow including mRNA detection (FISH) plus mathematical calculations to arrive at a model, which additionally could be useful for general biological processes where transcription occurs in a burst-like manner. The weakness of this work in its present state is that in order to "quantify" the export rate of the transcripts, several assumptions regarding the viral infection are made without empirical data. It would greatly improve if more precise experiments could be performed and/or include demonstration of the assumptions made (i.e., synchronized infections, empirically demonstrating that cRNA production does not occur within the first 2 hours of infection, and/or separate transcription and replication, inhibiting RNA degradation during viral infection).

Reviewer #1 (Public Review):

This study revealed that one of the mechanisms for iTreg (induced-Treg) lineage instability upon restimulation is through sustained store-operated calcium entry (SOCE), which activates transcription factor NFAT and promotes changes in chromatin accessibility to activated T cell-related genes. The authors revealed that, unlike thymus-derived Tregs (tTreg) with blunted calcium signaling and NFAT activation, iTregs respond to TCR restimulation with fully activated SOCE and NFAT similar to activated conventional T cells. Activated NFAT binds to open chromatin regions in genes related to T helper cells, increases their expression, and leads to the instability of iTreg cells. On the other hand, inhibition of the SOCE/NFAT pathway by chemical inhibitors could partially rescue the loss of Foxp3 expression in iTreg upon restimulation. The conclusion of the study is unexpected since previous studies showed that NFAT is required for Foxp3 induction and iTreg differentiation (Tone Y et al, Nat Immunol. 2008, PMID: 18157133; Vaeth M et al, PNAS, 2012, PMID: 22991461). Additionally, Foxp3 interacts with NFAT to control Treg function (Wu Y et al, Cell, 2006, PMID: 16873067). The data presented in this study demonstrated the complex role NFAT plays in the generation and stability of iTreg cells.

Several concerns are raised from the current study.<br /> 1. Previous studies showed that iTregs generated in vitro from culturing naïve T cells with TGF-b are intrinsically unstable and prone to losing Foxp3 expression due to lack of DNA demethylation in the enhancer region of the Foxp3 locus (Polansky JK et al, Eur J Immunol., 2008, PMID: 18493985). It is known that removing TGF-b from the culture media leads to rapid loss of Foxp3 expression. In the current study, TGF-b was not added to the media during iTreg restimulation, therefore, the primary cause for iTreg instability should be the lack of the positive signal provided by TGF-b. NFAT signal is secondary at best in this culturing condition.

2. It is not clear whether the NFAT pathway is unique in accelerating the loss of Foxp3 expression upon iTreg restimulation. It is also possible that enhancing T cell activation in general could promote iTreg instability. The authors could explore blocking T cell activation by inhibiting other critical pathways, such as NF-kb and c-Jun/c-Fos, to see if a similar effect could be achieved compared to CsA treatment.

3. The authors linked chromatin accessibility and increased expression of T helper cell genes to the loss of Foxp3 expression and iTreg instability. However, it is not clear how the former can lead to the latter. It is also not clear whether NFAT binds directly to the Foxp3 locus in the restimulated iTregs and inhibits Foxp3 expression.

Reviewer #1 (Public Review):

Terzioglu and co-workers tested the provocative hypothesis that mitochondria maintain an internal temperature considerably higher than cytosolic/external environmental temperature due to the inherent thermodynamic inefficiency of mitochondrial oxidative phosphorylation. As a follow-up to a prior paper from some of the same authors, the goal of this study was to conduct additional experiments to assess mitochondrial temperature in cultured cells. Consistent with the prior work, the authors provide consistent evidence that the temperature of mitochondria in four different types of cultured mammalian cells, as well as cells from Drosophila (poikilotherms), is 15oC or more above the external temperature at which cells are maintained (e.g., 37oC). Additional evidence shows that mitochondria maintain higher temperatures under several different types of cellular metabolic stresses predicted to decrease the dependence on OxPhos, adding to the notion that natural thermodynamic inefficiency and heat generation may be an important, and potentially regulated, characteristic of mitochondrial metabolism.

Strengths<br /> Demonstration that both a fluorescent (Mito Thermo Yellow) and a genetic-based (mito-gTEMP) mitochondrial targeted temperature probe elicit similar quantitative changes in mitochondrial temperature under different experimental conditions is a strength. The addition of the genetic probe to the current study supports prior findings using the fluorescent probe and thus achieves a primary objective of the study.

The experiments are well-designed and executed. Specific attention given to potential artifacts affecting probe signal and/or non-specific effects from the different experimental interventions is a strength.

The use of different cultured cell lines from different organisms provides additional evidence of elevated temperature as a general property of functioning mitochondria, representing additional validation.

Weakness:<br /> While the findings and potential interpretations put forward by the authors are intriguing, the severity of the interventions (e.g., mitochondrial complex-specific inhibitors, inhibition of protein synthesis) and the absence of simultaneous or parallel measurements of other key bioenergetic parameters (i.e., membrane potential, oxygen consumption rate, etc.) limits the ability to interpret potential cause and effect - whether the thermogenesis aspect of OxPhos is being sensed and regulated, or whether temperature changes are more of a biproduct of adjustments in OxPhos flux under the experimental circumstances. In other words, the physiological relevance of the findings remains unclear.

Related, several of the interventions are employed to either increase or decrease dependence on OxPhos flux, but no outcome measures are reported to document whether the intended objective was achieved (e.g., increased OxPhos flux in low glucose plus galactose, decreased ATP demand-OxPhos flux with anisomycin, etc.).

Millionairres are just regular people lol. They don't (always) have luxury and other high paid stuff.

Becoming a millionaire takes skillset and effort, not saving.

Becoming wealthy means aiming high. You will not go higher than the goals you set. Aim for a crazy amount, and do the work it takes. It filters behavior down to the essentials.

Success is about delaying gratification and building momentum. Be okay with a big goal taking time. Just work towards it, focus on the process, rather than the goal.

Persistence and perseverance as well.

Perfection is a big limiter. Don't obsess with finding the perfect path before starting. Build the map while going. Of course, starting with a rough idea or sketch for a map is always good.

Advice doesn't matter as much as guidance, this way, not everyone needs to know about your goals. The fewer, the better. Those who do know, let them mentor you (also seek the correct mentors).

To become unstoppable, you must:

1) Outwork everybody

2) Outsmart everybody

3) Hire the greatest talent in the world

The four primary questions to ask yourself for a 100x 10-year vision:

1. What is the commitment I desire to have?
2. What are my hindrances (goal-conflicting actions or inactions)? -- Past-Based Actions/Behaviors
3. What are my hidden commitments of my former self? (things that might've helped my past self but are not as helpful right now.) -- Past-Based Commitments/Identities
4. What are my limiting beliefs or assumptions toward achieving this goal? -- Past-based Beliefs

Step 1 is to fill out these questions. Step 2 is to go backwards, and start identifying what is necessary, so what are the necessary beliefs to achieve this goal, what commitments must I make and thus what actions must I take?

Reviewer #1 (Public Review):

This is an interesting study deploying convergent methodologies to address a timely question: can non-human primates distinguish theory of mind from random behaviours during passive viewing of animated shapes, and what brain regions are implicated? As the authors note, fMRI studies of brain activation in response to the theory of mind stimuli in non-human primates are scarce, and none have explored the processing of abstract stimuli in this context.

The major strengths of the study are the application of the Frith-Happé shapes task in a group of marmosets during fMRI in conjunction with concurrent eye tracking recording. Eye tracking is a very nice addition as it enables the authors to determine the gaze patterns and fixation duration on distinct aspects of the task stimuli (e.g., large triangle versus small triangle) as well as group differences. Overall, the study seems well-designed and technically rigorous, and the major conclusions appear to be supported by the data.

However, there is one aspect I would appreciate some clarity on, namely the failure to include the original "Goal directed condition" from the Frith-Happé task. The authors contrast visuo-oculomotor and fMRI activation between the Random (no discernible interaction or purposeful behaviour) and the ToM (goal-directed behaviours with mental interaction) but neglect the intermediate step of physical interaction between the shapes that the Goal-directed behaviour condition portrays. As such, it is difficult to make clear statements as to what the activation patterns in the ToM condition represent - perhaps this merely reflects the processing of an unfolding narrative rather than random movements.

Reviewer #1 (Public Review):

The study of Aso and colleagues seeks to understand how learned information is steering motor output. Using an artificial training paradigm consisting of odor presentation combined with dopamine neuron activation, they identify upwind orientation as an important parameter of appetitive memory recall (as has been shown before - e.g. Handler 2019). Using the Drosophila genetic targeting library and optogenetic activation, they identify several populations of neurons responsible for upwind orientation by analyzing freely moving animals in an airflow chamber. They concentrate on a specific subset, which they call upwind neurons (UPWINs), and which they can anatomically link downstream to the flies' memory center, the mushroom body (MB), building on the ultrastructural connectome brain atlas. In combination with electrophysiology, in-vivo calcium imaging, and memory assays, they successfully show that (1) UPWINs promote upwind orientation including acceleration of angular speed and bias turning towards the upwind direction, (2) UPWINs receive excitatory and inhibitory input from specific parts of the MB, (3) UPWINs increase odor-evoked activity upon (artificial) appetitive training and (4) appetitive memory recall is impaired when blocking UPWIN neurons only during the memory test.

The authors use state-of-the-art techniques combining tools like optogenetics, connectome analysis as well as electrophysiology, in-vivo calcium imaging, and memory/behavioral assays tracking individual flies. It provides new insights into mushroom body memory retrieval circuits and how they integrate with information from other brain areas. However, some concerns remain regarding some claims of the paper. The timeline of the behavioral and the physiological experiments differ. It is therefore difficult to define the memory phases when upwind orientation is important for recall. Moreover, one main conclusion the authors draw from their data is that upwind orientation is promoted by disinhibition from a specific MB output connection, however, physiological evidence of this effect is missing. The UPWINs seem to have a more complex function in behavioral control beyond memory recall. The fact that optogenetic UPWIN activation is leading to upwind orientation only in starved flies together with the fact that flies show a high returning probability even without any odor present suggests a functional role in state-dependent exploration behavior.

Reviewer #1 (Public Review):

The authors present a PyTorch-based simulator for prosthetic vision. The model takes in the anatomical location of a visual cortical prostheses as well as a series of electrical stimuli to be applied to each electrode, and outputs the resulting phosphenes. To demonstrate the usefulness of the simulator, the paper reproduces psychometric curves from the literature and uses the simulator in the loop to learn optimized stimuli.

One of the major strengths of the paper is its modeling work - the authors make good use of existing knowledge about retinotopic maps and psychometric curves that describe phosphene appearance in response to single-electrode stimulation. Using PyTorch as a backbone is another strength, as it allows for GPU integration and seamless integration with common deep learning models. This work is likely to be impactful for the field of sight restoration.

However, one of the major weaknesses of the paper is its model validation - while some results seem to be presented for data the model was fit on (as opposed to held-out test data), other results lack quantitative metrics and a comparison to a baseline ("null hypothesis") model.<br /> - On the one hand, it appears that the data presented in Figs. 3-5 was used to fit some of the open parameters of the model, as mentioned in Subsection G of the Methods. Hence it is misleading to present these as model "predictions", which are typically presented for held-out test data to demonstrate a model's ability to generalize. Instead, this is more of a descriptive model than a predictive one, and its ability to generalize to new patients remains yet to be demonstrated.<br /> - On the other hand, the results presented in Fig. 8 as part of the end-to-end learning process are not accompanied by any sorts of quantitative metrics or comparison to a baseline model. The results seem to assume that all phosphenes are small Gaussian blobs, and that these phosphenes combine linearly when multiple electrodes are stimulated. Both assumptions are frequently challenged by the field. For all these reasons, it is challenging to assess the potential and practical utility of this approach as well as get a sense of its limitations.

Another weakness of the paper is the term "biologically plausible", which appears throughout the manuscript but is not clearly defined. In its current form, it is not clear what makes this simulator "biologically plausible" - it certainly contains a retinotopic map and is fit on psychophysical data, but it does not seem to contain any other "biological" detail. In fact, for the most part the paper seems to ignore the fact that implanting a prosthesis in one cerebral hemisphere will produce phosphenes that are restricted to one half of the visual field. Yet Figures 6 and 8 present phosphenes that seemingly appear in both hemifields. I do not find this very "biologically plausible".

Review #1 Public Review:

This is an interesting study which attempts to assess the effect of the pandemic on diagnoses of pancreatic cancer. The authors have used a large national database to evaluate this, however, it should be noted that this database only captures 40% of the population in England. The authors have looked at specific parameters including Body Mass Index (BMI) as well as markers of diabetes and liver function. Only BMI had a difference in the frequency of measurements during the pandemic, presumably due to reduced face-to-face visits to allow weight and height to be captured.

Interestingly the authors noticed a reduction in surgery for pancreatic cancer by 25%, yet reported that there were no differences in the frequency of death within 6 months following the diagnosis of pancreatic cancer. The reduction in surgery is likely related at least in part to the loss of operating lists due to pandemic restrictions, however, this paper is not equipped to address another important possibility behind this, which is that pancreatic cancers were presenting too late for surgical intervention. It is not sufficient to comment that pancreatic cancer treatment was not affected by the pandemic based on the data presented on deaths within 6 months of the diagnosis of pancreatic cancer alone, as the median survival of patients diagnosed with pancreatic cancer within the pandemic has not been captured and compared to that of patients diagnosed in the preceding 5 years.

Therefore while the study can conclude no difference in pancreatic cancer diagnoses before and during the pandemic, more work needs to be done to truly assess if the pandemic had any effect on the outcomes from pancreatic cancer for patients diagnosed within this timeframe.

Reviewer #1 (Public Review):

This research aimed to discern the pattern of methylation changes that occur during aging, distinguishing between a unified specific mechanism and stochastic changes. To date, no unified hypothesis exists to guide our understanding of the changes in chromatin geography observed during the aging of cells. This work analysed six different types of purified blood-borne white blood cells allowing comparison across different immune cell subsets to determine if similar patterns occurred in all cell populations. Intriguingly, each subset exhibited its own distinct differential methylation rather than a single program. However, a core set of gene changes close to age-associated CpGs was identified suggesting that a central program existed, but that individual cell type function and metabolism shaped the overall chromatin landscape for the population. These findings establish a new framework for considering the aging process and open new questions about how the individual clocks of different populations might be regulated. While circulating cells are readily accessible for evaluation in humans, the majority of immune cells that regulate immune homeostasis are found within the tissues of the body. Whether these cells exhibit a similar profile to circulating cells or are rather shaped by their tissue or organ-specific ecosystem remains to be determined. In this setting, these tissue-resident cells are exposed to very different oxygen tensions and metabolic substrates. Furthermore, genes identified have been associated with aging, they concurrently appear to be associated with inflammation, thus it is not clear whether aging and low-grade inflammation are inherently linked, or whether these two pathways can be segregated. Thus a number of questions remain warranting further investigation.

Reviewer #1 (Public Review):

The authors convincingly show in this study the effects of the fas5 gene on changes in the CHC profile and the importance of these changes toward sexual attractiveness.

The main strength of this study lies in its holistic approach (from genes to behaviour) showing a full and convincing picture of the stated conclusions. The authors succeeded in putting a very interdisciplinary set of experiments together to support the main claims of this manuscript.

The main weakness stems from the lack of transparency behind the statistical analyses conducted in the study. Detailed statistical results are never mentioned in the text, nor is it always clear what was compared to what. I also believe that some tests that were conducted are not adequate for the given data. I am therefore unable to properly assess the significance of the results from the presented information. Nevertheless, the graphical representations are convincing enough for me to believe that a revision of the statistics would not significantly affect the main conclusions of this manuscript.

The second major problem I had with the study was how it brushes over the somewhat contradicting results they found in males (Fig S2). These are only mentioned twice in the main text and in both cases as being "similarly affected", even though their own stats seem to indicate otherwise for many of the analysed compound groups. This also should affect the main conclusion concerning the effects of fas5 genes in the discussion, a more careful wording when interpreting the results is therefore necessary.

Reviewer #1 (Public Review):

"Melanocortin 1 receptor regulates cholesterol and bile acid metabolism in the liver" by Thapa et al. extends previous findings that MC1R global knockout mice have dysregulated lipid metabolism in APOE KO mice. The authors generated a hepatocyte-specific MC1R KO mouse to assess the hepatic effects of MC1R on the regulation of lipid metabolism. Thapa et al. go on to show that hepatic MC1R deletion leads to dyslipidemia and hepatic steatosis. The authors subsequently show that altered cholesterol homeostasis disrupts bile acid metabolism in hepatic MC1R KO mice. Finally, the authors provide data to suggest a role for AMPK in mediating the effects of MSH on hepatic cholesterol metabolism. The authors designed rigorous experiments using multiple different models (in vivo and in vitro) as well as different approaches (genetic and pharmacological).

The work described herein would have an impact on the field in multiple ways. Firstly, it demonstrates a novel metabolic role for MSH in the regulation of hepatic cholesterol metabolism. This may prove to be a viable therapeutic strategy for the treatment of dyslipidemia. Furthermore, the authors demonstrate an alternative signaling cascade elicited by MSH independent of cAMP, but rather relying on AMPK. This novel interaction between AMPK and MC1R could have more widespread implications beyond the control of hepatic cholesterol metabolism.

For the most part, the conclusions offered by the authors are supported by the data that is presented. There are, however, a number of concerns in the current version of this manuscript detailed below:

1) The authors demonstrate the expression of MC1R in hepatocytes through IHC staining and western blot analysis. Furthermore, the authors show an alteration in systemic bile acid homeostasis in MC1R KO mice. However, no mention of MC1R expression or function in cholangiocytes is discussed. This is important to assess both experimentally and within the discussion given the profound role of the biliary epithelium in modulating bile acid homeostasis. Furthermore, in figure 1 the authors validate the MC1R knockdown only through mRNA expression. Given panels A and C of figure 1 shows there is clearly a functional antibody for MC1R, validation of protein knockdown is needed.

2) Figure 2 demonstrates a steatotic effect of MC1R knockdown in hepatocytes. The authors attempt to provide mechanistic insight into this phenomenon through assessing the mRNA expression of genes involved in cholesterol and fatty acid synthesis. The data provided is modest at the gene level and no protein validation was provided to demonstrate functional alterations of these proteins in MC1R KO mice. Key proteins proposed such as SREBP2 and HMGCR need to be validated via a western blot of IHC analysis.

4) The authors suggest the involvement of AMPK in mediating the cholesterol-lowering effects of MSH. However, MSH is still able to lower free cholesterol levels even in the presence of an AMPK inhibitor. This suggests that MSH does not in fact rely on the activation of AMPK to elicit these cholesterol-lowering effects. The authors' conclusions are stronger than the actual data support. Furthermore, the authors claim LD211 phenocopies the effects of MSH in the presence of an AMPK inhibitor. However, the authors only measured the phosphorylation of Akt as their outcome. This begs the question, does LD211 still lower total cholesterol in the presence of AMPK inhibitors? This experiment is essential to conclude whether or not LD211 phenocopies the effects of MSH.

5) The authors initiate the project by showing high-fat diet disrupts the expression of MC1R. However, all of the subsequent experiments in hepatic MC1R KO mice are performed under normal chow. This begs the question of what is the phenotype of the hepatic MC1R KO mice fed a high-fat diet. Does KO of MC1R in the liver exacerbate HFD-induced obesity, glucose intolerance, and dyslipidemia? Inversely, can WT mice challenged with an HFD be rescued metabolically by treatment with either MSH or LD211? Providing data along these lines of investigation will provide physiological/clinical relevance to their findings.

Reviewer #1 (Public Review):

The authors aim to understand the role of clonal heterogeneity of tumors in immunogenicity of clonally expressed antigens. This is a significant problem with many basic as well as translational implications.

The strength of the manuscript lies in the novel demonstration that a poorly immunogenic tumor antigen, when paired with a stronger tumor antigen, begins to elicit significant immune response. The weakness lies in the fact that the actual mechanism of the key demonstration is never shown. There is a lot of speculation and tangential experimentation, but little actual evidence of a mechanism.

By making the key observation (mentioned in the strength section in the previous paragraph), the authors did achieve their objective albeit very partially. Their observation is based on excellent experimental tools and design. This study will stimulate further experiments in this important field.

Their key observation is somewhat reminiscent of the practice of conjugating small "non-immunogenic" antigens (such as some carbohydrates) to large protein carriers (such as serum albumin) in order to elicit strong antibody response to the weaker antigen. It is interesting to contemplate if the underlying mechanisms have any commonality.

Reviewer #1 (Public Review):

The manuscript described the mechanism of Spermidine modulation of Src kinase on IDO1, accelerating the kinetics of the reaction. Spermidine can act on the backside of the SH2 domain of Src, by the interaction of specific amino acids. Considering the important role of IDO1 in the immune response the results provide proof of principle for the development of molecules that can modulate the kinase activity and the nonenzymatic functions of Src and IDO1 at once. The conclusions of this paper are mostly well supported by data, but some aspects of figure construction and data analysis need to be improved for the sake of clarity.

Reviewer #1 (Public Review):

The authors examine the role of the K700E mutation in the Sf3B1 splicing factor in PDAC and report that this Sf3B1 mutation promotes PDAC by decreasing sensitivity to TGF-b resulting in decreased EMT and decreased apoptosis as a result. They propose that the Sf3b1 K700E mutant causes decreased expression of Map3K7, a known mediator of TGFb signaling and also known to be alternately spliced in other systems by the Sf3b1 K700E mutation. The role of splicing defects in cancer is relatively understudied and could identify novel targets for therapeutic intervention so this work is of potential significance. However, the data is over-interpreted in many instances and it is not clear the authors can make the claims they do based on the data shown. In particular, the data showing that decreased Map3k7 underlies the effects of the Sf3b1K700E mutant is very weak. Does over-expression of Map3k7 promote the EMT signature and induce apoptosis? Do the Map3k7 expressing organoids form tumors more effectively when transplanted into mice? Also, the novelty of the work is a concern since aberrant Map3k7 splicing due to SF3B1 mutation was seen previously in other systems. The authors also do not address the apparent conundrum of Sf3b1 K700E mutation promoting tumorigenesis despite there being less EMT which is also required for progression to metastasis in PDAC.

Major Concerns.<br /> 1. The analysis of the effect of Sf3b1K700E expression on normal pancreas and on PanINs in KC mice and PDAC in KPC mice is superficial and could be enhanced by staining for amylase, cytokeratin-19 and insulin. In particular, the data quantified in figure 1L should be accompanied by staining for CK19, Mucin5AC or some other marker of ductal transformation. Also, are any effects seen at older ages in normal mice?<br /> 2. The invasion assays used are limited and should be complemented by more routine quantification of cell migration and invasion including such assays as a scratch assay, Boyden chamber assays and use of the IncuCyte system to quantify. As it stands the image in Figure 3B is difficult to interpret since it is very poorly described in the figure legend. Additional evidence is needed to make the claims made by the authors.<br /> 3. The authors should show the actual CC3 staining quantified in Suppl. Figure 2G.<br /> 4. The graph in Figure 3L should show WT and Sf3b1K700E expressing organoids number both with and without TGF-b.

Reviewer #1 (Public Review):

This is a nice and elegant genetic study on the role of the Sgs1 and Exo1 factors involved in long DNA resection in the mechanism of double-strand break (DSB) repair by homologous recombination (HR). Most studies have focused on the need for these two factors for the long resection of a DSB to allow efficient HR. Now, this study shows that a major role of the function of long resection mediated by Sgs1 and Exo1 is to activate the DNA damage checkpoint to allow the chromosomal mobility needed to allow the DNA ends to find a distant homologous sequence with which repair via homologous recombination.

Reviewer #1 (Public Review):

The goal of the manuscript is a joint analysis of genetic variation, open chromatin, and gene expression in a genetically diverse population of mouse embryonic stem cells.

This is an important manuscript that links gene expression to genetic variants and regions of open chromatin. The mechanisms of genetic gene regulation are essential to understanding how standing genetic variation translates to function and phenotype. This data set has the ability to add substantial insight into the field. In particular, the authors show how the relationships between variants, chromatin, and genes are spatially constrained by topologically associated domains.

The description of the results is hard to follow, specific terms are not well-defined, and the methods section lacks detail. Several fundamental approaches cannot be understood easily without going to references (particularly #6, #15, and #33). The manuscript will benefit from efforts to improve readability.

In addition, the CTCF binding data (ChIP-seq) gets too little attention. The fundamental question of whether regulatory domains vary between individuals is not directly addressed.

Reviewer #1 (Public Review):

In this manuscript, the authors are building on their previous work showing Delta-Notch regulates the entrance and exit from embryo-larval quiescence of neural stem cells of the central brain (called CB neuroblasts (NB) (PMID: 35112131)). Here they show that continuous depletion of Notch in NBs from early embryogenesis leads to cycling NBs in the adult. This - cycling NBs in the adult - is not seen in controls. The assumption here is that these Notch-RNAi NBs in adults are those that did not undergo terminal differentiation in pupal development. The authors show that Notch is activated by its ligand Delta which is expressed on the GMC daughter cell and on cortex glia. They determine that the temporal requirement for Notch activity is 0-72 hours after larval hatching (ALH) (i.e., 1st instar through mid-3rd instar at 25C). In NBs/GMCs depleted for Notch, early temporal markers were still expressed at time points when they should be off and late markers were delayed in expression. These effects were observed in ~20-40% of NBs (Figures 5 and 6). Through mining existing data sets, they found that the early temporal factor Imp - an RNA binding protein - can bind Delta mRNA. They state that Delta transcripts decrease over time (without any reference to a Figure or to published work), leading to the hypothesis that Delta mRNA is repressed by the late temporal factors. Over-expressing late factors Syp or E93 earlier in development leads to downregulation of a Delta::GFP protein trap. These results lead to a model in which Notch regulates expression of early temporal factors and early temporal factors regulate Notch activity through translation of Delta mRNA.

There are several strengths of this study. The authors report rigorous measurements and statistical analyses throughout the study. Their conclusions are appropriate for the results. Data mining revealed an important mechanism - that Imp binds Delta mRNA - supporting the model that early temporal factors promote Delta expression, which in turn promotes Notch signaling.

There are also several weaknesses:<br /> 1. The activation of Notch in NBs by Delta in GMCs was already shown by this group in their Dev 2022 paper, reducing some of the impact of this study.<br /> 2. The authors do not explain their current results in context of their prior paper (2022 Dev) until the Discussion, but this would be useful to read in the Introduction. Similarly, it would be good to mention that in the 2022 paper, they find a significant number of wor>Notch RNAi NBs at 2 AHL that are cycling. Are the adult Notch RNAi in this study descended from those NBs at 2 hours ALH in the 2022 study? In other words, how does the early requirement for Notch between 0-72 hours ALH reported in the current study relate to the Notch-depleted NBs identified in the 2022 paper?<br /> 3. Most of the experiments rely upon continuous depletion of Notch from embryonic stage 8 until adulthood using the wor-GAL4 driver. There is no lineage tracing of this driver and there is no citation about the published expression pattern of this driver. The inclusion of these details is important for a broad audience journal.<br /> 4. Most of the experiments utilize a single RNAi transgene for Notch, Delta, Imp, Syp, E93. There are no experiments demonstrating the efficacy of the RNAi lines and no references to prior use and/or efficacy of these lines.

An appraisal: The authors use temperature shifts with Gal80TS to show that Notch is required between 0-72 hours ALH. They show with the use of known markers of the temporal factors and Delta protein trap, that Imp promotes Delta protein expression and the later temporal factors reduce Delta, although the molecular mechanisms are not clearly delineated. Overall, these data support their model that the reduction of Delta expression during larval development leads to a loss of Notch activity.

As noted in the Discussion, this study raises many questions about what Notch does in larval CB NBs. For example, does it inhibit Castor or Imp? Is Notch required in certain neural lineages and not others. These studies will be of interest in the community of developmental neurobiologists.

Reviewer #1 (Public Review):

The authors set out to investigate the hypothesis that mirror neurons in ventral premotor area F5 code actions in a common motor representation framework. To achieve this, they trained a linear discriminant classifier on the neural discharge of three types of action trials and test whether the thus trained classifier could decode the same categories of actions when observed. They showed that codes were fully matched for a small subset of neurons during the action epoch, while a wider set of "mirror neurons" showed only poorly matched codes for different epochs.

The authors controlled for potential visual object confounds by having identical objects be manipulated in three different ways and by having the animal carry out the motor execution in the dark. The main strength of the study lies in the clever decoding approach testing the matched tuning to behavioural categories in a model-free way. The central result is in the identification of the small sub-group of mirror neurons that show true matching during the execution epoch, which can dissociate the three types of action almost perfectly. This aligns well with some previous work while offering a novel avenue to identify and investigate those neurons.

The underlying neuronal mechanism and behavioural relevance of these neurons remain an open question. It would have been interesting to understand better whether the specific motor representations at a recording site, for instance identified through microstimulation prior to recording (see Methods), the reaction times on individual trials or the specific gaze targets (object/hand) had a bearing on the decoding performance for a neuron/trial. Ultimately, the uncovered matched mirror representations should in future experiments be tested with causal interventions and linked trial-by-trial to action selection performance.

The authors put the focus of their discussion on the wider, less well-matched neuronal pool to support an action selection framework, which is of course a valid view and well established in motor representations. From a sensory perspective, sparse coding, as suggested by the small group of "true" mirror neurons identified with the decoding approach, should also be considered as the basis for a possible neuronal mechanism. A particular strength of the paper is that it could give new data and impetus to the important discussion about how motor and sensory coding frameworks come together in cortical processing.

Reviewer #1 (Public Review):

Cedillo et al. address the critically important question of how biguanides exert their positive effects on longevity using the powerful C. elegans model. Biguanides metformin and phenformin have been widely prescribed in the clinic to address metabolic challenges of diabetes; more recently the value of metformin in addressing specific cancers has emerged, and testing for impact on healthy human aging is getting underway. The need to understand the mechanism of biguanide action and the metabolic consequences of biguanide administration is clear.

The authors report that three genes that suppress longevity associated with metformin or phenformin treatment affect a common pathway for ether lipid biosynthesis; this ether lipid biosynthesis pathway is required for mitochondrial lifespan extension, eat-2 mediated dietary restriction longevity, and TOR inhibition-associated longevity, but not insulin pathway mediated longevity. Authors document with lipid profiling how ether lipids and some other lipids are impacted by phenformin vs. genetic disruption of ether lipid biosynthesis, define the tissue primarily responsible for the ether lipid biosynthesis, show that over-expression of enzyme fard-1 is sufficient to confer most of the phenformin effect, and implicate conserved stress transcription factor SKN-1 as a downstream outcome of the ether lipid change.

Strengths include the exploitation of the nematode model to address requirements not readily discerned in other models, the rigor of genetic documentation, the inclusion of metabolic profiling, the testing of multiple potential pathways that have been in the general discourse regarding metformin action, and the elaboration of a reasonably supported model that ether lipid biosynthesis is required for phenformin to activate longevity-promoting metabolic defenses downstream of conserved stress-responsive transcription factor SKN-1/NRF2. The novelty includes that ether lipids are directly linked to lifespan, ether lipid biosynthesis is needed for specific longevity pathways, and that ether lipids might play a role in a shift to pro-longevity metabolism.

There are some points that require clarification and could benefit from additional study, some wording and presentation issues, and a few missing points of potential discussion.

Overall, the data reported in this paper contribute a highly valuable advance in the biguanide field and adds stimulating hypotheses to the scientific community for moving forward in this biomedically important area.

Reviewer #1 (Public Review):

The authors expand upon prior findings and show that basolateral amygdala (BLA) activity is necessary for defensive responses elicited by both innate and learned threats. The authors also show that a projection from the auditory thalamus (MGM thalamic nucleus) mediates these effects.

Learned threats were modelled with auditory fear conditioning. The authors finding showing that the MGM-BLA pathway is required for auditory fear learning is largely a replication of prior results.

The novelty in this paper is that the authors show that the auditory MGM-BLA pathway is involved in defense evoked by a visual looming stimulus.

Overall, this is a reasonably designed study. The main weakness is that the loss of function manipulations use either caspase-induced lesions or contralateral chemogenetic disconnection studies, which lack temporal resolution.

Reviewer #1 (Public Review):

It has been shown previously that there are relationships between a transdiagnostic construct of anxious-depression (AD), and average confidence rating in a perceptual decision task. This study sought to investigate these results, which have been replicated several times but only in cross-sectional studies. This work applies a perceptual decision-making task with confidence ratings and a transdiagnostic psychometric questionnaire battery to participants before and after an iCBT course. The iCBT course reduced AD scores in participants, and their mean confidence ratings increased without a change in performance. Participants with larger AD changes had larger confidence changes. These results were also shown in a separate smaller group receiving antidepressant medication. A similar sized control group with no intervention did not show changes.

The major strength of the study is the elegant and well-powered data set. Longitudinal data on this scale is very difficult to collect, especially with patient cohorts, so this approach represents an exciting breakthrough. Analysis is straightforward and clearly presented. However, no multiple comparison correction is applied despite many different tests. While in general I am not convinced of the argument in the citation provided to justify this, I think in this case the key results are not borderline (p<0.001) and many of the key effects are replications, so there are not so many novel/exploratory hypothesis and in my opinion the results are convincing and robust as they are. The supplemental material is a comprehensive description of the data set, which is a useful resource.

The authors achieved their aims, and the results clearly support the conclusion that the AD and mean confidence in a perceptual task covary longitudinally.

I think this study provides an important impact to the project of computational psychiatry.Sspecifically, it shows that the relationship between transdiagnostic symptom dimensions and behaviour is meaningful within as well as across individuals.

Reviewer #1 (Public Review):

The authors consider data by the Heisenberg group on rheological properties of non-confluent tissue in zebrafish embryos. These data had shown a steep increase and subsequent saturation in viscosity with cell density. The authors introduce a physical agent-based model of such tissues that accounts for the dispersion in cell size and the softness of the cells. The model is inspired by previous models to study glassy dynamics and reveals essential physical features that can explain the observed behavior. It goes beyond previous studies that had analysed the observations in terms of a percolation problem. The numerics are thoroughly done and could have a deep impact on how we describe non-confluent tissues.

A major weakness of the manuscript is the way it is written, which gives the impression to have been done rather carelessly. Several quantities are not properly introduced and at places physical jargon is used that makes the work difficult to access for readers without a background in soft matter.

Reviewer #1 (Public Review):

Many drugs have off-target effects on the gut microbiota but the downstream consequences for drug efficacy and side effect profiles remain unclear. Herein, Wang et al. use a mouse model of liver injury coupled to antibiotic and microbiota transplantation experiments. Their results suggest that metformin-induced shifts in gut microbial community structure and metabolite levels may contribute to drug efficacy. This study provides valuable mechanistic insights that could be dissected further in future studies, including efforts to identify which specific bacterial species, genes, and metabolites play a causal role in drug response. Importantly, although some pilot data from human subjects is shown, the clinical relevance of these findings for liver disease remain to be determined.

The major strength of this work is its scope, including detailed mouse phenotyping, inter-disciplinary methods, and numerous complementary experiments. The antibiotic depletion and FMT experiments provide support for a role of the gut microbiota in this mouse model.

A major limitation is the lack of studies narrowing down which microbes are responsible. Sequencing data is shown, but no follow-up studies are done with bacterial isolates or defined communities.

The link to GABA is also somewhat tenuous. While it does match the phenotypic data, there are no targeted experiments in which GABA producing microbial communities/strains are compared to a control community/strain. As such, it seems difficult to know how much of the effects in this model are due to GABA vs. other metabolites.

My major recommendation would be to revise the title, abstract, and discussion to provide more qualification and to consider alternative interpretations.

Some key controls are also missing, which could be addressed by repeat experiments in the mouse model. The antibiotic depletion experiment would be improved by testing the effect of antibiotics in the absence of metformin, to see if the effect is just driven by the model itself as opposed to an interaction between metformin and antibiotics. The FMT experiment lacks a control group and suffers from pseudoreplication: multiple donors from metformin treated and untreated mice could be used to colonize separate groups of recipient mice.

Reviewer #1 (Public Review):

This manuscript provides important evidence on the association between sleep regularity and mortality in the UK Biobank, which is a popular topic in recent sleep and circadian research in population-based studies. The analysis reported robust associations between sleep irregularity and increased total, CVD and cancer mortality, and provided evidence to support the role of sleep and circadian health in disease progression and longevity in human populations. The Sleep Regularity Index (SRI) used in this study is a novel metric that quantifies the consistency in rest-activity rhythms over consecutive 24 hour periods, thus providing objective assessment of potential circadian disruption. The study is based on a large accelerometer study with validated follow-up of incident diseases and deaths. The data quality and large sample size strengthen the credibility of the conclusion. Overall, the analyses are appropriately done and the manuscript is clearly written. Additional justification for the assessment of nonlinearity and further subgroup analyses would further improve the manuscript.

Joint Public Review

In the presence of predators, animals display attenuated foraging responses and increased defensive behaviors that serve to protect them from potential predatory attacks. Previous studies have shown that the basolateral nucleus of the amygdala (BLA) and the periaqueductal gray matter (PAG) are necessary for the acquisition and expression of conditioned fear responses. However, it remains unclear how BLA and PAG neurons respond to predatory threats when animals are foraging for food. The authors employed single-unit recording of BLA and PAG neurons and optogenetic tools to address this question in an 'approach food-avoid predator' paradigm.

The authors observed that rats exhibited a significant increase in the latency to obtain the food pellets and a reduction in the pellet success rate when the predator robot was activated. A subpopulation of PAG neurons showing increased firing rate in response to the robot activation did not change its activity in response to food pellet retrieval during the pre- or post-robot sessions. Optogenetic stimulation of PAG neurons increased the latency to procure the food pellet in a frequency- and intensity-dependent manner, similar to what was observed during the robot test. Combining optogenetics with single-unit recordings, the authors demonstrated that photoactivation of PAG neurons increased the firing rate of 10% of BLA cells. A subsequent behavioral test in three of these same rats demonstrated that BLA neurons responsive to PAG stimulation displayed higher firing rates to the robot than BLA neurons nonresponsive to PAG stimulation. Next, because the PAG does not project monosynaptically to the BLA, the authors used a combination of retrograde and anterograde neural tracing to identify possible regions that could convey robot-related information from PAG to the BLA. They observed that neurons in specific areas of the paraventricular nucleus of the thalamus (PVT) that are innervated by PAG fibers contained neurons that were retrogradely labeled by the injection of CTB in the BLA. In addition, PVT neurons showed increased expression of the neural activity marker cFos after the robot test, suggesting that PVT may be a mediator of PAG signals to the BLA.

Strengths

Overall, the idea that the PAG interacts with the BLA via the midline thalamus during a predator vs. foraging test is new and quite interesting. The authors have used appropriate tools to address their questions. The major impact in the field would be to add evidence to claims that the BLA can be downstream of the dPAG to evoke defensive behaviors. The study also adds to a body of evidence that the PAG mediates primal fear responses.

Weaknesses

The two most significant weaknesses relate to a) anatomical concerns related to the subregions of the BLA and PAG that were targeted by manipulations and analyses and b) the correlational nature of the PVT measures and the lack of any causal role demonstrated. Other concerns are also detailed below.

Anatomical concerns:

1. The authors claim that the recordings were performed in the dorsal PAG (dPAG), but the histological images in Fig. 1B and Supplementary S2 for example show the tip of the electrode in a different subregion of PAG (ventral/lateral). They should perform a more careful histological analysis of the recording sites and explain the histological inclusion and exclusion criteria. Diagrams showing the sites of all PAG and BLA recordings, as well as all fiber optics, would be helpful.<br /> 2. Prior studies investigating the role of BLA neurons during a foraging vs. robot test similar to the one used in this study should be also cited and discussed (e.g., Amir et al 2019, PMID: 30840520; Amir et al 2015, PMID: 26400931). These two studies demonstrated that most neurons in the basal portion of the BLA exhibit inhibitory activity during foraging behavior and only a small fraction of neurons (~4%) display excitatory activity in response to the robot (in contrast to the 25% reported in the present study). A very accurate histological analysis of BLA recording sites should be performed to clarify whether distinct subregions of the BLA encode foraging and predator-related information, as previously shown in the two described studies.<br /> 3. An important claim of this study that the PAG sends predator-related signals to BLA via the PVT (Fig. 4). The authors stated that PVT neurons labeled by intra-BLA injection of the retrograde tracer CTB were activated by the predator, but a proper immunohistochemical quantification with a control group was not provided to support this claim. To provide better support for their claim, the authors should quantify the double-labeled PVT neurons (cFos plus CTB positive neurons) during the robot test.<br /> 4. The AVV anterograde tracer deposit spread to a large part of the PAG, including dorsolateral and lateral PAG, and supraoculomotor regions (Fig. 4B). Is the projection to the PVT from the dPAG or other regions of the PAG?

Concerns about the strength of the evidence supporting a role for the PVT:

5. The authors conclude in the discussion section that the dPAG-amygdala pathway is involved in generating antipredatory defensive behavior. However, the current results are entirely based on correlational analyses of neural firing rate and there is no direct demonstration that the PAG provides information about the robot to the BLA. Therefore, the authors should tone down their interpretation or provide more evidence to support it by performing experiments applying inhibitory tools in the dPAG > PVT > BLA pathway and examining the impact on behavior and downstream neural firing.

Other concerns:

6. One of the main findings of this study is the observation that BLA neurons that are responsive to PAG photostimulation are preferentially recruited during the foraging vs. robot test (Fig. 3). However, the experimental design used to address this question is problematic because the laser photostimulation of PAG neurons preceded the foraging vs. robot test. Prior photoactivation of PAG may have caused indirect short-term synaptic plasticity in BLA cells, which would favor the response of these cells to the robot. Please see Oishi et al, 2019 PMID: 30621738, which demonstrated that 10 trains of 20Hz photoactivation (300 pulses each) was sufficient to induce LTP in brain slices.<br /> 7. The authors should perform a longitudinal analysis of the behavioral responses of the rats across the trials to clarify whether the animals habituate to the robot or not. In Figure 1E, it appears that PAG neurons fire less across the trials, which could be associated with behavioral habituation to the predator robot. If that is the case, the activity of many other PAG and BLA neurons will also most likely vary according to the trial number, which would impact the current interpretation of the results.<br /> 8. In Figure 1, it is unclear why the authors compared the activity of neurons that respond to the robot activation against the activity of the neurons during the retrieval of the food pellets in the pre-robot and post-robot sessions. The best comparison would be aligning the cells that were responsive to the activation of the robot with the moment in which the animals run back to the nest after consuming the pellets during the pre-robot or post-robot sessions. This would enable the authors to demonstrate that the PAG responses are directly associated with the expression of escaping behavior in the presence of the robot rather than associated with the onset of goal-directed movement in direction to the next during the pre- and post-robot sessions. A graphic showing the correlation between PAG firing rate and escape response would be also informative.

Reviewer #1 (Public Review):

The authors performed a comparative study of the effect of the anesthetics isoflurane and ketamine on whole-brain network activation by mapping whole-brain c-fos expression in mice. Principle component analysis on the normalized Fos density showed opposite effects of the 2 anesthetics, consistent with top-down functioning for ketamine and bottom-up functioning for isoflurane. Based on the network analysis the authors suggest that isoflurane mediates anesthesia through a bottom-up mechanism activating subcortical regions and inactivating cortical regions with the locus coeruleus being the most important region while ketamine produced anesthesia through a top-down mechanism activating the cortex and subcortical nuclei with the somatosensory cortex as the most important region. Overall they show that these two anesthetics have two opposite mechanisms to induce unconsciousness, although they also have overlapping coactivation of central sleep-wake, pain, and neuroendocrine regulating areas. This manuscript highlights some interesting findings through interesting analysis. The results are likely to have a significant impact on the field of anesthesia but also on the much larger field of neuropsychopharmacology as the tools and analyses used in this report will be useful for researchers investigating the effects of any psychoactive drugs on the brain. However, there are several issues that should be addressed to support their conclusions. The two main issues of this report are the lack of behavioral/physiological measures of the depth of anesthesia produced by ketamine/isoflurane and inadequate data analysis/interpretations for some of the results.

Strengths<br /> Comparison of two different anesthetics<br /> Use of single-cell whole-brain imaging<br /> Advanced network analysis

Weaknesses<br /> Lack of behavioral/physiological measures<br /> Interpretation of the data is sometimes confusing/unclear<br /> Some statistical tests are missing and others are not controlled for multiple comparisons

Major concerns<br /> 1. The lack of behavioral/physiological measures of the depth of anesthesia (ventilation, heart rate, blood pressure, temperature, O2, pain reflexes, etc...) combined with the lack of dose-response and the use of different routes of administration makes the data difficult to interpret. Sure, there is a clear difference in network activation between KET and ISO, but are those effects due to the depth of the anesthesia, the route of administration, and the dose used? The lack of behavioral/physiological measures prevents the identification of brain regions responsible for some of the physiological effects and different effects of anesthetics.<br /> 2. Under anesthesia there should be an overall reduction of activity, is that the case? There is no mention of significantly downregulated regions. The authors use multiple transformations of the data to interpret the results (%, PC1 values, logarithm) without much explanation or showing the full raw data in Fig 1. It would be helpful to interpret the data to compare the average fos+ neurons in each region between treatment and control for each drug.<br /> 3. I do not understand their interpretation of the PCA analyses. For instance, in Fig 2 they claim that KET is associated with PC1 while ISO is associated with PC2. Looking at the distribution of points it's clear that the KET animals are all grouped at around +2.5 on PC1 and -2.0 on PC2, this means that KET is associated with both PC1 and PC2 to a similar degree (2 to 2.5). Moreover, I'm confused about why they use PCA to represent the animals/group. PCA is a powerful technique to reduce dimensionality and identify groups of variables that may represent the same underlying construct; however, it is not the best way to identify clusters of individuals or groups.<br /> 4. The actual metric used for the first PCA is unclear, is it the FOS density in each of the regions (some of those regions are large and consist of many subregions, how does that affect the analysis) is it the %-fos, or normalized cells? The wording describing this is variable causing some confusion. How would looking at these different metrics influence the analysis?<br /> 5. Based on Fig 3 the authors concludes that ISO activates the hypothalamic regions and inhibits the cortex, however, Fig 1 shows neither an activation of the hypothalamus in the ISO nor an inhibition of the cortex when compared to home cage control. If anything it suggests the opposite.<br /> 6. Control for isoflurane should be air in the induction chamber rather than home cage. It is possible that Fos activation reflects handling/stress pre-anesthesia in the animals, which would increase Fos expression in the stress-related regions such as the BST, striatum (CeA), hypothalamus (PVH) and potentially the LC.<br /> 7. In the Ket network there are a few anticorrelated regions, most of which are amongst the list of the most activated regions, does this mean that the strong correlation results from an overall decreased activation? And if so, is it possible that the ketamine anesthesia was stronger than the isoflurane, causing a more general reduction in activity?<br /> 8. Since they have established networks it would be easy and useful to look at how the different regions identified (sleep, pain, neuroendocrine, motor-related, ...) work together to maintain analgesia, are they within the same module? Do they become functionally connected and is this core network of functional connections similar for KET and ISO?<br /> 9. The naming of the function of some of the regions is very much debatable. For instance, PL/ILA are named "sleep-wakefulness regulation" regions in the paper. I can think of many more important functions of the PL/IL including executive functions, behavioral flexibility, and emotional control. It is unclear how the functions of all the regions were attributed. I am not sure that this biased labeling of structure-function is useful to the reports, it may instead suggest wrong conclusions.<br /> 10. A point of concern and confusion is the number of brain regions analyzed. In the introduction, it is mentioned that 987 brain regions are considered, but this is reduced to 53 selected brain regions in Figure 2, then 201 brain regions in Figure 3, and reduced again to 63 for the network analysis. The rationale for selecting different brain regions is not clear.<br /> 11. The statistical analysis does not seem appropriate considering the high number of comparisons. They use simple t-tests without correction for multiple comparisons.<br /> 12. There is no statistical analysis in Fig 2C,

Reviewer #1 (Public Review):

This EEG study probes the prediction of a mechanistic account of P300 generation through the presence of underlying (alpha) oscillations with a non-zero mean. In this model, the P300 can be explained by a baseline shift mechanism. That is, the non-zero mean alpha oscillations induce asymmetries in the trial-averaged amplitudes of the EEG signal, and the associated baseline shifts can lead to apparent positive (or negative) deflections as alpha becomes desynchronized at around P300 latency. The present paper examines the predictions of this model in a substantial data set (using the typical P300-generating oddball paradigm and careful analyses). The results show that all predictions are fulfilled: the two electrophysiological events (P300, alpha desynchronization) share a common time course, anatomical sources (from inverse solutions), and covariations with behaviour; plus relate (negatively) in amplitude, while the direction of this relationship is determined by the non-zero-mean deviation of alpha oscillations pre-stimulus (baseline shift index, BSI). This is indicative of a tight link of the P300 with underlying alpha oscillations through a baseline shift account, at least in older adults, and hence that the P300 can be explained in large parts by non-zero mean brain oscillations as they undergo post-stimulus changes.

Reviewer #1 (Public Review):

The present study by Berger et al. analyzes to what extent memory formation is dependent on available energy reserves. This has been dealt with extensively in the case of aversive memory formation, but only very sparsely in the case of appetitive memory formation. It has long been known that an appetitive memory in flies can only be formed by starvation. However, the authors here additionally show that not only the duration of starvation plays a role, but also determines which form of memory (short- or long-term memory) is formed. The authors demonstrated that internal glycogen stores play a role in this process and that this is achieved through insulin-like signaling in octopaminergic reward neurons that integrates internal energy stores into memory formation. Here, the authors suggest that octopamine plays a role as a negative regulator of different forms of memory.

The study sheds light on an old question, to what extent the octopaminergic neuronal system plays a role in the formation of appetitive memory, since in recent years only the dopaminergic system has been in focus. Furthermore, the data are an interesting contribution to the ongoing debate whether insulin receptors play a role in neurons themselves or in glial cells. The experiments are very well designed and the authors used a variety of behavioural experiments, genetic tools to manipulate neuronal activity and state-of-the-art imaging techniques. In addition, they not only clearly demonstrated that octopamine is a negative regulator of appetitive memory formation, but also proposed a mechanism by which the insulin receptor in octopaminergic neurons senses the internal energy status and then controls the activity of those neurons. The conclusions are mostly supported by the data, but some aspects related to the experimental design, some explanations and literature references need more clarification and revision.

1. Usually, long-term memory (LTM) is tested 24 hours after training. Here, the authors usually refer to LTM as a memory that is tested 6 hours after training. The addition of a control experiment to show that LTM that the authors observe here lasts longer would increase the power of this study immensely.

2. The authors define here another consolidated memory component as ARM, when they applied a cold-shock 2 hours after training. However, some publications showed that LTM is formed after only one training cycle (Krashes et al 2008, Tempel et al 1983). This makes it difficult to determine, whether appetitive ARM can be formed. Furthermore, one study showed that appetitive ARM is absent after massed training (Colomb et al 2009). Therefore, the conclusion could be also, that different starvation protocols, would lead to different stabilities of LTM. Therefore, additional experiments could help to clarify this opposing explanation. From these results, it can then be concluded either that different stable forms of LTM are formed depending on the starvation state, or that two differently consolidated memory phases (LTM, ARM) are formed, as has already been shown for aversive memory. This is also important for other statements in the manuscript, and therefore the authors should address this. For example, the findings about the insulin receptor (is it two opposing memories or different stabilities of LTM).

Reviewer #1 (Public Review):

She et al studied the evolution of gene expression reaction norms when individuals colonise a new environment that exposes them to physiologically challenging conditions. Their objective was to test the "plasticity first" hypothesis, which suggest that traits that are already plastic (their value changes when facing a new environment compared to the original environment) facilitates the colonisation of novel environments, which, if true, would be predicted to result in the evolution of gene expression values that are similar in the population that colonised the new environment and evolved under these particular selection pressures. To test this prediction, they studied gene expression in cardiac and muscle tissues in individuals originating from three conditions: lowland individuals in their natural environment (ancestral state), lowland individuals exposed to hypoxia (the plastic response state), and a highland population facing hypoxia for several generations (the coloniser state). They classified gene expression patterns as maladaptive or adaptive in lowland individuals responding to short term hypoxia by classifying gene expression patterns using genes that differed between the ancestral state (lowland) and colonised state (highland). Genes expressed in the same direction in lowland individuals facing hypoxia (the plastic state) as what is found in the colonised state are defined as adaptative, while genes with the opposite expression pattern were labelled as maladaptive, using the assumption that the colonised state must represent the result of natural selection. Furthermore, genes could be classified as representing reversion plasticity when the expression pattern differed between the plasticity and colonised states and as reinforcement when they were in the same direction (for example more expressed in the plastic state and the colonised state than in the ancestral state). They found that more genes had a plastic expression pattern that was labelled as maladaptive than adaptive. Therefore, some of the genes have an expression pattern in accordance with what would be predicted based on the plasticity-first hypothesis, while others do not.

As pointed out by the authors themselves, the fact that temperature was not included as a variable, which would make the experimental design much more complex, misses the opportunity to more accurately reflect the environmental conditions that the colonizer individuals face at high altitude. Also pointed out by the authors, the acclimation experiment in hypoxia lasted 4 weeks. It is possible that longer term effects would be identifiable in gene expression in the lowland individuals facing hypoxia on a longer time scale. Furthermore, a sample size of 3 or 4 individuals per group depending on the tissue for wild individuals may miss some of the natural variation present in these populations. Stating that they have a n=7 for the plastic stage and n= 14 for the ancestral and colonized stages refers to the total number of tissue samples and not the number of individuals, according to supplementary table 1.

Impact of the work:

There has been work showing that populations adapted to high altitude environments show changes in their hypoxia response that differs from the short-term acclimation response of lowland population of the same species. For example, in humans, see Erzurum et al. 2007 and Peng et al. 2017, where they show that the hypoxia response cascade, which starts with the gene HIF (Hypoxia-Inducible Factor) and includes the EPO gene, which codes for erythropoietin, which in turns activates the production of red blood cell, is LESS activated in high altitude individuals compared to the activation level in lowland individuals (which gives it its name). The present work adds to this body of knowledge showing that the short-term response to hypoxia and the long term one can affect different pathways and that acclimation/plasticity does not always predict what physiological traits will evolve in populations that colonize these environments over many generations and additional selection pressure (UV exposure, temperature, nutriment availability).

Altogether, this work provides new information on the evolution of reaction norms of genes associated with the physiological response to one of the main environmental variables that affects almost all animals, oxygen availability. It also provides an interesting model system to study this type of question further in a natural population of homeotherms.

Erzurum, S. C., S. Ghosh, A. J. Janocha, W. Xu, S. Bauer, N. S. Bryan, J. Tejero et al. "Higher blood flow and circulating NO products offset high-altitude hypoxia among Tibetans." Proceedings of the National Academy of Sciences 104, no. 45 (2007): 17593-17598.

Peng, Y., C. Cui, Y. He, Ouzhuluobu, H. Zhang, D. Yang, Q. Zhang, Bianbazhuoma, L. Yang, Y. He, et al. 2017. Down-regulation of EPAS1 transcription and genetic adaptation of Tibetans to high-altitude hypoxia. Molecular biology and evolution 34:818-830.

Reviewer #1 (Public Review):

The authors were seeking to improve understanding of how wind and wave action affect the use of energetically demanding wing flapping and running by albatross engaged in takeoff flight. To accomplish this in the complex and challenging environment in which albatross live, the authors sought to use accelerometry and geographic positioning to infer patterns of locomotion, flight orientation relative to the prevailing wind, and wave height during takeoff.

The major strength of the methods and results is that the use of accelerometry and novel interpretations of data from a geographic positioning system provides new insight into the use of waves by albatross and how the effects of wave magnitude interact with wind to modulate energy demands during takeoff. Weaknesses of the approach are due to the challenging environmental conditions in which albatross live. The interpretation of accelerometry data was not validated using a subset of the sample synchronized with video (prior validation was cited for shearwaters). The interpretation of wind direction relative to flight path is based on the behavior of the bird without concurrent measures of local wind velocity.

The authors achieved their aims, and their results support their conclusions.

Although it is generally understood that albatross and many other birds choose to takeoff into the wind to reduce energetic costs, the authors provide novel quantitative data on this behavior. Their results on the effects of wave height and the interactions between wave height and wind provide novel insight into how albatross harvest energy from their complicated and dynamic environment to reduce the energy they must output to get into the air. In particular, the new insight into the effects of wave height should revise understanding among ornithologists, ocean ecologists and those who study the mechanics of animal locomotion. The use of accelerometry and geographic positioning systems to measure flight behavior and ocean ecology should inspire other researchers to adopt similar methods.

Albatross live in a complex and poorly understood environment that is likely to be threatened by climate change. This research provides worthwhile new insight into how wind and wave action affect takeoff in albatross, and can therefore improve insight into how changes in these variables with climate change may affect the distribution of albatross populations.

Reviewer #1 (Public Review):

The manuscript provides analyses on a very complete dataset on weight and length growth, as well as several physiological markers related to growth, in bonobos. Moreover, there is a good overview of the presence of adolescent growth spurts in non-human primates, by reviewing published data, in comparison to their own dataset. They discuss the need to consider scaling laws when interpreting and comparing growth curves of different species and variables.

The manuscript is very well written, the sample is large, and the methods are well explained. It seems they have analyzed a very complete dataset. Also, the discussion and the references supporting the findings are complete.

The main weakness of this manuscript is that they do not provide a direct comparison with previously analyzed datasets in other species, using their own method (in part maybe because there is not available data, but just published figures).

On the other side, conclusions are well supported by the results, and the previously published datasets are discussed in the manuscript, although not in detail.

Reviewer #1 (Public Review):

This paper describes the discovery, functional analysis and structure of TcaP, a protein encoded by the Vibrio phage satellite PLE that forms a size-determining scaffold around PLE procapsids made from helper phage ICP1 structural proteins. The system displays a fascinating similarity to the P2/P4 system, which had previously been unique in its use of a size-determining external scaffolding protein, Sid. The work is interesting, comprehensive and of high quality. The presentation could be improved as listed in the suggestions below.

An interesting observation is that PLE appears to be dependent on small capsids for efficient transduction. This is not completely surprising if the element uses a cos site type mechanism for packaging, since this requires an integer number of genomes to be packaged when the capsid is full, and this might be more difficult to accomplish when the helper capsid is much larger than the satellite, as is the case with ICP1. The authors mention in a few places that this is the first known satellite to have this requirement. However, this is not quite correct: a similar defect was seen in phi12/SaPIbov5, where the large phi12 capsid was not quite the right size for either two or three copies of the wild-type ("unevolved") SaPIbov5 (Carpena et al. 2016).

The authors present several micrographs showing capsids formed in the presence or absence of wildtype or mutant TcaP and CP (Fig. 1, Fig 2., Fig 3). However, each micrograph shows only a handful of particles of the "correct" size, in addition to a few shells that are aberrant or of a different size. I miss a more statistically rigorous enumeration of shells of different size (PLE or ICP1 sized, or different), empty vs. full, aberrant shells etc. This could be presented as a size distribution graph, a histogram or in table form.

In the abstract, the term "divergent satellite P4" is vague and unclear. Divergent from what? Probably they mean distinct from or unrelated to PLE. Please clarify.

How do they know that gp123 is a decoration protein? Was this previously determined, does it have (sequence) similarity to other known decoration proteins, or is it simply the most likely designation based on its position in the genome?

Although the reconstruction and modeling statistics are good, it is difficult to assess the quality of the map and the model from the presented figures. Details of the density and FSC curves (half-map and model-to-map) should be shown. It is also difficult to see the TcaP structure and how it compares to Sid from the figures presented.

Introduction, Paragraph 3: "...which is the number of coat proteins divided by 60" is not strictly speaking the definition of T number. The T number corresponds to the number of subtriangles that one triangular face of the icosahedron is divided into. It corresponds to the number of coat proteins divided by 60 in the canonical case, but in tailed phages, 5 copies are removed to make way for the portal protein. (Other viruses could be described as having architecture corresponding to a specific T number, but with divergent numbers of subunits, e.g. adenoviruses or polyomaviruses.)

Reviewer #1 (Public Review):

This is a paper describing in detail the seasonal movements of a vole-eating raptor, the rough-legged buzzard, from their Arctic breeding areas to the temperate wintering areas and back, in an annual cycle perspective. The basis of the descriptions (using satellite tags) is state of the art, and so are the analyses on aspects of time and space. Of particular relevance is the degree in which this study successfully pinpoints the ecological shaping factors, food availability of course, in this case strongly affected by snow cover (which can be remotely sensed over large areas). The authors claim a new migration pattern called 'foxtrot' with phases with rapid and phases with slower migration movements.

My concern with this paper is the framing. A story on the how and why of these continental movements in response to snow and other habitat features would be a grand contribution.

Reviewer #1 (Public Review):

The authors Wang et al. present a study of a mouse model K74R that they claim can extend the life span of mice, and also has some anti-cancer properties. Importantly, this mechanism seems to be mediated by the hematopoietic system, and protective effects can be transferred with bone marrow transplantation.

The authors need to be more specific in the title and abstract as to what is actually novel in this manuscript (a single tumor model), and what relies on previously published data (lifespan). Because many of these claims derive from previously published data, and the current manuscript is an extension of previously published work. The authors need to be more specific as to the actual data they present (they only use the B16 melanoma model) and the actual novelty of this manuscript.

Especially experiments on life span are published and not sufficiently addressed in this actual paper, as the title would suggest.

Reviewer #1 (Public Review):

In this manuscript, Bockorny, Muthuswamy, and Huang et al. performed proteomics analysis of plasma extracellular vesicles (EVs) from pancreatic ductal adenocarcinoma (PDAC) patients and patients with benign pancreatic diseases (chronic pancreatitis and intraductal papillary mucinous neoplasm, IPMN) to develop a 7-EV protein signature that predicts PDAC. Moveover, the authors identified PSMB4, RUVBL2, and ANKAR as being associated with metastasis. These studies provide important insight into alterations of EVs during PDAC progression and the data supporting predict PDAC with EV protein signatures are solid. However, there are certain concerns regarding the rigor and novelty of the data analysis and interpretation, as well as the clinical implications, as detailed below.

1. Plasma EVs were characterized by transmission electron microscopy and nanoparticle tracking analysis to confirm their morphology and size. The authors should also include an analysis of putative EV markers (e.g., tetraspanins, syntenin, ALIX, etc.) to confirm that the analyzed particles are EVs.

2. The authors identified multiple over-expressed proteins in PDAC based on their fold change and p-value; however, due to the heterogeneity of PDAC, it is necessary to show a heatmap displaying their abundance in all samples. High fold change does not necessarily indicate consistently high abundance in all PDAC samples.

3. PSMB4, RUVBL2, and ANKAR were identified as being associated with metastasis. The authors state that they intended to distinguish early and late-stage cancer samples, but it is unclear why they chose to compare metastatic and non-metastatic samples, as the non-metastatic group also includes late-stage cancer samples. This sentence should be rephrased to more accurately reflect the sample types profiled.

4. Non-metastatic and metastatic patients were separated based on global protein abundance. The samples within each group display significant heterogeneity with, some samples displaying similar patterns although they were classified into different groups (Figure 3A), and the samples within the same group, particularly the metastasis group, did not consistently exhibit similar patterns of protein abundance. The authors should clarify this point.

5. The authors performed the survival analysis on a set of EV proteins but did not specify the origin of these markers or how many markers were examined. The authors should show their abundances across different groups, such as different stages and metastasis status.

6. The classification model yielded a 100% accuracy, which may refer to AUC, in their discovery cohort, but it decreased to 89% in the independent cohort. This suggests that the authors have encountered overfitting issues with their model, where it performed well on the discovery cohort but did not generalize well to the independent cohort. The authors should clarify this point. The AUC score of the 7-EV signature is 0.89 and is not equivalent to prediction accuracy. In order to demonstrate prediction accuracy, the authors should show the confusion matrix of training and testing data as well as other evaluation metrics, such as accuracy, precision, and recall.

7. The authors should include more details of their model and the process of selection of signatures to enhance the reproducibility and transparency of their methods.

Reviewer #1 (Public Review):

The study investigates the nature of "trailblazer" cells in distinct tumor models, including luminal B (MMTV/PyMT) and triple negative (TNBC) tumors (C3-TAg). The authors note that the trailblazer phenotypes in the TNBC model are more complex relative to the Luminal B model and represent distinct EMT programs associated with the expression of distinct EMT-TFs (Zeb1, Zeb2 and Fra-1). They demonstrated that of numerous EMT-TFs, Zeb1 and Fra-1 were required for increased cancer cell migration and invasion. They reveal that TGF-beta and EGF-mediated signaling are required for the diverse EMT states that are required for trailblazer cell activity and increased cell migration/invasion. TGF-beta signaling engaged Zeb 1 and Zeb2 while EGF signaling activated Fra-1. Indeed, inhibitors of either TGF-beta or EGF signaling could impair cell migration/invasion. While both pathways contributed to trailblazer phenotypes, EGF signaling was shown to interfere with certain TGF-beta induced transcriptional response, including the expression of genes encoding extracellular matrix proteins.

One concern was the heavy reliance of the C3-TAg as the sole TNBC model in which the distinct trailblazer phenotypes were described. The data in Fig. 3 of the submission reveals that the phenotypes observed in the C3-TAg model could be recapitulated in a TNBC patient-derived xenograft model (PDX). Using this PDX, the authors were able to show vimentin expression in lung metastatic TNBC cells that were intravascular, those that had extravasated and clusters of cancer cells fully within the lung parenchyma. This was an important addition to the manuscript. The additional experiments to investigate the role of Zeb1 and Zeb1 more fully, beyond the focus on Fra-1 in the initial submission was an additional strength of the new submission. Additional clarifications to the discussion also clarified the concepts articulated in the study. The study employs multiple breast cancer models, utilizes numerous in vitro and in vivo assessments of the trailblazer phenotypes, and the experimental design is rigorous and the interpretation of the data is sound. The manuscript will be of general interest to the research community.

Reviewer #1 (Public Review):

In this manuscript by Wu et al., the authors present the high-resolution cryoEM structures of the WT Kv1.2 voltage-gated potassium channel. Along with this structure, the authors have solved several structures of mutants or experimental conditions relevant to the slow inactivation process that these channels undergo and which is not yet completely understood.

One of the main findings is the determination of the structure of a mutant (W366F) that is thought to correspond to the slow inactivated state. These experiments confirm results in similar mutants in different channels from Kv1.2 that indicate that inactivation is associated with an enlarged selectivity filter.

Another interesting structure is the complex of Kv1.2 with the pore-blocking toxin Dendrotoxin 1. The results show that the mechanism of the block is different from similar toxins, in which a lysine residue penetrates the pore deep enough to empty most external potassium binding sites.

The quality of the structural data presented in this manuscript is very high and allows for the unambiguous assignment of side chains. The conclusions are supported by the data. This is an important contribution that should further our understanding of voltage-dependent potassium channel gating. Specific comments are appended below.

1) In the mains text's reference to Figure 2d residues W18' and S22' are mentioned but are not labeled in the insets.

2) On page 8 there is a discussion of how the two remaining K+ ions in binding sites S3 and S4 prevent permeation K+ in molecular dynamics. However, in Shaker, inactivated W434F channels can sporadically allow K+ permeation with normal single-channel conductance but very reduced open times and open probability at not very high voltages.

3) The structures of WT in the absence of K+ show a narrower selectivity filter, however, Figure 4 does not convey this finding. In fact, the structure in Figure 4B is constructed at such an angle that it looks as if the carbonyl distances are increased, perhaps this should be fixed. Also, it is not clear how the distances between carbonyls given in the text on page 12 are measured. Is it between adjacent or kitty-corner subunits?

4) It would be really interesting to know the authors' opinions on the driving forces behind slow inactivation. For example, potassium flux seems to be necessary for channels to inactivate, which might indicate a local conformational change is the trigger for the main twisting events proposed here.

Reviewer #1 (Public Review):

The authors have previously employed micrococcal nuclease tethered to various Mcm subunits to the cut DNA to which the Mcm2-7 double hexamers (DH) bind. Using this assay, they found that Mcm2-7 DH are located on many more sites in the S. cerevisiae genome than previously shown. They then demonstrated that these sites have characteristics consistent with origins of DNA replication, including the presence of ARS consensus sequences, location of very inefficient sites of initiation of DNA replication in vivo, are free of nucleosomes, they contain a G-C skew and they locate to intergenic regions of the genome. The authors suggest, consistent with published single molecule results, that there are many more potential origins in the S. cerevisiae genome than previously annotated.

The results are convincing and are consistent with prior observations. The analysis of the origin associated features is informative.

Reviewer #1 (Public Review):

The authors investigated the function of BATF in hepatic lipid metabolism. They found BATF alleviated high-fat diet (HFD)-induced hepatic steatosis. In addition, BATF could inhibit programmed cell death protein (PD)1 expression induced by HFD. By using over expression and transcriptional activity analysis, this study confirmed that BATF regulates fat accumulation by inhibiting PD1 expression and promoting energy metabolism. Then, they found PD1 antibodies alleviated hepatic lipid deposition. These data identified the regulatory role of BATF in hepatic lipid metabolism and that PD1 is a target for alleviation of NAFLD.

The conclusions of this manuscript are supported by data, but some remaining concerns need to be addressed.

1. There are different cells in liver tissue, in which BATF protein is expressed most.<br /> 2. The statistical data should be provided to support the liver specific over-expression of BATF.<br /> 3. For in vivo study, food intake is key data to exclude the change of energy intake.<br /> 4. For Fig.6 Since PD1 are also highly expressed in heart and spleen, how to exclude the effect of PD1 antibody on these tissues?

Reviewer #1 (Public Review):

This study delves into the impact of imidacloprid, an insecticide documented for its toxicity towards honeybees, on the development of bee larvae. The investigation involved exposing bee larvae to various concentrations of imidacloprid, and observing the resultant effects.

The findings of this study revealed that imidacloprid exerted a dose-dependent delay in the development of bee larvae, marked by reductions in body mass, width, and an overall decline in the growth index. Moreover, at elevated concentrations, imidacloprid was observed to impair neural transmission, induce oxidative stress, inflict damage to the gut, and inhibit hormones and genes essential for development. The larvae were found to engage antioxidant defense systems and deploy detoxification mechanisms to mitigate these effects.

However, the manuscript could be significantly enhanced through several improvements. Firstly, the structure of the manuscript warrants refinement to foster coherence and clarity. Additionally, there is a need for careful reevaluation of the concentrations of imidacloprid employed in the study, to ensure their relevance and applicability. In terms of references, greater attention to accuracy in citation is imperative.

Furthermore, while the authors have provided an overview of the general effects of imidacloprid on both vertebrates and invertebrates, the inclusion of a more exhaustive literature review with a specific focus on honey bees and other insects would bolster the context and significance of this research. This would be particularly beneficial in the introduction section, which should be subjected to a major revision.

In summary, this study offers preliminary evidence of the detrimental effects of imidacloprid on the development of bee larvae by interfering with molting and metabolism. This research holds potential as a valuable resource for assessing the risks posed by pesticides to juvenile stages of various animal species.

Reviewer #1 (Public Review):

This is a straightforward paper that uses TraDIS (high-density TnSeq) with Klebsiella pneumoniae to infer essential genes, and genes required for survival under various infection-relevant conditions. The gene sets identified, together with the raw sequence data, will be valuable resources for the Klebsiella research community. The evidence to support the lists of essential and conditionally-important genes is solid, although a few additional follow-up experiments would strengthen some of the claims made based on the TraDIS data.

1. The data strongly suggest that iron depletion in urine leads to conditional essentiality of some genes. It would be informative to test the single gene deletions (Figure 3G) for growth in urine supplemented with iron, to determine how many of those genes support growth in urine due to iron limitation.<br /> 2. Line 641. The authors raise the intriguing possibility that some mutants can "cheat" by benefitting from the surrounding cells that are phenotypically wild-type. Growing a fepA deletion strain in urine, either alone or mixed with wild-type cells, would address this question. Given that other mutants may be similarly "masked", it is important to know whether this phenomenon occurs.<br /> 3. In cases where there are disparities between studies, e.g., for genes inferred to be essential for serum resistance, it would be informative to test individual deletions for genes described as essential in only one study.

Something to introduce into your yearly review is to reflect on the period and find out what your 10x cycles were.

A 10x mindset is defined by letting go of the 80% that isn't useful, and focusing on the 20% that is essential while building 80% new skills or standards that benefit your purpose. A lot of true progress requires sacrifice (stripping down that which is not beneficial or essential).

Related to what Mihaly Csikszentmihaliy, author of Flow, calls the Ulterior purpose, where the purpose serves as a big filter to focus on what actually matters. Antonin Sertillanges gives a similar account in The Intellectual Life

The solid maxim: Big change requires great sacrifice.""

Likely, identifying the essential 20% (and the 80% to learn) requires a lot of introspection and reflection. Something that will help significantly is Kolb's.

One) Successful men realize that the most important decision in their life is the woman they choose, because outside of work, this is what they'll be spending most time on. The woman must understand the man's grand ambition, and support them with it. (Cf. Flow & The Intellectual Life as well). Women should be chosen on personality, not looks. Looks fade (attraction as well), personality "stays".

Two) Everyone deserves an opinion but not everyone deserves a say. Charlie Munger sums this up right: "I don't ever allow myself to have [express] an opinion about anything that I don't know the opponent side's argument better than they do." Or Marcus Aurelius, who says: "The opinion of ten thousand men is of no value if none of them know anything about the subject." In short: Only state your opinion when you can back it up!; knowledge and experience. The same goes for judging opinion (and advice) from others.

Three) Successful people buy assets when the money is enough. Assets > Luxury. (See also: Rich Dad, Poor Dad, Robert Kiyosaki). Only buy glamor and other "interests" once your assets are there to secure your financial success.

Four) Be pragmatic. Do what's practical, not what is "sexy". Notice inefficiencies and solve them. The entrepreneurial mindset.

Five) The morning sets the tone for the rest of the days. Time is subjective, waking up early doesn't matter as much as waking up later. It depends on the person. Someone who wakes up at 10am can be as successful as someone who wakes up at 6am. Instead, what defines success, is a highly effective morning routine.

Six) The less you talk, the more you listen. Talking less means less mistakes. In addition, the less you talk, the more people will listen when you do speak. It puts extra weight on your message. Listening means analysis and learning.

Seven) Pick the right opportunity at the right time. Pick the right vehicle. Do the right things in the right order! The advice "don't do what someone says, do what they do" is bullshit, as you can't do what someone is able to do after ten years of experience.

Eight) Discipline > Motivation. Motivation, like Dr. Sung says, fluctuates and is multifactorial dependent... When you are lead by motivation you will not be as productive. Don't rely on chance. Rely on what is stable.

Nine) Once a good career has been made, buy A1 assets and hold on to them to secure a financially successful future.

Ten) Just because you won, you are not a winner. Being a winner is a continuous process, it means always learning and reflecting as well as introspecting. Don't overvalue individual wins but do celebrate them when appropriate.

Eleven) Build good relationships with the banks early on. At times you need loans to fund certain ventures, when having a good relation with them, this will be significantly easier. Understand finance as early as possible. Read finance books.

Twelve) Keep the circle small. Acquintances can be many, but real close relationships should be kept small. Choose your friends wisely. "You become the average of the five people you spend most time with." Privacy is important. Only tell the most deep secrets to the Inner Circle, to avoid overcomplication.

Thirteen) Assume that everything is your fault. Responsibility. It leads to learning. It requires reflection and introspection. It leads to Dr. Benjamin Hardy's statement: "Nothing happens to you, everything happens for you."

Fourteen) Work like new money, but act like your old money. Combine the hunger of the new with the wisdom of the old.

Fifteen) Assume that you can't change the world, but slightly influence it. It prevents disappointments and gives a right mindset. Do everything (that has your ambition) with an insane drive. Aim to hit the stars. To become the best of the best.

Sixteen) Private victories lead to public victories. The solid maxim is the following: "The bigger the public victory, the more private victories went into it." Work in private. Social media doesn't need to known the struggle. Let your results talk for you. This is also why you should never compare yourself to others, but rather to your own past self.

Seventeen) After extreme experience, the most complicated task will look elegant and effortless. Unconscious competence.

Reviewer #1 (Public Review):

The present study combines quantitative histomorphometry, live cell imaging and tracking, functional analyses, and computational modeling to define potentially pathologic interactions between lung CD8 T cells and fibrocytes in human COPD. The authors use multiple technical approaches to establish the close proximity of CD8 T cells with fibrocytes in peri-bronchial tissue in COPD subjects that notably correlate with functional disease parameters (FEV1/FEV). Their follow-on studies identify specific chemokine pathways and inflammatory consequences of these interactions. Collectively, these seminal data acquired in a unified experimental context, provide support for pathogenic interactions between lung CD8 T cells and fibrocytes and now offer the consideration of mediators and pathways that may be amenable to therapeutic targeting. The strength of the study is the integration of the multi-modality approach, the quality of the quantitative data, and the creation of a tenable model for the interaction role in COPD of CD8 T cells and fibrocytes. While both have been previously implicated in COPD, this new study is more definitive by using this integrated approach.

Reviewer #1 (Public Review):

The cerebral cortex, or surface of the brain, is where humans do most of their conscious thinking. In humans, the grooves (sulci) and bumps (convolutions) have a particular pattern in a region of the frontal lobe called Broca's area, which is important for language. Specialists study features imprinted on the internal surfaces of braincases in early hominins by casting their interiors, which produces so-called endocasts. A major question about hominin brain evolution concerns when, where, and in which fossils a humanlike Broca's area first emerged, the answer to which may have implications for the emergence of language. The researchers used advanced imaging technology to study the endocast of a hominin (KNM-ER 3732) that lived about 1.9 million years ago (Ma) in Kenya to test a recently published hypothesis that Broca's remained primitive (apelike) prior to around 1.5 Ma. The results are consistent with the hypothesis and raise new questions about whether endocasts can be used to identify the genus and/or species of fossils.

Reviewer #1 (Public Review):

Recent works have documented the observation that transcription factors (TFs) and other transcriptional machinery proteins, e.g., Pol2 and mediator, can form high-concentration clusters at target genes within the nucleus and such behavior plays an important role in transcriptional activation. It is also well-established that the intrinsically disordered regions (IDRs) within many of the transcriptional regulators can undergo multivalent protein-protein interactions, which can lead to phase separation under certain conditions. It is thus thought that the IDRs are essential drivers of the clustering behaviors of transcriptional regulators. However, direct proof of this hypothesis remains missing. To fill this gap, Hannon and Eisen conducted a survey of the subnuclear localization of 75 IDRs derived from Drosophila TFs. They found that many full-length TFs but not IDRs alone form subnuclear clusters. They also did not detect a change in the clustering of TFs after deleting IDRs. Based on these data, they concluded that IDRs are unlikely to be the primary molecular drivers of the clustering phenomenon observed during transcription.

This study tackles an interesting question related to transcriptional regulation and IDR behaviors. The subnuclear distribution of many Drosophila TFs and TF IDRs measured in this work provides a valuable resource for future studies of these TFs and IDRs. The authors' finding that the distribution of an IDR alone is distinct from a full-length TF containing the IDR is new and informative though not surprising. Protein-chromatin binding is known to be stoichiometric with a clear structural basis, which is likely stronger than IDR-IDR interactions that are known to be weaker and more transient. Thus, adding a chromatin-binding capability to an IDR of interest indeed likely significantly affects the distribution of the IDR. Despite being a natural hypothesis based on existing knowledge, it was not previously verified until this current work that systematically compared TF and TF IDR distributions. However, the authors' other conclusion that deleting the IDR from a TF does not affect the TF's clustering behavior is not fully supported. This is because the change of TF's clustering behavior due to IDR deletion, if any, is likely quantitative (decreasing) instead of qualitative (completely disappearing), due to the fact that protein-chromatin binding is stronger than IDR-IDR interactions. This work lacks quantitative characterization of TF clusters before and after IDR deletion. The spinning disk confocal microscopy used here likely does not provide the necessary spatial resolution to quantitatively characterize TF clusters, which often have dimensions near or below the diffraction limit of light.

Reviewer #1 (Public Review):

The expression and localization of Foxc2 strongly suggest that its role is mainly confined to As undifferentiated spermatogonia (uSPGs). Lineage tracing demonstrated that all germ cells were derived from the FOXC2+ uSPGs. Specific ablation of the FOXC2+ uSPGs led to the depletion of all uSPG populations. Full spermatogenesis can be achieved through the transplantation of Foxc2+ uSPGs. Male germ cell-specific ablation of Foxc2 caused Sertoli-only testes in mice. CUT&Tag sequencing revealed that FOXC2 regulates the factors that inhibit the mitotic cell cycle, consistent with its potential role in maintaining a quiescent state in As spermatogonia. These data made the authors conclude that the FOXC2+ uSPG may be the true SSCs, essential for maintaining spermatogenesis. The conclusion is supported by the data presented.

Joint Public Review:

The study has main limitations which need to be addressed and there is lack of functional explanation of carriage. These limitations are: a) the lack of inclusion of non-Black patients; and b) the lack of appropriate explanation if results are false-positive since APOL1 provides risk for chronic renal disease (CRD) and patients with CRD are predisposed to sepsis. Sepsis occurred in 565 Black subjects, of whom 105 (29% ) had APOL1 high-risk genotype and 460 had-low risk genotype. Importantly, the risk for sepsis associated with APOL1 HR variants was no longer significant after adjusting for subjects pre-existing severe renal disease or after excluding these subjects. Thus, the susceptibility pathway seems to be: APOL1 variants > CKD > sepsis diathesis.

Suggestions to the authors:<br /> • The authors need to provide analysis of patients of non-Black origin.<br /> • The Table of demographics needs to include the type of infections and the underlying pathogen.<br /> • The authors need to provide convincing analysis if results are false-positive since APOL1 provides risk for chronic renal disease (CRD) and patients with CRD are predisposed to sepsis. For this purpose, they have to provide evidence if the sepsis causes (both type of infection and implicated pathogens) in patients with CRD who are carriers of APOL1 variants are different than in patients with CRD who are not carriers of APOL1 variants.<br /> • Why concentrations of APOL1 were not measured in the plasma of patients?<br /> • Why analysis towards risk for death is not done?<br /> • The authors need to explain why functional information is not provided.<br /> • n 162-172: too many assumptions have been used for the trial; thus, progression to sepsis is difficult to define. According to Sepsis-3 sepsis is no more a continuum from infection to sepsis and septic shock. Some patients presented with sepsis (-1, 0, 1 days considered by the authors) and when electronic health records are used, we are not able to detect the exact timepoint of SOFA score turning to a 2-point increase. This is a major limitation of the methodology presented.<br /> Same applies for all comorbidities and data extracted from electronic health records.<br /> • P value significance thresholds were set at 0.05, except for the PWAS where the threshold was set at 0.05/5 (p13). It would be helpful to list at this point what the 5 outcomes were that led to this adjusted threshold.<br /> "Risk of sepsis was significantly increased among patients with high-risk genotypes (OR 1.29, 1.0 to 1.67, P1.29, CI 1.00-1.67, P<0.47)." Some would argue that a confidence interval that includes 1.0 indicates non-significance.<br /> • The Discussion is too long and should be shortened.

Reviewer #1 (Public Review):

In this manuscript Budinska and colleagues aim to align morphologically distinct areas of colorectal cancers with the gene expression profiles and published signatures. They observe that distinct morphotypes such as serrated or mucinous align with certain subtypes but that these contradict the bulk subtype assignment. Although these data are of interest they may not be as novel as suggested by the authors and lack clarity in terms of patient selection and subtype definition.

1. Patient selection and tumor area selection are crucial for this study but not very carefully defined. Why are some core and others not? Figure referral is an issue here (sup figure 6 where all core and non-core samples are supposed to be according to the legend of Fig 4 is likely sup fig 7 but this is then a complete copy paste of Figure 4). In the methods it is stated that the core samples are based on limited contamination of additional morphotypes (<20%) but Fig 4 suggests that all tumours listed have multiple morphotypes.

2. CMS subtype should be performed with single sample predictor rather than CMScaller.

3. A couple of surprising observations need specification. MUC2 is a strong CMS3 reporter gene yet Mucinous tumours appear to end up in CMS4 rather than 3. Can the authors show that indeed stroma cells are very evident in these samples?

4. The SE PP and CT are assigned to CMS2, but in Figure 4 this appears a lot more variable than the authors would make the reader believe. The full data are not completely clear (see point 1)

5. The tumor response rates are rather weird as this is likely dependent on the complete tumour and not so much the subareas. It is not very well described what we see in this analysis.

6. Serrated adenomas have previously been aligned with CMS4. Is this different from serrated areas in cancers?

7. The fact that iCMS2 and iCMS3 align rather well with the current analysis of the distinct regions suggests that the analysis that was reported last year is the proper way to view tumor intrinsic signatures. The authors now propose a rather similar outcome to this issue which does take away a lot of the novelty of the findings of this study.

Reviewer #1 (Public Review):

This is an interesting, timely and informative article. The authors used publicly available data (made available by a funding agency) to examine some of the academic characteristics of the individuals recipients of the National Institutes of Health (NIH) k99/R00 award program during the entire history of this funding mechanism (17 years, total ~ 4 billion US dollars (annual investment of ~230 million USD)). The analysis focuses on the pedigree and the NIH funding portfolio of the institutions hosting the k99 awardees as postdoctoral researchers and the institutions hiring these individuals. The authors also analyze the data by gender, by whether the R00 portion of the awards eventually gets activated and based on whether the awardees stayed/were hired as faculty at their k99 (postdoctoral) host institution or moved elsewhere. The authors further sought to examine the rates of funding for those in systematically marginalized groups by analyzing the patterns of receiving k99 awards and hiring k99 awardees at historically black colleges and universities.

The goals and analysis are reasonable and the limitations of the data are described adequately. It is worth noting that some of the observed funding and hiring traits are in line with the Matthew effect in science (https://www.science.org/doi/10.1126/science.159.3810.56) and in science funding (https://www.pnas.org/doi/10.1073/pnas.1719557115). Overall, the article is a valuable addition to the research culture literature examining the academic funding and hiring traits in the United States. The findings can provide further insights for the leadership at funding and hiring institutions and science policy makers for individual and large-scale improvements that can benefit the scientific community.

Reviewer #1 (Public Review):

This paper proposes and evaluates a new approach for the registration of human hippocampal anatomy between individuals. Such registration is an essential step in group analysis of hippocampal structure and function, and in most studies to date, volumetric registration of MRI scans has been employed. However, it is known that volumetric deformable registration, due to its formulation as an optimization problem that minimizes the combination of an image similarity term and relatively simple geometric regularization terms, fails to preserve the topology of complex structures. In the cerebral cortex, surface-based registration of inflated cortical surfaces is broadly preferred over volumetric registration, which often causes voxels of different tissue types to be matched (e.g., voxels belonging to a sulcus in one individual mapping onto voxels belonging to a gurys in another). The authors recognize that hippocampal anatomy is similarly complex, and, with proper tools, can benefit from surface-based registration. They propose to first unfold the hippocampus to a two-dimensional rectangle domain using their prior HippUnfold technique, and then to perform deformable registration in this rectangle domain, matching geometric features (curvature, thickness, gyrification) between individuals. This registration approach is evaluated by comparing how well hippocampal subfields traced by experts using cytoarchitectural information align between individuals after registration. The authors indeed show that surface-based registration aligns subfields better than volumetric registration applied to binary segmentations of the hippocampal gray matter.

Overall, I find the methods and results in this paper to be convincing. The authors framed the comparison between surface-based and volumetric registration in a fair way, and the results convincingly show the advantage of surface-based registration. One slight limitation of the current study is that it is uncertain whether the benefits demonstrated here translate to in vivo MRI data for which the authors' HippUnfold algorithm is tailored. The current study utilized the unfolding technique used in HippUnfold on manual segmentations of high-resolution ex vivo MRI and blockface 3D volumes, which are likely closer to anatomical ground truth than automated segmentations of in vivo MRI. However, it is reasonable to assume that given that the volumetric registration to which the proposed approach was compared also used this high-detail data, the advantages of surface-based over volumetric registration would extend to in vivo MRI as well. However, I would encourage the authors to perform future evaluations on datasets with available in vivo and ex vivo MRI from the same individuals.

I would also like to point out the relevance of the 2021 paper "Unfolding the Medial Temporal Lobe Cortex to Characterize Neurodegeneration Due to Alzheimer's Disease Pathology Using Ex vivo Imaging" by Ravikumar et al. (https://link.springer.com/chapter/10.1007/978-3-030-87586-2_1) to the current work. This paper applied an earlier version of the unfolding method in HippUnfold to ex vivo extrahippocampal cortex and performed registration using curvature features in the rectangular unfolded space, also finding slight improvement with surface-based vs. volumetric registration, so its findings support the current paper.

Overall, the paper has the potential to significantly influence future research on hippocampal involvement in cognition and disease. Outside of simple volumetry studies, most hippocampal morphometry studies rely on volumetric deformable registration of some kind, typically applied to whole-brain T1-weighted MRI scans. With HippUnfold available for anyone to use and not requiring manual registration, the paper provides a strong impetus for using this approach in future studies, particularly where one is interested in localizing effects of interest to specific areas of the hippocampus. Additional evaluation of in vivo HippUnfold using in vivo / ex vivo datasets, would make the use of this approach even more appealing.

Reviewer #1 (Public Review):

Mignerot et al. performed a Herculean effort to measure and describe natural variation in C. elegans egg-laying behavior and egg retention. The paper is well written and organized, but almost seems like two papers in one. However, I understand the desire to put these stories together. The authors show wild strains vary in egg retention with some extremes that appear phenotypically similar to species with viviparity (or live birth / internal hatching of offspring). They previously published a rare variant in the gene kcnl-1 that plays a role in egg retention but identify common variants in this study. They classify wild strains based on egg-retention to separate out the extremely different isolates. Egg laying has been extensively studied in the laboratory strain N2, but rarely addressed in natural strains. The authors investigate egg-laying behaviors using standard assays and find that their classified egg-laying groups have differences in sub-behaviors suggesting diverse roles in the ultimate egg-laying output. Then, they turn to the egg-laying circuit using both exogenous serotonin (5-HT), 5-HT modulatory drugs (e.g. SSRIs), and even genome editing to test epistasis with the mod-5 5-HT reuptake. The effects of 5-HT modulation and mutants are not predictive based on the basal behaviors and egg-retention phenotypes with the most extreme egg-retention strains differing in their responses. Interestingly, strains with more egg retention have decreased fitness (in their laboratory) measures but also provide a protective environment for offspring when exposed to common "natural" stressors. Their final conclusion that egg retention could be a trade-off between antagonistic effects of maternal vs. offspring fitness is supported well and sets the stage for future mechanistic studies across Caenorhabditis.

Joint Public Review:

It has been shown previously that maternal aging in mice is associated with an increase in accumulation of damaged mitochondria and activation of parkin-mediated autophagy (see DOI: 10.1080/15548627.2021.1946739). It has also been shown that C-natriuretic peptide (CNP) regulates oocyte meiotic arrest and that its use during in vitro oocyte maturation can improve parameters associated with decreased oocyte quality. Here the authors tested whether use of CNP treatment in vivo could improve oocyte quality and fertility of aged mice, for which they provided convincing evidence. They also attempted to determine how CNP improves oocyte developmental competence. They showed a correlation between CNP use in vivo and the appearance (and some functional qualities) of cytoplasmic organelles more closely approximating those of oocytes from young mice. However, this correlation could not be interpreted to imply causation. Additional experiments performed using CNP during in vitro maturation were not properly controlled and so are not possible to interpret.

A strength of the manuscript is that the authors use an in vivo treatment to improve oocyte quality rather than just using CNP during oocyte maturation in vitro as has been done previously. This strategy provides more potential for improving oocyte quality - over the course of oocyte growth and maturation - rather than just the final few hours of maturation alone. This strategy also has the potential to be translated into a more generally useful clinical therapeutic method that using CNP during in vitro maturation. However, it is difficult to glean information regarding how CNP might have its effects in vivo. A range of models are used in the manuscript with a mix of in vivo studies with in vitro experiments, which results in some disconnect between systemic CNP and its reported intrafollicular action as well as in the short-term versus longer-term actions of CNP on oocyte quality. Specifically, CNP was shown to be reduced in the plasma of aged mice, but this was not shown in the granulosa cells, which are the reported source of CNP that acts on oocytes. Whether the ovarian source of CNP is reduced in aged females was not demonstrated, and CNP is not known to act on oocytes through an endocrine effect. In vivo treatments with CNP by i.p. injection were performed, but the dose (120 ug/kg) and time (14 days) of treatment were not validated by any prior experiments to give them physiological relevance.

Weaknesses:

1. There are errors in the manuscript writing that make the Results difficult to follow. Reference to the Figures in the Results section does not match what is shown in the Figure panels. For example, the Results text reports differences in CNP levels in aged and young mice shown in Figure 1C, but the relevant panel is actually shown in Figure 1F. Other Figures have the same problem.<br /> 2. The Results section is not always clear regarding what CNP treatment was done - in vivo injections or in vitro maturation. For example, what is the difference, if any, between Figures 2C-D and Figures S2A-B?<br /> 3. Immature oocytes from aged females (~1 year) were treated with a two-step culture system with a pre-IVM step with CNP. Controls included oocytes from young (6-8 weeks) females or oocytes from aged females treated by conventional IVM. The description of these methods suggests that control oocytes did not receive an equivalent pre-IVM culture, hence the relevance of comparisons of CNP-treated versus control oocyte is questionable. It was observed that aged oocytes pre-cultured in CNP improved polar body extrusion rates and meiotic spindle morphology compared to oocytes in conventional IVM, as has been well established. The description of statistical methods does not make clear whether the PBE rate in CNP-treated old oocytes remained significantly lower than young controls.<br /> 4. The main effect of the CNP 2-week treatment appears to be increasing the number of follicles that grow into secondary and antral stages, but there is no attempt made to discover the mechanism by which this occurs and therefore to understand why there might be an increase in the number of ovulated eggs, quality of the eggs, and litter size. It is also not clear how an intraperitoneal injection can guarantee its effectiveness because the half-life of CNP is very short, only a few minutes.<br /> 5. Meiotic spindle morphology, as well as a number of putative markers of cytoplasmic maturation are also suggested to be improved after pre-culture with CNP. In each case a subjective interpretation of "normal" morphology of these markers is derived from observations of the young controls and the proportions of oocytes with normal or abnormal appearance is evaluated. However, parameters that define abnormal patterns of these markers appear to be subjective judgements, and whether these morphological patterns can be mechanistically attributed to the differences in developmental potential cannot be concluded.<br /> 6. In addition to the localization patterns of mitochondria, the mitochondrial membrane potential, oocyte ATP content and ROS levels were assessed through more objective quantitative methods. These are well known to be defective in oocytes of aged females and CNP treatment improved these measures. Mitochondrial dysfunction is the most obvious link between oocyte apoptosis, autophagy, cytoplasmic organelle miss-localization and aberrant spindle morphology. Among the most intriguing results is the finding that CNP mediated a cAMP-dependent protein kinase (PKA) dependent reduction in mitochondrial autophagy mediators PINK and Parkin and reduced the recruitment of Parkin to mitochondria in oocytes. However, it may not be possible to directly link this observation to the improvements in IVM oocyte quality, since PINK/Parkin assessments were performed in oocytes from cultured follicles treated with CNP for 6 days.<br /> 7. The gold standard assay for oocyte quality is embryo transfer and live birth. The authors assessed the impact of maturing oocytes in vitro in the presence of CNP on oocyte quality by less robust assays (e.g., preimplantation embryo development in vitro), so the impact on oocyte quality is less certain.<br /> 8. The terminology used to describe many of the Results exaggerates the findings. For example, the authors claim that many of their immunofluorescent markers of the various organelles have a pattern that is "restored" by CNP. However, in most cases the pattern is "improved" toward the control condition but is not fully restored.<br /> 9. The numbers of embryos should have been corrected for the number of eggs fertilized as a starting point so that the percentage that developed to each stage could be expressed as a percentage of successfully fertilized eggs rather than overall percentages. As currently shown in the Figures and described in the Legend, there is no information regarding what the percentage on the y-axis means. For example, does Figure 4B show the number of 2C embryos divided by the number of eggs inseminated? Or is it divided by the number of successfully fertilized eggs, and if so, how was that assessed?<br /> 10. When fewer eggs are fertilized, the numbers of embryos per group are lower and so the impact of culturing multiple embryos together is lost. As a result, it is possible that culture conditions rather than oocyte quality drove the differences in the numbers of embryos that achieved each stage of development.<br /> 11. Not all claims in the Discussion are supported by the evidence provided. For example, "In addition, the findings demonstrated that CNP improved cytoplasmic maturation events by maintaining normal CG, ER and Golgi apparatus distribution and function in aged oocytes" but it was never demonstrated that the altered distribution had any functional impact.<br /> 12. Incompleteness and errors in the Methods section reduce confidence in many of the results reported.<br /> 13. The methods used for Statistical Analysis are never explained in either the Methods or the Figure legends. It is unclear whether appropriate analyses were done, and it is frequently unclear what was the sample size and how many times a particular experiment was repeated. These weaknesses detract from confidence in the data.

Reviewer #1 (Public Review):

In this manuscript, the authors used an unbiased method to identify proteins from porcine oocyte extracts associated with permeabilised boar spermatozoa in vitro. The identification of the proteins is done by mass spectrometry. A previous publication of this lab validated the cell-free extract purification methods as recapitulating early events after sperm entry in the oocyte. This novel method with mammalian gametes has the advantage that it can be done with many spermatozoa at the time and allows the identification of proteins associated with many permeabilised boar spermatozoa at the time. This allowed the authors to establish a list of proteins either enriched or depleted after incubation with the oocytes extract or even only associated with spermatozoa after incubation for 4h or 24h. The total number of proteins identified in their test is around 200 and with very few present in the sample only when spermatozoa were incubated with the extracts.

The list of proteins identified using this approach and these criteria provide a list of proteins likely associated with spermatozoa remnants after their entry and either removed or recruited for the transformation of spermatozoa-derived structures. Using WB and histochemistry labelling of spermatozoa and early embryos using specific antibodies the authors confirmed the association/dissociation of 6 proteins suspected to be involved in autophagy.

While this unique approach provides a list of potential proteins involved in sperm mitochondria clearance it is (only) a starting point for many future studies and does not provide the demonstration that any of these proteins has indeed a role in the processes leading to sperm mitochondria clearance. The protein identified may also be involved in other processes going on in the oocyte at this time of early development.

Reviewer #1 (Public Review):

The first synapses of the pain pathway are concentrated in the superficial spinal cord dorsal horn. Here peripheral inputs are processed by local interneuron circuitry before ascending to the brain. The spinal dorsal horn is organized into lamina with the resident interneurons differentiated by their anatomy, physiological and molecular properties. Over the past decade, the restricted expression of select genes has been used to assign potential function to dorsal horn neuron "cell types". This type of work has relied on the genesis of Cre-reporter mouse strains and intersectional tools to generate mice where select sets of neurons can be activated, inhibited, or ablated. The picture that has emerged from these types of experiments is murky but favors the model where there exist genetically defined cell-types play distinct roles in the detection of painful, itchy, thermal, and mechanical stimuli under normal and pathological situations. The current work by Boyle and colleagues concerns itself with the dorsal horn neurons expressing the neuropeptide NPY. This study is directly related to previously published work that demonstrated that ablating spinal cord neurons that express Npy, including those who express this gene transiently during development, resulted in mice that had heightened touch-evoked itch that seemed different from the canonical chemical itch pathways previously identified. A major conclusion from this previous work was that other modalities were unaffected. Subsequent work built on these findings to identify the potential touch inputs and spinal neuron expressing the Npy receptor as part of a mechanical itch circuit.

This current work by Boyle and colleagues challenge challenges this view by providing evidence that in adult mice, the dorsal horn neurons expressing Npy function to broadly inhibit pain and itch. The authors use direct injection of viral vectors, chemogenetics and synaptic silencing to probe the behavioral effects of stimulating or silencing Npy-expressing dorsal horn neurons in a variety of assays under normal and pathological conditions known to produce allodynia and hyperalgesia. Overall, this is a rather carefully conducted study with the appropriate controls. The data are clear, the effect sizes robust and the presentation easy to follow. These findings challenge the conclusion that these neurons are involved selectively in mechanical itch and instead reveal a potentially clinically important group of neurons for pain.

Reviewer #1 (Public Review):

The study utilizes a variety of methods, chemical and expressed probes, caged release of IP3, as well as oocytes with mutations that alter zinc availability, that provide an elegant examination of how zinc deficiency and zinc excess modulate the transient and cyclic release of calcium during egg activation. In this manuscript, the authors sought to determine if there is any interplay between zinc and calcium, two divalent cations that have been demonstrated to have important roles during fertilization. They employ agents that disrupt normal zinc homeostasis and then monitor the resulting calcium oscillations during egg activation. If zinc was made unavailable via chelation with TPEN, then the calcium oscillations halted. This occurred regardless of the activation method, which included ICSI, PLC𝛇, Acetylcholine, strontium chloride, and thimerosal. This phenotype could be rescued by introducing zinc back into the egg via an ionophore, such as zinc pyrithione; however, too much zinc pyrithione also halted calcium oscillations. Taken together, these two results demonstrate that there is a threshold level of zinc that is required for proper calcium oscillations to occur.

Furthermore, the authors sought to understand how zinc affects the IP3 receptor, IP3R1. IP3R1 is the receptor that modulates the release of calcium from the endoplasmic reticulum. The authors cited a previous study that identified zinc binding sites on IP3R1. The authors highlight that there exist no studies regarding the regulation of IP3R1 by zinc; however, such studies were cited for a similar calcium channel, the RyRs. The authors use thapsigargin to inhibit the SERCA pump, leading to calcium leak from the IP3R1. TPEN blunted the amount of calcium leaked from the ER following treatment, suggesting that zinc occupancy is necessary for IP3R1 function.

The results of these experiments support the authors conclusions that zinc is essential for the IP3R1-mediated release of calcium in an oscillatory manner during egg activation. These results provide further insight into signals necessary for proper egg activation and the ultimate success of the resulting embryo.

Reviewer #1 (Public Review):

This paper introduces a new transgenic mouse line that allows the labelling of the AIS and nodes of Ranvier (noR) by tagging Ank-G with GFP in a Cre-dependent manner. The authors characterise the properties of the AIS and noR when labelled with GFP to show that it has no adverse effects on the properties of the AIS and noR, as well as the intrinsic excitability of neurons. They also show that this mouse line can be used to follow AIS plasticity in vitro and visualise the AIS of neurons in vivo. This is a very useful and timely tool that will make an important impact in the field.

In general, it is clear that this mouse line can label the AIS and noR and will certainly be a useful tool for the community. Although the authors provide a thorough description of the intrinsic properties of neurons and some of the structural properties of the AIS and noR, there are some aspects of these experiments that could be refined to help show that tagging Ank-G with GFP is mostly inert. In particular, some of the basal properties of the AIS (length, position, molecular distribution) following tagging with GFP are not fully explored.

An important advantage of this mouse line is the ability to follow the AIS in live neurons. This is particularly important for imaging the dynamics and plasticity of the AIS, which the authors show is possible both in vitro and ex vivo. Finally, they also show that it is possible to image the AIS in vivo, a finding that opens many experimental doors for the future.

Reviewer #1 (Public Review):

Genetic, physiological, and environmental manipulations that increase roaming increase leaving rates. The connection between increased roaming and increased leaving is lost when tax4-expressing sensory neurons are inactivated. This study is conceptually important in its characterization of worm behaviors as time-series of discrete states, a promising framework for understanding behavioral decisions as algorithms that govern state transitions. This framework is well-established in other animals, thanks to Berman and others, but relatively new to worms.

A key discovery is that lawn leaving behavior is probabilistically favored in states of behavioral arousal. I like the use of response-triggered averages (triggered on leaving events) that illustrate a "state-dependent receptive field" of the behavioral response. Response-triggered averages are common in sensory neuroscience, used, for example, to characterize the diverse "stimulus-dependent receptive fields" of different retinal ganglion cell types. It's nice to adapt the idea to illustrate the state-dependence of behavioral state transitions.

The simplest metric of arousal state is crawling speed. When animals crawl faster, they are more likely to leave lawns. A more sophisticated metric of behavioral context is whether the animal is in a "roaming" or "dwelling" state, two-state HMM modeling from previous work (Flavell et al., 2013). Roaming animals are more likely to leave lawns than dwelling animals. Different autoregressive HMM tools can segment worm behavior into 4-states. Also with ARHMMs, the most aroused state is again the state that promotes lawn-leaving.

(With the AR-HMM, I have a small quibble in its characterization as "orthogonal" to the 2-state HMM. Orthogonal has a precise mathematical meaning, but here orthogonal is taken loosely to only mean "very different". I'd prefer the authors just call them "very different" and not use mathematical terms so loosely.)

HMM analysis seems to disentangle effects that were lumped by the simpler metric of overall speed. Crawling speed before lawn leaving events, when analyzed only within roaming periods, is only higher for ¡1 min before the event. I presume that the higher speed that is observed for several minutes before lawn leaving when all states are taken into account (e.g., Fig 1J, Fig 2A, and others) reflects the tendency to be in the faster roaming state than the slower dwelling state for several minutes before lawn leaving? If this is correct, it would be nice for the authors to be explicit about this interpretation, to help the reader understand what is going on.

My principal worry is about the possible artifact if worms are more likely to be at lawn boundaries when moving quickly or in an arousal state (roaming in the 2-state HMM or in state 3 in the AR-HMM)? Lawn-leaving events only occur when the animal is at lawn boundaries. If animals are more likely to be at lawn boundaries when aroused, this should artificially increase the likelihood that these states precede lawn-leaving behaviors for a trivial environment-dependent reason instead of their interesting internal state-dependent reason. The authors might consider trying to disentangle the state-dependent statistics of lawn edge proximity when assessing by how much arousal states precede lawn-leaving events. I realize this is could be a formidable analytical challenge.

One recourse is to align speed, HMM, and AR-HMM states to the other behavioral events that only happen at lawn boundaries. When they do this for head poke-reversals in Figure 2-supplement 3, they also observe an (albeit modest) increase in arousal states before head poke-reversals. It should be easy to also compare what happens with head poke-forward and head poke-pause to better understand potential artifacts in quantifying edge-associated events. In any case, this concern and their strategies to address it should be discussed for clarity and transparency.

The authors use diverse environmental, genetic, and optogenetic perturbations to regulate the roaming state, thereby regulating the statistics of leaving in the expected manner. One surprise is that feeding inhibition evokes roaming and lawn-leaving in both pdfr-1 and tph-1 mutants, even though the tph-1-expressing NSM neurons have been shown to sense bacterial ingestion and food availability. I'm curious, is there anything in these new results that is inconsistent with previous claims by Rhoades et al., 2019, or did Rhoades et al. simply not do these tests?

Another surprise is that evoking roaming does not evoke leaving in tax-4 mutants (which is something of an internal control that argues against the worry that roaming artificially increases the likelihood of leaving, see above). Without sensory neuron activity, worms are only more likely to roam for a minute before leaving rather than roaming for several minutes before leaving like wild-type (Figure 6C). ASJ seems to be the most important sensory neuron in this coupling between roaming and leaving (which is uncoupled when sensory neurons are inactivated).

I'm a little puzzled why the wild-type animals shown in Figure 6C show elevated roaming for several minutes before leaving events, whereas the wild-type animals shown in Figures 4I,J,K show elevated roaming for only about a minute, not much different than tax-4 mutants. Am I missing something? What is different about these different wild-type animals?

Reviewer #1 (Public Review):

The authors demonstrate that reactivation of mild vs strong aversive contextual associations produces dissociable effects on fos expression across a wide network of relevant brain regions. Mild, 2-shock memory recruits a 'small-world' network in which amygdalar regions are functionally connected to other regions that modulate their activity and behavioral output, whereas strong, 10-shock memory isolates amygdalar nuclei from the rest of the network. These different patterns of correlated neural activity correspond with functional/behavioral differences - the authors confirm that weak, 2-shock memory is more effectively extinguished and is susceptible to reconsolidation relative to strong, 10-shock memory.

One major drawback of the manuscript is the fact that the data were collected from male subjects only. One might expect similar behavioral outcomes from male and female rats receiving 2-shock and 10-shock training. However, increasing attention to sex as a biological variable has revealed an interesting truth, namely that males and females can engage distinct neural pathways to arrive at the same behavioral destination. It should not be taken for granted that retrieval of aversive contextual associations would reproduce the same networks in females, and, as such, the manuscript does not give a complete accounting of the phenomenon under study.

The aversive associative memories described by the authors are characterized as mild or strong. More analysis of the meaning of memory strength, and its relationship to conditioning parameters, is needed. In particular, the authors should discuss issues such as amount of training, US magnitude, and rate of shock delivery. If amount of training is important, would 2 vs 10 presentations of a milder shock produce the same networks at retrieval? Would a larger shock require fewer presentations to isolate amygdalar regions from the rest of the network? If the shocks were presented at the same rate during training, would you get the same result in both groups? More data examining these questions would be ideal, but, in the absence of that, a discussion of these issues is needed and missing from the manuscript in its current form.

Reviewer #1 (Public Review):

The present study provides a phylogenetic analysis of the size prefrontal areas in primates, aiming to investigate whether relative size of the rostral prefrontal cortex (frontal pole) and dorsolateral prefrontal cortex volume vary according to known ecological or social variables.

I am very much in favor of the general approach taken in this study. Neuroimaging now allows us to obtain more detailed anatomical data in a much larger range of species than ever before and this study shows the questions that can be asked using these types of data. In general, the study is conducted with care, focusing on anatomical precision in definition of the cortical areas and using appropriate statistical techniques, such as PGLS. That said, there are some points where I feel the authors could have taken their care a bit further and, as a result, inform the community even more about what is in their data.

The introduction sets up the contrast of 'ecological' (mostly foraging) and social variables of a primate's life that can be reflected in the relative size of brain regions. This debate is for a large part a relic of the literature and the authors themselves state in a number of places that perhaps the contrast is a bit artificial. I feel that they could go further in this. Social behavior could easily be a solution to foraging problems, making them variables that are not in competition, but simply different levels of explanation. This point has been made in some of the recent work by Robin Dunbar and Susanne Shultz.

In a similar vein, the hypotheses of relating frontal pole to 'meta-cognition' and dorsolateral PFC to 'working memory' is a dramatic oversimplification of the complexity of cognitive function and does a disservice to the careful approach of the rest of the manuscript. One can also question the predicted relationship between frontal pole meta-cognition and social abilities versus foraging, as Passingham and Wise show in their 2012 book that it is frontal pole size that correlates with learning ability-an argument that they used to relate this part of the brain to foraging abilities. I would strongly suggest the authors refrain from using such descriptive terms. Why not simply use the names of the variables actually showing significant correlations with relative size of the areas?

The major methodological judgements in this paper are of course in the delineation of the frontal pole and dorsolateral prefrontal cortex. As I said above, I appreciate how carefully the authors describe their anatomical procedure, allowing researchers to replicate and extend their work. They are also careful not to relate their regions of interest to precise cytoarchitectonic areas, as such a claim would be impossible to make without more evidence. That said, there is a judgement call made in using the principal sulcus as a boundary defining landmark for FP in monkeys and the superior frontal sulcus in apes. I do not believe that these sulci are homologous. Indeed, the authors themselves go on to argue that dorsolateral prefrontal cortex, where studied using cytoarchitecture, stretches to the fundus of principal sulcus in monkeys, but all the way to the inferior frontal sulcus in apes. That means that using the fundus of PS is not a good landmark. Of course, any definition will attract criticism, so the best solution might be to run the analysis multiple times, using different definitions for the areas, and see how this affects results.

If I understand correctly, the PGLS was run separately for the three brain measure (whole brain, FP, DLPFC). However, given that the measures are so highly correlated, is there an argument for an analysis that allows testing on residuals. In other words, to test effects of relative size of FP and DLPFC over and above brain size?

In the discussion and introduction, the authors discuss how size of the area is a proxy for number of neurons. However, as shown by Herculano-Houzel, this assumption does not hold across species. Across monkeys and apes, for instance, there is a different in how many neurons can be packed per volume of brain. There is even earlier work from Semendeferi showing how frontal pole especially shows distinct neuron-to-volume ratios.

Overall, I think this is a very valuable approach and the study demonstrates what can now be achieved in evolutionary neuroscience. I do believe that they authors can be even more thorough and precise in their measurements and claims.

Reviewer #1 (Public Review):

In this study, the authors have compared object recognition in humans and rats. To this end, they trained rats to touch a target object shown along with a distractor object. The rats were initially trained on a base pair, and then tested on sets of variant pairs where the target or distractor could be transformed through size, position, 3d rotation or lighting variations. In addition, the authors then used a cDNN to find image pairs that would elicit different performance from early vs late layers, and tested rats and humans on these pairs (zero vs high and high vs zero protocols). A similar protocol was used for humans as well to get their performance on the base pair and test pairs. Finally the authors find the correlation between cDNN performance on each layer and rat or human performance across all test protocols. The main finding is that rats show the best match to earlier cDNN layers compared to humans. Based on this the authors conclude that humans and rats show contrasting performance on object recognition.

General comments<br /> Whether rats and humans have similar object representations is an interesting and fundamental question, and I commend the authors for their extensive matched experiments on rats and humans. However, the conclusions must be tempered by the fact that the authors are testing a limited set of object variations derived from just two objects. There are also potentially substantial differences in the tasks given to rats and humans, if I understand the methods and procedures correctly. My concerns are detailed below.

My main concern is that the authors find very low agreement between rats and humans on comparable tasks, but it would be important if they can identify qualitative differences in the performance. For instance, can they say that rats are using low-level visual cues compared to humans. They could compare several low-level visual models (see below) and report how human and rat accuracy compares to each of these models. Since the visual representations of cDNNs are unknown, such a comparison would be useful.

The authors should also discuss the potential reason for the human-rat differences too, and importantly discuss whether these differences are coming from the rather unusual approach of training used in rats (i.e. to identify one item among a single pair of images), or perhaps due to the visual differences in the stimuli used (what were the image sizes used in rats and humans?). Can they address whether rats trained on more generic visual tasks (e.g. same-different, or category matching tasks) would show similar performance as humans?

I also found that a lot of essential information is not conveyed clearly in the manuscript. Perhaps it is there in earlier studies but it is very tedious for a reader to go back to some other studies to understand this one. For instance, the exact number of image pairs used for training and testing for rats and humans was either missing or hard to find out. The task used on rats was also extremely difficult to understand. An image of the experimental setup or a timeline graphic showing the entire trial with screenshots would have helped greatly.

The authors state that the rats received random reward on 80% of the trials, but is that on 80% of the correctly responded trials or on 80% of trials regardless of the correctness of the response? If these are free choice experiments, then the task demands are quite different. This needs to be clarified. Similarly, the authors mention that 1/3 of the trials in a given test block contained the old base pair - are these included in the accuracy calculations?

It would be good for the authors to articulate more clearly the nature of the differences between humans and rats. For instance, rat behaviour was found to be correlated with low-level image properties like brightness, whereas presumably, human behaviour is not. It would be useful if the authors can compare rat behaviour against several possible alternative models, including the dCNN layers in Figure 4. These models could include other rats (giving a reliability estimate), luminance based models, contrast based models, models based on V1 simple cells, etc - these models would elucidate further the nature of the rat performance. A similar analysis could be done for human performance.

The authors were injecting noise with stimuli to cDNN to match its accuracy to rat. However, that noise potentially can interacted with the signal in cDNN and further influence the results. That could generate hidden confound in the results. Can they acknowledge/discuss this possibility?

The authors claimed that discrimination task in rats was more dependent on concavity than component arrangement (figure 1 left panel). But that could be just an artifact due to sampling more values of concavity than component arrangement. In that case these two attributes are not comparable at all. Could the authors address this issue in some way.

Reviewer #1 (Public Review):

The authors were trying to investigate whether viral IBs are involved in antagonizing IFN-I production during EBOV trVLPs infection. They found that IRF3 is hijacked and sequestered into EBOV IBs after viral infection, thereby leading to the spatial isolation of IRF3 with TBK1 and IKKε. In such a progress, the activity of IRF3 is suppressed and downstream IFN-I induction is inhibited. The authors designed many experiments, such as the PLA that examined the colocalization, to support their conclusions. However, necessary negative controls were missed in several assays. More key index is needed to be examined in several assays.

The paper is well organized and most data in this paper could support the conclusions, while there are several issues that need to be further solved.

1) In Figure 2-4, authors should examine the expression of downstream IFNs as well as the phosphorylation and nuclear localization of IRF3 to further prove the suppression of IRF3 activity by infecting with trVLPs.

2) In Figure 5, to better prove the conclusion that EBOV NP and VP35 play an important role in sequestering IRF3 in IBS, authors should add the "NP+VP35+VP30" and "NP+VP35+VP24" groups to reperform the assay.

3) In Figure 6f, the expression of STING should be examined by immunostaining to show the knockdown efficiency in trVLPs-infected cells.

Reviewer #1 (Public Review):

The enteroviruses comprise a medically important genus in the large and diverse picornavirus family, and are known to be released without lysis from infected cells in large vesicles containing numerous RNA genome-containing capsids - a feature allowing for en bloc transmission of multiple viral genomes to newly infected cells that engulf these vesicles. SIRT-1 is an NAD-dependent protein deacetylase that has numerous and wide ranging effects on cellular physiology and homeostasis, and it is known to be engaged in cellular responses to stress and autophagy.

Jassey et al. show that RNAi depletion of SIRT-1 impairs the release of enterovirus D-68 (EV-D68) in EVs recovered from the supernatant fluids of infected cells using a commercial exosome isolation kit. The many functions attributed to SIRT-1 in the literature reflect its capacity to deacetylate various cell proteins engaged in transcription, DNA repair, and regulation of metabolism, apoptosis and autophagy. However, Jassey et al. make the surprising claim that the proviral role of SIRT-1 in promoting enterovirus release is not dependent on its deacetylase activity. Fig. S1C is crucial to this suggestion, as it is said to show that reconstituting expression with a catalytically-inactive mutant can rescue virus release from SIRT-1 depleted cells. However, no information is provided concerning the levels of endogenous and ectopically-expressed SIRT-1 proteins in this experiment, making it very difficult to interpret the results. Is the mutant SIRT-1 protein expressed at a higher level than the non-mutant protein? Is there a 'sponging' effect with these transfections that lessens the siRNA efficiency and reduces knockdown of the endogenous protein? Fig. S1B and Fig. 4C convincingly show that EX527, a small molecule inhibitor of the deacetylase activity of SIRT-1, inhibits extracellular release of the virus. This suggests that the deacetylase activity of SIRT-1 is in fact required for the proviral effect of SIRT-1. This is a fundamentally important question that will require more investigation.

Fig. 6 shows how SIRT-I knockdown impacts the release of enterovirus D68 in EVs recovered from cell culture supernatant using a commercial 'Total Exosome Isolation Kit'. The authors should describe the principle this kit exploits to isolate 'exosomes' (affinity isolation?) and specify which antibodies it involves (anti-phosphatidylserine, anti-CD63, others?) This could impact the outcome of these experiments, and moreover is important to include in the long-term scientific record. The authors are appropriately cautious in describing the vesicles they presume to be isolated by the kit as simply 'extracellular vesicles', since there are multiple types of EVs with very different mechanisms of biogenesis, of which 'exosomes' are but one specific type. It would have been more elegant had the authors shown that SIRT-1 is required for EV-D68 release in detergent-sensitive vesicles with low buoyant density in isopycnic gradients, and to characterize the size and number of viral capsids in these vesicles by electron microscopy.

Fig. 6 shows that SIRT-1 depletion upregulates CD63 expression, but has no apparent impact on the release of CD63-positive 'EVs' from uninfected cells. EV-D68 infection also upregulates CD63 expression in SIRT-1 replete cells, and in this case, increases the release of CD63-positive EVs. The combination of infection and SIRT-1 depletion massively upregulates CD63 expression, but appears to eliminate the enhanced release of CD63-positive EVs resulting from infection alone. These are interesting results, from which the authors infer CD63 is associated with EVs containing EV-D68. But, do we know this? Can a CD63 pulldown immunoprecipitate EV-D68 capsid proteins or viral RNA? CD63 is strongly associated with exosomes released from cells through the multi-vesicular body pathway, which are distinct from the LC3-positive EVs released by secretory autophagy that have previously been associated with enteroviruses. The authors suggest that 'knockdown of SIRT-1 may prevent the exocytosis of CD63-positive EVs", but this is a very broad claim (and not really demonstrated by Fig. 6): it requires a clearer definition of what the authors mean by 'exocytosis' and a much more detailed analysis of the size and buoyant density of EVs released in a SIRT-1-dependent process.

The authors suggest that almost all EV-D68 released from infected cells is released without cell lysis in EVs. However, they generally show data from only a single time point following infection (5 or 6 hrs post-infection). It would have been interesting to see a more complete temporal analysis, and to know whether a high proportion of virus continues to be released in EVs, or if it is swamped out ultimately by lytic release of nonenveloped virus.

Fig. 1D indicates that a small fraction of SIRT-1 leaks from the nucleus in EV-D68 infected cells. The authors suggest this is due to targeted nuclear export, rather than simply leaky nuclear pores which are well known to exist in enterovirus-infected cells. The authors present similar fluorescent microscopy data showing inhibition of TFEB export in leptomycin-B treated cells in Fig. S2A in support of their claim that this is specific SIRT-1 export, but these data are far from convincing - there is equivalent residual TFEB and SIRT-1 in the cytoplasm of the treated cells. Quantitative immunoblots of cytoplasmic and nuclear cell fractions might prove more compelling.

Finally, the authors should be more specific in describing the viruses they have studied (EV-D68 and PV). It would be preferable to describe these as 'enteroviruses' (including in the title of the manuscript), rather than more broadly as 'picornaviruses'. There is no certainty that the requirement for SIRT-1 in non-lytic release of virus extends to hepatoviruses or other picornaviral genera, for which mechanisms of nonlytic release may be quite different.

Reviewer #1 (Public Review):

Nitta et al, in their manuscript titled, "Drosophila model to clarify the pathological significance of OPA1 in autosomal dominant optic atrophy." The novelty of this paper lies in its use of human (hOPA1) to try to rescue the phenotype of an OPA1 +/- Drosophilia DOA model (dOPA). The authors then use this model to investigate the differences between dominant-negative and haploinsufficient OPA1 variants. The value of this paper lies in the study of DN/HI variants rather than the establishment of the drosophila model per se as this has existed for some time and does have some significant disadvantages compared to existing models, particularly in the extra-ocular phenotype which is common with some OPA1 variants but not in humans. I judge the findings of this paper to be valuable with regards to significance and solid with regards to the strength of the evidence.

Suggestions for improvements:

1. Stylistically the results section appears to have significant discussion/conclusion/inferences in each section with reference to existing literature. I feel that this information would be better placed in the separate discussion section. E.g. lines 149-154

2. I do think further investigation as to why a reduction of mitochondria was noticed in the knockdown. There are conflicting reports on this in the literature. My own experience of this is fairly uniform mitochondrial number in WT vs OPA1 variant lines but with an increased level of mitophagy presumably reflecting a greater turnover. There are a number of ways to quantify mitochondrial load e.g. mtDNA quantification, protein quantification for tom20/hsp60 or equivalent. I feel the reliance on ICC here is not enough to draw conclusions. Furthermore, mitophagy markers could be checked at the same time either at the transcript or protein level. I feel this is important as it helps validate the drosophila model as we already have a lot of experimental data about the number and function of mitochondria in OPA+/- human/mammalian cells.

3. Could the authors comment on the failure of the dOPA1 rescue to return their biomarker, axonal number to control levels. In Figure 4D is there significance between the control and rescue. Presumably so as there is between the mutant and rescue and the difference looks less.

4. The authors have chosen an interesting if complicated missense variant to study, namely the I382M with several studies showing this is insufficient to cause disease in isolation and appears in high frequency on gnomAD but appears to worsen the phenotype when it appears as a compound het. I think this is worth discussing in the context of the results, particularly with regard to the ability for this variant to partially rescue the dOPA1 model as shown in Figure 5.

5. I feel the main limitation of this paper is the reliance on axonal number as a biomarker for OPA1 function and ultimately rescue. I have concerns because a) this is not a well validated biomarker within the context of OPA1 variants b) we have little understanding of how this is affected by over/under expression and c) if it is a threshold effect e.g. once OPA1 levels reach x%. I think this is particularly relevant when the authors are using this model to make conclusions on dominant negativity/HI with the authors proposing that if expression of a hOPA1 transcript does not increase opa1 expression in a dOPA1 KO then this means that the variant is DN. The authors have used other biomarkers in parts of this manuscript e.g. ROS measurement and mito trafficking but I feel this would benefit from something else particularly in the latter experiments demonstrated in figure 5 and 6.

6. Could the authors clarify what exons in Figure 5 are included in their transcript. My understanding is transcript NM_015560.3 contains exon 4,4b but not 5b. According to Song 2007 this transcript produces invariably s-OPA1 as it contains the exon 4b cleavage site. If this is true, this is a critical limitation in this study and in my opinion significantly undermines the likelihood of the proposed explanation of the findings presented in Figure 6. The primarily functional location of OPA1 is at the IMM and l-OPA1 is the primary opa1 isoform probably only that localizes here as the additional AA act as a IMM anchor. Given this is where GTPase likely oligomerizes the expression of s-OPA1 only is unlikely to interact anyway with native protein. I am not aware of any evidence s-OPA1 is involved in oligomerization. Therefore I don't think this method and specifically expression of a hOPA1 transcript which only makes s-OPA1 to be a reliable indicator of dominant negativity/interference with WT protein function. This could be checked by blotting UAS-hOPA1 protein with a OPA1 antibody specific to human OPA1 only and not to dOPA1. There are several available on the market and if the authors see only s-OPA1 then it confirms they are not expressing l-OPA1 with their hOPA1 construct.

Reviewer #1 (Public Review):

Summary:

Favate et al. measure the relative levels of metabolites in 12 Escherichia coli strains isolated from different replicate populations after 50,000 generations of the Lenski long-term laboratory evolution experiment. They use untargeted LC/MS methods that include standards and report both positive and negative ionization mode measurements. They initially use principal component analysis (PCA) to broadly compare how the metabolomes of these strains are similar and different. Then, they describe several instances where the changes in metabolite abundance they see in specific pathways correlate with mutations that lead to changes in the expression of genes that encode enzymes in those pathways.

Strengths:

The statistical analyses and presentation of the high-throughput data are excellent. The most compelling results are communicated in wonderful figures that integrate their measurements of metabolite levels in this study with results from a prior study they conducted looking at changes in gene expression levels in the same bacterial strains. These sections include the ones describing large increases in NAD(P) pools due to mutations in nadR, changes in the levels of arginine and related compounds due to mutations in argR, and changes in metabolites from glycolysis and the TCA cycle related to iclR and arcB.

Weaknesses:

After addressing prior reviews, the main remaining weaknesses of the study are limitations inherent to the metabolomics approach that are noted by the authors. Namely, that it gives a static and incomplete picture of cellular metabolism, lacking any information about flux and missing measurements for many metabolites. Additional biochemical and genetic experiments will be necessary to fully test the hypotheses suggested by the metabolomics data.

Impact and Significance:

While there has been past speculation about the effects of LTEE mutations on metabolism, this study measures changes in the levels of metabolites in related metabolic pathways for the first time. Therefore, it provides useful information about how metabolism evolves, in general, and will also be a useful resource those studying other aspects of the LTEE related to metabolism, such as contingency in the evolution of citrate utilization.

Reviewer #1 (Public Review):

This paper provides new evidence on the relationship between genetic/chromosome divergence and capacity for asexual reproduction (via unreduced, clonal gametes) in hybrid males or females. Whereas previous studies have focussed just on the hybrid combinations that have yielded asexual lineages in nature, the authors take an experimental approach, analysing meiotic processes in F1 hybrids for combinations of species spanning different levels of divergence, whether or not they form asexual lineages in nature. As such, the findings here are a substantial advance towards understanding how new asexual lineages form.

The quality of the work is high, the analyses are sound, and the authors sensibly link their observations to the speciation continuum. I should also add that the cytogenetic work here is just beautiful!

A key finding is that the precondition for asexual reproduction - the formation of unreduced gametes - is not unusual among hybrid females, so that we have to consider other factors to explain the rarity of asexual species - a major unresolved issue in evolutionary biology. This work also highlights a previously overlooked effect of chromosome organisation on speciation.

Joint Public Review:

The flowering plant Capsella bursa-pastoris is an allotetraploid formed from the genomes of Capsella orientalis and Capsella grandiflora. An outstanding question in the evolution of allotetraploids is the relative contribution of immediate consequences of allopolyploidization vs. long-term evolution after the event. The authors address this question by re-synthesizing the allotetraploid in the lab using the two progenitor species, and comparing its phenotypic and gene expression variation to naturally occurring C. bursa-pastoris. They compared five categories of plant: the two progenitors of the allopolyploid, hybrids resynthesized from the progenitors with a whole-genome duplication either before or after the hybridization event, and the naturally occurring allopolyploid. Two lines of evidence were used: phenotypic data from the plants grown in a common environment, and RNAseq data from a subset of the plants.

The phenotypic data indicate that the selfing syndrome of C. bursa-pastoris likely evolved after the initial allopolyploidization event, and that pollen and seed viability recovered following the allopolyploidization event. They find evidence primarily for long-term phenotypic evolution towards a selfing syndrome in C. bursa-pastoris, and a combination of short and long-term changes to gene expression.

The manuscript is thorough and provides lots of new insights into the mechanisms driving evolution in allopolyploids. The work provides an interesting and valuable contribution to the field's understanding of how expression evolves in interaction with hybridization and polyploidy. Particularly in combination with the team's previous study on these lines, this experimental design is effective for separating the contributions of hybridization, WGD, and evolution over time.

>>The results are compelling but would benefit from small clarifications to the methods and statistics to account for possible positional effects in the growth chamber. Using a linear mixed model rather than a simple ANOVA would solve this problem.

>>The RNAseq data are used to explore overall expression patterns (using multi-dimensional scaling), patterns of differential expression (additive, dominant, or transgressive), and homeolog expression bias, and to determine the relative contributions of the original allopolyploidization event and subsequent evolution. Statistical cutoffs were used to categorize gene expression patterns, but the description and categorization of these patterns appears to have been largely qualitative and might be strengthened by including more statistical detail in questions like whether homeologous expression bias did indeed show more variation in resynthesized and evolved allopolyploids.

>>The study includes evidence that homeolog expression bias (overrepresentation of an allele from one species) results in part from homeologous synapsis (uneven inheritance of chromosome segments). These deviations from patterns consistent with 2:2 inheritance of genomic regions are highly variable between individuals in resynthesized allopolyploids but appeared to be mostly consistent within (but not between) populations in natural C. bursa-pastoris. This is intriguing evidence that segregation can be an important source of variation in allopolyploids. However, it was limited by the difficulty of inferring homeologous recombination breakpoints with RNAseq data because of the scale of recombination in wild populations (rather than resynthesized allopolyploids). In the future identifying such breakpoints will be an interesting direction for this and other allopolyploid systems.

>>The study could also valuably explore what kinds of genes experienced what forms of expression evolution. A brief description of GO terms frequently represented in genes which showed strong patterns of expression evolution might be suggestive of which selective pressures led to the changes in expression in the C. bursa-pastoris lineage, and to what extent they related to adaptation to polyploidization (e.g. cell-cycle regulators), compensating for the initial pollen and seed inviability or adapting to selfing (endosperm- or pollen-specific genes), or adaptation to abiotic conditions.

Reviewer #1 (Public Review):

The paper offers some potentially interesting insight into the allosteric communication pathways of the CTFR protein. A mutation to this protein can cause cystic fibrosis and both synthetic and endogenous ligands exert allosteric control of the function of this pivotal enzyme. The current study utilizes Gaussian Network Models (GNMs) of various substrate and mutational states of CFTR to quantify and characterize the role of individual residues in contributing to two main quantities that the authors deem important for allostery: transfer entropy (TE) and cross correlation. I found the TE of the Apo system and the corresponding statistical analysis particularly compelling. I found it difficult, however, to assess the limitations of the chosen model (GNM) and thus the degree of confidence I should have in the results. This mainly stems from a lack of a proposed mechanism by which allostery is achieved in the protein. Proposing a mechanism and presenting logical alternatives in the introduction would greatly benefit this manuscript. It would also allow the authors to place the allosteric mechanism of this protein in the broader context of protein allostery.

Reviewer #1 (Public Review):

Liu et al. investigated the brain functional lateralization in typically developing infants and infants with congenital sensorineural hearing loss (SNHL) to understand how early auditory deprivation disrupts the development of functional network organization using resting-state fNIRS imaging and the graph theory approach. They found that hemispheric asymmetry formed in early life and the initial lack of auditory exposure affected the typical development of functional network asymmetry in infants with hearing loss. Although the infants with hearing loss exhibited a balance between information segregation and integration within two hemispheres, consistent with the typically developing (TD) controls, the development of the leftward hemispheric asymmetry in network efficiency measures was disrupted. At the regional level, infants with hearing loss exhibited aberrant development of hemispheric network asymmetry especially in frontal regions.

Strengths:<br /> The strengths of this study include its focus on a relatively understudied area of research, namely the impact of hearing loss on brain network asymmetry in infants. The study used advanced neuroimaging techniques to examine the development of cerebral asymmetry in infants with hearing loss and compared their results to typically developing controls. The study's findings provide valuable insights into the importance of early auditory exposure for typical brain development. Overall, this study contributes to our understanding of the brain functional network changes underlying hearing loss and has important implications for early intervention and treatment strategies.

Weaknesses:<br /> Although this study does have strengths in principle, the weaknesses of this work are that the key claims cannot be fully supported due to inappropriate statistical analyses, the theoretical significance and the narrative logic are not well presented. In particular:

Theoretical significance: In the Introduction, the authors did not nicely explain why it is important to investigate how the brain functional network asymmetry develops in SNHL infants, and what new knowledge this analytical approach can tell the readers. It is insufficient to merely state that few studies have focused on this. The authors did not elaborate on the broader significance of studying the hemispherical asymmetry in SNHL infants.

Narrative logic: The organization of the Results part needs substantial improvement. The authors did not provide an overview of the analysis at the beginning of each results section, including the relationships between different measurements, the purpose of each analysis, the specific methods employed, and the meaning of the neural index used. It is therefore very difficult to understand why the authors conducted each analysis and how it contributes to the main narrative of the study. For instance, what is the relationship between the small-world properties within the hemisphere and the hemispherical asymmetry of network efficiency? What is the relationship between global/local efficiency and regional nodal efficiency? What global efficiency and local efficiency reflect? It is crucial to clarify and justify the analysis.

Problems on the statistics:<br /> 1) To support the major claim that the left hemisphere dominance of the functional network organization was significantly disrupted in SNHL infants, the authors should also report a statistically significant interaction (between leftward hemispheric asymmetry and type of infants), but instead they only reported that one effect (the leftward hemispheric asymmetry in the TD infants) was statistically significant, whereas the other effect (the leftward hemispheric asymmetry in the infants with SNHL) was not. And why not directly use asymmetry index and compare it between groups?<br /> 2) The necessary statistical values to support the conclusions are missing in several places. For example, Lines 111 - 113 and section 2.4.<br /> 3) The authors conducted multiple comparisons without correction in section 2.3 and section 2.5. It is likely that some of these comparisons would not survive the multiple comparison correction; therefore, the results need to be rephrased and the findings reinterpreted accordingly.<br /> 4) Inconsistent results exist. If "a significant group × age interaction effect on the mean AI of nodal efficiency was observed only in the frontal cortex, while other regions did not exhibit such an interaction" (Line 170-172), and the authors "investigated the group × age interaction effect on the mean nodal efficiencies of the frontal regions for each hemisphere" (Line 178-179), why "a significant interaction effect was observed in the frontal, temporal, parietal, and occipital regions of the left hemisphere" (Line 179-182)?

Reviewer #1 (Public Review):

Olszyński and colleagues present data showing variability from canonical "aversive calls", typically described as long 22 kHz calls rodents emit in aversive situations. Similarly long but higher-frequency (44 kHz) calls are presented as a distinct call type, including analyses both of their acoustic properties and animals' responses to hearing playback of these calls. While this work adds an intriguing and important reminder, namely that animal behavior is often more variable and complex than perhaps we would like it to be, there is some caution warranted in the interpretation of these data. The authors also do not provide adequate justification for the use of solely male rodents. With several reported sex differences in rat vocal behaviors this means caution should be exercised when generalizing from these findings.

Firstly, the authors argue that the shift to higher-frequency aversive calls is due to an increase in arousal (caused by the animals having received multiple aversive foot shocks towards the end of the protocols). However, it cannot be ruled out that this shift would be due to factors such as the passage of time and increase in fatigue of the animals as they make vocalizations (and other responses) for extended periods of time. In fact the gradual frequency increase reported for 22kHz calls and the drop in 44 kHz calls the next day in testing is in line with this.

Secondly, regarding the analysis where calls were sorted using DBSCAN based on peak frequency and duration, it is not surprising that the calls cluster based on frequency and duration, i.e. the features that are used to define the 44 kHz calls in the first place. Thus presenting this clustering as evidence of them being truly distinct call types comes across as a circular argument. The sparsity of calls in the 30-40 kHz range (shown in the individual animal panels in Figure 2C) could in theory be explained by some bioacoustics properties of rat vocal cords, without necessarily the calls below and above that range being ethologically distinct.

The behavioral response to call playback is intriguing, although again more in line with the hypothesis that these are not a distinct type of call but merely represent expected variation in vocalization parameters. Across the board animals respond rather similarly to hearing 22 kHz calls as they do to hearing 44 kHz calls, with occasional shifts of 44 kHz call responses to an intermediate between appetitive and aversive calls. This does raise interesting questions about how, ethologically, animals may interpret such variation and integrate this interpretation in their responses. However, the categorical approach employed here does not address these questions fully.

In sum, rather than describing the 44kHz long calls as a new call type, it may be more accurate to say that sometimes aversive calls can occur at frequencies above 22 kHz. Individual and situational variability in vocalization parameters seems to be expected, much more so than all members of a species strictly adhering to extremely non-variable behavioral outputs.

Reviewer #1 (Public Review):

The authors have studied the effect of temperature on the interspecific interaction strength of coastal marine fish communities, using eDNA samples. Their introduction describes the state of the art concerning the dynamics of interspecific interactions in ecological communities. This introduction is well written and highly information dense, summarizing all that the reader needs to know to further understand their study setup and execution.

The authors hypothesize that water temperature changes could have an effect on the interspecific interaction strength between marine fishes, and they studied this with a two year long, bi-weekly eDNA sampling campaign at 11 study sites in Japan with different temperature gradients. These 550 water samples were analysed for fish biodiversity through eDNA-metabarcoding using MiFish primers. By using the most abundant fish species as an internal spike in and quantifying the copy numbers from this species by qPCR, the authors were able estimate DNA copy numbers for the total dataset. From the 50 most frequently detected fish species in these samples they showed that temperature affected the interspecific interaction strength between some species. Their work provides a highly relevant approach to perform species-interaction strength analysis based on eDNA biodiversity assessments, and as such provides a research framework to study marine community dynamics by eDNA, which is highly relevant in the study of ecosystem dynamics. The models and analytical methods used are clearly described and made available, enabling application of these methods by anyone interested in applying it to their own site and species group of interest.

Strengths:

The authors have a study setup that is suitable to measure the effects of temperature of the eDNA diversity, and have taken a large number of samples and all appropriate controls to be able to accurately measure and describe these dynamics. The applied internal spike in to enable relative eDNA copy number quantification is convincing.

Weaknesses:

The authors were able to find a correlation between water temperature and interaction strengths observed. However, since water temperature is dependent on many environmental variables that are either directly or indirectly influencing ecosystem dynamics, it is hard to prove a direct correlation between the observed changes in community dynamics and the temperature alone

Reviewer #1 (Public Review):

This study by Cao et al. demonstrates role of Neutrophil in clearing apoptotic hepatocytes by directly burrowing into the apoptotic hepatocytes and ingesting the effete cells from inside without causing inflammation. The authors applied intravital microscopy, Immunostaining and electron microscopy to visualize perforocytosis of neutrophil in hepatocytes. They also found that neutrophil depletion impairs the clearance of apoptotic hepatocytes causing impaired liver function and generation of autoantibodies, implying a role of defective neutrophil- mediated clearance of apoptotic cells in Autoimmune Liver disease. The experiments were well designed and conducted, the results were reasonably interpreted, and the manuscript was clearly written with logical inputs.

Further studies to explore the signals/mechanisms that determine why neutrophil specifically target apoptotic hepatocytes in liver would be of great clinical significance.

Reviewer #1 (Public Review):

Summary:<br /> Codol et al. present a toolbox that allows simulating biomechanically realistic effectors and training Artificial Neural Networks (ANNs) to control them. The paper provides a detailed explanation of how the toolbox is structured and several examples that demonstrate its usefulness.

Main comments:<br /> 1. The paper is well written and easy to follow. The schematics help in understanding how the toolbox works and the examples provide an idea of the results that the user can obtain.

2. As I understand it, the main purpose of the paper should be to facilitate the usage of the toolbox. For this reason, I have missed a more explicit link to the actual code. As I see it, researchers will read this paper to figure out whether they can use MotorNet to simulate their experiments, and how they should proceed if they decide to use it. I'd say the paper provides an answer to the first question and assures that the toolbox is very easy to install and use. Maybe the authors could support this claim by adding "snippets" of code that show the key steps in building an actual example.

3. The results provided in Figures 1, 4, 5 and 6 are useful, because they provide examples of the type of things one can do with the toolbox. I have a few comments that might help improving them:<br /> a. The examples in Figures 1 and 5 seem a bit redundant (same effector, similar task). Maybe the authors could show an example with a different effector or task? (see point 4).<br /> b. I missed a discussion on the relevance of the results shown in Figure 4. The moment arms are barely mentioned outside section 2.3. Are these results new? How can they help with motor control research?<br /> c. The results in Figure 6 are important, since one key asset of ANNs is that they provide access to the activity of the whole population of units that produces a given behavior. For this reason, I think it would be interesting to show the actual "empirical observations" that the results shown in Fig. 6 are replicating, hence allowing a direct comparison between the results obtained for biological and simulated neurons.

4. All examples in the paper use the arm26 plant as effector. Although the authors say that "users can easily declare their own custom-made effector and task objects if desired by subclassing the base Plant and Task class, respectively", this does not sound straightforward. Table 1 does not really clarify how to do it. Maybe an example that shows the actual code (see point 2) that creates a new plant (e.g. the 3-joint arm in Figure 7) would be useful.

5. One potential limitation of the toolbox is that it is based on Tensorflow, when the field of Computational Neuroscience seems to be, or at least that's my impression, transitioning to pyTorch. How easy would it be to translate MotorNet to pyTorch? Maybe the authors could comment on this in the discussion.

6. Supervised learning (SL) is widely used in Systems Neuroscience, especially because it is faster than reinforcement learning (RL). Thus providing the possibility of training the ANNs with SL is an important asset of the toolbox. However, SL is not always ideal, especially when the optimal strategy is not known or when there are different alternative strategies and we want to know which is the one preferred by the subject. For instance, would it be possible to implement a setup in which the ANN has to choose between 2 different paths to reach a target? (e.g. Kaufman et al. 2015 eLife). In such a scenario, RL seems to be a more natural option Would it be easy to extend MotorNet so it allows training with RL? Maybe the authors could comment on this in the discussion.

Impact:<br /> MotorNet aims at simplifying the process of simulating complex experimental setups to rapidly test hypotheses about how the brain produces a specific movement. By providing an end-to-end pipeline to train ANNs on the simulated setup, it can greatly help guide experimenters to decide where to focus their experimental efforts.

Additional context:<br /> Being the main result a toolbox, the paper is complemented by a GitHub repository and a documentation webpage. Both the repository and the webpage are well organized and easy to navigate. The webpage walks the user through the installation of the toolbox and the building of the effectors and the ANNs.

Reviewer #1 (Public Review):

This study explored how expectations influence tactile perception. In summary, anticipating a tactile event enhances detection compared to when knowledge is lacking or ambiguous. However, prior information can also impair performance if the expected and actual stimuli are incongruent. The authors used fMRI and multivariate decoding analyses to investigate the underlying mechanisms of this behavioural phenomenon.

They stimulated two fingers (thumb and ring) of the left hand and analysed activity patterns in contralateral and ipsilateral somatosensory regions during and before stimulation. They were able to distinguish activity patterns for the two fingers during both stimulation and the pre-stimulation stage, specifically for the congruent condition. The authors suggest that congruent vibrotactile stimulation leads to higher multivariate information content and improved behavioural detection performance. They also found that the expectation of vibrotactile stimulation elicits somatotopic activity in contralateral S1, similar to the activity generated by actual stimulation.

I thoroughly enjoyed reading this well-written and clear work. The incorporation of multivariate decoding analysis alongside univariate analysis is a good choice for addressing the claimed questions. In the following sections, I will highlight the strengths and weaknesses of the study. While I generally agree with the authors' conclusions regarding the functional mechanisms underlying behavioural improvements, I believe there are limitations in the experimental design and chosen measures that constrain the interpretations drawn from the results. I hope that my comments can contribute to clarifying certain details and improving aspects of the study that may be considered weak. I believe this study holds significance for the field and provides a foundation for future investigations into the influence of top-down processing on tactile processing.

Strengths:<br /> 1) The research question is highly intriguing as it delves into the unexplored territory of top-down processes within the tactile domain that still needs to be well characterised.

2) The addition of multivariate decoding analysis alongside the univariate analysis was a good choice in my opinion, since activity level per se may not accurately reflect the underlying information content. Both high activity levels and absence of activity (as observed in this study) can still contain information. To be more specific, Figure 2C shows no significant activity in the congruent condition, but significant decoding for the two finger activity patterns is still possible in this condition (Figure 3A).

3) The utilization of a staircase before each functional run was also a good approach, although a potential limitation is noted (discussed below). Considering that prior knowledge can be particularly influential in the presence of weak or noisy stimuli, it is crucial to confirm that the stimulation was at threshold to maximize the likelihood of detecting differences in the pre-stimulus stage.

Weaknesses:<br /> 1) My main concern regarding this study lies in the choice of a detection paradigm, which may introduce response biases and affect the interpretation of results. If the threshold was set too low for some participants, it is possible that they reported feeling the touch more frequently on the cued finger, even when no actual sensation was present. Consequently, accuracy may be inflated for the congruent condition and reduced for the incongruent condition, making it difficult to attribute the observed improvements solely to enhanced detection. I think it would have been more appropriate to use a discriminatory task (e.g., discriminating pin patterns), as employed in Kok et al., 2012, where behavioural performance can be directly linked to decoding accuracy between related activity patterns. Additionally, incorporating trials with no stimulation (I am not sure whether this was the case in this study) and utilizing "None" responses to calculate accuracy could provide a more reliable measure of performance. Using dprime as a performance measure, which is bias-free, may be more appropriate. However, I remain concerned that participant responses are influenced more by the cue than the actual detection of stimuli.

2) While I appreciate the use of the staircase method, I was somewhat surprised by the relatively short length of each staircase (only 7 trials). I might not have extensive experience in this area, therefore this might still be ok for fingers, but I want to emphasize the importance of accurately determining the threshold for this study (as discussed in the previous point). However, I can see from Figure 1B that there seems to be consistency across runs (at least in the shown participant).

3) The absence of significant decoding in the incongruent condition (Figure 3A) raises some questions. It seems reasonable to expect that discrimination between the two finger activity patterns should still be possible in this condition, albeit with reduced accuracy as observed in Kok et al., 2012. Could this lack of significant decoding result from the detection task or possibly due to the smaller number of trials in the incongruent condition?

4) I am a bit confused about which specific region of interest (ROI) was used for both the univariate and decoding analysis during the stimulation stage, and the decoding analysis and RSA during the pre-stimulation phase. From my understanding, the entire S1 region (as defined using the SPM Anatomy toolbox) was included, encompassing not only the hand territory but the entire body. However, I may have misinterpreted the methodology. Given that an independent localizer was used to define ROIs for the univariate analysis during the pre-stimulation phase, it raises the question of why the same approach was not applied to the analyses during the stimulation phase and the multivariate analysis during the pre-stimulation phase.

5) By using a large ROI for analysis (as mentioned in point 4), the straightforward interpretation of BOLD level (i.e., no significant activity) in the congruent condition (Figure 2C) becomes less clear. It raises the question of whether there is truly no activity in the congruent condition or if the activity would be observed with a smaller region. This aligns with the findings of Kok et al., 2012, where they demonstrate activity in both expected and unexpected conditions, albeit reduced in the expected condition.

6) Point 5 raises another issue regarding the suggestion that significant decoding results imply higher multivariate information content in finger representations of congruent vibrotactile stimulations. Suppose a smaller ROI were used, revealing activity in the congruent condition and differential activity between the two finger conditions. In that case, the substantial difference in activation levels suggests that increased decoding accuracy may not necessarily require higher multivariate information content. It is conceivable that discrimination between the two conditions could be achieved with just two voxels-one in the thumb territory and one in the index territory.

Reviewer #1 (Public Review):

The modeling approaches are very sophisticated, and clearly demonstrate the selective nature of acute ketamine to reduce the impact of trial losses on subsequent performance, relative to neutral or gain outcomes. The authors then, not unreasonably, suggest that this effect is important in the context of the negative bias in interpreting events that is prominent in depression, in that if ketamine reduces the ability of negative outcomes to alter behavior, this may be a mechanism for its rapid acting antidepressant effects. However, there is a very strong assumption in this regard, as shown by the first sentence of the discussion which implies this is a systematic study of ketamine's acute antidepressant effects. In actuality, this is a study of the acute effects of ketamine on reinforcement learning (RL) modeled parameters. A primary concern here is that an effect presented as a "robust antidepressant-like behavioral effect" should be more enduring than just an alteration during the acute administration. As it is, the link to an "anti-depressant effect" is based solely on the selective effects on losses. This is not to say this is not an interesting observation, worthy of exploration. It is noted that a similar lack of enduring effects on outcome evaluation is observed in humans, as shown in supplemental fig. S4, but there is not accompanying citation for the human work. One question that comes to mind in terms of the selectivity observed is whether similar work has been done to examine the acute effects of any other drugs. If ketamine is unique in this regard, that would be quite interesting.

Reviewer #1 (Public Review):

In this article, Vardakalis et al. propose a novel model of hippocampal oscillations whereby an external input (emulating the medial septum) can drive theta rhythms. This model displays phase-amplitude coupling of gamma oscillations, as well as theta resetting, which are known features of physiological theta that have been missing in previous models. The end goal proposed by the authors is to have a framework to explore the mechanisms of neurostimulation, which have shown promising applications in pathological conditions, but for which the underlying dynamics remain largely unknown. To reach this objective, the authors implement an existing biophysical model of the hippocampus that is able to generate gamma oscillations, and receives inputs from a set of Kuramoto oscillators to emulate theta drive originating from the medial septum.

Overall, the hypotheses and results are clearly presented and supported by high quality figures. The study is presented in a didactic way, making it easy for a broad audience to understand the significance of the results. The study does present some weaknesses that could easily be addressed by the authors. First, there are some anatomical inaccuracies: line 129 and fig1C, the authors omit medial septum projections to area CA1 (in addition to the entorhinal cortex). Moreover, in addition to CA1, CA3 also provides monosynaptic feedback projections to the medial septum CA3. Finally, an indirect projection from CA1/3 excitatory neurons to the lateral septum, which in turn sends inhibitory projections to the medial septum could be included or mentioned by the authors. This could be of particular relevance to support claims related to effects of neurostimulations, whereby minutious implementation of anatomical data could be key. If not updating their model, the authors could add this point to their limitation section, where they already do a good job of mentioning some limitations of using the EC as a sole oscillatory input to CA1. The authors test conditions of low theta inputs, which they liken to pathological states (line 112). It is not clear what pathology the authors are referring to, especially since a large amount of 'oscillopathies' in the septohippocampal system are associated with decreased gamma/PAC, but not theta oscillations (e.g. Alzheimer's disease conditions). While relevant for the clinical field, there is overall a missed opportunity to explain many experimental accounts with this novel model. Although to this day, clinical use of DBS is mostly restricted to electrical (and thus cell-type agnostic) stimulation, recent studies focusing on mechanisms of neurostimulations have manipulated specific subtypes in the medial septum and observed effects on hippocampal oscillations (e.g. see Muller & Remy, 2017 for review). Focusing stimulations in CA1 is of course relevant for clinical studies but testing mechanistic hypotheses by focusing stimulation on specific cell types could be highly informative. For instance, could the author reproduce recent optogenetic studies (e.g. Bender et al. 2015 for stimulation of fornix fibers; Etter et al., 2019 & Zutshi et al. 2018 for stimulation of septal inhibitory neurons)? Cell specific manipulations should at least be discussed by the authors.

Beyond these weaknesses, this study has a strong utility for researchers wanting to explore hypotheses in the field of neurostimulations. In particular, I see value in such models for exploring more intricate, phase specific effects of continuous, as well as close loop stimulations which are on the rise in systems neuroscience.

Reviewer #1 (Public Review):

It is known that aberrant habit formation is a characteristic of obsessive-compulsive disorder (OCD). Habits can be defined according to the following features (Balleine and Dezfouli, 2019): rapid execution, invariant response topography and action 'chunking'. The extent to which OCD behavior is derived from enhanced habit formation relative to deficits in goal-directed behavior is a topic of debate in the current literature. This study examined habit-learning specifically (cf. deficits in goal-directed behavior) by regularly presenting, via smartphone, sequential learning tasks to patients with OCD and healthy controls. Participants engaged in the tasks every day over the course of a month. Automaticity, including the extent to which individual actions in the sequence become part of a unified 'chunk', was an important outcome variable. Following the 30 days of training, in-laboratory tasks were then administered to examine 1) if performing the learned sequences themselves had become rewarding 2) differences in goal-directed vs. habitual behavior.

Several hypotheses were tested, including:<br /> Patients would have impaired procedural learning vs. healthy volunteers (this was not supported, possibly because there were fewer demands on memory in the task used here)<br /> Once the task had been learned, patients would display automaticity faster (unexpectedly, patients were slower to display automaticity)<br /> Habits would form faster under a continuous (vs. variable) reinforcement schedule

Exploratory analyses were also conducted: an interesting finding was that OCD patients with higher self-reported symptoms voluntarily completed more sessions with the habit-training app and reported a reduction in symptoms.

Strengths

This paper is well situated theoretically within the habit learning/OCD literature.<br /> Daily training in a motor-learning task, delivered via smartphone, was innovative, ecologically valid and more likely to assay habitual behaviors specifically. Daily training is also more similar to studies with non-humans, making a better link with that literature. The use of a sequential-learning task (cf. tasks that require a single response) is also more ecologically valid.<br /> The in-laboratory tests (after the 1 month of training) allowed the researchers to test if the OCD group preferred familiar, but more difficult, sequences over newer, simpler sequences.

Weaknesses

The sample size was relatively small. Some potentially interesting individual differences within the OCD group could have been examined more thoroughly with a bigger sample (e.g., preference for familiar sequences). A larger sample may have allowed the statistical testing of any effects due to medication status.<br /> The authors were not able to test one criterion of habits, namely resistance to devaluation, due to the nature of the task

The authors achieved their aims in that two groups of participants (patients with OCD and controls) engaged with the task over the course of 30 days. The repeated nature of the task meant that 'overtraining' was almost certainly established, and automaticity was demonstrated. This allowed the authors to test their hypotheses about habit learning. The results are supportive of the author's conclusions.

This article is likely to be impactful -- the delivery of a task across 30 days to a patient group is innovative and represents a new approach for the study of habit learning that is superior to an in-laboratory approach.

An interesting aspect of this manuscript is that it prompts a comparison with previous studies of goal-directed/habitual responding in OCD that used devaluation protocols, and which may have had their effects due to deficits in goal-directed behavior and not enhanced habit learning per se.

Reviewer #1 (Public Review):

This manuscript describes a set of four passage-reading experiments which are paired with computational modeling to evaluate how task-optimization might modulate attention during reading. Broadly, participants show faster reading and modulated eye-movement patterns of short passages when given a preview of a question they will be asked. The attention weights of a Transformer-based neural network (BERT and variants) show a statistically reliable fit to these reading patterns above-and-beyond text- and semantic-similarity baseline metrics, as well as a recurrent-network-based baseline. Reading strategies are modulated when questions are not previewed, and when participants are L1 versus L2 readers, and these patterns are also statistically tracked by the same transformer-based network.

I should note that I served as a reviewer on an earlier version of this manuscript at a different venue. I had an overall positive view of the paper at that point, and the same opinion holds here as well.

Strengths:

- Task-optimization is a key notion in current models of reading and the current effort provides a computationally rigorous account of how such task effects might be modeled<br /> - Multiple experiments provide reasonable effort towards generalization across readers and different reading scenarios<br /> - Use of RNN-based baseline, text-based features, and semantic features provides a useful baseline for comparing Transformer-based models like BERT

Weaknesses:

- Generalization across neural network models seems, to me, somewhat limited: The transformer-based models differ from baseline models in numerous ways (model size, training data, scoring algorithm); it is thus not clear what properties of these models necessarily supports their fit to human reading patterns.<br /> - Inferential statistics are based on a series of linear regressions, but these differ markedly in model size (BERT models involve 144 attention-based regressor, while the RNN-based model uses just 1 attention-based regressor). How are improvements in model fit balanced against changes in model size? Also, it was not clear to me how participant-level variance was accounted for in the modeling effort (mixed-effects regression?) These questions may well be easily remedied by more complete reporting.<br /> - Experiment 1 was paired with a relatively comprehensive discussion of how attention weights mapped to reading times, but the same sort of analysis was not reported for Exps 2-4; this seems like a missed opportunity given the broader interest in testing how reading strategies might change across the different parameters of the four experiments.<br /> - Comparison of predictive power of BERT weights to human annotations of text relevance is limited: The annotation task asked participants to chose the 5 "most relevant" words for a given question; if >5 words carried utility in answering a question, this would not be captured by the annotation. It seems to me that the improvement of BERT over human annotations discussed around page 10-11 could well be due to this arbitrary limitation of the annotations.

Reviewer #1 (Public Review):

This manuscript describes extensive transcriptomic and epigenomic profiling for high-grade serous 'ovarian' cancer (HGSC) and its precancerous precursor the fallopian tube secretory epithelium cells (FTSEC). This study identifies MECOM, PAX8, SOX17 and WT1 as master transcription factors that regulate HGSC and FTSEC, as well as the transition from FTSEC to HGSC.

Overall, most the experiments described in the manuscript are well designed and executed. The data presented are of high quality, convincing, and in general support the conclusions made in the manuscript.

Given the complexity of the data and analysis, some clarification is needed to guide readers to better understand the results.

1) The definition of super enhancers should be clarified. In general, super enhancers are defined by large domains of enhancer clusters with high levels of H3K27ac, typically at least 10KB in size. The "super enhancers" presented in Figure 2 do not appear to be large clusters of enhancers.

2) Fig. 4D. Difficult to understand. Multiple bars seem to be represented by the same binding patterns by the four TFs. Need better description in both the text and figure legends.

3) "These data suggest that the antiproliferative effects of THZ1 and THZ531 in HGSC cells may be due to tumor-specific inhibition of MECOM, PAX8 and SOX17 expression by these drugs." Can the author expand the discussion on how CDK7/12 inhibitors could achieve tumor-specific inhibition of MECOM, PAX8 and SOX17?

Reviewer #1 (Public Review):

The authors prepared several Acinetobacter baumannii strains from which an essential protein of known or unknown function can be depleted. They chose to study one of the proteins (AdvA) in more detail. AdvA is a known essential cell division protein that accumulates at cell division sites together with other such proteins. No clear homologs are present in model bacteria such as E.coli, and the precise role(s) of AdvA is still unclear. The authors rename AdvA here as Aeg1. The authors searched for suppressors of lethality caused by AdvA-depletion and recovered an allele of ftsA (E202K) that is capable of doing so. Based on similar superfission alleles previously recovered in other division genes in E.coli, they test several mutant genes and find that certain alleles in ftsB, L and W can also suppress lethality of AdvA-minus cells.

In addition, the authors perform bacterial two-hybrid assays and protein sublocalization studies of AdvA and of other division proteins, but the results of these studies are either not new (confirming previous work) or not convincing.

Reviewer #1 (Public Review):

Bolumar et al. isolated and characterized EV subpopulations, apoptotic bodies (AB), Microvesicles (MV), and Exosomes (EXO), from endometrial fluid through the female menstrual cycle. By performing DNA sequencing, they found the MVs contain more specific DNA sequences than other EVs, and specifically, more mtDNA were encapsulated in MVs. They also found a reduction of mtDNA content in the human endometrium at the receptive and post-receptive period that is associated with an increase in mitophagy activity in the cells, and a higher mtDNA content in the secreted MVs was found at the same time. Last, they demonstrated that the endometrial Ishikawa cell-derived EVs could be taken by the mouse embryos and resulted in altered embryo metabolism.

This is a very interesting study and is the first one demonstrating the direct transmission of maternal mtDNA to embryos through EVs.

Reviewer #1 (Public Review):

Huan Wang et al. analyzed more than 10 million sequences and find that T12I, T102I and A104V were the top 3 frequently occurring mutations. They verified whether these mutations affect the stability and binding ability of NSP10, and whether there are structural changes. They find that three mutations destabilize the NSP10 by NMA prediction and determine their prediction by TSA. In addition, the Kd values shows that variants have similar binding ability or slightly improved affinity to NSP14 and NSP16 than native NSP10. Even though crystallization of the two variants is missing, the comparison of the crystallization of the T102I crystalline protein with the native shows that there is no structural change. Simultaneously, the dihedral angles in the variants do not explore any additional minima than that observed in wild-type NSP10, and there is no major conformational change.

Reviewer #1 (Public Review):

The manuscript by Goetz et al. takes a new perspective on sensory information processing in cells. In contrast to previous studies, which have used population data to build a response distribution and which estimate sensory information at about 1 bit, this work defines sensory information at the single cell level. To do so, the authors take two approaches. First, they estimate single cells' response distributions to various input levels from time-series data directly. Second, they infer these single-cell response distributions from the population data by assuming a biochemical model and extracting the cells' parameters with a maximum-entropy approach. In either case, they find, for two experimental examples, that single-cell sensory information is much higher than 1 bit, and that the reduction to 1 bit at the population level is due to the fact that cells' response functions are so different from each other. Finally, the authors identify examples of measurable cell properties that do or do not correlate with single-cell sensory information.

The work brings an important and distinct new insight to a research direction that generated strong interest about a decade ago: measuring sensory information in cells and understanding why it is so low. The manuscript is clear, the results are compelling, and the conclusions are well supported by the findings. Several contributions should be of interest to the quantitative biology community (e.g., the demonstration that single cells' sensory information is considerably larger than previously implied, and the approach of inferring single-cell data from population data with the help of a model and a maximum-entropy assumption).

Reviewer #1 (Public Review):

This manuscript sets out to implement a multi-stage fluorescence imaging essay to test two working models in understanding the folding states of RNA-binding proteins (RBPs) in stress-induced nuclear bodies. In conjunction with live-cell fluorescence lifetime imaging, the authors revealed and conformed a previously unclear phenomenon that the RBPs investigated in this work initially enter the nuclear bodies in native state in transient stress and then begin to misfold after prolonged stress. Comparing to conventional methods, the imaging strategy reported in this work is unique, comprehensive, and effective in surveying all three-stages (native, soluble oligomer, aggregates) of folding states for RBPs in one shot. Using this strategy, the authors then found that the heat shock protein 70 may protects RBPs from being degraded under stress. The manuscript is very well-written.

Reviewer #1 (Public Review):

In the manuscript titled "GABAergic synaptic scaling is triggered by changes in spiking activity rather than transmitter receptor activation," the authors present an investigation of the role of GABAergic synaptic scaling in the maintenance of spike rates in networks of cultured neurons. Their main findings suggest that GABAergic scaling exhibits features consistent with a key homeostatic mechanism that contributes to the stability of neuronal firing rates. Their data demonstrate that GABAergic scaling is multiplicative and emerges when postsynaptic spike rates are altered. Finally, their data suggest that, in contrast to their prior data on glutamatergic scaling, GABAergic scaling is driven by spike rates. The authors set the paper up as an argument that GABAergic scaling, rather than glutamatergic scaling, serves as the critical homeostatic mechanism for spike rate regulation.

While the paper is ambitious in its rhetorical scope and certainly presents intriguing findings, there are several serious concerns that need to be addressed to substantiate the interpretations of the data. For example, the CTZ data do not support the interpretations and conclusions drawn by the authors. Summarily, the authors argue that GABAergic scaling is measuring spiking (at the time scale of the homeostatic response, which they suggest is a key feature of a homeostat) yet their data in figure 5B show more convincingly that CTZ does not influence spiking levels - only one out of four time points is marginally significant (also, I suspect that the bootstrapping method mentioned in line 454-459 was conducted as a pairwise comparison of distributions. There is no mention of multiple comparisons corrections, and I have to assume that the significance at 3h would disappear with correction). Then, the fact that TTX applied on top of CTZ drives a increase in mIPSC amplitude is interpreted as a conclusive demonstration that GABAergic scaling is sensing spiking. It is inevitable, however, that TTX will also severely reduce AMAP-R activation - a very plausible alternative explanation is that the augmentation of AMPAR activation caused by CTZ is not sufficient to overcome the dramatic impact of TTX. All together, these data do not provide substantial evidence for the conclusion drawn by the authors.

Specific points:

- The logic of the basis for the argument is somewhat flawed: A homeostat does not require a multiplicative mechanism, nor does it even need to be synaptic. Membrane excitability is a locus of homeostatic regulation of firing, for example. In addition, synapse-specific modulation can also be homeostatic. The only requirement of the homeostat is that its deployment subserves the stabilization of a biological parameter (e.g., firing rate).<br /> - Line 63 parenthetically references an important, but contradictory study as a brief "however". Given the tone of the writing, it would be more balanced to give this study at least a full sentence of exposition.<br /> - The authors state (line 11) that expression of a hyperpolarizing conductance did not trigger scaling. More recent work ('Homeostatic synaptic scaling establishes the specificity of an associative memory') does this via expression of DREADDs and finds robust scaling.<br /> - Supplemental figure 1 looks largely linear to me? Out of curiosity, wouldn't you expect the left end to be aberrant because scaling up should theoretically increase the strength of some synapses that would have been previously below threshold for detection? Given that figure 2B also shows warping at the tail ends of similar distributions, how is this to be interpreted?<br /> - The readability of the figures is poor. Some of them have inconsistent boundary boxes, bizarre axes, text that appears skewed as if the figures were quickly thrown together and stretched to fit.<br /> - I'm concerned about the optogenetic restoration of activity experiment. Cortical pyramidal neuron mean firing rates are log normally distributed and span multiple orders of magnitude. The stimulation experiments can only address the total firing at a network-level - given than a network level "mean" is meaningless in a lognormal distribution, how are we to think about the effect of this manipulation when it comes to individual neurons homeostatically stabilizing their own activities? In essence, the argument is made at the single-neuron level, but the experiment is conducted with a network-level resolution.<br /> - Line 198-99: multiplicativity is not a requirement of a homeostatic mechanism.<br /> - Line 264-265 - again, neither multiplicativity and synaptic mechanisms are fundamentally any more necessary for a homeostatic locus than anything else that can modulate firing rate in via negative feedback.<br /> - 277: do you mean AMPAR?<br /> - Example: Figure 1A is frustratingly unreadable. The axes on the raster insets are microscopic, the arrows are strangely large, and it seems unnecessary to fill so much realestate with 4 rasters. Only one is necessary to show the concept of a network burst. The effect of time+CNQX on the frequency of burst is shown in B and C.<br /> - Example: Figure 2 appears warped and hastily assembled. Statistical indications are shown within and outside of bounding boxes. Axes are not aligned. Labels are not aligned. Font sizes are not equal on equivalent axes.<br /> - The discussion should include mention of the limitations and/or constraints of drawing general conclusions from cell culture.<br /> - The discussion should include mention of the role of developmental age in the expression of specific mechanisms. It is highly likely that what is studied at ~P14 is specific to early postnatal development.

It is essential to ensure that the data presented in the paper adequately supports the conclusions drawn. A more cautious approach in interpreting the results may lead to a stronger argument and a more robust understanding of the underlying mechanisms at play.

Public, mais sur une page protégée par WordPress.

Reviewer #1 (Public Review):

The authors sought to address the longstanding question of which cell types are infected during congenital or perinatal rubella virus infection. They used brain slice and organoid-microglia experimental models to demonstrate that the main cell types targeted by rubella virus are microglia. The authors further show that infection results in augmented interferon responses in neighboring neuronal cells but not in the microglia themselves. The data convincingly support the conclusions, with major strengths being the sophisticated primary cell models and single-cell RNA-Seq used to pinpoint microglia as the main cellular targets of rubella virus, and neurons as the bystander targets of immune signaling. This study reveals a new cellular target that will have important implications for basic studies on rubella virus-host interactions and for the potential development of therapies or improved vaccines targeting this virus. As rubella virus is a pathogen of high concern during human pregnancy, this study is also relevant in the field of neonatal infectious diseases.

Joint Public Review:

As nucleoporins can function at intact nuclear pore complexes (NPCs) or outside of NPCs as individual proteins or subcomplexes, it remains challenging to molecularly define the pool of molecules that exert a specific function. To address this challenge, here the authors develop a new method for specifically mapping NPC-associated loci by DamID with a recombinant fusion protein of the Dam methylase and the nuclear transport receptor, importin b (Dam-Impb), in permeabilized cells. The authors demonstrate that Dam-Impb is active, accumulates at the NPC and, using super-resolution microscopy, methylates NPC-adjacent regions; other observations further support the assertion that the approach is specific for NPC-associate chromatin regions. Furthermore, NPC-DamID does not require genetic manipulation and they show that it can be applied to both diverse cell lines as well as tissues. The authors confirm the association of nucleoporins with super-enhancers (SEs) in line with their prior work, now confirmed to occur at NPCs based on this study. Among SEs categorized as hierarchical enhancers (Nat Commun 9, 943 (2018)), hub enhancers are over-represented for methylation by Dam-Impb. The association of such enhancers with cohesin and CTCF suggests these regions could have a critical role in chromatin folding; enhancer-associated factors and marks such as H3K27 acetylation, RNA polymerase II, P300, CTCF and BRD4 also enrich at Dam-Impb methylation peaks. Using proximity ligation, the authors provide further evidence that Tpr, which interacts with the NPC basket, colocalizes with CTCF, BRD4 and P300. Based on these observations, the authors hypothesized that nucleoporin phase separation at SEs might potentiate phase separation of other factors at these elements. Consistent with previous work, over-expression of the intrinsically disordered region (IDR) of Nup153, a component of the NPC basket, forms nuclear droplets that are largely dispersed by 1,6-hexanediol. In this same condition, colocalization RNAPII and both Tpr and BRD4 is reduced, although some interactions between IDRs were not sensitive to this treatment. Last, using a lac operator array as a tethering site, the authors show that tethered Nup153 IDR recruits the carboxy terminal domain of RNAPII and Med1. However, whether the biology of how nucleoporins at NPCs influence SEs depends on biomolecular condensation will require future study.

Overall, the reviewers agree that this is an excellent manuscript that will impact our understanding of nuclear pore complex-genome interactions and how nucleoporins impact super enhancer function. The data are generally of high quality and are reasonably interpreted. There are, however, several important controls or analyses that would strengthen the conclusions of the paper, as outlined below.

1. NPC vs nucleoplasmic interactions: One of the main claims of the paper is that it provides a way to study specifically the NPC-associated loci and contrast them to the nucleoplasmic Nup-associated loci. Unfortunately, the authors do not devote much space to this comparison and many of the manipulations involve proteins that are in both locations (see below). This seems like an important, missed opportunity. The choices of Tpr or Nup153 should be more clearly justified. The Dpn8 staining appeared in regions outside of the nuclear envelope, which is inconsistent with the text. This should be addressed.

2. The PLA experiments: Although Tpr exists both at the NPC and in the nucleoplasm, the authors interpret these experiments as if they are exclusively reporting on proximity of enhancer proteins to the NPC. The images (e.g. Figure 5a, supplementary Figure 5) make it clear that the foci are throughout the nucleus. Where are the antigens recognized by the antibodies to Tpr and what this may mean for the findings? Further, PLA experiments are prone to artefacts and, while the authors have included a knockdown of Tpr as a negative control, additional controls would strengthen their conclusions. For example, what is the result when Tpr colocalization with NPC-specific proteins is assessed? How is that affected by hexanediol? A better PLA experiment might be to assess colocalization of Dam-ImpB or Dpn8 (bound to Dam-ImpB methylated sites) with super enhancer proteins such as Med1, CTCF, Brd4, etc. With regards to the PLA with

3. Analysis of genomic data: The normalization of the DNA sequencing tracks is not sufficiently explained. Moreover, some of the correlations using meta-site plots are not convincing. For example, the peaks of Nup153 or Nup98 methylation over Imp-B peaks are apparently weak. Although the authors report local maxima, these may not be strong associations. This raises the possibility that the stronger Nup153 or Nup98 peaks are not ImpB peaks. A better way to test for this would be to correlate the ImpB peak intensity to the Nup153 or Nup98 peak intensity globally. The expectation is that there will be both correlated peaks that show strong methylation by Nup153/Nup98 and ImpB, as well as peaks that do not (i.e. those in the nucleoplasm). Along these lines, the Dam alone control can be used for comparison. Peaks identified by Dam alone should not be correlated with ImpB, Nup153, Nup98, CTCF, RNAPII, Cohesin, H3K27Ac, Brd4, Mediator, super enhancers, hubs, etc. Also, what is the source of the Nup93 CUT&RUN data? It was unclear if it was from this study or a prior publication.

4. FISH experiments: these should be in the main figures of the paper and better described. How many loci were assessed in each category? Are the differences between the three classes significant? Also, the order of the legend is the opposite of the order of the bar segments, which is confusing to the reader. Related to Figure 2j: What are the FISH probes used here? How many cells were quantified?

5. The focus on IDRs as the primary functional mechanism for the NPC-SE connection was felt to be the least well-justified of the authors' conclusions. In particular, the quantitative effects in Fig. 6 are over-stated while caveats including possible over-expression artifacts and changes in the nuclear concentration of the IDRs due to efflux out of the nucleus in response to 1,6 hexanediol treatment as a consequence of the effect on the barrier of NPCs are not addressed. Additional experimental follow-up - for example does critical depletion of Nup153 (now possible with auxin degrons) disrupt the NPC-DamID profile? - would strengthen the support for the model.

6. Recent evidence points to the fact that 1,6-HD treatment probes the presence of hydrophobic interactions, rather than distinguishing between LLPS and interactions with spatially clustered binding sites (ICBS). These possibilities should be taken into account when interpreting the data, and should be discussed more thoroughly.

Joint Public Review:

This study is concerned with the general question as to how pools of synaptic vesicles are organized in presynaptic terminals to support different types of transmitter release, such as fast synchronous and asynchronous release. To address this issue, the authors employed the classical method of loading synaptic vesicle membranes with FM-styryl dyes and assessing dye destaining during repetitive synapse stimulation by live imaging as a readout of the mobilization of vesicles for fusion. Among other findings, the authors provide evidence indicating that there are multiple reserve vesicle pools, that quickly and slowly mobilized reserves do not mix, and that vesicle fusion does not follow a mono-exponential time course, leading to the notion that two separate reserve pools of vesicles - slowly vs. rapidly mobilizing - feed two distinct releasable pools - reluctantly vs. rapidly releasing. These findings are valuable to the field of synapse biology, where the organization of synaptic vesicle pools that support synaptic transmission in different temporal and stimulation regimes has been a focus of intense experimentation and discussion for more than two decades.

On the other hand, the present study has limitations, so that the authors' key conclusions remain incompletely supported by the data, and alternative interpretations of the data remain possible. The approach of using bulk FM-styryl dye destaining as a readout of precise vesicle arrangements and pools in a population of functionally very diverse synapses bears problems. In essence, the approach is 'blind' to many additional processes and confounding factors that operate in the background, from other forms of release to inter-synaptic vesicle exchange. Further, averaging signals over many - functionally very diverse - synapses makes it difficult to distinguish the dynamics of separate vesicle pools within single synapses from a scenario where different kinetics of release originate from different types of synapses with different release probabilities.