Reviewer #2 (Public Review):

The authors convincingly show that their reconstructed ancestral nitrogenases are active both in vivo and in vitro, and show similar inhibitory effects as extant/wild-type enzymes.

The conclusion that, evolutionarily, there is a "single available mechanism for dinitrogen reduction" is not well explored in the paper. This suggests a limitation of using ancestral sequence reconstruction in this instance.

Reviewer #2 (Public Review):

In this paper, Kliesmete et al. analyze the protein and regulatory evolution of TRNP1, linking it to the evolution of brain size in mammals. We feel that this is very interesting and the conclusions are generally supported, with one concern.

The comparison of dN/dS (omega) values to 125 control proteins is helpful, but an important factor was not controlled. The fraction of a protein in an intrinsically disordered region (IDR) is potentially even more important in affecting dN/dS than the protein length or number of exons. We suggest comparing dN/dS of TRNP1 to another control set, preferably at least ~500 proteins, which have similar % IDR.

Reviewer #2 (Public Review):

Nutrigenomics has advanced in recent years, with studies identifying how the food environment influences gene expression in multiple model organisms. The molecular mechanisms mediating these food-gene interactions are poorly understood. Previous work identified the enzyme O-GlcNAC (OGT) in mediating the decreased sensitivity in sweet-taste cells when exposed to a high-sugar diet. The present study, using fly gustatory neurons as a model, provides mechanistic insight into how nutrigenomic signaling encodes nutritional information into cellular changes. The authors expand previous work by showing that OGT is associated with neural chromatin at introns and transcriptional start sites, and that diet-induced changes in chromatin accessibility were amplified at loci with presence of both OGT and PRC2.1. The work also identifies Mitogen Activated Kinase as a critical mediator in this pathway. This is an elegant group of experiments revealing mechanisms for how nutrigenomic signaling triggers cellular responses to nutrients.

Reviewer #2 (Public Review):

The authors address a very old question: what is the mechanism that controls genetic exchanges (crossovers) between the maternal and paternal chromosomes during sexual reproduction (meiosis). Specifically, what could account for two crucial aspects of the non-random distribution of crossovers: the lower-than-expected rate of non-exchange chromosomes, and the larger-than-expected distance between adjacent crossovers on the same chromosome. Despite the great progress that was made in the last few decades in understanding the molecular details crossover formation, the mechanism accounting for their non-random distribution remains a matter of heated debate. Hence, an ability to provide new insight into this question will be of interest to the wide chromosome biology community.

In this work, the authors combine two important findings/resources. The first is their own modeling of a biophysical framework called 'coarsening'. Coarsening relates to the well-described behavior of liquid compartments, which tend to get larger with time, at the expense of smaller compartments. As the authors note, their coarsening work builds on research by many labs, and on the recent understanding of the role of condensates in cell biology in general, and the liquid nature of the synaptonemal complex - a conserved meiotic chromosomal interface. In their previous paper, the authors found that coarsening could account for multiple cytological aspects of crucial regulators of crossovers - a conserved protein called HEI10. Their modeling was able to recapitulate temporal changes in HEI10 distribution and to account for changes that occur upon changes to HEI10 expression levels (halving of expression and over-expression). The second is the recent analysis of plant strains lacking the synaptonemal complex (zyp1). In that mutant, crossovers do occur (this is different than in some organisms), but the non-random distribution of crossovers is mostly lost: both crossover interference and the paucity of non-exchange chromosomes fit mostly random distribution.

Here, the authors combine these resources and adjust their modeling to account for the lack of the synaptonemal complex. A crucial difference is that instead of diffusing inside the SC (which spans each chromosome pair end-to-end), HEI10 now diffuses in the nucleoplasm. With this modified simulation they mostly account for crossover distribution in zyp1 mutants, using both published and new data they have acquired.

Despite the very limited amount of new data included in this manuscript, the clever combination of these two sources of data manages to add yet another layer of evidence to the idea that coarsening can explain crossover distribution. The main concern regarding the manuscript is that most of the aspects of crossover distribution that the model reproduces are quite trivial - for example, the resulting random distribution of the number of crossovers per chromosome. Some of the non-trivial aspects of the distribution - for example, the telomere enrichment - were built into the simulation as an explicit parameter. The only aspect that would be considered truly non-trivial is the narrower-than-expected number of total crossovers, despite the random distribution of crossovers per chromosome (Fig. 2A). Indeed, the modeling recapitulates this parameter, albeit to a much stronger degree than the in vivo data.

The ability of the model to recreate one non-trivial aspect of the crossover distribution is not sufficient to rule out other possible models, which would be necessary to consider this work a significant advance. However, if the authors are able to provide additional, non-trivial predictions relating to this and to other experimental conditions, this would dramatically elevate their ability to claim that a coarsening-based mechanism is indeed the most plausible one to explain crossover distribution. Some of these conditions could involve experimental perturbation of key parameters in the model: HEI10 levels, the number of DSBs or recombination intermediates (the 'substrate' that ends up resulting in crossovers), the length of time coarsening is allowed to proceed, or the volume of the nucleus.

Reviewer #2 (Public Review):

There is a lot of interest in how cells transfer materials (proteins, RNA, organelles) by extracellular vesicles (EV) and tunneling nanotubes (TNTs). Here, Zhang and Schekman developed quantitative assays, based on two different reporters, to measure EV and direct contact-dependent mediated transfer. The first assay is based on transfer of Cas9, which then edits a luciferase gene, whose enzymatic activity is then measured. The second assay is based on a split-GFP system. The experiments on EV trafficking convincingly show that purified exosomes, or any other diffusible agent, are unable to transfer functional Cas9 (either EV-tethered or untethered) and induce significant luciferase activity in acceptor cells. The authors suggest a plausible model by which Cas9 (with the gRNA?) gets "stuck" in such vesicles and is thus unable to enter the nucleus to edit the gene.

To test alternative pathways of transfer, e.g. by direct cell-cell contact, the authors co-cultured donor and acceptor cells and detect significant luciferase activity. The split GFP assay also showed successful transfer. The authors further characterize this process by biochemical, genetic and imaging approaches. They conclude that a small percentage of cells in the population produce open-ended membrane tubules (which are wider and distinct from TNTs) that can transfer material between cells. This process depends on actin polymerization but not endocytosis or trogocytosis. The process also seems to depend on endogenously expressed Syncytin proteins - fusogens which could be responsible for the membrane fusion leading to the open ends of the tubules.

The paper provides additional solid evidence to what is already known about the inefficiency of EV-mediated protein transport. Importantly, it provides an interesting new mechanism for contact-dependent transport of cellular material and assigns valuable new information about the possible function of Syncytins. However, the evidence that the proteins and vesicles transfer through the tubules is incomplete and a few more experiments are required. In addition, certain inconsistencies within the paper and with previous literature need to be resolved. Finally, some parts of the text, methods and the figures require re-writing or additional information for clarity.

Major comments<br /> 1. In Figure 1F, the authors compare the function of exosome-transported SBP-Cas9-GFP vs. transient transfection of SBP-Cas9-GFP. It is not clear if the cells in the transiently transfected culture also express the myc-str-CD63 and were treated with biotin. It is important to determine if CD63-tethering itself affects Cas9 function.<br /> 2. The authors do not rule out that TNTs are a mode of transfer in any of their experiments. Their actin polymerization inhibition experiments are also in-line with a TNT role in transfer. This possibility is not discussed in the discussion section.<br /> 3. Issues with the Split GFP assay:<br /> a. On page 4, line 176, the authors claim that "A mixture of cells before co-culture should not exhibit a GFP signal". However, this result is not presented.<br /> b. The authors show in Figure 2C and F that in MBA/HEK co-culture or only HEK293T co-culture, there are dual-labeled, CFP-mCherry, cells. First - what is the % of this sub-population? Second, the authors dismiss this population as cell adhesion (Page 5, line 192) - but in the methods section they claim they gated for single particles (page 17, line 642), supposedly excluding such events. There is a simple way to resolve this - sort these dual labeled cells and visualize under the microscope. Finally - why do the authors think that the GFP halves can transfer but not the mature CFP or mCherry?<br /> c. In the Cas9 experiments - the authors detect an increase in Nluc activity similar in order of magnitude that that of transient transfection with the Cas9 plasmid - suggesting most acceptor cells now express Nluc. However, only 6% of the cells are GFP positive in the split-GFP assay. Can the authors explain why the rate is so low in the split-GFP assay? One possibility (related to item #2 above) is that the split-GFP is transferred by TNTs.<br /> 4. The membrane tubules, the membrane fusion and the transfer process are not well characterized:<br /> a. The suggested tubules are distinct from TNTs by diameter and (I presume, based on the images) that they are still attached to the surface - whereas TNTs are detached. However, how are these structures different from filopodia except that they (rarely) fuse?<br /> b. Figure 5E shows that the acceptor cells send out a tubule of its own to meet and fuse. Is this the case in all 8 open-ended tubules that were imaged? Is this structure absent in the closed-ended tubules (e.g. as seen in Figures 6 & 8)?<br /> c. The authors suggest a model for transport of the proteins tethered to vesicles (via CD63 tethering). However, the data is incomplete.<br /> i. They show only a single example of this type of transport, without quantification. How frequent is this event?<br /> ii. Furthermore, the labeling does not conclusively show that these are vesicles and not protein aggregates. Labeling of the vesicle - by dye or protein marker will be useful to determine if these are indeed vesicles, and which type.<br /> iii. The data from Figure 2 suggest (if I understand correctly) transfer of the CD63-tethered half-GFP, further strengthening the idea of vesicular transfer. However, the authors also show efficient transfer of untethered Cas9 protein (Figure 2A and other figures). Does this mean that free protein can diffuse through these tubules? The Cas9 has an NLS so the un-tethered versions should be concentrated in the nucleus of donor cells. How, then, do they transfer? The authors do not provide visual evidence for this and I think it is important they would.<br /> iv. In Figures 6 & 8, where transfer is diminished, there are still red granules in acceptors cells (representing CD63-mcherry). Does this mean that vesicles do transfer, just not those with Cas9-GFP? Is this background of the imaging? The latter case would suggest that the red granule moving from donor to acceptor cells in figure 4 could also be "background". This matter needs to be resolved.<br /> 5. Why do HEK293T do not transfer to HEK293T?<br /> a. A major inexplicable result is that HEK293T express high levels of both Syncytin proteins (Figure 7 - supp figure 1A) yet ectopic expression of mouse Syncytin increases transfer (Figure 7E). Why would that be? In addition, Fig 3A shows high transfer rates to A549 cells - which express the least amount of Syncytin. The authors suggest in the discussion that Syncytin in HEK293T might not be functional without real evidence.<br /> b. In addition - previous publications (e.g. PMID: 35596004; 31735710) show that over expression of syncytin-1 or -2 in HEK293T cells causes massive cell-cell fusion. The authors do not provide images of the cells, to rule out cell-cell fusion in this particular case.

Reviewer #2 (Public Review):

To explore their dataset, the authors first identify all eligible women (n = 4673) in the database queried and use propensity score matching (PSM) to match group A (not infected by HPV) with group B (infected by HPV) for several covariates thought to affect bone mineral density (e.g.: age, smoking, alcohol). After PSM, no significant difference for selected covariates can be detected between the two groups.

Because they add matched their groups for relevant covariates possibly affecting bone mineral density, the authors then use Welch two-sample t-test to compare bone mineral densities of leg and lumbar spine between group A and group B, and detect significantly lower bone mineral densities for participants infected by HPV, group B. Here, the statistical approach chose by the author seems limited, and although PSM had been applied to match group earlier in the analysis pipeline, the reader could expect the statistical approach to be more robust, i.e. accounting for other covariates, like a linear mixed model.

Then, the authors analyse each HPV subtype independently and use Kendall's tau-b correlation test to estimate a correlation between a given HPV subtype and bone mineral density. To apply this test, the authors had to transform the bone mineral density to a binary variable, i.e. greater or equal to 1. Here again, the statistical approach does not control for any of the bone mineral density potentially affecting covariates. Also, the authors' study performed 32 Kendall's tau-b correlation tests and did not seem to correct for multiple testing.

Finally, the authors use the Restricted cubic spline model to establish a non-linear relationship between the number of infected HPV subtypes and bone mineral density.

The authors had set the aim to explore the association between HPV and bone mineral density. Unfortunately, due to possibly not high enough robustness of statistical approaches used in this manuscript, it does not seem sufficient to establish a clear association between HPV infection status and a lower bone mineral density. However, given the database the authors have created, it is believed that they have all the tools needed to pursue their aim.

Reviewer #2 (Public Review):

This study investigates whether frequency tuning in the avian auditory midbrain is changed by the reliability of a key sound localization cue (Interaural Time Differences, ITDs) during development. It tests whether auditory neurons become more sensitive to sound frequencies that provide more reliable information about ITDs.

To manipulate the reliability of ITDs in a frequency-specific way, the authors removed the facial ruff of barn owls during development, which alters the acoustical input available to the animal in a number of important ways. When these animals reached adulthood, electrophysiological recordings were performed in the external nucleus of the inferior colliculus (ICx). Compared to control animals, these recordings revealed a weaker relationship between the best-frequency and best-ITD of individual neurons. A similarly weak relationship was observed in young animals whose ruff had not yet fully developed.

These results arise partly because animals without a facial ruff possess neurons with a best ITD of 0 that are tuned to unusually low frequencies. Having considered a number of possible explanations, the authors argue that this occurs because facial ruff removal reduces the reliability of high-frequency ITDs for frontal locations. Consequently, neurons tuned to frontal locations shift their frequency sensitivity to lower frequencies, which provides more reliable information about ITD. This shift toward lower frequencies is also thought to partly explain changes in tuning width that are observed in the absence of a facial ruff.

The study concludes that these results collectively provide evidence that the brain learns to implement probabilistic coding of sound location during development. However, although the study clearly shows changes in neural tuning in the absence of a fully developed facial ruff, the causal link with ITD reliability is complicated by a number of technical issues. The most important of these include a tendency to ignore the rear hemifield for some analyses but not others, the complex acoustical effects of facial ruff removal, and a model of IPD reliability that may or may not accurately reflect real-world listening. Nevertheless, the study presents an interesting set of results and shows an innovative approach in a number of places.

ACOUSTICS: A key strength of the study is its attempt to quantify the reliability of ITDs, which forms the foundation for the rest of the study. However, it is not entirely clear whether the method used for calculating ITD reliability is the most appropriate, and the way the data are presented raises a number of questions.<br /> 1) Why is IPD variability plotted instead of ITD variability (or indeed spatial reliability)? The relationship between these measures is likely to vary across frequency, which makes it difficult to compare ITD variability across frequency when IPDs are plotted. Normalizing data across frequencies also makes it difficult to compare different locations and acoustical conditions. For example, in Fig.1a and Fig.1b, the data shown for 3 kHz at ~160 degrees seems quantitatively and visually quite different, but the difference (in Fig.1c) appears to be negligible.

2) How well do the measures of ITD reliability used reflect real-world listening? For example, the model used to calculate ITD reliability appears to assume the same (flat) spectral profile for targets and distractors, which are presented simultaneously with the same temporal envelope, and a uniform spatial distribution of sounds across space. It is therefore unclear how robust the study's results are to violations of these assumptions.

3) Does facial ruff removal produce an isolated effect on ITD variability or does it also produce changes in directional gain, and the relationship between spatial cues and sound location? Although the study considers this issue in some places (e.g. Fig.2, Fig.5), a clearer presentation of the acoustical effects of facial ruff removal and their implications (for all locations, not just those to the front), as well as an attempt to understand how these acoustical changes lead to the observed changes in ITD reliability, would greatly strengthen the study. In addition, Fig.1 shows average ITD reliability across owls, but it would be helpful to know how consistent these measures are across owls, given individual variability in Head-Related Transfer Functions (HRTFs). This potentially has implications for the electrophysiological experiments, if the HRTFs of those animals were not measured. One specific question that is potentially very relevant is whether the facial ruff attenuates sounds presented behind the animal and whether it does so in a frequency-dependent way. In addition, if facial ruff removal enables ILDs to be used for azimuth, then ITDs may also become less necessary at higher frequencies, even if their reliability remains unchanged.

ELECTROPHYSIOLOGY: The electrophysiological recordings in young owls are impressive, particularly since they were done longitudinally (although the follow-up data in adults is not shown). The decision to look at the relationship between different tuning properties following different types of developmental experience (e.g. relationship between best ITD and best frequency in the absence/presence of a fully developed facial ruff) is also a major strength, particularly in light of the very interesting results observed. The authors have succeeded in identifying clear evidence for the importance of acoustical input for determining frequency-tuning properties in the auditory midbrain. However, a number of points remain unclear.

1) It is unclear why some analyses (Fig.5, Fig.7) are focused on frontal locations and frontally-tuned neurons. It is also unclear why neurons with a best ITDs of 0 are described as frontally tuned since locations behind the animal produce an ITD of 0 also. Related to this, in Fig.1, facial ruff removal appears to reduce IPD variability at low frequencies for locations to the rear (~160 degrees), where the ITD is likely to be close to 0. Neurons with a best ITD of 0 might therefore be expected to adjust their frequency tuning in opposite directions depending on whether they are tuned to frontal or rearward locations.

2) The study suggests that information about high-frequency ITDs is not passed on to the ICX if the ICX does not contain neurons that have a high best frequency. However, neurons might be sensitive to ITDs at frequencies other than the best frequency, particularly if their frequency tuning is broader. It is also unclear whether the best frequency of a neuron always corresponds to the frequency that provides the most reliable ITD information, which the study implicitly assumes.

Reviewer #2 (Public Review):

Octopuses are known for their abilities in solving complex tasks and numerous apparently complex cognitive behaviours such as astonishment at octopuses learning how to open jars by watching others and the mind-boggling camouflage. They are very clever molluscs. The octopus shows the famously advanced brain plan but it is one that has little research progress due to its large size and structural complexity. This was originally recognised by the work of BB Boycott, JZ Young, EG Gray, and others in mid last century. Since then, however, little progress has been achieved towards a modern-day description of the octopus neural network particularly in the higher-order brain lobe, despite intense interest and indeed research progress concerning their complex behavioural and cognitive abilities.

This study applied a combination of EM-based imaging, neural tracing, and analyses to start revealing a further detailed view of a part of the lateral gyrus of the vertical lobe (learning and memory centre) of the common European octopus. It is a long overdue contribution and starts to bring octopus neuroscience a step close to the details of some vertebrates achieved. The new findings of neurons and the associated network provide new insights into this very complex but unfamiliar brain, allowing to propose a functional network that may link to the octopus memory formation. Also, this work could be of potential interest to a broad audience of neuroscientists and marine biologists as well as those in bio-imaging and deep-learning fields.

Strengths:<br /> Current knowledge of the neuroanatomy and the associating network of the octopus vertical lobe (learning and memory centre) remains largely based on the pioneering neuroanatomical studies in the '70s, this work indeed provides a rich and new dataset using modern-day imaging technology and reveals numerous previously-unknown neuron types and the resulting further complex network than we thought before. This new dataset reveals hundreds of cell processes from seven types of neurons located in one gyrus of the vertical lobe and can be useful for planning further approaches for advanced microscopy and other approaches including electrophysiological and molecular studies.<br /> Another strength of this study is to apply the current fashion of the deep learning technique to accelerate the imaging process on this octopus complex neural network. This could trigger some inventions to develop new algorithms for further applications on those non-model animals.

Weakness/limitations:<br /> In an effort to match the key claims of the first connectome of the octopus vertical lobe, mapping up an entire vertical lobe is essential. However, also understandably, given challenges in imaging a large-sized brain region, this study managed to image a very small proportion of the anterior part of the lateral gyrus. Along with the current limited dataset, a partially reconstructed neural network of one gyrus, it is unclear whether the wiring pattern found in this study would appear as a similar arrangement throughout an entire lateral gyrus. Furthermore, it is also unknown if another 4 gyri might keep a similar pattern of neural network as it found in the lateral gyrus. Considering some recent immunochemistry evidence that showed distinct different signals in different gyri in terms of heterogeneity of neuron types amongst gryi, to assume this newly-discovered network can represent the wiring pattern across an entire 5-gyrus vertical lobe is inadequate. As this study is the first big step to reveal the complex network in the octopus vertical lobe system, the title may be changed to "Toward connectomics of the Octopus vulgaris vertical lobe - new insights of memory acquisition network".

Reviewer #2 (Public Review):

The chemosensory systems of vertebrates and insects share a lot of structural and functional similarities. However, looking deeper into their molecular components reveals that these similarities likely represent remarkable examples of convergent evolution. For instance, receptor molecules that detect odors are unrelated between vertebrates and insects - vertebrates use G-protein coupled receptors while insects use ligand-gated ion channels. The latter was long regarded as specific to insects, but later studies identified putative homologs in other animals, (but not in vertebrates), some unicellular eukaryotes, and plants, raising the possibility that it is an ancient family. Still, the evolution of this protein family is notoriously difficult to analyze due to a high degree of sequence divergence between the genes despite the shared structural features of the proteins they encode. Here, the authors make use of the recent explosion of high-quality structural predictions produced by AlphaFold to conduct a deep search for previously undiscovered homologs of insect odorant and gustatory receptors.

The study describes two major findings:<br /> 1. In contrast to the previous idea that vertebrates lack any homologs of the insect receptors, two proteins in vertebrates turn out to display a similar structure (Fig. 2B).<br /> 2. The authors describe a previously uncharacterized family of Drosophila "gustatory receptor-like" proteins with a putative function in chemoreception as suggested by expression data (Fig 3A, G).

All analyses are extremely thorough, the logic of the narrative is very clear, and I find all conclusions well supported by data. The authors clearly favor a hypothesis that the family that includes insect odorant and gustatory receptors has a very deep evolutionary origin, and the homologous genes in other animals and non-animals have strongly diverged at the level of the sequence but retained detectable structural homology. However, they also acknowledge the limitations of some of their arguments and they discuss an alternative whereby the observed structural similarity is the result of convergence (which would be equally interesting). Overall, this study represents a major advance in our understanding of protein evolution and opens several avenues of research into the question of how functional demands steer the preservation of structural features of proteins while allowing their amino acid sequences to diverge.

Reviewer #2 (Public Review):

In this foundational article, the authors conduct an ancient DNA characterization of maize unearthed in archaeological contexts from Paredones and Huaca Prieta in the Chicama river valley of Peru. These maize specimens were recovered by painstakingly controlled excavation. Their context would appear to be beyond reproach though the individual radiocarbon determinations should be subject to further scrutiny.

Radiocarbon determination for at least one of the maize cobs analyzed for aDNA is not a direct date, but dates associated material. The authors should provide a table of the direct dates on the specimens that were analyzed for ancient DNA. They should also specify the type and quantity of material sent and whether the cob, glumes, pith, or husks were submitted for dates. Include δ13C determinations for each cob with laboratory analysis numbers because there is justifiable concern that at least one of these cob dates has a δ13C value suggesting the material dated is not maize. Generally, the δ13C for maize ranges from -14 to -7. One or more of the specimens subjected to ancient DNA analysis in this paper have δ13C values far outside of this confidence interval.

From the perspective of future scientists being able to repeat the analyses performed here, I would hope that all details of specimen treatment, extraction methods, read length and quality would need to be assiduously described. Routine analytical results should be reported so that comparisons with earlier and future results are facilitated, and not made difficult to decipher or search for.

The aDNA analysis may or may not be affected by the anomalous δ13C values but one would anticipate that standard aDNA extraction and analysis protocols would provide a means by which the specimen's preservation of the specimens could be ascertained, for example, perhaps deamination and fragmentation rates could be compared or average read length evaluated with modern-contemporary materials so that preservation of the Paredones samples relative to that of maize in the CIMMYT germplasm bank and the San Marcos specimens investigated by the same researchers can be evaluated.

The size and shape of the cobs depicted are similar to specimens occurring much later in Mesoamerican assemblages. For example, the approximate rachis diameter of the San Marcos specimens depicted by Valle-Bueno et al. (2016: Fig.1) averages less than 0.5cm while the specimens depicted in Valle-Bueno et al. (this manuscript) average 1.0 cm. The former - San Marcos - specimens are dated at 5300-4970 BP cal while the larger - Paredones - specimens date roughly 6777 - 5324 BP cal. The considerable disparity among the smaller more recent specimens compared to the very much larger putatively older specimens suggests the Paredones specimen's radiocarbon determinations are equivocal. The authors point this out but repeatedly state these cobs are the most ancient; a conundrum that should be resolved.

I would suggest the authors consider redating these three specimens and if they do, hope that they will prepare the laboratory personnel with depositional environment information. MacNeish was skeptical about late dates on maize at Tehuacan, at first. Adovasio was initially certain about maize's associated dates from Meadowcroft. One would prefer to be reasonably certain the foundation this article creates is solid; the author's repeated reference to these cobs as the most ancient in the Americas should be reaffirmed so retraction will not be necessary.

Reviewer #2 (Public Review):

This study reports a novel role of thalamic activity in the late components of a cortical event-related potential (ERP). To show this association, the authors used high-density EEG together with multiple deep electrophysiological recordings combined with electrical stimulation of superficial and deep cortical layers. Stimulation of deep layers elicits a late ERP component that is closely related to bursts of thalamic activity during quiet wakefulness. This relationship is quite noticeable when deep layers of the cortex are stimulated, and it does depend on the arousal state, being maximal during quiet wakefulness, diminished during active wakefulness, and absent during anesthesia.

The study is very well performed, with a high number of subjects and appropriate methodology. Performing simultaneous recording of EEG and several neuropixels probes together with cortical microstimulation is no small feat considering the size of the mouse head and the fact that mice are freely behaving in many of the experiments. It is also noticeable how the authors use a seemingly outdated technique (electrical microstimulation) to produce compelling and significant research. The conclusions regarding the thalamic contributions to the ERP components are strongly supported by the data.

The spatiotemporal complexity is almost a side point compared to what seems to be the most important point of the paper: showing the contribution of thalamic activity to some components of the cortical ERP. Scalp ERPs have long been regarded as purely cortical phenomena, just like most EEGs, and this study shows convincing evidence to the contrary.

The data presented seemingly contradicts the results presented by Histed et al. (2009), who assert that cortical microstimulation only affects passing fibers near the tip of the electrodes, and results in distant, sparse, and somewhat random neural activation. In this study, it is clear that the maximum effect happens near the electrodes, decays with distance, and is not sparse at all, suggesting that not only passing fibers are activated but that also neuronal elements might be activated by antidromic propagation from the axonal hillock. This appears to offer proof that microstimulation might be much more effective than it was thought after the publication of Histed 2009, as the uber-successful use of DBS to treat Parkinson's disease has also shown.

Reviewer #2 (Public Review):

This paper set out to investigate disparities in how authors of scientific papers are quoted in the context of science journalism. Quotations, the authors argue, reveal who a science journalist approaches as a source and thus who is considered an expert. At the same time, quotation in the news legitimizes experts and signals the importance of their perspective and opinions. It is therefore important to identify disparities in a quotation, both as a matter of justice and to ensure the representation of diverse viewpoints in journalism.

Here, the authors investigate disparities in quotation based on the gender and national origin of experts. They focus on science journalism in non-research articles published in the journal Nature. Articles are scraped from the Nature website and using established NLP tools the article content is parsed for quotations and the names of scientists being quoted. The gender and national origin of scientists are inferred based on their names and gendered pronouns used in the text. The rates of quotation based on gender/national origin are then compared to the demographics of authors (also inferred) of research articles published in Nature; this establishes a baseline to compare who is quoted vs. who is actually doing research. Based on these data, a variety of analyses are presented showing various aspects of bias and disparity in who is quoted in science journalism.

From their analysis, the authors make the following claims:

• Authors inferred as men were over-represented in quotations in journalistic Nature articles relative to their share of first and last authors in Nature.

• A quotation is sharply trending towards gender parity, with variation by the type of article.

• Authors with names inferred as originating from Celtic/English regions were over-represented, whereas authors with names inferred as originating from East Asia were heavily under-represented in quotations.

• The representation of authors with inferred East Asian names has increased faster among the last authors of research articles in Nature than it has in a journalistic quotation.

Claims 2-4 are solidly supported by the evidence presented in the manuscript. Claim 1 is supported by the evidence, but with some caveats. Support for Claim 1 depends on whether Nature's first or last authors are the most appropriate comparison set; if the last authors are the most appropriate, then Claim 1 only holds for 2005 through 2010. I expand on this point below.

I praise the manuscript and the authors for their commitment to reproducibility. Supplied with the paper is all the data (where possible) and code necessary to reproduce the results, as well as a Docker image that ensures that it can be re-executed far into the future.

The analyses conducted are methodologically rigorous. The authors provide bootstrapped confidence intervals for all analyzed values, choose appropriate baselines, and validate their name inference approach. In addition, I found their analysis comprehensive. By this I mean that they sufficiently explored their data to support their claims; nearly every caveat or limitation I could think of while reading was appropriately addressed either in the main or in a supplemental figure or table.

While a good paper, it is not without weaknesses. The paper is generally well-written, and the visualizations do a good job of communicating results. There is, of course, room to improve on both. In some cases, the manuscript lacks consistency in terminology, and uses word choice that is strange (e.g., "enrichment" and "depletion" when discussion representation). While this paper is methodologically rigorous and professional in its presentation, I feel that the authors could have done a better job of interpreting and contextualizing their findings. Specifically, readers should be aware of the caveats regarding Claim 1 (listed above), the limits of generalizing these findings to other areas of science journalism, and a somewhat shallow discussion section that I believe detracts from the study's significance. I outline these points in more detail below.

Despite these quibbles, the authors find solid support for their claims and achieve their goals. This paper, I believe will be of general interest to scientists and science communicators, to those interested in science communication as a field, to meta-scientists, and to those aiming to improve diversity and equity in the scientific process.

Caveats to Claim Claim 1:

One of the claims made by the authors (Claim 1) is that quotations in the dataset skew towards men. I find this true, but with two related caveats: that it depends on the choice of comparator set, and that it changes over time.

The authors assess the representation of quotation by comparison to either Nature's first authors, or last authors. However, the authors do not discuss whether one is more appropriate, and what is implied if, say, quotations match the last author but not the first authors. In most scientific fields, the last author corresponds to the conceptual lead of a paper and is often the corresponding author who is most likely to be contacted to discuss the paper's significance. First authors, in contrast, will often represent the "driver" of the project-basically the person doing most of the actual work and is usually a student or more junior researcher. This distinction is important because cases could be made for either being a more appropriate comparator - last authors due to their seniority, first authors due to their closeness to the study, and (typically) greater diversity.

The choice of comparator set becomes an issue because, as per Claim 2, the representation of women is increasing over time. Claim 1 only holds for the last authors from 2005 through 2010, and after 2018 women have higher representation given the demographics of the last authors. For the first authors, Claim 1 holds through 2017, after which they are representative or slightly over-representative of women authors.

So while Claim 1 holds, it does not hold for all comparator sets and for all years. I don't think this is critical of the paper-the authors do discuss the trend in Claim 2-but interpretation of this claim should take care of these caveats, and readers should consider the important differences in first and last authorship.

Generalizability to other contexts of science journalism:

Journalistic articles in Nature may not be representative of all contexts of science journalism. Nature has a unique readership, consisting of scientists from many disciplines who have not only a generalist interest in science but also an interest in aspects of science as a profession. Science journalism as a whole, however, is part of the broader landscape of mainstream media, consisting of outlets such as ABC, BBC, and Scientific American. The audiences for these outlets will be more general, less interested in science as a career, and will likely have a different appetite for direct quotations and for more technical topics.

This does not make the study bad. On the contrary, the author's focus on Nature allowed for many interesting analyses-but their findings should still be understood as coming from a specific context. While the authors outline many limitations of their study, they do not grapple with the limits of its generalizability, and what aspects of their analysis might translate to other contexts of science journalism. For example, part of the trend towards gender parity in a quotation is explained by the higher representation of women in the "Career Feature" article type. However, this article type will likely not be present in more general-interest contexts, which would affect the representation of women.

Shallow discussion:

I feel that the authors missed an opportunity to use their discussion to not only properly contextualize their results, but also explore their significance. In broad terms, there is literature on science journalism, its consequences for science, and the impact on public perceptions, as well as a continuous meta-discourse on journalistic ethics and best practices. The authors pay lip service to some of these themes but do little to actually place their findings in the broader discourse. Below, I provide a few specific points that could be further discussed:

What might be the downstream impacts on the public stemming from the under-representation of scientists with East Asian names?

The authors highlight gender parity in career features, but why exactly is there gender parity in this format of Representation in quotations varies by first and last author, most certainly as a result of the academic division of labor in the life sciences. However, what does it say about the scientific quotation that it appears first authors are more often to be quoted? Does this mean that the division of labor is changing such that the first authors are the lead scientists? Or does it imply that senior authors are being skipped over, or giving away their chance to comment on a study to the first author?

Moreover, there are several findings in the study which are notable but don't seem to have been mentioned at all in the discussion.

Below I highlight a few:

• According to Figure 3d, not only are East Asian names under-represented in quotations, but they are becoming more under-represented over time as they appear as authors in a greater number of Nature publications.

• Those with European names are proportionately represented in quotations given their share of authors in Nature. Why might this be, especially seeing as Anglo names are heavily over-represented?

Reviewer #2 (Public Review):

Ibar and colleagues address the role of the spectrin cytoskeleton in the regulation of tissue growth and Hippo signaling in an attempt to elucidate the underlying molecular mechanism(s) and reconcile existing data. Previous reports in the field have suggested three distinct mechanisms by which the Spectrin cytoskeleton regulates Hippo signaling and this is, at least in part, due to the fact that different groups have mainly focused on different spectrins (alpha, beta, or beta-heavy) in previous reports.

The authors start their investigation by trying to reconcile their previous data on the role of Ajuba in the regulation of Hippo signaling via mechanotransduction and previous observations suggesting that Spectrins affect Hippo signaling independently of any effect on myosin levels or Ajuba localization. Contrary to previous reports, the authors reveal that, indeed, depletion of alpha- and beta-heavy-spectrin leads to an increase in myosin levels at the apical membrane. Moreover, the authors also reveal that the depletion of spectrins leads to an increase in Ajuba levels.

The authors suggest that Ajuba is required for the effect of beta-heavy spectrin. However, it is still formally possible that this could be a parallel pathway that is being masked by the strong phenotype of Ajuba RNAi flies.

One of the major points of the manuscript is the observation that alpha- and beta-heavy-spectrin are potentially working independently and not as part of a spectrin tetramer. This is mostly dependent on the observation that alpha- and beta-heavy-spectrin appear to have non-overlapping localizations at the membrane and the fact that alpha- and beta-heavy-spectrin localize at the membrane seemingly independently. It is not entirely obvious that a potential lack of colocalization and the fact that protein localization at the membrane is not affected when the other partner is absent is sufficient to argue that alpha- and beta-heavy-spectrin do not form a complex. Moreover, it is possible that the spectrin complexes are only formed in specific conditions (e.g. by modulating tissue tension).

If indeed spectrins function independently, would it not be expected to see additive effects when both spectrins are depleted?

Related to the two previous points, the fact that the authors suggest that both alpha- and beta-heavy-spectrin regulate Hippo signaling via Ajuba would be consistent with the necessity of an alpha- and beta-heavy-spectrin complex being formed. How would the authors explain that both spectrins require Ajuba function but work independently?

Another major point of the manuscript is the potential competition between beta-heavy-spectrin and myosin for F-actin binding. The authors suggest that there is a mutual antagonism between the two proteins regarding apical F-actin. However, this has not been formally assessed. Moreover, despite the arguments put forward in the discussion, it seems hard to justify a competition for F-actin when beta-heavy-spectrin seems to be unable to compete with myosin. Myosin can displace beta-heavy-spectrin from F-actin but the reciprocal effect seems unlikely given the in vitro data.

Reviewer #2 (Public Review):

The data generated for this paper provides an important resource for the neuroscience community. The locus coeruleus (LC) is the known seed of noradrenergic cells in the brain. Due to its location and size, it remains scarcely profiled in humans. Despite the physically minute structure containing these cells, its impact is wide-reaching due to the known neuromodulatory function of norepinephrine (NE) in processes like attention and mood. As such, profiling NE cells has important implications for most neurological and neuropsychiatric disorders. This paper generates transcriptomic profiles that are not only cell-specific but which also maintain their spatial context, providing the field with a map for the cells within the region.

Strengths:

Using spatial transcriptomics in a morphologically distinct region is a very attractive way to generate a map. Overlaying macroscopic information, i.e. a region with greater pigmentation, with its corresponding molecular profile in an unbiased manner is an extremely powerful way to understand the specific cellular and molecular composition of that brain structure.

The technologies were used with an astute awareness of their limitations, as such, multiple technologies were leveraged to paint a more complete and resolved picture of the cellular composition of the region. For example, the lack of resolution in the spatial transcriptomic platform was compensated by complementary snRNA-seq and single molecule FISH.

This work has been made publicly available and accessible through a user-friendly application such that any interested researcher can investigate the level of expression of their gene of interest within this region.

Two important implications from this work are 1) the potential that the gene regulatory profiles of these cells are only partially conserved across species, humans, and rodents, and 2) that there may be other neuromodulatory cell types within the region that were otherwise not previously localized to the LC

Weaknesses:

Given that the markers used to identify cells are not as specific as they need to be to definitively qualify the desired cell type, the results may be over-interpreted. Specifically, TH is the primary marker used to qualify cells as noradrenergic, however, TH catalyzes the synthesis of L-DOPA, a precursor to dopamine, which in turn is a precursor for epinephrine and norepinephrine suggesting some of the cells in the region may be dopaminergic and not NE cells. Indeed, there are publications to support the presence of dopaminergic cells in the LC (see Kempadoo et al. 2016, Takeuchi et al., 2016, Devoto et al. 2005). This discrepancy is further highlighted by the apparent lack of overlap per given Visium spots with TH, SCL6A2, or DBH. While the single-nucleus FISH confirms that some of the cells in the region are noradrenergic, others very possibly represent a different catecholamine. As such it is suggested that the nomenclature for the cells be reconsidered.

The authors are unable to successfully implement unsupervised clustering with the spatial data, this greatly reduces the impact of the spatial technology as it implies that the transcriptomic data generated in the study did not have enough resolution to identify individual cell types.

The sample contribution to the results is highly unbalanced, which consequently, may result in ungeneralizable findings in terms of regional cellular composition, limiting the usefulness of the publicly available data.

This study aimed to deeply profile the LC in humans and provide a resource to the community. The combination of data types (snRNA-seq, SRT, smFISH) does in fact represent this resource for the community. However, due to the limitations, of which, some were described in the manuscript, we should be cautious in the use of the data for secondary analysis. For example, some of the cellular annotations may lack precision, the cellular composition also may not reflect the general population, and the presence of unexpected cell types may represent the accidental inclusion of adjacent regions, in this case, serotonergic cells from the Raphe nucleus.

Nonetheless having a well-developed app to query and visualize these data will be an enormous asset to the community especially given the lack of information regarding the region in general.

Reviewer #2 (Public Review):

This work by Sidhaye, Trepte et al. systematically investigates the relationship between transcript and protein abundance across the genome in human neurogenesis. Through analysis of the transcriptome and proteome in brain organoids, they find that for specific gene modules, transcript and protein abundance are highly disconnected. While there are already several anecdotic examples of this phenomenon in the literature, highlighting the role of post-transcriptional gene regulation in corticogenesis, Sidhaye, Trepte et al. for the first time systematically explore the pervasiveness of this phenomenon in a genome-wide manner at different stages of human neurogenesis using a dual reporter cell line to isolate neural progenitor cells and neurons.

The authors then focus on one of the modules that is characterized by the enrichment of the 5'TOP (terminal oligopyrimidine) motif in the 5'UTR of transcripts and enriched in ribosomal proteins and translation initiation factors. The authors show that partial inhibition of the translation of ribosomal genes in neural progenitor cells inhibits the translation of differentiation genes, a process that involves mTOR-mediated regulation.

Strength:

The integration of transcriptome and proteome data enables an unbiased systemic analysis revealing gene modules that follow similar trajectories, and as such may share common regulatory principles. For one of the modules, the authors dissect the posttranscriptional regulatory cascade using an elegant combination of fluorescent reporter human pluripotent stem cell lines in combination with gene knockouts.

Overall, the data presented in this work is of a very high standard and supports the conclusions put forward by the authors. The processed omics data sets are made available via a Shiny app web interface for easy access and therefore promote exploration by the scientific community.

Limitations:

This study uses a large range of specific reporter and knockout hPSC lines generated in the context of this work, however, very limited information is provided on these lines. For example, do the lines remain karyotypically normal throughout the targeting procedure? Does reporter gene expression faithfully recapitulate the activity of the promoters controlling their expression? Specifically, it appears that a significant GFP signal is detected within the neuronal layer (Figure 1B) and that there is a much larger double reporter-positive population than expected (Figure S2A).

The authors propose that stress-associated translational regulation takes place in early neural progenitors, involving the sequestration of transcripts in stress granule-like structures. However, given that at least some human brain organoid protocols have been reported to lead to ectopic activation of cellular stress pathways (Bhaduri et al., Nature 2019), it would be desirable to see this aspect of the study confirmed in primary tissue (mouse or human).

Reviewer #2 (Public Review):

The authors set out to understand how a room-temperature X-Ray crystallography-based chemical-fragment screen against a drug target may differ from a cryo screen. They carried out two room-temperature screens and compared the results with that of a cryo screen they previously performed. With a substantial set of crystallographic evidence they showed that the modes of protein-fragment binding are affected by temperature. The conclusion of the work is compelling. It suggests that temperature provides another dimension in X-ray crystallography-based fragment screening. In a practical sense, it suggests that room-temperature fragment screen is a promising new avenue for hit identification in drug discovery and for obtaining insights into the fragment binding. Room-temperature screening carries unique advantage over cryo screening. This work is confirmative to the notion, which seems not yet universally considered, that very weak protein-small molecule binding may be inherently fluid structurally, and that crystal structures of such weak binding, especially cryo structures, cannot be taken for granted without cross validation.

Reviewer #2 (Public Review):

In this study, the authors developed a mouse model to specifically investigate whether GC B cells that present nuclear protein (NucPr) could be specifically suppressed by Tfr cells. Most current mouse models that have been used in investigating Tfr functions are based on the overall readout of autoantibody production in the scenario of loss-of-function of Tfr cells. The proposed model of gain-of-function of Tfr cells is novel and valuable.

The authors mainly compared two boosting immunizations by Strepatividin (SA) alone or SA-conjugated with nuclear proteins (SA-NucPr) and demonstrated SA-NucPr boosting immunization was able to expand Tfr cells, suppress overall and SA-specific GC/memory/plasma cell responses. The results are mostly convincing.

One major concern is the conditions and controls used in the study. The control group (SA boosting immunization) would have enhanced T and B cell responses by this boosting. Unfortunately, there was no non-boosting control group so the level was unclear. It is therefore to strictly match such boosting condition in the SA-NucPr group. Notably, both SA and SA-NucPr were used at 10ug for boosting immunization. Considering NucPr were comparable or much larger (Nucleosome, about 200KDa) than SA (about 60KDa), the dose of SA in the SA-NucPr group was far less than that in the SA group. Due to this cavity, it is difficult to judge the difference between two groups was due to less SA boosting immunization or NucPr-induced Tfr function. This was a fundamental issue weakens the conclusion.

The single cell analyses clearly demonstrated the expansion of Tfr clones. It remains unclear why other Treg populations other than Tfr cells were not expanded? The Treg cells in the CXCR5intPD-1int population were recently activated and should be able to respond to the boosting immunization. On an alternative explanation, the changes in Tfr cells could be indirectly driven by the changes in Tfh cells. For example, Tfh can produce IL-21 and restrict Tfr expansion (Jandl C, et al.2017). This could be the case of the reduction in Tfr cells in the SA-OVA group as compared to the SA group.

Reviewer #2 (Public Review):

In this proof-of-concept study, Richardson et al explore lifecourse effects of adiposity on leptin levels using life course Mendelian randomization and perform a tissue-partitioned MR to study the effects of tissue-specific BMI genetic instruments on leptin levels. The methods are solid and they have been nicely applied in the context of the present study. The results are important, revealing differences in the impact of adiposity on leptin levels in childhood vs adulthood, and highlighting the importance of the adipose-brain pathway in leptin homeostasis.

Additional MR analyses are suggested to explore bidirectional associations between leptin levels and adiposity, due to the interrelation of these two markers. Also, the fact that the MR instruments for childhood adiposity are based on self-reported body size, while the MR instruments for adult adiposity are based on measured adult BMI should be highlighted in the manuscript, and the possible impact of this in the findings should be discussed.

In summary, this important study is a proof of concept of life course and tissue-partitioned MR, while providing interesting insights into the regulation of leptin homeostasis by adiposity in different life stages.

Reviewer #2 (Public Review):

The authors are aiming to characterize the developmental process and functional heterogeneity of liver ILC1s. The role of liver ILC1's in human health is still unknown. ILC1's are abundant in fetal liver and decline throughout development into adults.

The authors have gone to great lengths to establish the relationship between IL-7R expression and ILC1 ontogeny.

The study provides insight into the complex ILC1 ontogeny by revealing relationships among heterogenous ILC1 subsets.

The data suggests intrinsic cytotoxic programs of 7R− ILC1s differ to NK cells, proposing them as critical steady-state sentinels against infection prevention and tumor surveillance.

The big unresolved question is why ILC1 dominate fetal innate lymphocytes versus NK cells in adult life.

Reviewer #2 (Public Review):

Scagliotti et al address how organ size is regulated by imprinted genes. Using a series of mouse models to modulate the dosage of the paternally expressed gene, Dlk1, the authors demonstrate that DLK1 is important for the maintenance of the stem cell compartment leading to the growth of the pituitary gland and the expansion of growth hormone-producing cells. The authors show that overexpression of Dlk1 leads to pituitary hyperplasia while deletion of the paternal allele leads to reduced pituitary size. Reduced pituitary size is accompanied by reduced cell proliferation in the cleft at e13.5 and an increase in the number of POU1F1+ cells, suggesting that loss of Dlk1 alters the balance between the number of cells remaining in the replicating stem cell pool and those differentiating into the POU1F1 lineage. An elegant caveat of this paper is the rescue of Dlk1 expression in the population of cells expressing Pou1f1 but not in SOX2+ stem cells. Expression of Dlk1 only in POU1F1+ cells is not sufficient to rescue pituitary size. The authors suggest that this is because DLK1 must be present in stem cells which then activate paracrine WNT signaling to promote cell proliferation in POU1F1+ cells.

Strengths:

This is an important study that provides a mechanistic understanding of how the imprinted gene, Dlk1, regulates organ size. The study employs an elegant experimental design to address the dosage requirement for Dlk1 in regulating pituitary gland size. Rescuing Dlk1 in the POU1F1+ cells, but not the marginal zone SOX2+ cells provides intriguing results about a possible role for DLK1 in paracrine signaling between these different pituitary cell types. The study uses publicly available scRNAseq and ChIPseq data to further support their findings and identify Dlk1 as a likely target of POU1F1.

Weaknesses:

The study only analyzes females for the adult time point. For embryonic and postnatal time points sexes are pooled. Gender differences in pituitary gene expression embryonically or postnatally could potentially affect experimental outcomes.

The authors employ a mouse model that rescues Dlk1 expression starting at e15.5 in POU1F1+ parenchymal cells but not in marginal zone stem cells. Rescuing Dlk1 expression in a specific population of cells is one of the strengths of this study. Based on this information and the fact that overexpression of Dlk1 leads to increased pituitary size, the authors suggest that DLK1+ marginal zone stem cells and DLK+ parenchymal cells may interact to promote postnatal proliferation. However, the ability to more carefully parse out the complex spatial and temporal contributions of DLK1 to pituitary size would be enhanced by the addition of a mouse model that rescues Dlk1 expression only in SOX2+ cells and a model that rescues expression in both stem cells and POU1F1+ cells.

Reviewer #2 (Public Review):

In this manuscript, Rahsepar et al. test the hypothesis that the precise timing of engram cell activation in relation to the phase of hippocampal theta oscillations plays a causal role in recall. This hypothesis is derived from theories (e.g. the SPEAR model) positing that the hippocampus segregates information for memory encoding and retrieval in time and that separation is organized across the many neurons and subregions of the hippocampus by theta oscillations. They test this hypothesis using stimulation of dentate gyrus neurons active during the encoding of fear memory. Using closed-loop stimulation that they developed, the authors stimulate these dentate engram cells at different phases of theta to measure freezing behavior to determine if the fear memory is recalled. They compare this stimulation to stimulation at the same average frequency regardless of theta phase, or at a constant 20Hz, in line with prior research, as control conditions. The authors use an elegant within animal design. They find that stimulating at the theta phase when CA3 inputs most strongly influence CA1 leads to significant increases in freezing (relative to baseline), while none of the other stimulation conditions have significant effects on freezing. They then show that this stimulation also causes increases in gamma modulation by theta, which is correlated with learning in prior work. However, the gamma that is theta-modulated appears to be medium gamma which is not associated with CA3 inputs to CA1. Overall, the study is well-designed and well-controlled. The stimulation effects at the "best" theta phase are modest but do appear different than the other conditions. It is unclear why the authors chose to stimulate in dentate and not CA3 as the SPEAR hypothesis centers around CA3 and EC inputs to CA1. Furthermore, I wonder if the freezing behavior itself confounds the detection of the theta phase. Finally, some of the statistical analyses require controlling for multiple comparisons.

Reviewer #2 (Public Review):

Prasad et al investigate mechanisms of interface contractility that occur at borders between cells of different specification states. Cells of different specification states typically sort out, minimizing interface contact, in association with increased junctional contractility that can be visualized by phalloidin labeling. Here, Prasad et al show, for multiple different examples of specification and/or signaling states, that bilateral activation of JnK flanks these interfaces, which are associated with elevated rates of Jnk-dependent apoptosis. Blocking Jnk activity does not seem to affect phalloidin labeling, however, placing interphase contractility upstream or parallel to Jnk activity and apoptosis. Interestingly, activated Ras[V12] is an exceptional case where interphase contractility and bilateral Jnk activation occur without elevated apoptosis. Indeed, RasV12 can suppress apoptosis associates with interfaces between other distinct cell types. Prasad et al suggest that this property of Ras[V12] activated cells may underlie their oncogenic potential in mammals. These are potentially interesting observations that address what happens when cell of disparate signaling and/or specification states are opposed. In principle, they could be of interest both to developmental biologists, from the perspective of correction of developmental errors, and to cancer biologists, from the perspective of eliminating precancerous cells.

It is not clear how much advance is represented over the prior description of 'morphogenetic apoptosis', in which bilateral Jnk activity was also an integral part (Adachi-Yamada and O'Connor, Devl Biol vol251 pp74-90 2002). There is little new mechanistic insight provided here. As such, the observations seem preliminary and to represent only a limited advance.

Reviewer #2 (Public Review):

Enteroendocrine cells (EEC) line the gut and prior evidence suggest that they are primary sensors of gut contents. In turn, these cells release transmitters that regulate gut function, including gut motility, enzyme secretion, and gut permeability. More recent studies have also found synaptic connections between EEC and neural sensory fibers that connect the gut to the brain, implicating this pathway in taste learning. Thus, EEC signals can be integrated with sensory signals originating in more distal areas of the alimentary canal.

EECs express a variety of receptors and transmitters that are hypothesized to contribute to the diversity of sensing and motor functions. In this report, Hayashi et al develop a novel transgenic mouse that permits manipulation of EEC subtypes via intersectional methods. Using this approach, they identify differential roles for EEC subtypes in controlling gut motility and taste learning.

Strengths

• The authors supplement existing single-cell RNA sequencing of the proximal intestine.<br /> • A Vil1-2a-Flp mouse was generated, which exhibits highly selective expression in the gut epithelium. This mouse line can be used to manipulate EEC subtypes when bred with other Cre driver lines and double conditional (Flp/Cre) mice.<br /> • Using the above tool, different EEC subtypes were histologically characterized along the alimentary canal. Additionally, other tissues were examined, including the brain, pancreas, and lungs to demonstrate the gut specificity of their approach. The intersectional approach yield sparse recombination in the pancreas, therefore the authors included controls in their gut motility and feeding studies to account for this.<br /> • In probing the function of distinct EECs, it was found that Cck(cholecystokinin) and Gcg (GLP-1) expressing EECs slow down gut motility, whereas Tac1 (substance P) and Pet1(serotonin) expressing cells increase motility.<br /> • Food intake studies revealed several subpopulations that decrease feeding (Pet1, Npy1r, Cck, Gcg).<br /> • A conditioned flavor preference assay suggests that some of the above EEC subtypes (Pet1, Tac1, Npy1r, Gcg) decrease feeding in part through conditioned flavor avoidance.

Reviewer #2 (Public Review):

In the manuscript by Porter et al., the authors describe a putative role for the STAG proteins (SA1 and SA2), not as part of the cohesin complex, but in isolation and in particular at R-loops where they contribute to R-loop regulation, linking chromatin structure and cohesin loading.

My major concern is rather general: " the role of SA1 and SA2 proteins (or cohesion subunits) its only highlighted upon acute depletion of RAD21 (cohesin subunit that holds together the complex)". I am not sure that this context is recapitulated in living cells. I.e is there a particular phase of the cell cycle where RAD21 is acutely depleted or targeted for specific degradation? How do we know that we are not looking at remnants of a complex (cohesin) that has been partially targeted by IIA mediated degradation? Is the RNA binding of SA1 an SA2 CTCF-independent (as CTCF encompasses an RNA binding domain?).

Is there any proof that in untreated cells (ie before depletion) SA1 AND SA2 are chromatin bound independently of Rad21 (and /or SMC1-3)? Overall, it is a nice manuscript, but I am not sure whether the IAA-dependent degradation of a single subunit of pentameric complex is the right tool to assess whether other subunits of the same complex work independently.

Reviewer #2 (Public Review):

The study of Koropouli is a tour the force investigation of the Semaphorins receptor, Neuropilin-2, modification by Palmitoylation. The work consists of biochemical, cellular and in vivo experiments and overall underscore an interesting layer of regulation of axonal guidance receptors membrane localization and function by lipid modification.

https://www.youtube.com/watch?v=ifDi2SsQjQM

Comparing the various e-note/e-reader devices, Kit Betts-Masters ranks them overall as follows: - Boox Note Air 2 - Supernote A5X - Remarkable 2 - Bigme Inknote - Kobo Elipsa - Boyue P10

Reviewer #2 (Public Review):

Gold and his colleagues first ectopically expressed aACTN2 constructs with various deletions and determine the spatial proximity to CaMKII by PLA. Chemical LTP induced by brief glycine application in hippocampal cultures strongly augmented the PLA puncta density in spines (postsynaptic sites). This interaction specifically depended on the 4 EF hands near the C-terminus of aACTN. At the same time expression of the 4 EF hands (plus the C-terminal PDZ ligand) impaired the formation of larger mushroom spines under unstimulated conditions and the increase in mushroom spines seen after chemLTP when compared to non-transfected conditions or transection of the EF hands with a point mutation (L854R) that disrupted binding to CaMKII.

To further define the interaction between aACTN and CaMKII the authors then solved a crystal structure formed by the aACTN EF3/4 and regulatory segment of CaMKII. This structure confirmed the role of L854 in the interaction. It also explained earlier results that phosphorylation of threonine in position 306 but not of threonine 305 of the CaMKII regulatory domain impaired aACTN binding as T306 but not T305 is engaged in critical interactions. This contrasts with Ca/CaM binding to CaMKII, which engages both threonines and is blocked by the phosphorylation of either residue. Consistently, earlier structures of Ca/CaM with the CaMKII regulatory domains showed respective differences to the new aACTN-CaMKII structure.

Additional analysis of these data indicated that the association of the regulatory domain with the kinase domain occludes access to aACTN EF3/4. This is an important finding because it implies that only active CaMKII like T286 autophosphorylated CaMKII or bound to GluN2B would be able to effectively interact with aACTN in intact cells.

Finally, and remarkably, binding was augmented by a protein fragment of the GluN2B C-terminus that contains the binding site for CaMKII even when Ca/CaM was still present. This result suggests that with GluN2B present aACTN can bind to CaMKII even though in the absence of GluN2B Ca/CaM occludes this binding. This finding opens up new research directions.

Reviewer #2 (Public Review):

In this paper, Xiao et al. suggest that PASK is a driver for stem cell differentiation by translocating from the cytosol to the nucleus. This phenomenon is dependent on the acetylation of PASK mediated by CBP/EP300, which is driven by glutamine metabolism. Furthermore, this study showed that PASK interferes/weakens the Wdr5-APC/C interaction, where PASK interacts with Wdr5, resulting in repression of Pax7, leading to stem cell differentiation.

There exist huge interest in maintaining adult stem cells and ES cells in their pluripotent form and the work painstakingly perform several experiments to present that PASK is a good target to achieve that goal.

However, the work on the paper relies mostly on data from C2C12 cells as adult muscle stem cell models, in vivo experimental data, and primary myoblasts from mice. Using these models makes the story contextual in muscle stem cells. Authors have not tried to extrapolate similar claims in other adult stem cell models. This severely restricts the claim to muscle stem cells even though PASK is required for the onset of embryonic and adult stem cell differentiation in general. Their work could be much strengthened if it is also tried on mesenchymal stem cells as these cells are also as metabolically active as muscle cells.

Reviewer #2 (Public Review):

In this work, Verstegen and colleagues try to delineate human B cell differentiation trajectories by using in vitro differentiation culture of human naive B cells. The authors adopted a protocol of B cell stimulation with CD40L-expressing fibroblasts and IL-4/IL-21, and cultured B cells were analyzed by single-cell transcriptome analysis. Five distinct clusters were identified with features of memory B cells, germinal center-like B cells, ASCs, pre-ASCs, or post-GC B cells. This work provides a precise description of gene expression profiles of activated B cell populations and some insight into the pathways of effector B cell differentiation. This work will be a solid basis for human B cell study using in vitro culture of target B cell populations, providing an excellent experimental protocol.

Reviewer #2 (Public Review):

My main concern is in regards to the interpretation of these results has to do with the sparseness of data available to fit with the models. The authors pit two linear models against a nonlinear (normalization) model. The predictions for weighted average and summed models are both linear models doomed to poorly match the fMRI data, particularly in contrast to the nonlinear model. So, while I appreciate the verification that responses to multiple stimuli don't add up or average each other, the model comparisons seem less interesting in this light. This is particularly salient of an issue because the model testing endeavor seems rather unconstrained. A 'true' test of the model would likely need a whole range of contrasts tested for one (or both) of the stimuli, Otherwise, as it stands we simply have a parameter (sigma) that instantly gives more wiggle room than the other models. It would be fairer to pit this normalization model against other nonlinear models. Indeed, this has been already been done in previous work by Kendrick Kay, Jon Winawer and Serge Dumoulin's groups. So far, may concern above has only been in regards to the "unattended" data. But the same issue of course extends to the attended conditions. I think the authors need to either acknowledge the limits of this approach to testing the model or introduce some other frameworks.

Reviewer #2 (Public Review):

This study generated a valuable preclinical model of patients with Mfn2-related lipodistrophy (R707W). Such a mouse model enables the understanding the pathogenic mechanism causing this lipodistrophy and testing specific therapeutic approaches for these patients.

The strengths are the thorough phenotypic characterization of the mice and the clear decrease in circulating leptin and adiponectin levels in the absence of changes in fat mass observed in Mfn2 R707W/R707W mice. This partially recapitulates one of the key phenotypes of human patients with these mutations.

The major weakness is the conclusion that the integrated stress response is activated in white adipose tissue is not supported by the data and the phenotype. The ISR caused by primary insults to mitochondria was defined as a response that decreases the translation of mitochondrial proteins, thus decreasing mitochondrial respiratory function via ATF4 without engaging ATF5 (Quiros et al., JCB 2016). In addition, the increase in ATF4 caused by phosphorylation of eif2alpha is in ATF4 translation and translocation to the nucleus, not in ATF4 transcription. It is a possibility that it is a selective increase in ER stress that is responsible for defective leptin secretion, as Mfn2 R707W/R707W adipose tissue shows no mitigation of mitochondrial function as expected from ATF4-ISR activation.

Reviewer #2 (Public Review):

Barthé et al. present a manuscript examining membrane-domain specific signaling by βAR stimulation in cardiomyocytes. Specifically, the authors seek to use a size exclusion approach using PEGylated-isoproterenol to allow only surface sarcolemmal βAR receptor stimulation without T-tubule βAR stimulation. This innovative approach was advanced using confocal microscopy to determine the accessibility of the PEGylated substrates to the T-tubule network. The authors show comparable responses of L-type Ca channels, Ca transients, and contraction using equipotent doses of PEG-Iso and Iso, but differences in nuclear and cytoplasmic cAMP responses based on FRET reporters.

Strengths<br /> 1. The size exclusion strategy using PEGylation technology is well rationalized and well supported by the physicochemical characterization of PEGylated Iso. This represents a novel strategy to decipher cardiomyocyte cell surface signaling from T-tubule network signaling resulting from the stimulation of β-adrenergic receptors. This approach can be used to study the compartmentalization of various signaling pathways in cardiomyocytes as well as in other cell types that exhibit complex cytoarchitecture. The authors use multiple cAMP FRET sensors as well as assay a number of relevant physiological cellular responses to assess the effect of Iso vs. PEGylated Iso which are informative.

Weaknesses<br /> 1. The authors' evidence that PEG-FITC does not penetrate the TT network is not convincing as presented in Figure 1. A single confocal image from one cell showing a lack of fluorescence (Figure 1A) could be due to an outlier cell or lack of penetration to more central regions of the cell where images are taken from. More convincing would be a confocal Z-scan series comparing PEG-FITC and FITC in ARVM. Some form of quantification of T-tubule network density from multiple cells would provide even more robust evidence, similar to the many studies that have done this characterization in models of dilated cardiomyopathy showing a loss of TT network. This exclusion of PEG-FITC provides the critical foundation for the paper and it is somewhat unanticipated given the large dimensions of the t-tubules relative PEG-Iso, so strong data here are particularly important.

2. The conclusion on line 160 that 'the maximal efficacy of PEG-Iso was significantly lower by 30% than that of Iso,' may be overstated. What approach was used to conclude significantly differently as this implies a statistical comparison? Were the concentration-response curves fit to determine maximal responses? In the examples given, the responses are continuing to increase at the highest concentrations tested, so it is difficult to simply compare the responses to the highest doses tested.

3. For experiments using adenovirus delivery of FRET-based sensor, the culture of ARVM is required which may impact the biology. Such culture is known to result in changes in cell structure and physiology with loss of the TT network over time. It is essential for the authors to demonstrate that under the conditions of their FRET experiments, the cells continue to exhibit a robust TT network.

4. As pointed out by the authors, the interpretation of OSM/TTM adrenergic receptor functions in this study is limited by the fact that the relative contributions of β-adrenergic receptor subtypes had not been assessed. This particularly complicates the interpretation of their results in that the authors demonstrate in Figure 2 that PEGylation increases the Ki for Iso for β1 receptors by 700-fold whereas the increase for β2 receptors is about 200-fold. Thus, the relative contribution of β1 and β2 receptors to a 'comparable' dose of Iso and PEGylated Iso will potentially be different. Could that difference in relative β1/β2 receptors be the cause of the different 'efficacy of nuclear and cytoplasmic' cAMP changes between the two tested ligands in Figure 8 and supplemental Figure 3? This would fundamentally alter the conclusions of the paper.

5. The equipotent doses of Iso and PEG-Iso were initially defined based on their ability to elevate global [cAMP]i. The authors then further demonstrated that such equipotent doses of Iso and PEG-Iso also had equal effects on ICa,L amplitude, Ca2+ transient parameters, and cellular contractility (shortening), presumably because they raised global [cAMP]i to the same levels. These findings seem to defy the importance of nanodomain organization and local [cAMP]i in the regulation of LTCCs, Ca2+ cycling proteins, and contractile machinery. The authors argued that "Since OSM contributes to ~60% of total cell membrane in ARVMs, either β-ARs and ACs are more concentrated in OSM than TTM, or they are in large excess over what is needed to activate PKA phosphorylation of proteins involved in EC coupling. Also, cAMP produced at OSM must diffuse rapidly in the cytosol in order to activate PKA phosphorylation of substrates located deep inside the cell, such as LTCCs in TTM" (lines 336-341). Although this argument may be valid at high concentrations of Iso and PEG-Iso when PKA activation is saturated, it also implies that discrepancy could be detectable at lower (non-saturating) doses of Iso and PEG-Iso. Thus, additional experiments using lower Iso and PEG-Iso doses are required to support this notion.

6. The size excluded compartment for PEG-Iso proposed by the authors is the TT network, but this ignores other forms of sarcolemmal nanodomains such as caveolae, which include β2 receptors and AC, and may exhibit similar if not great sensitivity to the size exclusion approaches pioneered by the authors.

Reviewer #2 (Public Review):

The study systematically looks at dynamic differences across variants longitudinally and the authors appropriately only limit their analyses to peptides that are conserved across the different variants.

There are some concerns listed below, particularly related to the ensemble heterogeneity that is reported and need considerable revision.

1) The authors explain that cold-temperature treatment of the S trimer ectodomain constructs has been shown to lead to instability and heterogeneity. They also show this with a comparison of untreated vs. 3-hour 37 C treated samples. I'm confused as to why "During automated HDXMS experiments protein samples were stored at 0 degrees". Will this not cause issues in protein heterogeneity, where the longer the protein sits at 0 C the more potential heterogeneity there will be, and thus greatly confound the analysis?

2) The authors presume that the bimodal spectra that are observed reflect EX1 kinetics, however, there can be multiple reasons for an apparent bimodal distribution in the spectra. I agree that some of the spectra indicate that more than a single species is present, but what the two populations represent is murky. In Figure 2D, the apparent size of the highly deuterated population gets larger going from the 60 sec to the 600-sec spectra, as expected for an EX1 transition. However, in Figure 3D the WT highly deuterated population gets smaller going from the 60-sec to the 600-sec spectra. Were bimodal examples observed beyond those shown in Figure 2?

3) How were the spectra that appeared broadened analyzed? There is no description of this in the methods, and the only data shown for this is in table 1. The left/right percentages are reported without any description of how they were obtained. Are these solely from a single spectrum? The most alarming issue is that Table 1B reports 9.4% for the right population of the 988-998 peptide, but the corresponding spectra in Figure 3D doesn't seem to have any highly deuterated population at all.

4) The authors state on page 12: "Replicate analysis of stabilized S trimers with incubation at 4C prior to deuterium exchange (see methods) showed a time-dependent reversal of stabilization as reported previously (Costello et al., 2022), most evident at the same peptides." Is this data shown anywhere? If not then it should be included somewhere, possibly in table 1 as I would expect the cold treatment to offset the left/right population sizes.

5) The authors state that peptide 899-913 'exhibits a slow conformational interconversion (time scale ~ 15-30 min)'. Where did this estimated rate come from? From the data shown and the limited number of time points, I don't think there is sufficient sampling of this conformational transition to really narrow down the exact timescale, especially since the ratio of left/right populations is so dependent on the pre-treatment of the sample prior to deuterium exchange. (See 1st comment)

6) The woods plots presented in the Supporting information: (Figures 2-S4, 2-S5, 3-S4, 4-S2, 5-S2, 6-S2) are not conventional Woods plots. Normally the plots would indicate a global threshold for what is deemed to be significant based on the overall error in the dataset. From what I gather the authors used error within an individual peptide to establish significance for each specific peptide, which would be okay, but the authors don't describe the number of replicates or how the p-value was calculated. I would strongly recommend that the authors instead rely on a hybrid significance testing approach, as described recently: (PMID 31099554). What's really alarming with the current approach is that several of the Woods plots shown have data points found to be significantly different that are right at zero on the y-axis.

7) Table 1: The summary of the peptides with observed bimodal behavior should include data from the replicates, particularly for assessment of how consistent the left/right population sizes are across replicates. Instead of just a percentage, the table should report an average and the standard deviation from the replicate measurements. Furthermore, the table should also include peptides that are overlapping with those presented. Based on Figure 2-figure supplement 1, there are at least two other peptides that cover the 899-913 region. These additional peptides should show a similar trend with bimodal profiles and will be important for showing how reproducible the apparent EX1 kinetics are in the dataset.<br /> All available replicates and overlapping peptides should be analyzed to ensure that these percentages reported are consistent across the data. It is also odd that the authors choose to use the 3+ charge state of the WT, but the 2+ for the D614G mutant. If both charge states were present, then both of them should be analyzed to ensure the population distributions are consistent within different charge states.

8) The method for calculating p-values used to assess the significance of a difference in observed deuterium uptake is not described. The manuscript mentions technical replicates, but no specific information as to how many replicates were collected for each time point. These details should be included as they are also part of the summary table that is recommended for the publication of HDX data.

Reviewer #2 (Public Review):

This beautiful study identifies a genetic mechanism controlling colony morphology differences in Burkholderia thailandensis. There is a large region of the genome which can be duplicated or triplicated in a RecA-dependent recombination process, leading to phenotypic changes. In addition to colony morphology differences in cells with one, two, or three copies of the region, other phenotypes like biofilm formation are impacted. This appears to be an unstable genetic change since some of the colony types can interconvert to others after restreaking. The authors are commended for the development of elegant genetic approaches to study and carefully prove the existence of the copy number variation of this genomic region. These approaches will be of great use to the field in studying copy number variation in bacteria far beyond Burkholderia or colony morphology/biofilm formation. Bacteriology has for decades focused on average measurements of a culture, and this study helps usher the field to a new future where we appreciate and measure the behaviors of individual populations of cells within the same culture.

Reviewer #2 (Public Review):

Zhang et al. addressed an intriguing question - whether the presence of mesenchymal stem cells (MSCs) could influence the efficacy of CAR-T therapy. After observing that CAR-T cytotoxicity was strongly inhibited by MSCs by modulating certain correlated immune response pathways, the authors sought to uncover the underlying mechanisms by examining the interaction between MSCs and macrophage, immune escaping mechanisms, and oxidative stress. Notably, the authors discovered that a single gene, STC1, played a major role in reversing the suppression when it was knocked down/out. Although more research is necessary to clarify the signaling pathways, the data presented by the authors were generally well-supported and convincing.

Major points:

1. STC-1 is expressed and secreted by many human cancer cells. This should be discussed in the introduction or discussion with more inter-related background info on both its regulation in cancer cells and secretion pattern into TME. It is important because you state that the STC-1 secreted by MSC has such strong functions, then how about those produced and secreted by cancer cells? Are those also stimulated by macrophages or other components in TME? Do they have possible functions in helping cancer cell to escape the immune surveillance mechanisms?

2. In Figure 4B, using a single marker of IL-1β to show the immune suppressive capability of MSC in vivo is not sufficient, staining for CD4+ and CD8+ should also be included to demonstrate whether MSC could modulate T cell compositions, which can give more direct evidence about MSC's impacts on CAR-T cell.

3. One of the major risks associated with CAR-T therapy is an excessive immune response that causes cytokine release syndrome. MSCs have been used in clinics as a way to suppress immune response including post-CAR-T. What does the author think about using MSC with STC-1 knockout? Can it still help reduce toxicity while maintaining CAR-T efficacy? This might be a potential application.

4. There was a recent study published in Cancer Cell (Lin et al. Stanniocalcin 1 is a phagocytosis checkpoint driving tumor immune resistance. 2021), and they also reported that STC1 negatively correlates with immunotherapy efficacy and patient survival. It should be cited, and in fact, it provided support to the authors' present study with completely different experimental settings.

Reviewer #2 (Public Review):

Kang et. al., model the cortical dynamics, specifically distributions of beta burst durations and proportion of different kind of spatial waves using a firing rate model with local E-I connections and long range and distance dependent excitatory connections. The model also predicts that the observed cortical activity may be a result of non stationary external input (correlated at short time scales) and a combination of two sources of input, global and local.

Overall, the manuscript is very clear, concise and well written. The modeling work is comprehensive and makes interesting and testable predictions about the mechanism of beta bursts and waves in the cortical activity. There are just a few minor typos and curiosities if they can be addressed by the model. Notwithstanding, the study is a valuable contribution towards developing data driven firing rate.

1) The model beautifully reproduces the proportion of different kind of waves that can be seen in the data (Fig 3), however the manuscript does not comment on when would a planar/random wave appear for a given set of parameters (eg. fixed v_ext, tau_ext, c) from the mechanistic point of view. If these spatio-temporal activities are functional in nature, their occurrence is unlikely to be just stochastic and a strong computational model like this one would be a perfect substrate to ask this question. Is it possible to characterize what aspects of the global/local input fluctuations or interaction of input fluctuations with the network lead to a specific kind of spatio-temporal activity, even if just empirically ? Do different waves appear in the same trial simulation or does the same wave type persist over the whole trial? If former, are the transition probabilities between the different wave types uniform, i.e probability of a planar wave to transit into a synchronized wave equal to the probability of a random wave into synchronized wave?

2) Denker et al 2018, also reports a strong relationship between the spatial wave category, beta burst amplitude, the beta burst duration and the velocity (Fig 6E - Denker et. al), eg synchronized waves are fastest with the highest beta amplitude and duration. Was this also observed in the model ?

Reviewer #2 (Public Review):

Luckey et al. investigated the mechanisms by which non-invasive transcutaneous electrical stimulation of the greater occipital nerve (NITESGON) enhances long-term memory. They find that NITESGON applied during or after a word-association task enhances memory recall at a retrieval test 7 days later but not at an immediate test, suggesting NITESGON's memory-enhancing effect involves the consolidation process. They show that NITESGON applied during a second spatial memory task not only enhances later recall for that task, but also for an initial word-association memory task unpaired with stimulation administered before the second task. This highlights NITESGON's ability to retroactively strengthen memories and provides further evidence for behavioral tagging. Furthermore, the authors perform a series of in-depth experiments to examine the mechanisms by which NITESGON enhances memory consolidation. They show that NITESGON increases salivary a-amylase levels, a marker of endogenous noradrenergic activity, and spontaneous eye blink levels, a proxy for dopamine levels, both in support of locus coeruleus involvement. Resting-state fMRI results further suggest NITESGON induces increased communication between the locus coeruleus and hippocampus, suggesting a circuit-based mechanism by which NITESGON enhances memory consolidation. Interestingly, the data also indicate that NITESGON's memory-enhancing effect is not sleep-dependent but is dopamine-receptor-dependent.

The conclusions of this paper are mostly well supported by the data, however, some of the key mechanistic findings lack the appropriate controls required for the authors' claims.

Strengths<br /> 1) The manuscript is written in an easy-to-read manner with clarity for each of the individual experiments conducted.<br /> 2) The authors provide convincing evidence that NITESGON targets the memory consolidation process and enhances long-term but not short-term memory. This provides a unique non-invasive method for enhancing memory and has an important potential impact on neurocognitive disorders.<br /> 3) The manuscript provides convincing evidence that NITESGON increases LC-hippocampus connectivity as well as MTL gamma power, providing a circuit-based mechanism by which stimulation enhances memory.

Weaknesses (major)<br /> 1) Adding control groups (sham stimulation) to Experiment 5 and Experiment 8 would be needed to increase confidence that NITESGON's memory-enhancing effects do not depend on sleep but do depend on dopamine receptor activity.<br /> 2) Task order in the interference study in Experiment 4 was randomized during the first visit for task training as well as during the memory test, however, the word-association and spatial navigation tasks used in Experiments 3 and 4 were not counterbalanced during training or memory testing. Thus, the authors cannot rule out the possibility of order effects.<br /> 3) It is unclear how Experiment 3 and Experiment 4 differ. Percent of words recalled is the measure of memory performance, however, there is not a clear measure of interference in Experiment 4 (i.e. words recalled during Memory task II that were from Memory task I).<br /> 4) In Experiment 5 the learning and test phases for the two sleep groups were conducted at different times of day (sleep group: training at 8pm and testing the next morning at 8am, sleep deprivation group: training at 8am and testing at 8pm) which introduces the possibility of circadian effects between the two groups. Additionally, the memory test occurred at the 12h point for this experiment instead of the 7-day point. Therefore, the authors' conclusions are not addressed by this experiment, and it remains unclear whether the 7-day long-term memory effects of NITESGON are sleep-dependent.

Weaknesses (minor)<br /> 1) Salivary amylase is being used as a proxy of noradrenergic activity, however, salivary amylase levels increase with stress as well, which impacts memory performance. It would be helpful if the authors addressed this and whether they measured other physiological indicators of stress/sympathetic nervous system activation.<br /> 2) Insufficient details of how the blinding experiment was conducted make it difficult to determine whether participants had awareness or subjective responses during the NITESGON stimulation. Adding physiological indicators of heart rate, skin conductance, and respiration would provide a better indicator of a sympathetic nervous system response. Additionally, a series of randomized stimulation and sham trials delivered to the participant would provide a more objective measure of the detectability of the stimulation.<br /> 3) It would be appreciated if the authors could speak to the possible role of the amygdala in the memory-enhancing effects of NITESGON, as this region is a well-known modulator of many types of memory consolidation and is implicated in noradrenergic-related memory enhancement.

Reviewer #2 (Public Review):

The authors have demonstrated a covalent strategy to target the oncogenic K-Ras(G13C) mutation, which is found in about 3,000 cancer patients in the US each year. G13C is a major contributor to G13 mutations, the next hotspot mutation after codon 12. Moreover, there is no approved therapy for G13 mutations and no published inhibitors of any KRAS G13 mutant proteins, making this a particularly important contribution to the rapidly expanding repertoire of RAS inhibitors. A striking difference in comparison to G12 mutations, mutations occurring at Codon 13 exhibit impaired pM-nucleotide binding affinity of K-Ras. This weaker nucleotide affinity offered the authors the opportunity to develop a nucleotide based inhibitor of a RAS protein. With the high nucleophilicity of cysteine mutation, G13C the authors set out to target this mutant oncogene.

The authors developed several covalent molecules derived from GDP/GTP, the natural substrate of K-Ras's nucleotide binding pocket, interestingly, not through the oligophosphate chain (explored by Gray and co-workers in an earlier report) but the 2,3-diol of the ribose. This turned out to be a judicious choice for targeting G13C because of the closer proximity to the 2',3' rather than the phosphates. Previous work by Gray et. al. used the phosphate attachment point for the electrophile but this compromised binding affinity overall-whereas the relatively tolerant modifications at 2',3' led to higher affinity electrophilic ligands. This change led to much tighter binders and effective covalent modifiers through C13. With two co-crystal structures resolved, the authors unambiguously showed the covalent cross-linking between artificial G-nucleotides and K-Ras(G13C).

It is not surprising that one of the major limitations of these GDP-based competitive ligands suffer from permeability issues. GDP or GTP analogs made in this study were not permeable through plasma membrane. The authors nicely worked around these limitations by delivering the fully modified proteins to the cells and measured cell signaling effects. Through electroporation the authors demonstrated the covalent adduct to be able to inhibit downstream signaling by compare introduction of K-Ras WT or K-Ras(G13C) or K-Ras(G13C) covalent adduct.

A number of very intriguing aspects of the covalent adduct were noted which should guide others in the field, including that the adduct with eda-GTP could get hydrolysed to eda-GDP after the covalent modification of the protein--furthermore GAP stimulation of this adduct still occurred. By use of a non-hydrolyzable form of GTP (CP) this could be prevented and could be a very useful method for preventing hydrolysis after introduction in cells--an application Goody and coworkers applied to a previous covalent base adduct.

Overall, the manuscript addresses an important problem relating to whether covalent small molecules can engage K-Ras(G13C) and provided two timely co-crystal structures for future research and development.

Reviewer #2 (Public Review):

The manuscript by Aggad et al., describes an interesting folded structure that links the epidermis to the cuticle in C. elegans. They analyzed the structure by TEM and tomography and found groups of parallel folds in both L4 and adult animals. They show VHA-5 localizes to this structure and have used VHA-5::GFP transgenic reporter to investigate differently cuticle furrow-related genes by RNAi. It is an important step to describe the character of this structure, which the authors named "meisosomes". However, the structure has been reported and well defined as "apical membrane stacks" in previous studies and reviewed by a few articles (Liegeois et al., 2006, Hyenne et al., 2015, Chisholm and Xu, 2012, Cohen and Sundaram 2020). It is very confusing that the authors want to change the name of this structure.

The major problem of this paper is that there is not much new information. It is already known that these stacks exist, VHA-5 localizes to the stacks, cuticle damage induces AMPs, "furrowless" dpy mutants result in complete disorganization of the epidermis, defective cuticle structure causes abnormalities via gene expression, etc. The function of these stacks remains unknown. Another issue is the transgenic reporter of VHA-5::GFP, which is not endogenously expressed, and its puncta intensity only reflects the protein distribution but not the stack structure.

Reviewer #2 (Public Review):

Wu Yang et al. investigated how exophers (large vesicles released from neuronal somas) are degraded. They find that the hypodermal skin cells surrounding the neuron break up the exophers into smaller vesicles that are eventually phagocytosed. The neuronal exophers accumulate early phagosomal markers such as F-actin and PIP2, and blocking actin assembly suppressed the formation of smaller vesicles and the clearance of neuronal exophers. They show the smaller vesicles are labeled with various markers for maturing phagosomes, and inhibiting phagosome maturation blocked the breakdown of exophers in to smaller vesicles. Interestingly, they discover that GTPase ARF-6, effector SEC-10/Exocyst, and the phagocytic receptor CED-1 in the hypodermis are required for efficient production of exophers by neurons.

Strength<br /> The study clearly demonstrates that exophers are eliminated via hypodermal cell-mediated phagocytosis. Exophers are broken down into smaller vesicles that accumulate phagocytic markers, and inhibiting this process shows that exophers are not resolved. The paper does a thorough examination of various markers and mutants to demonstrate this process.

The hypodermal cells not only engulf these small vesicles, but they also play a role in the formation of exophers. Exopher production is reduced when ARF-6, SEC-10, or CED-1 are knocked down in the hypodermis. This is intriguing because phagocytosis is a critical step in the final elimination of cells, but in this unique situation, it appears that the neuron fails to extrude the exopher without phagocytes.

Weakness

Non-professional phagocytes engulfing cell corpses and many other types of cellular debris (e.g. degenerating axons) have been shown in multiple systems and the observations here are not surprising. Many of the markers used in the study are well-established phagocytic markers and do not bring forward a new technological advance.

What's interesting is that the breakdown of exophers into smaller vesicles and eventual clearance follows a different sequence of events than macrophages. Exophers appear to undergo phagosomal fission before interacting with lysosomes. This would be difficult to appreciate by a general reader.

While the paper has strengths, it appears that the message is not clear. The title suggests that the reader will learn about how ARF-6 and CED-1 control exopher extrusion. Although this observation is intriguing and maybe the main point of the paper, there does not appear to be a substantial amount of data to support this claim. The only data to back this up is in the final figure and the majority of the paper is focused on how hypodermal cells phagocytose exophers.

To show exopher secretion is dependent on the hypodermal cells-

1. Could authors induce exopher production through other means? And test any involvement of CED-1? For example, authors note exopher production increases under stress conditions including expression of mutant Huntingtin protein. It would be intriguing if loss of CED-1 would be sufficient to block or reduce exopher production in that context and would highlight an exciting role for phagocytic cell types.<br /> 2. It is not clear if the CED-1 localization to the exopher is due to CED-1 expression during phagocytosis or is it involved in the extrusion. Perhaps the basal level of CED-1 is important for the extrusion but the strong expression is important for recognition of the exopher.<br /> 3. While the data with ttr-52 and anoh-1 alleles is compelling, do we know that exophers actually expose PS? Especially since at a certain point, the exopher is still attached to the neuronal soma. Is PS still exposed by exopher in CED-1 background?<br /> 4. What is the fate of a neuron that is unable to produce exophers? Could one look at lifespan of ALMR neuron in CED-1, ARF-6 or Sec-10 allele (potentially with specificity to hypodermis)?

Reviewer #2 (Public Review):

In this manuscript titled "S-adenosylmethionine synthases specify distinct H3K4me3 populations and gene expression patterns during heat stress", the authors Godbole et al investigated how C. elegans SAM synthases, SAMS-1 and SAMS-4, affected gene expression, H3K4 trimethylation (H3K4me3), and the survival under heat stress. They found in this study that SAMS-4 was required for survival during heat shock. They reasoned that SAM supplied by SAMS-4 but not SAMS-1 might be responsible for generating H3K4me3 under heat shock and claimed that the two SAM synthases differentially affected histone methylation and thus gene expression in the heat shock response. This study suggested a stress-responsive mechanism by which the specific isozyme of SAM synthetase provided a specific pool of cellular SAM for H3K4me3. Overall, this study is interesting but descriptive. Lacking necessary controls and mechanistic details weakened the significance of this work.

Strengths: Very interesting survival phenotypes in the loss of different SAM synthetases; technical success in CUT&tag in C. elegans.

Weaknesses: No clear conclusion can be drawn about whether and how SAM synthetases affect H3K4me3.

Reviewer #2 (Public Review):

The authors use a series of subsampling methods based on phylogenetic placement and geographic setting, informed by human movement data to control for differences in sampling of SARS-CoV-2 genomes across countries. Of note, the authors show that 2 variants likely arose in Mexico and spread via multiple introductions globally, while other variant waves were driven by repeat introductions into Mexico from elsewhere. Finally, they use human mobility data to assess the impact of movement on transmission within Mexico.

Overall, the study is well done and provides nice data on an under-studied country. The authors take a thoughtful approach to subsampling and provide a very thorough analysis. Because of the care given to subsampling and the great challenge that proper subsampling represents for the field of phylodynamics, the paper would benefit from a more thorough exploration of how their migration-informed subsampling procedure impacts their results. This would not only help strengthen the findings of the paper but would likely provide a useful reference for others doing similar studies. Additionally, I would suggest the authors provide a bit more discussion of this subsampling approach and how it may be useful to others in the discussion section of the paper.

Reviewer #2 (Public Review):

In "Complex plumages spur rapid color diversification in island kingfishers (Aves: Alcedinidae)", Eliason et al. link intraspecific plumage complexity with interspecific rates of plumage evolution. They demonstrate a correlation here and link this with the distinction between island and mainland taxa to create a compelling manuscript of general interest on drivers of phenotypic divergence and convergence in different settings.

This will be a fantastic contribution to the literature on the evolution of plumage color and pattern and to our understanding of phenotypic divergence between mainland and island taxa. A few key revisions can help it get there. This paper needs to get, fairly quickly, up to a point where the difference between plumage complexity and color divergence is defined carefully. That should include hammering home that one is an intraspecific measure, while one is an interspecific measure. It took me three reads of the paper to be able to say this with confidence. Leading with that point will greatly improve the paper if that point gets forgotten then the premise of the paper feels very circular.

Also importantly, somewhere early on a hypothesized causal pathway by which insularity, plumage complexity, and color divergence interact needs to be laid out. The analyses that currently follow are good ones, and not wrong, but it's challenging to assess whether they are the right ones to run because I'm not following the authors' reasoning very well here. I think it's possible a more holistic analysis could be done here, but I'll refrain from any such suggestions until I better get what the authors are trying to link.

We also need something near the top that tells us a bit more about the biogeography of kingfishers. Are kingfisher species always allopatric? I know the answer is no, but not all readers will. What I know less well though is whether your insular species are usually allopatric. I suspect the answer is yes, but I don't actually know.

In short, how do the authors think allopatry/sympatry/opportunity for competition link to mainland vs. island link to plumage complexity? And rates of color evolution? Make this clear upfront.

Reviewer #2 (Public Review):

Huang and colleagues present data from experiments assessing the role of cognitive inflexibility in the vulnerability to weight loss in the activity-based anorexia paradigm in rats. The experiments employ a novel in-home cage touchscreen system. The home cage touch screen system allows reduced testing time and increased throughput compared with the more widely used systems resulting in the ability to assess ABA following testing cognitive flexibility in relatively young female rats. The data demonstrate that, contrary to expectations, cognitive inflexibility does not predispose to greater ABA weight loss, but instead, rats that performed better in the reversal learning task lost more weight in the ABA paradigm. Prior ABA exposure resulted in poorer learning of the task and reversal. An additional experiment demonstrated that rats that had been trained in reversal learning resisted weight loss in the ABA paradigm. The findings are important and are clearly presented. They have implications for anorexia nervosa both in terms of potentially identifying those at risk also in understanding the high rates of relapse.

Reviewer #2 (Public Review):

The manuscript describes a novel transparent electrode array and demonstrates its combination with two-photon calcium imaging in mouse neocortex. Using a computational model, the authors propose that surface multi-unit activity mainly reflects L1 axonal activity and they find a small population of L2/3 neurons that correlates with this activity. While the multi-modal approach with the innovative device in our view is interesting and potentially useful, we have several technical and scientific concerns that should be addressed by the authors.

Strengths:<br /> We find the general scope of this manuscript, to establish a hybrid electrophysiological and optical approach for studying neocortical activity, very interesting and relevant. The authors provide a compelling use case for combined ECoG and two-photon imaging. While extracellular action potentials have been recorded from the cortical surface, the underlying source is unknown and the device and techniques introduced by the authors are appropriate to address this question. The introduced device can be implanted chronically and has good long-term stability, providing longitudinal optical and electrical recordings from the cortex. The authors perform recordings in awake, head-fixed animals which provides the opportunity to relate ECoG and single-cell data to the animal's behavioral state. The combination of empirical data and biophysical modelling is a powerful means by which to answer such questions.

Weaknesses:<br /> The central claim of the paper relies heavily on the computational model and the physiological data could be more completely analyzed. Based on a sample of 136 L2/3 neurons the authors find a small proportion (13%) that correlates with the ECoG MUA (eMUA). Based on this, they use a model to show that ECoG MUA likely reflects axonal spikes. They then posit that these layer 2/3 neurons are tightly correlated to the layer 1 input. The presentation of their data and the specifics of their model makes it difficult to assess the validity of this claim. They do not sufficiently discuss possible confounds in the data, caveats of their model, or alternative explanations of the observed low proportion of L2/3 neurons that correlate with the ECoG MUA.

Most relevantly, the authors do not measure single units with their ECoG. The eMUA is a complex mixture of many neuronal sources, and interpretation is therefore difficult. They relate the calcium transients of small populations of single L2/3 neurons with the aggregate measure of population activity reflected in eMUA. It is possible that the eMUA reflects population activity in the local circuit and might therefore have a low correlation with individual single units. Critically, there is no information on the sensitivity of calcium recordings. Do the imaging data detect single action potentials, or are they biased to bursts of more than 1 AP?

The analysis pipeline and values used for computing the correlation coefficients are counterintuitive. The fluorescence data are first interpolated from 15 Hz to 4 kHz and then both eMUA and imaging data are effectively down-sampled to 2 Hz. A single correlation coefficient is then estimated for each neuron, regardless of behavioral state, even though the authors themselves show that the activity of single neurons and the ECoG signal depend on the state of the animal.

There is also insufficient information on the weight of the implant and its effect on mouse behavior. How does the movement of implanted and non-implanted mice differ? Must mice be singly housed? Finally, the modeling parameters are highly specific, using independently driving spikes, while the activity of neurons can be highly correlated. Likewise, the contribution of tangentially oriented axons that could relate to long-range connections conveying information related to the animal's motion or level of arousal is not considered. The manuscript would benefit from further analysis of the physiological data, consideration of alternative explanations and forthright discussion of limitations and caveats of their device and approach.

Reviewer #2 (Public Review):

Mitochondrial dysfunction is now widely recognized as an underlying cause of many human diseases. In many cases, however, very little is known about the molecular etiology of mitochondrial disorders. In this comprehensive study Coyne et al. describe a mechanism by which dominant pathogenic variants of adenine nucleotide translocase Aac2p/ANT1 impair mitochondrial protein import pathway leading to cytotoxicity and mitochondrial dysfunction. By elucidating the fate of this protein in yeast, human cell culture, and murine models, the authors showed that mutant Aac2p variants accumulate the outer membrane translocase TOM complex jamming up mitochondrial protein import and affecting TIM22-mediated carrier import pathway, thus causing proteostatic stress. Furthermore, they showed that the i-AAA protease Yme1p and not the ubiquitin-proteasome system is responsible for proteolytic removal of the mutant Aac2p variants. Finally, the demonstrated that mitochondrial protein import clogging caused by the ANT1 A114P, A123D variant causes severe dominant neurodegenerative phenotype in mice, which resembles neuromuscular disease manifestations in humans. The authors propose this as a candidate pathological mechanism in ANT1-linked human disorders and by extension, to other diseases arising from defects in mitochondrial protein import.

Overall, this is a well-designed and thoroughly executed study that reports on a novel aspect of ANT1 associated dysfunction and provides mechanistic insights into the pathological mechanisms at play.

Reviewer #2 (Public Review):

The authors' goal is to uncover the most likely method used by mammals to make choices based on a time-limited stream of noisy incoming sensory data. To achieve this, they analyze with great rigor several large datasets obtained from tightly controlled two-alternative forced choice behavioral experiments. The tight control of fluctuating incoming sensory input over a large number of trials allows the authors to extract the influence of different components of that input on the behavioral choice. The conditional analysis, showing the impact of early information on the importance of later information, or vice versa, is an excellent new technique.

They compare three models and find one based on a form of weighted integration of evidence across time is very strongly favored compared to models in which only short segments of the sensory input are used, or the most extreme fluctuations of the sensory input generate a response. Overall, the results clearly do indicate that the integration-like family of models outperforms the other families. The authors succeed well in giving a fair comparison of the different families of models, allowing multiple parameters to be optimized to test different versions of each model.

It should be said that the integration model is a strange type of integration, as the weight of incoming evidence depends on the time at which it arrives-by a factor of 4 in one animal (Fig. 2)-and with an over-weighting of evidence in the middle of the sequence in one case, while the more expected effects of primacy and recency (over-weighting of early or late evidence) in another. It would be nice to see more discussion of how these differences might arise across animals, what it may say about the neural circuit performing such unbalanced integration, and how suboptimal such differential weighting of evidence is. This is important, as in some discussions integration is contrasted with state transitions, which are akin to integration over a barrier, and not necessarily ruled out by the models compared here.

Reviewer #2 (Public Review):

The work presented by Jordan and Keller aims at understanding the role of noradrenergic neuromodulation in the cortex of mice exploring a visual virtual environment. The authors hypothesized that norepinephrine released by Locus Coeruleus (LC) neurons in cortical circuits gates the plasticity of internal models following visuomotor prediction errors. To test this hypothesis, they devised clever experiments that allowed them to manipulate visual flow with respect to locomotion to create prediction errors in visuomotor coupling and measure the related signals in LC axons innervating the cortex using two-photon calcium imaging. They observed calcium responses proportional to absolute prediction errors that were non-specifically broadcast across the dorsal cortex. To understand how these signals contribute to computations performed by V1 neurons in layers 2/3, the authors activated LC noradrenergic inputs using optogenetic stimulations while imaging calcium responses in cortical neurons. Although LC activation had little impact on evoked activity related to visuomotor prediction errors, the authors observed changes in the effect of locomotion on visually evoked activity after repeated LC axons activation that were absent in control mice. Using a clever paradigm where the locomotion modulation index was measured in the same neurons before and after optogenetic manipulations, they confirmed that this plasticity depended on the density of LC axons activated, the visual flow associated with running, and the concurrent visuomotor coupling during LC activation. Based on similar locomotion modulation index dependency on speed observed in mice that develop only with visuomotor experience in the virtual environment, the authors concluded that changes in locomotion modulation index are the result of experience-dependent plasticity occurring at a much faster rate during LC axons optogenetic stimulations.

The study provides very compelling data on a timely and fascinating topic in neuroscience. The authors carefully designed experiments and corresponding controls to exclude any confounding factors in the interpretation of neuronal activity in LC axons and cortical neurons. The quality of the data and the rigor of the analysis are important strengths of the study. I believe this study will have an important contribution to the field of system neuroscience by shedding new light on the role of a key neuromodulator. The results provide strong support for the claims of the study. However, I also believe that some results could have been strengthened by providing additional analyses and experimental controls. These points are discussed below.

Calcium signals in LC axons tend to respond with pupil dilation, air puffs, and locomotion as the authors reported. A more quantitative analysis such as a GLM model could help understand the relative contribution (and temporal relationship) of these variables in explaining calcium signals. This could also help compare signals obtained in the sensory and motor cortical domains. Indeed, the comparison in Figure 2 seems a bit incomplete since only "posterior versus anterior" comparisons have been performed and not within-group comparisons. I believe it is hard to properly assess differences or similarities between calcium signal amplitude measured in different mice and cranial windows as they are subject to important variability (caused by different levels of viral expression for instance). The authors should at the very least provide a full statistical comparison between/within groups through a GLM model that would provide a more systematic quantification.

Previous studies using stimulations of the locus coeruleus or local iontophoresis of norepinephrine in sensory cortices have shown robust responses modulations (see McBurney-Lin et al., 2019, https://doi.org/10.1016/j.neubiorev.2019.06.009 for a review). The weak modulations observed in this study seem at odds with these reports. Given that the density of ChrimsonR-expressing axons varies across mice and that there are no direct measurements of their activation (besides pupil dilation), it is difficult to appreciate how they impact the local network. How does the density of ChrimsonR-expressing axons compare to the actual density of LC axons in V1? The authors could further discuss this point.

In the analysis performed in Figure 3, it seems that red light stimulations used to drive ChrimsonR also have an indirect impact on V1 neurons through the retina. Indeed, figure 3D shows a similar response profile for ChrimsonR and control with calcium signals increasing at laser onset (ON response) and offset (OFF response). With that in mind, it is hard to interpret the results shown in Figure 3E-F without seeing the average calcium time course for Control mice. Are the responses following visual flow caused by LC activation or additional visual inputs? The authors should provide additional information to clarify this result.

Some aspects of the described plasticity process remained unanswered. It is not clear over which time scale the locomotion modulation index changes and how many optogenetic stimulations are necessary or sufficient to saturate this index. Some of these questions could be addressed with the dataset of Figure 3 by measuring this index over different epochs of the imaging session (from early to late) to estimate the dynamics of the ongoing plasticity process (in comparison to control mice). Also, is there any behavioural consequence of plasticity/update of functional representation in V1? If plasticity gated by repeated LC activations reproduced visuomotor responses observed in mice that were exposed to visual stimulation only in the virtual environment, then I would expect to see a change in the locomotion behaviour (such as a change in speed distribution) as a result of the repeated LC stimulation. This would provide more compelling evidence for changes in internal models for visuomotor coupling in relation to its behavioural relevance. An experiment that could confirm the existence of the LC-gated learning process would be to change the gain of the visuomotor coupling and see if mice adapt faster with LC optogenetic activation compared to control mice with no ChrimsonR expression. Authors should discuss how they imagine the behavioural manifestation of this artificially-induced learning process in V1.

Finally, control mice used as a comparison to mice expressing ChrimsonR in Figure 3 were not injected with a control viral vector expressing a fluorescent protein alone. Although it is unlikely that the procedure of injection could cause the results observed, it would have been a better control for the interpretation of the results.

Reviewer #2 (Public Review):

Liu, Chen and Szolnoki investigated the coupled dynamics of individual cooperation level and collective risk (i.e. the probability of future loss of all endowment). Their model encapsulates the assumption that not only does risk affect individual decision-making, but that there is also feedback between individual strategies, i.e. the level of individual contributions, and the level of risk. The authors investigate two main forms of this feedback, considering strategies linearly affecting the evolution of risk as well as non-linear (exponential) feedback. They mathematically analyze both these dynamical systems, identifying the fixed points, parametrized by the enhancement rate of defection u and the cost/benefit ratio of cooperation, and analyzing the stability of these points. The results of this systematic analysis show that, while the undesirable equilibrium state of full defection and high risk is always stable independent of the form of the feedback, the coevolutionary dynamics can exhibit a wide range of behaviors. In particular, depending on the initial conditions (frequency of cooperators), sustainable cooperation levels can be reached. This can happen by convergence to a stable fixed point with positive cooperation rates; additionally, the authors also prove that a Hopf bifurcation can take place in the system, such that a stable limit cycle with persistent oscillations in strategy and risk state can appear. Interestingly, the evolutionary outcomes do not depend significantly on the character of the feedback between strategy and risk. These theoretical results are supplemented by representative numerical examples, visualizing the phase plane and temporal dynamics of cooperation and risk for particular initial conditions and parameters.

The main conclusions of the paper are fully supported by the results, as they are directly derived from the comprehensive mathematical analysis of the coevolutionary dynamics and do not rely on external data. Additionally, the stability analysis is clean and the comprehensive numerical examples deepen the reader's understanding. Another strength of the paper is the fact that the considered model is complex enough to be able to still represent somewhat realistic settings while being simple enough to rigorously analyze. One particularly interesting finding is the fact that the exact form of the risk feedback function or its speed does not play a very significant role in the outcome of the dynamics.

The paper hence adds to the literature on the coevolution of environment and strategies in a productive way and will be of interest to various research communities in mathematical biology/ecology and decision-making.

Reviewer #2 (Public Review):

Fever is an ancient and conserve response to infection from invertebrates to humans. However, the functional benefits of engaging fever responses are not clear, especially when it comes to moderate fever responses where pathogen growth Is not impaired by temperature. This study aims to develop a natural in vivo fever model in fish that overcomes many of the technical challenges to investigate fever in mammals. In ectotherms, fever is manifested as a behavioral response by which animals move to warmer temperatures. By using this new developed in vivo behavioral ring, the present study reveals new functional roles for fever in vertebrates. Additionally, upon infection, sickness behavior did not only consist of fever, but two novel lethargic behaviors not previously described in fish. The experimental evidence is compelling and supports the authors' conclusions. The data presented strongly indicates that moderate fever levels are critical for fine tuning immune responses to pathogens. By triggering earlier but weaker antimicrobial defenses, moderate fever in teleosts results in controlled inflammation and improved wound healing. These exciting results reveal novel roles of fever as a way to minimize the collateral damage that inflammatory responses often cause to the host. This work advances our conceptual view of the evolutionary advantages that fever brings to host-pathogen interactions. The technological development of the annular temperature preference tank can now become the gold standard platform to investigate the consequences of fever during teleost infection.

Reviewer #2 (Public Review):

The manuscript "A human tubular aggregate myopathy mutation unmasks STIM1-independent rapid inactivation of Orai1 channels" describes the effects of a disease-related gating checkpoint at the TM1-TM2 interface. The authors suggest that the mutation of one of the two oppositely located positions T92 - L138 into a large amino acid leads to constitutive activity due to steric clash. Notably, the mutants also exhibit robust Ca2+ dependent inactivation (CDI) suggesting that this feature is intrinsic to the Orai1 channel, and not as previously thought a key process that is triggered by STIM1. Nevertheless, STIM1 is able to fine-tune Ca2+ selectivity and CDI.

This study provides an extensive electrophysiological characterization of the tubular aggregate myopathy (TAM)-disease-related Orai1 L138F mutation and based on mutational studies provides compelling evidence that constitutive activity is caused by a steric clash between TM1/TM2 Orai helices. Additionally, yet unexpectedly, the constitutive Orai1 mutants exhibit CDI behavior which is thoroughly characterized by experiments using various intracellular Ca2+-buffering reagents. By this, it is proposed that the Orai1 T92W mutant shows increased sensitivity to intracellular Ca2+. This is further revealed in a sophisticated tow step protocol, which would profit from additional control experiments. The unusual behavior of the T92W Orai1 mutant is "corrected" to that of the Orai1 wild-type form by the presence of STIM1.

Reviewer #2 (Public Review):

Here the authors questioned the regulation and functional roles of anti-sense transcripts at the 3'end of an important flowering-time regulator FLC.

The authors present compelling genetic, molecular biology, transgene, and biochemical data on the molecular details of how COOLAIR is induced by cold temperatures. They report that cold-induction of COOLAIR is mediated by C-repeat/dehydration-responsive elements (CRT/DREs) at the 3'-end of the FLC and relatively small deletions of the CRT/DREs prevent cold-induction of COOLAIR. They also report that long-term cold results in an increase in the expression of CRT/DRE BINDING FACTORs (CBFs) that bind to the CRT/DREs and result in the activation of genes containing CRT/DREs.

Interestingly, in lines in which COOLAIR is not induced the vernalization proceeds normally with respect to flowering behavior and cold-mediated FLC chromatin changes, a result that is at odds with some publications but consistent with other reports.

The major strength of this research is the comprehensive battery of relevant assays used to address their aim. Using ChIP they demonstrate CBF3 directly binds to the 3'end of FLC in vivo, and of less interest, but still very relevant, CBF3 binds to a CRT/DRE motif containing oligo-nucleotides in vitro using an EMSA. Using CRISPR-mediated genetic deletion of these sequences in vivo, they demonstrated that the downstream antisense transcripts are no longer transcribed. Interestingly, in these CRISPR mutants or genetic mutants of higher-order CBF mutants, the vernalisation response (chromatin modifications) is not impaired. They also show that CBF mRNA transcription occurs in at least two waves, an early peak, and over a prolonged cold period.

While the CRISPR genetic motif mutants are relatively small, a few hundred base pairs, ideally they would have been smaller if only encompassing the CRT/DRE motif.

The authors clearly achieved their aims and the presented results strongly support their conclusions. The compelling data clearly questions a widely held view in the vernalisation field. The presented methods can be widely transferable to a broader research community.

Reviewer #2 (Public Review):

Recent work in the neurosciences has suggested that decision making in most domains consists of computations at multiple stages. In value-based choices, initial evidence is perceived, categorized, and evaluated, then accumulated over time in a process that essentially compares the relative value of two options, until the accumulated evidence passes a threshold for choice. Although previous work has shown that this basic structure also applies to decisions in the domain of prosocial choice, it has remained unclear at what stage of this decision process variation in prosocial choices arises. The authors aimed to resolve this issue by using a combination of computational modeling and EEG, applied to a choice paradigm that evokes variation in altruistic behavior through two distinct routes: exogenous variation in the inequality context of a choice (i.e., advantageous vs. disadvantageous inequality), and endogenous variation as a function of individual differences in prosocial preferences.

One of the strengths of this approach (particularly the use of EEG) over previous studies is that the authors can use the timing and nature of the EEG signals to disentangle both HOW preferences evolve, and WHEN differences evoked by context or individual preference emerge. This work very clearly shows that late-stage choice comparison processes, locked to the time of response (i.e., the evidence accumulation phase of a choice) are likely NOT where variations in altruistic choice arise. Instead, the evidence points to a set of distinct signals that occur time-locked to the onset of an option that enables participants to make a choice, which implies that the computations driving choice behavior likely occur at the perceptual and/or valuation stage. This is not wholly surprising, but is interesting and important to verify.

A second potential strength of this approach is that the methodology allows the authors to determine whether the observed signals more strongly resemble encoding of the overall magnitude of outcomes to self and others, or instead are more related to signals sensitive to distributional values (i.e., inequality/fairness). The evidence here paints a quite intriguing, but somewhat mixed picture, in my view, and I think needs to come with more caveats than the authors currently acknowledge. The authors claim that their evidence supports the idea that people are making choices by considering inequality, rather than by computing outcomes for self or other directly. The lack of a consistently-signed association between EEG signals and either self or other outcome magnitude across contexts is not consistent with the idea that values are encoded in terms of self and other, which has sometimes been argued from fMRI data. However, I also do not think they are fully consistent with the authors' claims that they are observing signals related directly to fairness considerations either. Fairness/inequality, as typically defined by economic models of social preferences, involves computing the differences between self and other payoffs. The authors find ERP signals scaling with payoff changes for self but not other. Those signals do move in opposite directions in the two inequality contexts, which is why the authors interpret this as meaning that these ERP signals represent some calculation related to fairness. But there is no sensitivity of these signals to payoff change for the other, suggesting that these signals are not precisely driven by fairness as it is canonically conceived. Instead, it seems that these signals might reflect something about how people orient to self outcomes differently in the two contexts. This actually is an intriguing finding, but is somewhat difficult to interpret, since it is not wholly clear what these ERP signals represent (i.e., are they related to perception, valuation, attention, etc.?). Moreover, as the authors acknowledge in their discussion, the design of the study, with its presentation of a first option that determines the inequality context and a second option that determines the relative values of the options, means that it is difficult to know when and how one would expect to see raw self and other values as opposed to comparative value signals related to differences in self and other. Finally, the sensitivity (or lack thereof) of EEG to more subcortical signals means that it is not clear one is getting a whole picture of the computations driving choice. Thus, I think the conclusion that behavior is related to inequality processing rather than to a focus on self- and other-payoffs directly, while intriguing, needs to be tempered a bit.

What also seems somewhat puzzling is that the behavioral and neural signals do not always seem fully consistent with one another, or with prior research. For example, behaviorally people seem to put more weight on others' payoff changes in the advantageous inequality context. And in other work (Morishima et al., 2012), it is behavioral variation in the advantageous context that correlates with neural (anatomical) variation. Yet here, there are no EEG signals that encode changes in other outcomes as a main effect in the advantageous context, and it is individual variation in encoding of others' payoffs in the DISADVANTAGEOUS context that relate to individual differences in equality-seeking in that context. Thus, it is actually in the context where one would expect people to be paying *less* attention to other outcomes (based on the modeling parameters) that neural signals seem to be *more* sensitive to those outcomes. This doesn't mean that these signals aren't interesting, but it does point to a need to more fully understand what they represent before coming to firm conclusions about what they actually mean, computationally and psychologically.

Thus, I think this paper will likely have an impact on the field largely for the intriguing questions it raises about how people make altruistic choices rather than for providing definitive answers. This is an important contribution and researchers will, I expect, find this paper thought-provoking.

Reviewer #2 (Public Review):

The authors provide here a very careful and thorough analysis of the effects of tomosyn elimination in neurons, in relation to dense-core vesicles. They find strong effects on vesicle generation (size, protein composition), but not on vesicle exocytosis, in spite of tomosyn's known interaction with the exocytosis SNAREs.

Reviewer #2 (Public Review):

In this manuscript, Polyák et al. report detailed and systematic functional, electrocardiographic, electrophysiologic (both in vivo and in vitro experiments) and histological analysis in a large animal (canine) model of exercise to assess risk of ventricular arrhythmia susceptibility. They find that exercise-trained dogs have a slower heart rate (not accounted by heightened vagal tone alone and consistent with recent work from Denmark), an increased ventricular mass and fibrosis, APD lengthening due to repolarisation abnormality, enhanced HCN4 expression and decreased outward potassium channel density together with increased ventricular ectopic beats and ventricular fibrillation susceptibility (open-chest burst pacing). The authors suggest these changes as underlying the risk of VA in athletes, and appropriately caution against consigning the beneficial effects of exercise. In general, this study is well done, reasonably well-written, with reasonable conclusions, supported by the data presented and is much needed. There are some methodological, however, given the paucity of experimental data in this area, I think it would still be additive to the literature.

Strengths<br /> 1. This is an area with very limited experimental data- this is an area of need.<br /> 2. The study, in general seems to be well-conducted with two clear groups<br /> 3. The use of a large animal model is appropriate<br /> 4. The study findings, in general, support the authors conclusions<br /> 5. The authors have shown some restraint in their conclusions and the limitations section is detailed and well written.

Weaknesses<br /> 1. There are some methodological issues:<br /> a. Authors should explain what the conditioning protocol was and why it was necessary.<br /> b. The rationale for the exercise parameters chosen needs to be presented.<br /> c. Open chest VF induction was a limitation, and it was unnecessary.<br /> d. A more refined VT/VF induction protocol was required. This is a major limitation to this work.<br /> e. The concept of RV dysfunction has not been considered in the study and its analysis.<br /> f. The lack of a quantitative measure for fibrosis is a limitation.<br /> 2. Statistical analysis requires further detail (checking of normality of the data/appropriate statistical test).<br /> 3. The use of Volders et al. study as a corollary in the discussion does not seem justified given that this study used AV block induced changes as an acquired TdP model.

Reviewer #2 (Public Review):

The authors study M1 cortical recordings in two non-human primates performing straight delayed center-out reaches to one of 8 peripheral targets. They build a model for the data with the goal of investigating the interplay of inferred external inputs and recurrent synaptic connectivity and their contributions to the encoding of preferred movement direction during movement preparation and execution epochs. The model assumes neurons encode movement direction via a cosine tuning that can be different during preparation and execution epochs. As a result, each type of neuron in the model is described with four main properties: their preferred direction in the cosine tuning during preparation (denoted by θ_A) and execution (denoted by θ_B) epochs, and the strength of their encoding of the movement direction during the preparation (denoted by η_A) and execution (denoted by η_B) epochs. The authors assume that a recurrent network that can have different inputs during the preparation and execution epochs has generated the activity in the neurons. In the model, these inputs can both be internal to the network or external. The authors fit the model to real data by optimizing a loss that combines, via a hyperparameter α, the reconstruction of the cosine tunings with a cost to discourage/encourage the use of external inputs to explain the data. They study the solutions that would be obtained for various values of α. The authors conclude that during the preparatory epoch, external inputs seem to be more important for reproducing the neuron's cosine tunings to movement directions, whereas during movement execution external inputs seem to be untuned to movement direction, with the movement direction rather being encoded in the direction-specific recurrent connections in the network.

Major:

1) Fundamentally, without actually simultaneously recording the activity of upstream regions, it should not be possible to rule out that the seemingly recurrent connections in the M1 activity are actually due to external inputs to M1. I think it should be acknowledged in the discussion that inferred external inputs here are dependent on assumptions of the model and provide hypotheses to be validated in future experiments that actually record from upstream regions. To convey with an example why I think it is critical to simultaneously record from upstream regions to confirm these conclusions, consider two alternative scenarios: I) The recorded neurons in M1 have some recurrent connections that generate a pattern of activity that is based on the modeling seems to be recurrent. II) The exact same activity has been recorded from the same M1 neurons, but these neurons have absolutely no recurrent connections themselves, and are rather activated via purely feed-forward connections from some upstream region; that upstream region has recurrent connections and is generating the recurrent-like activity that is later echoed in M1. These two scenarios can produce the exact same M1 data, so they should not be distinguishable purely based on the M1 data. To distinguish them, one would need to simultaneously record from upstream regions to see if the same recurrent-like patterns that are seen in M1 were already generated in an upstream region or not. I think acknowledging this major limitation and discussing the need to eventually confirm the conclusions of this modeling study with actual simultaneous recordings from upstream regions is critical.

2) The ring network model used in this work implicitly relies on the assumption that cosine tuning models are good representations of the recorded M1 neuronal activity. However, this assumption is not quantitatively validated in the data. Given that all conclusions depend on this, it would be important to provide some goodness of fit measure for the cosine tuning models to quantify how well the neurons' directional preferences are explained by cosine tunings. For example, reporting a histogram of the cosine tuning fit error over all neurons in Fig 2 would be helpful (currently example fits are shown only for a few neurons in Fig. 2 (a), (b), and Figure S6(b)). This would help quantitatively justify the modeling choice.

3) The authors explain that the two-cylinder model that they use has "distinct but correlated" maps A and B during the preparation and movement. This is hard to see in the formulation. It would be helpful if the authors could expand in the Results on what they mean by "correlation" between the maps and which part of the model enforces the correlation.

4) The authors note that a key innovation in the model formulation here is the addition of participation strengths parameters (η_A, η_B) to prior two-cylinder models to represent the degree of neuron's participation in the encoding of the circular variable in either map. The authors state that this is critical for explaining the cosine tunings well: "We have discussed how the presence of this dimension is key to having tuning curves whose shape resembles the one computed from data, and decreases the level of orthogonality between the subspaces dedicated to the preparatory and movement-related activity". However, I am not sure where this is discussed. To me, it seems like to show that an additional parameter is necessary to explain the data well, one would need to compare fit to data between the model with that parameter and a model without that parameter. I don't think such a comparison was provided in the paper. It is important to show such a comparison to quantitatively show the benefit of the novel element of the model.

5) The model parameters are fitted by minimizing a total cost that is a weighted average of two costs as E_tot = α E_rec + E_ext, with the hyperparameter α determining how the two costs are combined. The selection of α is key in determining how much the model relies on external inputs to explain the cosine tunings in the data. As such, the conclusions of the paper rely on a clear justification of the selection of α and a clear discussion of its effect. Otherwise, all conclusions can be arbitrary confounds of this selection and thus unreliable. Most importantly, I think there should be a quantitative fit to data measure that is reported for different scenarios to allow comparison between them (also see comment 2). For example, when arguing that α should be "chosen so that the two terms have equal magnitude after minimization", this would be convincing if somehow that selection results in a better fit to the neural data compared with other values of α. If all such selections of α have a similar fit to neural data, then how can the authors argue that some are more appropriate than others? This is critical since small changes in alpha can lead to completely different conclusions (Fig. 6, see my next two comments).

6) The authors seem to select alpha based on the following: "The hyperparameter α was chosen so that the two terms have equal magnitude after minimization (see Fig. S4 for details)". Why is this the appropriate choice? The authors explain that this will lead to the behavior of the model being close to the "bifurcation surface". But why is that the appropriate choice? Does it result in a better fit to neural data compared with other choices of α? It is critical to clarify and justify as again all conclusions hinge on this choice.

7) Fig 6 shows example solutions for 2 close values of α, and how even slight changes in the selection of α can change the conclusions. In Fig. 6 (d-e-f), α is chosen as the default approach such that the two terms E_rec and E_ext have equal magnitude. Here, as the authors note, during movement execution tuned external inputs are zero. In contrast, in Fig. 6 (g-h-i), α is chosen so that the E_rec term has a "slightly larger weight" than the E_ext term so that there is less penalty for using large external inputs. This leads to a different conclusion whereby "a small input tuned to θ_B is present during movement execution". Is one value of α a better fit to neural data? Otherwise, how do the authors justify key conclusions such as the following, which seems to be based on the first choice of α shown in Fig. 6 (d-e-f): "...observed patterns of covariance are shaped by external inputs that are tuned to neurons' preferred directions during movement preparation, and they are dominated by strong direction-specific recurrent connectivity during movement execution".

8) It would be informative to see the extreme case of very large and very small α. For example, if α is very large such that external inputs are practically not penalized, would the model rely purely on external inputs (rather than recurrent inputs) to explain the tuning curves? This would be an example of the hypothetical scenario mentioned in my first comment. Would this result in a worse fit to neural data?

9) The authors argue in the discussion that "the addition of an external input strength minimization constraint breaks the degeneracy of the space of solutions, leading to a solution where synaptic couplings depend on the tuning properties of the pre- and post-synaptic neurons, in such a way that in the absence of a tuned input, neural activity is localized in map B". In other words, the use of the E_ext term, apparently reduces "degeneracy" of the solution. This was not clear to me and I'm not sure where it is explained. This is also related to α because if alpha goes toward very large values, it would be like the E_ext term is removed, so it seems like the authors are saying that the solution becomes degenerate if alpha grows very large. This should be clarified.

10) How do the authors justify setting Φ_A = Φ_B in equation (5)? In other words, how is the last assumption in the following sentence justified: "To model the data, we assumed that the neurons are responding both to recurrent inputs and to fluctuating external inputs that can be either homogeneous or tuned to θ_A; θ_B, with a peak at constant location Φ_A = Φ_B ≡ Φ". Does this mean that the preferred direction for a given neuron is the same during preparation and movement epochs? If so, how is this consistent with the not-so-high correlation between the preferred directions of the two epochs shown in Fig. 2 c, which is reported to have a circular correlation coefficient of 0.4?

Reviewer #2 (Public Review):

This work profiles naturally acquired antibodies against Plasmodium falciparum proteins in two Ugandan cohorts, at incredibly high resolution, using a comprehensive library of overlapping peptides. These findings highlight the ubiquity and importance of intra- and inter-protein repeat elements in the humoral immune response to malaria. The authors discuss evidence that repeat elements reside in more seroreactive proteins, and that the breadth of immunity to repeat-containing antigens is associated with transmission intensity in children.

A key strength and value added to publicly available data are the breadth of proteome coverage and unprecedented resolution from using tiling peptides. The authors point out that a known limitation of PhIP-seq is that conformational and discontinuous-linear epitopes cannot be detected with short linear peptides. In addition, disulfide linkages and post-translational modifications would be absent in the T7 representations.

Several significant conclusions drawn from the results in this study are based on the humoral response to repeat elements that are present in multiple locations, including different genes. If antibodies to these regions are cross-reactive as described, it is not clear how the assay can differentiate antibodies that were developed against one or many of these loci. This potential confounding could change the conclusions about inter-protein motifs.

Reviewer #2 (Public Review):

The authors apply their previously developed concept that osteoclasts exist in at least two flavors, tolerogenic and inflammatory osteoclasts towards the treatment of osteoporosis. They suggest that selectively targeting inflammatory osteoclasts attenuates ovariectomy-induced bone loss by agonists of pattern recognition receptors (PRR) that are higher expressed on inflammatory osteoclasts. The vision would be that the tolerogenic osteoclasts are still functioning, allowing bone remodeling with high bone quality, while the strong resorbing inflammatory osteoclasts are resorbed. By expression profiling, they detected PPR differentially expressed and confirmed these by flow cytometry and RT-QPCR. The activation of the Tlr2, Dectin-1, and Mincle reduced inflammatory osteoclast generation in vitro and affected their resorptive activity. Dendritic syk cell-specific deletion abrogated the differentiation of this osteoclast subset as well. The application of yeast Saccharomyces boulardii (Sbb) into mice attenuated trabecular bone loss (but not cortical) and seemed to inhibit in vitro the generation of inflammatory osteoclasts.

Strength:<br /> - The expression profiling between very defined in vitro generated osteoclasts, which are somehow extreme phenotypes, provides a good tool to discern gene signatures on the osteoclast level.<br /> - The candidate of PPR were evaluated in their expression at the protein level by flow cytometry and their function was evaluated by loss of function studies.<br /> - The effect of S.b. treatment is striking and exploiting such probiotic fungi could be an elegant way to treat osteoporosis.

Weakness:<br /> - The osteoclasts are generated in vitro in the presence of M-CSF to induce tolerogenic osteoclasts or GM-CSF / Il-4 to generate inflammatory osteoclasts. The demonstration of these cell populations in the S.b. treated mice in vivo is not present, despite the challenge to do this. The author tried to tackle this, by analyzing the differentiation potential of bone marrow progenitor cells of S.b. treated animals, which provides some information.<br /> - The effect on tolerogenic osteoclasts could have been further evaluated, whether they are not affected at all, or whether there are also effects.

The authors strikingly show that agonists for PPR are affecting strongly GM-CSF/IL-4 progenitor-derived osteoclasts. They show that t-Ocl and i-Ocl differ in their gene signature and convincingly show the differential expression of the PPR, with exception of mincle which is clearly acknowledged. The molecular mechanism of how Sb treatment acts via the receptors remains obscure since it might act via changes in the gut permeability or by components directly released by the fungus. The kinase syk could play a role, at least some data in vitro suggest this.

Conceptionally the authors tried to utilize the previously generated knowledge by the group published 2016 and 2020 into an approach. If the use of a probiotic fungus would be beneficial indeed this could be a suitable drug with few side effects much superior to current treatments of osteoporosis.<br /> For me, an intriguing question arises from this study, in case these i-Ocl express these receptors and are thus so "vulnerable" to the agonists to decrease their activity, evt. a negative feedback to prevent overshooting reactions?

Reviewer #2 (Public Review):

This manuscript details the analytic methods and results of one arm of the PLATCOV study, an adaptive platform designed to evaluate low-cost COVID-19 therapeutics through enrollment of a comparatively smaller number of persons with acute COVID-19, with the goal of evaluating the rate of decrease in SARS-CoV-2 clearance compared to no treatment through frequent swabbing of the oropharynx and a Bayesian linear regression model, rather than clinical outcomes or the more routinely evaluated blunt virologic outcomes employed in larger trials. Presented here, is the in vivo virologic analysis of ivermectin, with a very small sample of participants who received the casirivimab/imdevimab, a drug shown to be highly effective at preventing COVID-19 progression and improving viral clearance (during circulation of variants to which it had activity) included for comparison for model evaluation.

The manuscript is well-written and clear. It could benefit however from adding a few clarifications on methods and results to further strengthen the discussion of the model and accurately report the results, as detailed below.

Strengths of this study design and its report include:<br /> 1. Selection of participants with presumptive high viral loads or viral burden by antigen test, as prior studies have shown difficulty in detecting effect in those with a lower viral burden.<br /> 2. Adaptive sample size based on modeling- something that fell short in other studies based on changing actuals compared to assumptions, depending on circulating variant and "risk" of patients (comorbidities, vaccine state, etc) over time. There have been many other negative studies because the a priori outcomes assumptions were different from the study design to the time of enrollment (or during the enrollment period). This highlight of the trial should be emphasized more fully in the discussion.<br /> 3. Higher dose and longer course of ivermectin than TOGETHER trial and many other global trials: 600ug/kg/day vs 400mcg/kg/day.<br /> 4. Admission of trial participants for frequent oropharyngeal swabbing vs infrequent sampling and blunter analysis methods used in most reported clinical trials<br /> 5. Linear mixed modeling allows for heterogeneity in participants and study sites, especially taking the number of vaccine doses, variant, age, and serostatus into account- all important variables that are not considered in more basic analyses.<br /> 6. The novel outcome being the change in the rate of viral clearance, rather than time to the undetectable or unquantifiable virus, which is sensitive, despite a smaller sample size<br /> 7. Discussion highlights the importance of frequent oral sampling and use of this modeled outcome for the design of both future COVID-19 studies and other respiratory viral studies, acknowledging that there are no accepted standards for measuring virologic or symptom outcomes, and many studies have failed to demonstrate such effects despite succeeding at preventing progression to severe clinical outcomes such as hospitalization or death. This study design and analyses are highly important for the design of future studies of respiratory viral infections or possibly early-phase hepatitis virus infections.

Weaknesses or room for improvement:

1. The methods do not clearly describe allocation to either ivermectin or casirivimab/imdevimab or both or neither. Yes, the full protocol is included, but the platform randomization could be briefly described more clearly in the methods section.<br /> 2. The handling of unquantifiable or undetectable viruses in the models is not clear in either the manuscript or supplemental statistical analysis information. Are these values imputed, or is data censored once below the limits of quantification or detection? How does the model handle censored data, if applicable?<br /> 3. Did the study need to be unblinded prior to the first interim analysis? Could the adaptive design with the first analysis have been done with only one or a subset of statisticians unblinded prior to the decision to stop enrolling in the ivermectin arm?<br /> 4. Can the authors comment on why the interim analysis occurred prior to the enrollment of 50 persons in each of the ivermectin and comparison arms? Even though the sample sizes were close (41 and 45 persons), the trigger for interim analysis was pre-specified.<br /> 5. The reporting of percent change for the intervention arms is overstated. All credible intervals cross zero: the clearance for ivermectin is stated to be 9% slower, but the CI includes + and - %, so it should be reported as "not different." Similarly, and more importantly for casirivimab/imdevimab, it was reported to be 52% faster, although the CI is -7.0 to +115%. This is likely a real difference, but with ten participants underpowered- and this is good to discuss. Instead, please report that the estimate was faster, but that it was not statistically significant. Similarly, the clearance half-life for ivermectin is not different, rather than "slower" as reported (CI was -2 to +6.6 hours). This result was however statistically significant for casirivimab/imdevimab.<br /> 6. While the use of oropharyngeal swabs is relatively novel for a clinical trial, and they have been validated for diagnostic purposes, the results of this study should discuss external validity, especially with respect to results from other studies that mainly use nasopharyngeal or nasal swab results. For example, oropharyngeal viral loads have been variably shown to be more sensitive for the detection of infection, or conversely to have 1-log lower viral loads compared to NP swabs. Because these models look for longitudinal change within a single sampling technique, they do not impact internal validity but may impact comparisons to other studies or future study designs.<br /> 7. Caution should be used around the term "clinically significant" for viral clearance. There is not an agreed-upon rate of clinically significant clearance, nor is there a log10 threshold that is agreed to be non-transmissible despite moderately strong correlations with the ability to culture virus or with antigen results at particular thresholds.<br /> 8. Additional discussion could also clarify that certain drugs, such as remdesivir, have shown in vivo activity in the lungs of animal models and improvement in clinical outcomes in people, but without change in viral endpoints in nasopharyngeal samples (PINETREE study, Gottlieb, NEJM 2022). Therefore, this model must be interpreted as no evidence of antiviral activity in the pharyngeal compartment, rather than a complete lack of in vivo activity of agents given the limitations of accessible and feasible sampling. That said, strongly agree with the authors about the conclusion that ivermectin is also likely to lack activity in humans based on the results of this study and many other clinical studies combined.

Reviewer #2 (Public Review):

Zhao, Shen et al. ran molecular dynamics simulations, followed by the application of Markov State Model analysis and deep machine learning dimensional reduction, to study the dynamical behavior of two loops close to the catalytic site of L1 Metallo-β-lactamase (MBL).

The simulations are carefully executed and of sufficient length to build a representative kinetic model. Using a dimensional reduction of the loop conformational sampling based on backbone dihedral features followed by tICA embedding, the authors obtain a Markov state model that identifies the main conformational states of the loops in the absence of bound ligands and provides estimates of the timescales for the transitions between them. Next, the authors employ an alternative way to cluster the conformations of the loops, using unsupervised dimensional reduction, implemented as a convolutional VAE applied to residue distances followed by tSNE embedding. This second step gives results that are not consistent with the clustering used for the kinetic modeling (for instance, supplement 2 of figure 4 shows that the 7 macrostates obtained by the MSM analysis don't always correspond to different areas in the CVAE+tSNE embedding).

Moreover, an inspection of the results from both analysis techniques just confirms the role of interactions that are readily observed in the available crystal structure stabilising the most populated, closed conformation of the loops. The sophisticated computational analysis does not elucidate much of the role of the loop dynamics beyond the intuitive conclusion that disruption of the key interactions keeping the loops in the closed state would affect the function. For instance, it does not clarify what is the role of the other observed metastable states.

Finally, the authors propose and test mutations that would likely disrupt the stability of the closed state and find that they have variable effects on the ability of the enzyme to contrast the antibiotic effect of a panel of substrates. These experimental results look useful and can potentially be used to elucidate the role of the loops in the recognition and activity of the enzyme, and for the design of inhibitors. However, no additional attempt is made to clarify the experimental results based on the mechanistic model of loop dynamics: why do different mutations have different effects? why do some mutations affect all substrates, other mutations only some substrates, and for others, no substrate is affected? What is the role of the tetrameric arrangement?

Reviewer #2 (Public Review):

The data presented are of high quality. Through complementary experiments involving the isolation of masseter muscle spindles, the authors perform RNA-seq and proteomic analysis, and identify genes and proteins that are differentially expressed in the muscle spindle versus the adjacent muscle fiber, and proteins that accumulate specifically in capsule cells and nerve endings. These data, while essentially descriptive, provide important information about the developmental framework of the sensory apparatus present in each muscle that accounts for its tension/contraction state. The data presented thus allow for a better characterization of muscle spindles and provide the community with a set of new markers for better identification of these structures. Analysis of the expression pattern of the Tomato reporter in transgenic animals under the control of Piezo2-CRE, Gli1-CRE and Thy1-YFP reporter reinforces the findings and the specificity of the expression pattern of the specific genes and proteins identified by the multi-omics approach and further validated by immunohistochemistry.

Reviewer #2 (Public Review):

Hu et al. developed a new reagent to enhance single mRNA imaging in live cells and animal tissues. They combined an MS2-based RNA imaging technique and a Suntag system to further amplify the signal of single mRNA molecules. They used 8xMS2 stem-loops instead of the widely-used 24xMS2 stem-loops and then amplified the signal by fusing a 24xSuntag array to an MS2 coat protein (MCP). While a typical 24xMS2 approach can label a single mRNA with 48 GFPs, this technique can label a single mRNA with 384 GFPs, providing an 8-fold higher signal. Such high amplification allowed the authors to image endogenous mRNA in the epidermis of live C. elegans. While a similar approach combining PP7 and Suntag or Moontag has been published, this paper demonstrated imaging endogenous mRNA in live animals. Data mostly support the main conclusions of this paper, but some aspects of data analysis and interpretation need to be clarified and extended.

Strengths:<br /> Because the authors further amplified the signal of single mRNA, this technique can be beneficial for mRNA imaging in live animal tissues where light scattering and absorption significantly reduce the signal. In addition, the size of an MS2 repeat cassette can be reduced to 8, which will make it easier to insert into an endogenous gene. Also, the MCP-24xSuntag and scFv-sfGFP constructs can be expressed in previously developed 24xMS2 knock-in animal models to image single mRNAs in live tissues more easily.

The authors performed control experiments by omitting each one of the four elements of the system: MS2, MCP, 24xSuntag, and scFV. These control data confirm that the observed GFP foci are the labeled mRNAs rather than any artifacts or GFP aggregates. And the constructs were tested in two model systems: HeLa cells and the epidermis of C. elegans. These data demonstrate that the technique may be used across different species.

Weaknesses:<br /> Although the paper has strength in providing potentially useful reagents, there are some weaknesses in their approach.

Each MCP-24xSunTag is labeled with 24 GFPs, providing enough signal to be visualized as a single spot. Although the authors showed an image of a control experiment without MS2 in Figure 1B, the authors should at least mention this potential problem and discuss how to distinguish mRNA from MCP tagged with many GFPs. MCP-24xSunTag labeled with 24 GFPs may diffuse more rapidly than the labeled mRNA. Depending on the exposure time, they may appear as single particles or smeared background, but it will certainly increase the background noise. Such trade-offs should be discussed along with the advantage of this method.

Also, more quantitative image analysis would be helpful to improve the manuscript. For instance, the authors can measure the intensity of each GFP foci, show an intensity histogram, and provide some criteria to determine whether it is an MCP-24xSuntag, a single mRNA, or a transcription site. For example, it is unclear if the GFP spots in Figure 2D are transcription sites or mRNA granules.

Another concern is that the heavier labeling with 24xSuntag may alter the dynamics of single mRNA. Therefore, it would be desirable to perform a control experiment to compare the diffusion coefficient of mRNAs when they are labeled with MCP-GFP vs MCP-24xSuntag+scFv-sfGFP.

The authors could briefly explain about the genes c42d4.3 and mai-1. Why were these specific genes chosen to study gene expression upon wound healing? Did the authors find any difference in the dynamics of gene expression between these two genes?

Reviewer #2 (Public Review):

In this manuscript, Zhang et al., address the role of Polo-like kinase signaling in restricting the activity of Chk2 kinase and coordinating synapsis among homologous chromosomes with the progression of meiotic prophase in C. elegans. While individual activities of PLK-2 and CHK-2 have been demonstrated to promote chromosome pairing, and double-strand break formation necessary for homologous recombination, in this manuscript the authors attempt to link the function of these two essential kinases to assess the requirement of CHK-2 activity in controlling crossover assurance and thus chromosome segregation. The study reveals that CHK-2 acts at distinct regions of the C. elegans germline in a Polo-like kinase-dependent and independent manner.

Strengths:<br /> The study reveals distinct mechanisms through which CHK-2 functions in different spatial regions of meiosis. For example, it appears that CHK-2 activity is not inhibited by PLK's (1 and 2) in the leptotene/zygotene meiotic nuclei where pairing occurs. This suggests that either CHK-2 is not phosphorylated by PLK-2 in the distal nuclei or that it has a kinase-independent function in this spatial region of the germline. These are interesting observations that further our understanding of how the processes of meiosis are orchestrated spatially for coordinated regulation of the temporal process.

Weaknesses:<br /> While the possibilities stated above are interesting, they lack direct support from the data. A key missing element in the study is the actual role of PLK-2 signaling in controlling CHK-2 activity and thus function. I expand on this below.

Throughout the manuscript, the authors test the role of each of the kinases (CHK-2 or PLK-1, or 2) using auxin-induced degradation, which would eliminate both phosphorylated and unphosphorylated pools of proteins. This experiment thus does not test the role of PLK-2 signaling in controlling CHK-2 function or the role of CHK-2 activation. To test the role of signaling from PLK-2 or CHK-2, the authors need to generate appropriate alleles such as phospho-mutants or kinase-dead mutants. The authors do generate unphosphorylatable and phosphomimetic versions of CHK-2, however, they find that the protein level for both these alleles is lower than wild-type CHK-2 (which the authors state is already low). The authors conclude that the lower level of protein in the CHK-2 phospho-mutants is because the mutations cause destabilization of the protein. I am sympathetic with the authors since clearly these results make interpretations of actual signaling activity more challenging. But there needs to be some evidence of this activity, for example through the generation of a phosphor-specific antibody to phosphorylated CHK-2. While not functional, at least the phosphorylation status of CHK-2 would provide more information on its spatial pattern of activation and inactivation. In addition, it would still be of interest to the readership to present the data on these phosphor-mutant alleles with crossover designation and COSA-1::GFP. Is the phenotype of the WT knockin, and each of the phosphomutant knock-ins similar to auxin-induced degradation of CHK-2?

Given that the CHK-2 phosphomutants did not pan out for assessing the signaling regulation of PLK-2 on CHK-2, to directly assess whether PLK-2 activity restricts CHK-2 function in mid-pachytene but not leptotene/zygotene, the authors should generate PLK-2 kinase dead alleles. These alleles will help decouple the signaling function of PLK-2 from a structural function.

Similarly, to assess the potentially distinct roles of CHK-2 in leptotene/zygotene and mid-pachytene it would be important to assess CHK-2 kinase-dead mutant alleles. At this time, all of the analysis is based on removing both active CHK-2 and inactive CHK-2 (i.e. phosphorylated and unphosphorylated pool) using auxin-induced degradation. The kinase-dead alleles will help infer the role of the kinase more directly. The authors can then superimpose the auxin-induced degradation and assess the impact of complete removal of the protein vs only loss of its kinase function. These experiments may help clarify the role of signaling outcomes of these proteins, vs their complete loss. For example, what does kinase dead PLK-2 recruitment to the synapsed chromosomes appear like? Are their distinct activities for active and inactive PLK-2 that are spatially regulated? The same can be tested for CHK-2.

Reviewer #2 (Public Review):

This is an interesting manuscript establishing a role for Ecdysone signaling in the control of sleep. The authors show that the Ecdysone receptor EcR is required primarily in cortex glia for the control of sleep and that its target E75 is also involved in sleep regulation. This is a novel function for both cortex glia and steroid signaling in Drosophila. The authors also present evidence that Ecdysone signaling would be important for response to starvation, and that lipid droplet mobilization would mediate the effect of ecdysone on sleep. This work is certainly innovative. However, the main conclusions need to be strengthened. In particular: variability in sleep amounts in certain strains could complicate interpretation, the idea that ecdysone modulates sleep response to starvation is not sufficiently well supported, and genetic evidence for mobilization of lipid droplets being the mechanism linking steroid signaling to sleep is currently quite weak.

Major concerns:

1) I have concerns with the variability observed with the GS drivers (whether nSyb or repo). This is particularly striking in figure S3 when comparing experiments conducted with EcR-c and the Ecl RNAi. Daytime is most affected, but even nighttime looks significantly different. Definitely, nighttime quantification should be shown in addition to total sleep in figure S3. However, I feel that confirming the key results of this study with an additional driver would be reassuring. Could repo-GAL4 combined with GAL80ts be used to drive EcR RNAi, instead of repo-GS? The same combination could help determine whether glia is responsible for the 20E-mediated increase in sleep after starvation (figure S4A).<br /> 2) The idea that ecdysone might suppress the response to starvation is interesting, but the results are not convincing. First, there is an important control missing. It is important to test the effect of Ecdysone on fed flies, to ensure that Ecdysone does not simply make flies sleepy. Second, it is not clear that EcR RNAi has a specific effect on starved flies. Starvation reduces sleep, but is this reduction really exaggerated in flies expressing EcR RNAi than in control flies? It seems to me that starvation reduces sleep by the same amount when comparing results in panels 3D and E. The effect of EcRNAi and starvation might be simply additive, which would suggest that 20E impacts sleep independently of starvation.<br /> 3) The material and method section needs to be improved. In particular, it is not clear to me how the starvation/ecdysone feeding assay was done. There are some additional explanations in the figure legend, but the approach is still not clear to me. Indicate clearly when the flies were starved, and when they were exposed to Ecdysone.<br /> 4) I am not convinced that the Lsd2 results necessarily support the idea that this gene is required for the effect of 20E on sleep. Sleep is dramatically reduced during the day in the Lsd2 mutant. This is actually an interesting observation, but this strong effect on baseline sleep might be masking the ability of 20E to modulate sleep.

Reviewer #2 (Public Review):

The manuscript reports on the complex variability of expression, trafficking, assembly/stability, and peptide loading among different MHC I haplotypes. In particular by analyzing two distinct MHC I molecules as representative members of groups of allotypes, that favor canonical or non-canonical assembly modes, the PI reports on preferential cytosolic or endo-lysosomal MHC I loading. Overall, the data shed light on the intersection between MHC I conformation and subcellular sites of peptide loading and help explain MHC I immunosurveillance at a different subcellular location.

In the first series of experiments the authors report an uneven surface expression of HLA-B vs HLA-A, and C on circulating monocytes, with HLA-B being expressed 4 times higher, also they report that as compared to the TAP-dependent allotype B*08:01 the TAP-independent allotype B*35:01 has a lower surface half-life and if often present as an empty molecule. These data set the basis for the author's hypothesis that B*35:01 could traffic in Rab11+ compartment and be involved in cross-presentation, which indeed is demonstrated in a series of pulse-chase peptide experiments and using cathepsin inhibitors.

Overall, the experiments could be improved by performing subcellular fractionation and organelle purification to conclusively demonstrate the differential trafficking of B*08:01 vs B*35:01, as well as quantitative mass spectrometry to determine cytosolic vs endosomal processing for one selected epitope presented by the different haplotypes.

Reviewer #2 (Public Review):

Yeatman and colleagues used MEG in pre-literate children following a literacy intervention program to investigate changes in cortical responses to visual images of words, faces, and objects. Children who participated in a literacy intervention program showed improvements in letter knowledge and increased neural responses to words relative to an object category. The authors interpret these findings in the framework of the neuronal recycling hypothesis proposed by Dehaene and colleagues. This is important work. The opportunity to use a causal manipulation to study neural and behavioral development in humans is rare. The finding of neural changes from just 2 weeks of intervention is striking. The scope of the work extends beyond understanding brain development and has potential relevance for social and educational policies. The study appears well-designed and includes an important control group. Overall, I am enthusiastic about this work. However, it is unclear whether the results are specific to the area of interest - the visual word form area. The increased response to words from the intervention appears quite widespread cortically (Figure 5). These issues are central to the idea of neuronal recycling and the authors' proposal that training leads to increased modularization. Thus, the results currently only provide modest support for the conclusions. Additionally, aspects of the analysis need clearer motivation/justification.

Reviewer #2 (Public Review):

The molecular characteristics of OCNs in normal or ototoxic conditions are poorly understood before. The strength of this study is that it provides the first single-cell RNA-seq database of OCNs as well as surrounding facial branchial motor neurons. By thoroughly analyzing the database, they found high heterogeneities within OCN populations and identified distinct markers that are enriched in different OCN subtypes. Furthermore, a few previously unknown neuropeptides are revealed, including Npy which is more enriched in the LOC-2 located on the medial side. They also found that neuropeptide expression levels and distributions are subjected to hearing experience and noise exposure. On the other hand, the weakness of the study is that the numbers of single-cell RNA-seq are not sufficient, and may underscore the MOC heterogeneity (Figure 3A). Moreover, the physiological functions of the LOC-2 are not revealed in this study, and no specific markers in one OCN subtype are identified that can predict the morphological or projecting axon features. Those might be addressed in the following studies.

Reviewer #2 (Public Review):

This study reports interesting findings on the influence of a conserved phosphatase on mitochondrial biogenesis and function. In the absence of it, many nucleus-encoded mitochondrial proteins among which those involved in ATP generation are expressed much better than in normal cells. In addition to a better understanding of th mechanisms that regulate mitochondrial function, this work may help developing therapeutic strategies to diseases caused by mitochondrial dysfunction. However there are a number of issues that need clarification.

1) The rationale of the screening assay to identify genes required for the gene expression modifications observed in mct1 mutant is not clear. Indeed, after crossing with the gene deletion libray, the cells become heterozygote for the mct1 deletion and should no longer be deficient in mtFAS. Thank you for clarifying this and if needed adjust the figure S1D to indicate that the mated cells are heterozygous for the mct1 and xxx mutations.

2) The tests shown in Fig. S1E should be repeated on individual subclones (at least 100) obtained after plating for single colonies a glucose culture of mct1 mutant, to determine the proportion of cells with functional (rho+) mtDNA in the mct1 glucose and raffinose cultures. With for instance a 50% proportion of rho- cells, this could substantially influence the results of the analyses made with these cells (including those aiming to evaluate the MMP).

3) The mitochondria area in mct1 cells (Fig.S1G) does not seem to be consistent with the tests in Fig. 1C. that indicate a diminished mitochondrial content in mct1 cells vs wild-type yeast. A better estimate (by WB for instance) of the mitochondrial content in the analyzed strains would enable to better evaluate MMP changes monitored with Mitotracker since the amount of mitochondria in cells correlate with the intensity of the fluorescence signal.

4) Page 12: "These data demonstrate that loss of SIT4 results in a mitochondrial phenotype suggestive of an enhanced energetic state: higher membrane potential, hyper-tubulated morphology and more effective protein import." Furthermore, the sit4 mutant shows higher levels of OXPHOS complexes compared to WT yeast.

Despite these beneficial effects on mitochondria, the sit4 deletion strain fails to grow on respiratory substrates. It would be good to know whether the authors have some explanation for this apparent contradiction.

Reviewer #2 (Public Review):

Shah and colleagues tackle a significant impediment to exploiting tissue culture systems that enable prospective ex vivo experimentation in real-time. Namely, the ability to identify and track dynamic and coordinated activities of multiple composite cell types in response to experimental perturbations. They develop a clever label-free approach that collects biologically-encoded autofluorescence of epithelial cells by 2-photon imaging of mouse tracheal explant culture over 2 days. They report the ability to distinguish 7 cell types simultaneously, including rare ones, by developing a machine-learning approach using a combination of fluorescence and cytologic features. Their algorithm demonstrates high accuracy by Mathew's Correlation Coefficient when applied to a test set. Lastly, they show the ability of their approach to visualize the dynamic uptake and expulsion of fluorescently-tagged dextran by individual secretory cells. Overall, the results are intriguing and may be very useful for specific applications.

Reviewer #2 (Public Review):

The manuscript of Penha et al performs genetic correlation, Mendelian randomization (MR), and colocalization studies to determine the role of genetically determined leukocyte telomere length (LTL) and susceptibility to lung cancer. They develop an instrument from the most recent published association of LTL (Codd et al), which here is based on n=144 genetic variants, and the largest association study of lung cancer (including ~29K cases and ~56K controls). They observed no significant genetic correlation between LTL and lung cancer, in MR they observed a strong association that persisted after accounting for smoking status. They performed colocalization to identify a subset of loci where LTL and lung cancer risk coincided, mainly around TERT but also other loci. They also utilized RNA-Seq data from TCGA lung cancer adenocarcinoma, noting that a particular gene expression profile (identified by a PC analysis) seemed to correlate with LTL. This expression component was associated with some additional patient characteristics, genome stability, and telomerase activity.

In general, most of the MR analysis was performed reasonably (with some suggestions and comments below), it seems that most of this has been performed, and the major observations were made in previous work. That said, the instrument is better powered and some sub-analyses are performed, so adds further robustness to this observation. While perhaps beyond the scope here, the mechanism of why longer LTL is associated with (lung) cancer seems like one of the key observations and mechanistically interesting but nothing is added to the discussion on this point to clarify or refute previous speculations listed in the discussion mentioned here (or in other work they cite).

Some broad comments:

1. The observations that lung adenocarcinoma carries the lion's share of risk from LTL (relative to other cancer subtypes) could be interesting but is not particularly highlighted. This could potentially be explored or discussed in more detail. Are there specific aspects of the biology of the substrata that could explain this (or lead to testable hypotheses?)

2. Given that LTL is genetically correlated (and MR evidence suggests also possibly causal evidence in some cases) across a range of traits (e.g., adiposity) that may also associate with lung cancer, a larger genetic correlation analysis might be in order, followed by a larger set of multivariable MR (MVMR) beyond smoking as a risk factor. Basically, can the observed relationship be explained by another trait (beyond smoking)? For example, there is previous MR literature on adiposity measures, for example (BMI, WHR, or WHRadjBMI) and telomere length, plus literature on adiposity with lung cancer; furthermore, smoking with BMI. A bit more comprehensive set of MVMR analyses within this space would elevate the significance and interpretation compared to previous literature.

3. In the initial LTL paper, the authors constructed an IV for MR analyses, which appears different than what the authors selected here. For example, Codd et al. proposed an n=130 SNP instrument from their n=193 sentinel variants, after filtering for LD (n=193 >>> n=147) and then for multi-trait association (n=147 >> n=130). I don't think this will fundamentally change the author's result, but the authors may want to confirm robustness to slightly different instrument selection procedures or explain why they favor their approach over the previous one.

4. Colocalization analysis suggests that a /subset/ of LTL signals map onto lung cancer signals. Does this mean that the MR relationships are driven entirely by this small subset, or is there evidence (polygenic) from other loci? Rather than do a "leave one out" the authors could stratify their instrument into "coloc +ve / coloc -ve" and redo the MR analyses.

Mainly here, the goal is to interpret if the subset of signals at the top (looks like n=14, the bump of non-trivial PP4 > 0.6, say) which map predominantly to TERT, TERC, and OBFC1 explain the observed effect here. I.e., it is biology around these specific mechanisms or generally LTL (polygenicity) but exemplified by extreme examples (TERT, etc.). I appreciate that statistical power is a consideration to keep in mind with interpretation.

Reviewer #2 (Public Review):

The study is a careful investigation of the physical properties of hagfish slime and the underlying cellular framework that enables this extraordinary evolutionary innovation. I appreciate the careful and detailed measurements and images that the authors provide. The results presented here will surely be extremely important for researchers working on this particular organism and those interested in understanding the evolution, biomedical relevance, and biochemistry of mucus. However, I had difficulty contextualizing the findings in broader biological questions (e.g., the evolution of functional novelty, the adaptive processes, and the links between genetic and phenotypic evolution). I also think that the conclusions on the evolutionary origins and underlying genetics of hagfish slime based on comparative transcriptomic data may be premature.

Reviewer #2 (Public Review):

Chinnaiya et al. integrated recent scRNA transcriptomics with high-resolution multiplexing in situ hybridization, fate mapping and tissue explants to unravel the spatiotemporal development of early chick tuberal hypothalamus. They show that a wave of BMP signaling passes through anterior and posterior regions sequentially. Interestingly, they showed that neuroepithelial-intrinsic BMPs drive and maintain tuberal hypothalamus late development. Using bioinformatical and in situ profiling, the authors indicated the potential of the tuberal progenitors transferring into radial glia-like cells.

This is a remarkable piece of work and I commend the authors for their bold endeavor to decipher the complex developmental of the tuberal hypothalamus.

Reviewer #2 (Public Review):

This manuscript shows that two doses of the live attenuated Coronavac vaccine induce neutralising antibodies in the majority of individuals, though neutralisation is modest for Omicron BA.1 even after 1 month post-dose two, and substantial waning at 12 months is noted. Boosting achieves higher neutralisation than for prior doses.

Strengths of the work are the significant sample size in the cross-sectional part and a smaller prospective part which adds value to the study as a whole.

The assays used are appropriate, with PV bearing Wu-hu-1, Delta, and Omicron spike proteins.

Weakness includes the fact that the cross-sectional aspect recruits at different sites at different time points, introducing the fact that observed differences in vaccine response may be related to the underlying population differences.

In addition, the data on third-dose boosting do not appear to include VOC. This is important because data from other vaccines suggest broadening of neutralisation with the third dose.

Reviewer #2 (Public Review):

To advance the understanding of the initial events in recognition of HIV-1 genome by the viral structural protein Gag, in this study, the authors examined the involvement of the CA domain in the specific interaction between Gag and the viral genomic RNA. Previous studies including a study from the same group (Kutluay et al 2010) showed that the CA C-terminal domain plays a role in Gag binding to viral genomic RNA. In the current study, they analyzed a panel of CA mutants using a modified PAR-CLIP RNA sequencing, which allows identification of Gag binding sites in the viral genome, and a chemical crosslinking approach, which allows assessment of the multimerization status of Gag in cells. They found that substitutions of CA residues at the CA dimer, trimer, or hexamer interfaces, which reduce Gag multimerization as expected, also reduce the Ψ sequence-specific viral RNA binding, whereas substitutions elsewhere in CA have no impact. They further found that substitutions of the Lys residues important for IP6 binding, which disrupt Gag lattice formation, reduce the Ψ-specific RNA binding, whereas a second-site mutation that restores virus assembly in these Lys substitution mutants restores the RNA binding. These results strongly support the authors' conclusion that Gag lattice formation driven by CA plays an important role in NC-mediated recognition of the Ψ sequence.

The strengths of the work include the application of the modified PAR-CLIP method to the analysis of a large panel of CANC constructs. This provided the detailed information on the specific molecular features in CA required for interactions between Gag and the Ψ sequence, which was not obtainable in the previous studies. The absence of the MA domain in these constructs allowed the authors to focus on the cytoplasmic interactions. The data obtained with oligomer-forming NC constructs and CANC constructs that differ in the IP6 dependence also add support to the authors conclusion that CA-mediated lattice formation of CANC and not just NC oligomerization plays a key role in Gag-vRNA binding. Overall, the data support the conclusion that the ability to form the CANC lattice is essential for the initial NC-vRNA interaction.

The only notable weakness is that previous work by this group and others have already shown that CA and/or its interaction interfaces plays an important role in the Gag-vRNA interaction. Therefore, the current work can be regarded as a refinement of the previously presented concept rather than a conceptual breakthrough. Nonetheless, these mechanistic details are likely to help the retrovirology community gain a clearer grasp of the early steps of infectious particle formation.

Reviewer #2 (Public Review):

This interesting manuscript uses a collection of whole genome sequences of TB isolates to associate specific sequence polymorphisms with MDR/XDR strains, and having found certain mutations in DNA repair pathways, does a detailed analysis of several mutations. The evaluation of the MutY polymorphism reveals it is loss of function and TB strains carrying this mutation have a higher mutation frequency and enhanced survival in serial passage in macrophages. The strengths of the manuscript are the leveraging of a large sequence dataset to derive interesting candidate mutations in DNA repair pathway and the demonstration that at least one of these mutations has a detectable effect on mutagenicity and pathogenesis. The weaknesses of the manuscript are a lack of experimental exploration of the mechanism by which loss of a DNA repair pathway would enhance survival in vivo. The model presented is that these phenotypes are due to hypermutagenicity and thereby evolution of enhanced pathogenesis, but this is not actually directly tested or investigated. There are also some technical concerns for some of the experimental data which can be strengthened.

This paper presents the following data:

- Analyzed whole-genome sequences 2773 clinical strains: 160 000 SNPs identified<br /> - 1815 drug-susceptible/422 MDR/XDR strains: 188 mutations correlated with Drug resistance.<br /> - Novel mutations associated with the drug resistance have been found in base excision repair (BER), nucleotide excision repair (NER), and homologous recombination (HR) pathway genes (mutY, uvrA, uvrB, and recF).<br /> - Specific mutations mutY-R262Q and uvrB-A524V were studied.<br /> - mutY-R262Q and uvrB-A524V mutations behave as loss of function alleles in vivo, as measured by non-complementation of the increased mutation frequency measured by resistance to Rif and INH.<br /> - The mutY deletion and the mutY-R262Q mutation increase Mtb survival over WT in macrophages when Mtb has not been submitted to previous rounds of macrophage infection.<br /> - This advantage is exacerbated in presence of antibiotic (Rif and Cipro but not INH).<br /> - The MutY deletion and the MutY-R262Q mutation result in an enhanced survival of Mtb during guinea pig infection.

Major issues:

The finding that mutations in MutY confers an advantage during macrophage infection is convincing based on the macrophage experiments, but it is premature to conclude that the mechanism of this effect is due to hypermutagenesis and selection of fitter bacterial clones. It is described in E. coli (Foti et al., 2012) and recently in mycobacteria (Dupuy et al., 2020) that the MutY/MutM excision pathways can increase the lethality of antibiotic treatment because of double-strand breaks caused by Adenine/oxoG excisions. The higher survival of the mutY mutant during antibiotic treatment could more be due to lower Adenine/oxoG excision in the mutant rather than acquisition of advantageous mutations, or some other mechanism. The same hypothesis cannot be excluded for the Guinea pig experiments (no antibiotics, but oxidative stress mediated by host defenses could also increase oxoG) and should at least be discussed. Experiments that would support the idea that the in vivo advantage is due to hypermutagenesis would be whole genome sequencing of the output vs input populations to directly document increased mutagenesis. Similarly, is the ΔmutY survival advantage after rounds of macrophage infections dependent on macrophage environment? What happens if the ΔmutY strain is cultivated in vitro in 7H9 (same number of generations) before infecting macrophages?

- It would be useful to present more data about the strain relatedness and genome characteristics of the DNA repair mutant strains in the GWAS. For example, the model would suggest that strains carrying DNA repair mutations should have higher SNP load than control strains. Additionally, it would be helpful to know whether the identified DNA repair pathway mutations are from epidemiologically linked strains in the collection to deduce whether these events are arising repeatedly or are a founder effect of a single mutant since for each mutation, the number of strains is small.

- Some of the mutation frequency, survival and competition data could be strengthened by more experimental replicates. Data Lines 370-372 (mutation frequency), lines 387-388 (Survival of strains ex vivo), line 394 (competition experiment) : "Two biologically independent experiments were performed. Each experiment was performed in technical triplicates. Data represent one of the two biological experiments." Two biological replicates is insufficient for the phenotypes presented and all replicates should be included in the analysis. In addition, the definition of "technical triplicates" should be given, does this mean the same culture sampled in triplicate?

- MutY phenotypes. One caveat to the conclusion that the MutY R262Q mutant is nonfunctional is the lack of examination of the expression of the complementing protein. I would be informative to comment on the location of this mutation in relation to the known structures of MutY proteins. Similarly, for the UvrB polymorphism, this null strain has a clear UV sensitivity phenotype in the literature, so a fuller interrogation for UV killing would be informative re: the A524V mutation.

Public speaking was practiced long before the Greeks.Systemic the-art of public speaking, which they called "rhetoric".

Reviewer #2 (Public Review):

Wang and colleagues previously characterized the protein interactome for GABA subunits and identified HSP47 chaperone as a top interacting protein. Here, they follow up to assess the function of this HSP47-GABA interaction. Using primarily HEK293 cells, they provide evidence that the ER-resident HSP47 chaperone promotes the folding of GABA receptor subunits and the assembly of GABA subunits into multimeric ion channels. Interestingly, they demonstrate HSP47 can rescue the folding and function of a missense mutant A332D epilepsy-associated GABA subunit. They also demonstrate similar enhanced folding/function for acetylcholine receptor assembly. Overall, the experimental data are well-presented and provide insight into new ion channel clients whose folding and assembly are dependent on the HSP47 chaperone. The study also identifies HSP47 expression as a potential strategy to target and enhance the function of misfolded ion channels, and this may have broader biomedical therapeutic significance beyond GABA channels.

Reviewer #2 (Public Review):

Overall, the manuscript is clearly written and remarkably comprehensive, presenting a very large amount of data. Experimental methods are well-documented and rigorous, and I have no significant technical concerns about any of the work presented. There are some points where the presentation might be improved by modifications to the text or figures, particularly with the goal of making this important work accessible to a broad audience.

Reviewer #2 (Public Review):

This mechanistic PK/PD model simultaneous characterized several important factors, including formation of immunological synapses synapse variants, target/tumor cell densities, target CD3/tumor antigen expression levels, tumor antigen escape and the associated cancer relapse, in a unified model structure.

This model has the potential to be used in optimization dosage of T cell redirecting bispecific treatment towards best clinical outcome.

Reviewer #2 (Public Review):

This study by Yang & al. explores the mechanism of X dosage compensation in the nematode species C. briggsae; which is a close relative of C. elegans. The mechanism is well described in C. elegans, and the authors have asked whether the same condensin-like complex (DCC) is responsible for the silencing of the X and which motifs on the X are responsible for this binding specificity in C. briggsae. They discovered that although the general principle of X inactivation is conserved between these 2 species, and ortholog proteins of the pathway (xol-1, sdc-2, and the genes encoding the DCC complex) are conserved, the sequences on the X that are recognized by the DCC complex have evolved very rapidly. The motifs of C. briggsae are not recognized by the C. elegans proteins and vice versa. The authors have accumulated very solid data, both in vitro and in vivo, to support this conclusion.

Overall, the results are very convincing and extremely interesting, for the chromatin field but also from an evolutionary perspective. This finding is comparable to the discovery that centromeric sequences and centromere proteins, despite their essential function in cells, evolve extremely rapidly. The reason is that they are involved in genetic conflicts, are a perfect target to generate hybrid incompatibilities during crosses, and therefore, under such selective pressure, evolve super fast. Most examples of hybrid incompatibilities rely on chromatin conflicts, and with this study, it appears that the dosage compensation system could be one other way to generate hybrid breakdown.

Reviewer #2 (Public Review):

Briševac et al. investigate the genetic architecture of an exceptional ecological system where Clunio marinus populations have diverged in their timing of reproduction, controlled by a circalunar clock. These loci may be important in sympatric speciation and/or rapid evolution of reproductive isolation but there are some issues that need to be resolved. I outline these below:

1) The QTL mapping relies on a modest number of individuals and there are important details missing. The manuscript is missing information on heritability of the trait which is important for interpretation. While the variance explained by the QTL is hight, for the estimates of QTL effect sizes from such small samples, there is a common issue known as the Beavis effect that can inflate the effect size of individual QTL.

2) My major concern with the paper is the interpretation of divergence within the inversion as linked causally to the genes underlying ecological divergence. As the authors observe, divergence will vary within an inverted region. This can be traced to myriad factors, including variation in mutation rate, variation in constraint, patterns of ancestral polymorphism within this region, and variation in gene conversion within the inversion. Given this, I do not think it is valid to interpret the regions of high differentiation as the causal drivers of the ecological differentiation.

3) The authors imply in the discussion based on historical results that the ecotype evolved in situ in the last ~60 years. This seems substantially less likely to me than a number of alternative hypotheses including missing the phenotype in previous samples, plasticity in the phenotype causing it to be missed or migration from populations where the phenotype already existed.

Reviewer #2 (Public Review):

This study aims to describe the distribution and functional status of monocytes and dendritic cells in the blood and nasopharyngeal aspirate (NPA) after respiratory viral infection in more than 50 patients affected by influenza A, B, RSV and SARS-CoV2. The authors use flow cytometry to define HLA-DR+ lineage negative cells, and within this gate, classical, intermediate and non-classical monocytes and CD1c+, CD141+, and CD123+ dendritic cells (DC). They show a large increase in classical monocytes in NPA and an increase in intermediate monocytes in blood and NPA, with more subtle changes in non-classical monocytes. Changes in intermediate monocytes were age-dependent and resolution was seen with convalescence. While blood monocytes tended to increase in blood and NPA, DC frequency was reduced in blood but also increased in NPA. There were signs of maturation in monocytes and DC in NPA compared with blood as judged by expression of HLA-DR and CD86. Cytokine levels in NPA were increased in infection in association with enrichment of cytokine-producing cells. Various patterns were observed in different viral infections suggesting some specificity of pathogen response. The work did not fully document the diversity of human myeloid cells that have arisen from single-cell transcriptomics over the last 5 years, notably the classification of monocytes which shows only two distinct subsets (intermediate cannot be distinguished from classical), distinct populations of DC1, DC2 and DC3 (DC2 and 3 both having CD1c, but different levels of monocyte antigens), and the lack of distinction provided by CD123 which also includes a precursor population of AXL+SIGLEC6+ myeloid cells in addition to plasmacytoid DC. Furthermore, some greater precision of the gating could have been achieved for the subsets presented. Specifically, CD34+ cells were not excluded from the HLA-DR+ lineage- gate, and the threshold of CD11c may have excluded some DC1 owing to the low expression of this antigen. Overall, the work shows that interesting results can be obtained by comparing myeloid populations of blood and NPA during viral infection and that lineage, viral and age-specific patterns are observed. However, the mechanistic insights for host defense provided by these observations remain relatively modest.

Reviewer #2 (Public Review):

The paper describes a fairly complete set of experiments describing a mechanism by which 4-hour treatment with 25HC can provide reductions in plasma membrane cholesterol for up to 22 hours. The basic finding is that 25HC depletes the ER of cholesterol by stimulating esterification and that SREBP activation is also inhibited. This effect is associated with the slow loss of 25HC from the cells.

The paper describes detailed studies of the long-lasting effects of a 4-hour exposure to 25HC on the loss of plasma membrane cholesterol. The paper characterizes the effects on SREBP processing to account for this. The possible long-lasting effects of ACAT stimulation were not investigated but may play an equal role.

The paper presents data that the effects on plasma membrane cholesterol can account for the inhibitory effects on some bacterial toxins and viruses.

Reviewer #2 (Public Review):

In this article, a multi-modal strategy for live birth prediction is proposed using blastocyst images and clinical features. The CNN architecture is used for the imaging dataset, while an MLP is built for the clinical features, and the final model is developed by concatenating CNN and MLP features. 17,580 samples are used for training and testing the model. The proposed model performed significantly better than the previous ones, with an AUC of 0.77.

By creating activation maps in both scenarios: I) when imaging and clinical features were used, and II) when only imaging data was used, authors highlight the parts of images that are crucial for predictions. Their results confirm the benefits of utilizing multi-modal datasets.

However, the manuscript is currently lacking crucial methodological information that is necessary to judge the validity of various claims.<br /> Furthermore, it lacks discussion of the potential applications of the proposed model in clinical settings.

Reviewer #2 (Public Review):

There are fundamental differences in resting state with eyes open or eyes closed regardless of visual stimulation. Without visual stimulation, these differences are attributed to the switching of involuntary attention from internal (eyes closed) to external (eyes open). The authors employ a monocular deprivation paradigm by patching one eye (with it either open or closed) to induce differences in alpha amplitude that are similar to differences measured with both eyes open or closed. They then examine how these differences from monocular deprivation impact after-effects in contrast sensitivity and binocular balance.

The authors pose an interesting and well-supported hypothesis based on prior knowledge that internal oscillations (i.e. alpha waves) can be modulated with eyes open vs eyes closed. The presented experiments build well upon one another and the authors clearly describe how relevant findings from experiment 1 contribute to the design of the following monocular deprivation experiments. The authors also combine several metrics including EEG, SSVEP and contrast sensitivity to assess both neural activity and perception in tandem.

Despite these strengths, the reported data in the first experiments only shows a modest difference between conditions. In experiment one, the authors make the assumption that differences in alpha measured with binocular eyes open vs closed translates to differences in alpha noted with a patched eye open or closed. Although changes in alpha amplitude appear comparable under monocular and binocular viewing, the differences in perceptual contrast sensitivity between the patched eye open and closed condition are quite modest. The authors do not report differences in contrast sensitivity in the binocular condition, so it is difficult to assess if these are comparable (contrast sensitivity changes in binocular (both eyes open vs closed) and monocular (patched eye open vs closed). The authors also employ their results to make claims about neuroplasticity, however this may be too general a claim. It seems as though the authors are specifically using an adaptation paradigm to elicit short-term changes (within 30 minutes from deprivation). While technically, the visual system is changing, it may be slightly misleading to refer to these neuroplastic changes given there are no measured long-term effects. The authors also fail to explain differences in binocular paradigm, noting recovery of binocularity in their phase combination paradigm, but persistent changes in their rivalry assessment. The authors also may overstate the implications of this in the discussion, as they provide no direct evidence that their reported changes after monocular deprivation are attributed to GABA interactions in primary visual cortex.

This work is important to our understanding of not only endogenous modulators of visual perception, but may have implications in how this knowledge is applied in clinical practice, specifically the treatment of amblyopia with patching.

Reviewer #2 (Public Review):

The manuscript compares the chondrogenic potential of iPSCs derived from human chondrocytes isolated from healthy and osteoarthritic AC tissue. Both iPSCs derived from healthy and osteoarthritic AC tissue exhibit markers of pluripotency and were able to give rise to mesenchymal progenitors, although they had distinct differences in metabolic and chromatin modifier genes, as found by RNA seq analysis. The impact of these transcriptome signatures was functionally reflected in a lower chondrogenic potential of the MSCs derived from OA iPSCs compared to healthy donor (AC) iPSCs. This was assessed based on the reduced expression of hyaline cartilage markers and the reduced deposition of the glycoprotein-rich ECM matrix upon chondrogenic differentiation of day 21 micromass cultures from OA patients compared to healthy donors. The distinct gene expression profiles of OA chondrocytes were also found to be consistent with publicly available RNA-seq data performed on healthy and OA cartilage tissues further confirming that the newly identified differences in epigenetic and metabolic signatures are imprint from healthy and OA-chondrocytes.

Reviewer #2 (Public Review):

Tools that enable labeling and genetic manipulations of synaptic partners are important to reveal the structure and function of neural circuits. In a previous study, Barnea and colleagues developed an anterograde tracing method in Drosophila, trans-TANGO, which targets a synthetic ligand to presynaptic terminals to activate a postsynaptic receptor and trigger nuclear translocation of a transcription factor. This allows the labeling and genetic manipulation of cells postsynaptic to the ligand-expressing starter cells. Here, the same group modified trans-TANGO by targeting the ligand to the dendrites of starter cells to genetically access pre-synaptic partners of the starter cells; they call this method retro-TANGO. The authors applied retro-TANGO to various neural circuits, including those involved in escape response, navigation, and sensory circuits for sex peptides and odorants. They also compared their retro-TANGO data with synaptic connectivity derived from connectivity obtained from serial electron microscopy (EM) reconstruction and concluded that retro-TANGO can allow trans-synaptic labeling of presynaptic neurons that make ~ 17 synapses or more with the starter cells.

Overall, this study has generated and characterized a valuable retrograde transsynaptic tracing tool in Drosophila. It's simpler to use than the recently described BAcTrace (Cachero et al., 2020) and can also be adapted to other species. However, the manuscript can be substantially strengthened by providing more quantitative data and more evidence supporting retrograde specificity.

Deja los tres siguientes comentarios antes de clase. Un comentario de algo que aprendiste Una conexión a algo que ya sabías Una pregunta

Reviewer #2 (Public Review):

The cycling of "co-substrates" in metabolic reactions is possibly a very important but often overlooked determinant of metabolic fluxes. To better understand how the turnover dynamics of co-substrates affect metabolic fluxes the authors dissect a few metabolic reaction motifs. While these motifs are necessarily much simpler than real metabolic networks with dozens or hundreds of reactions, they still include important characteristics of the full network but allow for a deeper mathematical analysis. I found this mathematical approach of the manuscript convincing and an important contribution to the field as it provides more intuitive insights how co-substrate cycling could affect metabolic fluxes. In the manuscript, the authors stress particularly how the pool sizes of co-substrates and the enzymes involved in the cycling of those can constrain metabolic fluxes but the presented results also go substantially beyond this statement as the authors further illustrate how turnover characteristics of substrates in branches/coupled reactions can affect the ratio of produced substrates.

The authors further present an analysis of previously published experimental data (around Figure 3). This is a very nice idea as it can in principle add more direct proof that the cycling of co-substrates is indeed an important constraint shaping fluxes in real metabolic networks and (instead of being merely a theoretical phenomena which occurs only in unphysiological parameter regimes). However, the way currently presented, it remained unclear to which extent the data analysis is adding convincing support that co-cycling substantially constrains metabolic fluxes. Particularly, it remains unclear for which organisms and conditions the used experimental dataset holds, how it has been generated, and with what uncertainty different measured values come. For example, the comparison requires an estimation of v_max. How can these values determined in-vivo? Are (expected) uncertainties sufficiently low to allow for the statement that fluxes are higher than what enzyme kinetics predict? Furthermore, I am wondering to which extent the correlations between co-substrate pool levels and flux is supporting the idea that co-substrate cyling is important. The positive relation between ATP/AMP/ADP levels for example, is a nice observation. However, it remains a correlation which might occur due to many other factors beyond the limitations of co-substrate cycling and which might change with provided conditions.

Reviewer #2 (Public Review):

The authors are building on previous work by Dahlén et al testing for phenome-wide associations between ABO/RhD blood groups. This is important for identifying potential disease mechanisms related to the blood groups, and for identifying blood groups that may be at higher risk of certain diseases. As we begin to create predictive models across diseases for precision medicine approaches in clinical care, this type of information informs the inclusion of blood groups as predictors in these models.

Notably, this study looks at each subset of A, B, AB, and O versus the remaining groups as compared to other studies which focus on comparing O and non-O blood groups. This paper successfully estimates the incidence rate ratios for 1,312 phecodes for A, AB, B, O, and RhD blood groups. The authors also tested for associations between the age of diagnosis and blood groups. The study's conclusions largely summarize these associations, which are important for the community to browse and interpret. However, the conclusion that ABO/RhD groups are the result of selective pressure driven partially by robustness to disease is not well founded simply from the significant association statistics within the paper.

As in all studies, there are inherent limitations in the data. The Danish National Patient Registry (DNPR) is a population-level cohort, so findings may be generalizable to Denmark or European countries. However, ascertainment biases may exist from what subset of the DNPR also had blood group determination (patients who may need blood transfusions during their hospital stay) and from the use of diagnoses from a hospital setting (most severe diseases) rather than the primary care setting.

The statistical model used to identify these associations is sound, although additional sensitivity analyses and rationale descriptions would add clarity to the appropriateness of this model and variable selection. The authors carefully note that, based on the study design, any associations here are not to be causally interpreted. The study is well powered with nearly 500,000 patients and a median follow-up time of 40.8 years. Multiple testing burden is accounted for using FDR-adjusted p-values. The established method of phecode mapping is used for this phenome-wide approach.

Reviewer #2 (Public Review):

The HIV inflammasome sensor CARD8 senses intracellular HIV-1 protease activity through direct cleavage by HIV-1 protease between the F59 and F60 positions in the human CARD8 protein. The authors show that the F60 position is variable across non-human primate species that show varying levels of cleavage efficacy. They also posit that inflammasome induction may be dependent upon Toll-like receptor signaling.

Strengths: The authors are able to show that both HIV-1 and HIV-2 cleave and activate the human CARD8 inflammasome. The authors also demonstrate that changes to the 60th position of CARD8 cause a decrease in cleavage efficacy in vitro by HIV-1.

Weaknesses: The study is limited to the introduction of a few mutations in human CARD8 and their cleavage and activation by HIV. The physiological relevance remains unclear without direct investigation of different versions of simian CARD8 protein and SIVs in T cells and macrophages.

Reviewer #2 (Public Review):

By now, the public is aware of the peculiarities underlying the omicron variants emergence and dissemination globally. This study investigates the mutational biography underlying how mutation effects and epistasis manifest in binding to therapeutic receptors.

The study highlights how epistasis and other mutation effect measurements manifest in phenotypes associated with antibody binding with respect to spike protein in the omicron variant. It rigorously tests a large suite of mutations in the omicron receptor binding domain, highlighting differences in how mutation effects affect binding to certain therapeutic antibodies.

Interestingly, mutations of large effect drive escape from binding to certain antibodies, but not others (S309). The difference in the mutational signature is the most interesting finding, and in particular, the signature of how higher-order epistasis manifests in the partial escape in S309, but less so in the full escape of other antibodies.

The results are timely, the scope enormous, and the analyses responsible.

My only main criticisms walk the stylistic/scientific line: many of the others have pioneered discussions and methods relating to the measurement of epistasis in proteins and other biomolecules. While I recognize that the purpose of this study is focused on the public health implications, I would have appreciated more of a dive into the peculiarity of the finding with respect to epistasis. I think the authors could achieve this by doing the following:

a) Reconciling discussions around the mutation effects in light of contemporary discussions of global epistasis "vs" idiosyncratic epistasis, etc. Several of the authors of the manuscript have written other leading manuscripts of the topic. I would appreciate it if the authors couched the findings within other studies in this arena.

B)While the methods used to detect epistasis in the manuscript make sense, the authors surely realize that methods used to measure is a contentious dimension of the field. I'd appreciate an appeal/explanation as to why their methods were used relative to others. For example, the Lasso correction makes sense, but there are other such methods. Citations and some explanation would be great.

Lastly (somewhat relatedly), I found myself wanting the discussion to be bolder and more ambitious. The summary, as I read it, is on the nose and very direct (which is appropriate), but I want more: What do the findings say for greater discussions surrounding evolution in sequence space? For discussions of epistasis in proteins of a certain kind? In, my view, this data set offers fodder for fundamental discussion in evolutionary biology and evolutionary medicine. I recognize, however, the constraints: such topics may not be within the scope of a single paper, and such discussions may distract from the biomedical applications, which are more relevant for human health.

But I might say something similar about the biomedical implications: the authors do a good job outlining exactly what happened, but what does this say about patterns (the role of mutations of large effect vs. higher-order epistasis) in some traits vs others? Why might we expect certain patterns of epistasis with respect to antibody binding relative to other pathogenic virus phenotypes?

In summary: rigorous and important work, and I congratulate the authors.

Reviewer #2 (Public Review):

In the submitted manuscript under the title "NSC-derived exosomes enhance therapeutic effects of NSC transplantation on cerebral ischemia in mice", Zhang et al. applied human induced pluripotent stem cells (iPSCs) together with exosomes extracted from NSCs to treat cerebral ischemia induced by middle cerebral artery occlusion/reperfusion (MCAO/R) in mice. They reported that NSC-derived exosomes can ease the inflammatory response, alleviated oxidative stress after NSC transplantation, and facilitated NSCs differentiation in mouse brain. Using the NSC together with their exosomes can ameliorate the injury of brain tissue including cerebral infarct, neuronal death and glial scarring, and promoted the motor function recovery. Finally, they speculated that the miRNA(s) in the exosomes is the key factor to improve the treatment of the NSC transplantation for the stroke. This is an interesting study that contributes important findings which will be of interest to the researcher in the field of the NSC transplantation. However, there are some key points should be further explained.

Major points:<br /> 1). This study does not provide any evidence about the cell death of the transplanted cells. The immunostaining of the Caspase-3 or TUNEL staining should be used to address this issue.

2). The authors showed that the neurological functions (evaluated by balance beam, ladder lung, rotarod test and Modified Neurological Severity Score (mNSS) up to 8 weeks after treatment (Figure 1C)) were significantly improved in the NES+Exo group compared to their control groups. However, these cells (transplanted cells) are progenitors (Nestin+) or undifferentiated cells (Tuj1+) at this stage (Figure 3). Thus, I was curious about that how can the immature neurons play neurological functions? This point should be explained.

3). The authors used the Golgi staining to show the NES+Exo can improve dendritic density and length. How do you know these neurons are transplanted cells?

4). The cell morphology of tdTomato+ cells is fuzzy and it is difficult to distinguish the cell body. It looks like that these cells out of whack.

Reviewer #2 (Public Review):

To understand the origins of life, it is often necessary to establish synthetic molecular systems that model how primitive cells might have operated. Adopting this approach, here Le Vay et al. tackle one of the mysteries of early cells: how could primitive biomolecules have controlled the behavior of the compartments they inhabited? By forming coacervate droplets from polylysine peptides and ribozymes (catalytic RNAs), they observe changes in droplet properties driven by ribozyme activity and propose a route to form an integrated protocellular system that allows the evolution of biomolecules based on compartment behavior, modeling potential early life processes.

Polymers of opposite charge can phase-separate into coacervate droplets in equilibrium with surrounding aqueous phases. Such condensates are thought to act as subcellular compartments mediating some cellular functions. Coacervates, though, are also of interest as model compartments for biomolecules at the origins of life. A number of studies have shown how the properties and behavior of coacervates can be modulated based on external biological or physicochemical changes. There remains a key question: for coacervates to serve as a vessel for biology at the origin of life, can coacervate behavior be controlled from within? Previously this has been shown possible in some systems of membranous vesicles, an alternative model of primordial compartments.

Proteinaceous enzymes have been deployed to transform precursor compounds into potential coacervate components and induce the formation of condensed-phase microdroplets, but such enzymes are not thought to have been available at the origins of life. Instead, ribozymes are thought to have catalysed key reactions in early biology. Here, by using a ribozyme ligase to concatenate RNA molecules when together in a polylysine coacervate, the authors clearly demonstrate that coacervate properties change, showing a more rounded droplet shape and reduced fusion tendencies. Interestingly, the authors find that this distinctive behavior emerges when the reaction occurs in the coacervate phase, instead of before coacervate formation.

This influence of sequence-encoded phenotype on compartment properties has few precedents and has long been a target of origin of life research. The authors propose that it could serve as the basis for the establishment of coacervate droplets as units of selection and evolution. For this, a trio of critical challenges must be overcome and the authors begin to shed light on these.

First, the droplets must support ribozyme activity, without overly inhibiting it (or the droplet becomes an unfavorable habitat for these catalysts). Other ribozymes have often suffered inhibition due to conformation effects or substrate availability when mixed in a coacervate. The authors show here that the ligase ribozyme maintains activity (and may even be accelerated) in the coacervate. However, it appears to operate under single-turnover conditions and it is not yet clear whether multiple-turnover catalysis is possible in the coacervate.

Second, the droplet properties must be responsive to the activity of the biomolecules inside. The authors' observations of changes in coacervate behavior are robust, and they make some suggestions as to how such changes might be leveraged to establish selection pressure to drive the evolution of content molecules. In this study, though, the ribozyme comprises a substantial fraction (~1/2) of the coacervate negatively charged components, and in an evolutionary situation (with fewer molecules of RNA catalyst per compartment) it is not known whether the resulting droplet phenotype will change impactfully.

Third, the droplet must hold together its contents and avoid mixing with the contents of other droplets, to hold a molecular species together and defend against molecular parasites. Though there may still be some exchange of smaller molecules, the authors demonstrate that the lengthening of RNAs by ribozyme ligases in a coacervate can prevent fusion with other similar droplets (which otherwise occurs in the absence of RNA ligation) and preserve droplet identity. To use the coacervate as an evolutionary unit, droplets with active ribozyme will also need to be resistant to fusion with inactive droplets.

Putting such a system together based on the phenomenon observed by the authors would be a breakthrough in modeling primordial biology. A range of compartments have been proposed to act as habitats for early molecular biology, including porous rocks, mineral surfaces, ice phases, aerosols as well as membranous vesicles, and a key challenge is demonstrating how internal biological activities can influence compartment behavior. Establishing coacervates as genetically-controllable habitats for biomolecules will add to experimental models of such "life but not as we know it" and provide a new view of early biology.

Reviewer #2 (Public Review):

Gyrencephaly has been linked to the split of the subventricular zone (SVZ) and the formation of an outer subventricular zone (OSVZ) during neurogenesis. This paper proposes a convincing multizone computational model of neurogenesis allowing exploration of the role of this OSVZ in the folding dynamics. This model is a bridge between knowledge of cell proliferation and migration and the physics of growth.

Strengths<br /> • The computational model described in this paper is probably the most ambitious to date. It succeeds in translating the complexity of microscopic biological phenomena that describe cell proliferation and migration into physical phenomena from continuum mechanics. It is truly a tour de force.<br /> • The description of neurogenesis is particularly clear, within the reach of a naive reader despite its complexity. The figure illustrating the chronology of the phenomena at work is a success.<br /> • The paper builds on impressive efforts to estimate from real human brain sections some of the complex parameters of the model such as the density of cells at different stages of migration.<br /> • The physical model is able to show ripples in the deep zones of proliferation that seem induced by the folding of the cortex. This observation is consistent with feedback from folding on the organization of the migration, as these ripples are not part of the model. I do not know to what extent these ripples have been demonstrated in reality.<br /> • The model shows that significant proliferation in the OSVZ leads to a doubling of the frequency of folding, a phenomenon observed in reality in large brains, which gives rise to allometric laws between folding and brain size (see Toro et al., Germanaud et al.)<br /> • The paper includes an experiment based on heterogeneous proliferation in the OSVZ, which is difficult to model in more classical models such as Tallinen's one. This is a particularly interesting possibility for modelling spatial heterogeneity in the expression of genes that modulate neurogenesis (see Llinares-Benadero et al.).

Weaknesses<br /> • To account for the complexity of biological phenomena, the model relies on a large number of ad hoc choices whose consequences are difficult to predict.<br /> • The physical model description is highly technical and out of reach for a non-specialist.<br /> • The description of neurogenesis shows three zones of cell proliferation, each inhabited by a specific cell type. Despite its realism, the proposed model does not take into account the ISVZ where the intermediate progenitors operate.<br /> • The experiment of comparing several regimes derived from the relative importance of proliferation in the VZ and OSVZ is not very clear. It leads to the observation of the evolution of cell density maxima over time, which seems insufficient to conclude the importance of the OSVZ for folding. One wonders whether the key parameter that leads to folding is the rate of OSVZ proliferation or simply the total quantity of neurons generated by the two or even the three zones.<br /> • The experiment on the heterogeneity of proliferation in the OSVZ is a bit frustrating. I would like to see a set-up corresponding to the mosaics found in ferrets and closely associated with folding patterns.<br /> • It would be interesting to elaborate a little on the possibility of extending the model in 3D, which seems imperative to evaluate the nature of the folding pattern generated. Comparing them to reality is an essential step in gauging the credibility of the model. For instance, it would be interesting to test to which extent the model can father the type of variability observed in the general population (Mangin et al.). It will also be particularly interesting to work on the inverse model between the real folding patterns and the heterogeneous proliferation maps that can generate them.

Conclusion

The computational model of neurogenesis described in this paper is the most sophisticated model proposed to date. It is a convincing step towards a model that could one day simulate perturbations of neurogenesis that may give rise to the gyration abnormalities observed in certain developmental pathologies. A better understanding of the genesis of these anomalies could contribute to their use as a signature of hidden deleterious events occuring during neurogenesis.

References

Toro, R., Perron, M., Pike, B., Richer, L., Veillette, S., Pausova, Z., & Paus, T. (2008). Brain size and folding of the human cerebral cortex. Cerebral cortex, 18(10), 2352-2357.<br /> Germanaud, D., Lefèvre, J., Toro, R., Fischer, C., Dubois, J., Hertz-Pannier, L., & Mangin, J. F. (2012). Larger is twistier: spectral analysis of gyrification (SPANGY) applied to adult brain size polymorphism. NeuroImage, 63(3), 1257-1272.<br /> Tallinen, T., Chung, J. Y., Rousseau, F., Girard, N., Lefèvre, J., & Mahadevan, L. (2016). On the growth and form of cortical convolutions. Nature Physics, 12(6), 588-593.<br /> Llinares-Benadero, C., & Borrell, V. (2019). Deconstructing cortical folding: genetic, cellular and mechanical determinants. Nature Reviews Neuroscience, 20(3), 161-176.<br /> Mangin, J. F., Le Guen, Y., Labra, N., Grigis, A., Frouin, V., Guevara, M., ... & Sun, Z. Y. (2019). "Plis de passage" deserve a role in models of the cortical folding process. Brain topography, 32(6), 1035-1048.

Reviewer #2 (Public Review):

The authors of this paper identify a knowledge gap in our understanding of the generalizability of ecological associations of gut bacteria across hosts. Theoretically, it is possible that ecological associations between bacteria are consistent within a host organism but differ between hosts, or that they are universal across hosts and their environmental gradients. The authors utilize longitudinal data with a unique temporal resolution, on Amboseli baboons, 56 individuals who were sampled for gut microbiome hundreds of times over a decade. This data allows disentangling ecological dynamics within and across individuals in a way that as far as I know has never been done before. The authors show that ecological relationships among baboon gut bacteria, measure through a correlation based on covariation, are largely universal (similar within and across host individuals) and that the most universally covarying taxa are almost always positively associated with each other. They also compare these results with two sets of human data, finding similar patterns in one human data set but not in the other.

The main aim of this paper is to establish whether gut microbial ecologies are universal across hosts, and this the authors generally show to be true in a thorough and convincing way. However, some re-assessment or re-assurance on the solidity of their chosen method of estimating co-variation would be needed to fully assess the robustness of subsequent results. Specifically, the authors measure the correlation between microbial taxa from data on their abundance co-variation across samples. While necessary steps have been taken to validate the estimates across spurious correlations due to the compositional nature and autocorrelation structures present in the data, I worry that the sparsity of the data might influence the estimation of positive and negative correlations in a slightly different manner. There exist more microbial taxa than samples in the data and some taxa are present in as few as 20% of the samples, meaning that the covariation data will have a large amount of 0-0 pairs. I worry that the abundance of 0-0 pairs in the data might inflate the measures of positive co-variation, making taxa seem highly positively correlated in abundance when they in fact are missing from many samples. Of course, mutual absence is also a form of biologically meaningful covariation but taking the larger number of taxa than samples and the inability of sequencing technology to detect all low-abundance taxa in a sample, I am currently not convinced that all of the 0-0 pairs are modeled as a realistic and balanced way as a continuum of the other non-zero co-variation between taxa in the data. This may become problematic when positive and negative relationships are compared: The authors state that even though most associations between taxa were negative, the most universally correlated taxa pairs (taxa pairs with strongest correlations in abundance both within and between hosts) were enriched in positive associations. It may be possible that this is influenced by the fact that zero inflation in the data lends more weight to positive links than negative links. Whether these universal positive correlations are driven by positive non-zero abundance covariation or just 0-0 links in the data is currently unclear.<br /> Another additional result that would benefit from a more clear context is the result that taxa correlation patterns were more similar between phylogenetically close taxa and between genetically close host individuals. The former notion is to be expected if taxa abundances are driven by environmental (or host physiology-related) selective forces that favor bacteria with similar phenotypes. This yields more support to the idea that covariation is environmentally driven rather than driven by the ecological network of the bacteria themselves, and this could be more clearly emphasized. The latter notion of covariation being more similar in genetically related hosts is currently impossible to disentangle from the notion that covariation patterns were more similar with individuals harboring a more similar baseline microbiome composition since microbiome composition and genetic relatedness were apparently correlated. To understand if something about relatedness was actually influential over correlation pattern similarity, one would need to model that effect on top of the baseline similarity effect. Currently, it is not clear if this was done or not.

The authors also slightly overemphasize the generalizability of their results to humans, taking that only one of the human data sets they compare their results to, shows similar patterns. While they mention that the other human data set (that was not similar in patterns to theirs) was different in some key aspects (sampling frequency was much higher), the other human data set was also dissimilar to the other two (it only contained infants, not adults). Furthermore, to back up the statement that higher sampling frequency would be the reason this data set had dissimilar covariation between taxa, one would need to show that the temporal variation in this data set was different from the baboon one and show that these covariation patterns were sensitive to timescale by subsampling either data to create mock data sets with different sampling frequency and see how this would change the inference of ecological associations.

To the extent that the results are robust, particularly regarding to the main result of the universality of gut microbial ecological associations, the impact of this paper is not small. This question has never been so thoroughly and convincingly addressed, and the results as they stand have the power to strongly influence the expectations of gut microbial ecology across many different systems. Moreover, as the authors point out, evidence for universal gut microbial ecology is important for the future development of probiotics. An important point here, under-emphasized by the authors, is that universal gut microbe ecologies will allow specific interventions that use gut microbe ecology to manipulate emergent community properties of microbiomes to be more beneficial for the host, rather than just designing compositional cocktails that should fit all. In addition to the main finding of this study, the unique data set and the methods developed as part of this study (e.g. the universality score, the enrichment measures, the model of log-ratio dynamics, the assessment of covariation from time-ordered abundance trajectories) will doubtlessly be translatable to many other studies in the future.

Reviewer #2 (Public Review):

The synaptonemal complex (SC) is a ladder-like structure that is assembled between homologous chromosomes during meiotic prophase I. This structure is critical for accurate chromosome segregation as it is required for both crossover formation and regulating crossover frequency. In this study, the composition of the SC throughout meiotic prophase, SC dynamics, and its contribution to crossover formation is compared between male meiosis and female meiosis using C. elegans. Although the SC is found in both sexes, many aspects of meiosis, including recombination initiation and formation, differ between sexes. Whether sex-specific differences extend to the SC and how this influences recombination events has not been investigated. The authors use fluorescently-tagged SC central region proteins (SYP-2 and SYP-3) to quantify the amount of SC protein accumulation per nucleus. The data indicate that the composition of the SC is dynamic throughout the meiotic prophase with sexually dimorphic properties. In addition, by examining and quantifying the number of proteins that mark different recombination intermediates, the authors found that not only does the SC regulate different aspects of recombination, but the regulation is sex-specific. Overall, the assays and quantification in this manuscript are of high quality.

Overall, the manuscript is largely descriptive and doesn't test possible mechanisms behind the observed sex-specific differences. However, this study is of high interest as these sexually dimorphic phenotypes have not been previously studied. The data presented in this paper set a nice foundation for future work. The manuscript is mostly well-written and the data is presented well but lacks explanations for some of the observed phenotypes. Some minor textual revisions would provide insights into some of the male-specific phenotypes that were noted without explanation (e.g. Why might SYP-3 be more dynamic in early pachytene in spermatocytes?). In addition, the introduction could be revised to provide a more coherent flow and to highlight the significance of sexual dimorphic aspects of meiosis.

Reviewer #2 (Public Review):

The study by Rossi et al. is focused on the role of the SASP factor BAFF as a key regulator of senescent cell biology. Using both in vivo and in vitro studies, the authors show that BAFF, particularly in the monocytic cell line THP-1, is a type I interferon-induced gene. The authors further showed, using both proteomics, transcriptomics, and genetic studies that while BAFF does not play a role in the cell viability or cell cycle arrest of senescent cells, BAFF does regulate other aspects of senescent cell Biology. This includes SA-B-GAL activity and inflammatory gene expression of multiple SASP genes. Lastly, the authors demonstrate that via potential autocrine/paracrine signaling mechanisms BAFF can likely bind to multiple BAFF receptors upregulated in senescent cells, and affect both the p53 and NF-kB pathways to control inflammatory gene expression.

In summary, we find the manuscript to be both well written and organized, and a nice study on the role of BAFF as a key regulator of senescent cell biology. We believe this finding will be of significant interest to both the senescent cell field and the aging field in general.

Reviewer #2 (Public Review):

In this work, the authors present a high-resolution cryo-EM structure of mitochondrial complex I, which was isolated from the model protostomian Drosophila melanogaster. Although multiple structures of related complexes have been published earlier, this system is particularly interesting as it seems not to adopt a so-called off-pathway "deactive" (D) state in contrast to the complex from Deuterostomia (including mammals) and therefore may provide novel mechanistic insights into complex I. The work is interesting, as it provides a novel contribution to the current discussion about the assignment of structural conformations to states in the catalytic cycle and/or in the active/deactive state transition of the complex.

Reviewer #2 (Public Review):

In this study, Labuz and collaborators characterize the impact of burn injury on the T cell populations of the human skin. The authors use multiparametric flow cytometry and single-cell transcriptomics to analyze the numbers and the transcriptional profile of conventional and unconventional T cell populations in samples collected from patients with acute burn injury, late burn injury, and without burn injury. Their results show that burn injury disturbs the balance of T cell subtypes by increasing the percentage of CD4 T cells and decreasing the percentage of CD8 T cells. Both CD4 and CD8 T cells in the burn tissue presented lower expression of CD69 and higher expression of CD38, IFN-gamma, and TNF-alpha. The percentage of gamma delta T cells and MAIT cells positive for TNF-alpha and IFN-gamma also increased in the burn tissue. The authors then use single-cell RNA sequencing to gain further insights into how burn injury impacts the overall functions of skin T cells. This unbiased transcriptional profiling confirmed their previous observations that both conventional and unconventional T cells in the skin are replaced by new clusters that express lower levels of "tissue-resident" signature genes such as CD69 and higher levels of homing markers such as SELL and S1PR1. CD8 T cells of the burn skin samples show a clear reduction in the expression of cytotoxic molecules such as GZMK, GZMH, and GNLY, and this contrasts with the upregulation of cytotoxic molecules that are observed in the populations of unconventional T cell populations.

This is a relatively simple and descriptive work that will likely be an important resource for future studies investigating the role of T cell responses in skin wound healing and the maintenance of skin barrier function against pathogens following burn injury. A broader and more unbiased analysis of scRNA-seq data is necessary to better understand the biological processes and cellular responses that are being affected by the transcriptional changes observed in each T cell population as well as the possible implications of their findings.

Reviewer #2 (Public Review):

With warming, fishes are generally expected to grow faster to smaller adult body sizes, as described by the temperature-size rule and other similar theories. However, the generality of this shrinking and the patterns among age classes within a species remain major research questions made all the more urgent by the rapid warming faced by many aquatic ecosystems. In this manuscript, the authors take advantage of an artificially heated ecosystem to investigate the impacts of warming on an unharvested population of fish and investigate patterns of growth, size structure, and mortality in an unexploited fish population. Surprisingly, while faster growth rates in juveniles are demonstrated, as would be expected, adult size remains higher in the heated habitat compared to a nearby non-heated habitat. This unexpected result will be of broad interest.

Strengths

The semi-natural experiment provided by the artificial warming from the power plant is a very nice design. While it is not the only place this type of study could be conducted, this system seems to have an unusually high degree of heating, that fact and the unexpected results make for a very interesting study that should be of broad interest. The study is also presented in a clear and concise manuscript and the conclusions are well-supported.

Weaknesses

In certain sections, it seems like the paper would benefit from a more thorough consideration of alternative explanations for the higher body size in the warmed population, like the release from density dependence or altered prey availability, and how those alternative explanations do or do not fit with the result that mortality was higher for the heated population. The consideration of mortality is a strength of the paper, but this result and how it fits with the result that heated adults did not shrink could be discussed in greater depth. It is unfortunate that factors other than the heat that might influence mortality, like predation rates, remain unknown in this system, but then they are rarely well understood in real-world settings like whole ecosystems.

Reviewer #2 (Public Review):

This is an interesting study. In this study, the authors have linked single-cell RNA sequencing, spatial transcriptomic, and multiplex fluorescence in situ hybridization to characterize human oral mucosa in health and oral chronic inflammatory disease. They defined highly specialized epithelial and stromal compartments and spatially mapped a rare pathogenic fibroblast population likely responsible for lymphocyte recruitment and angiogenesis. They highlighted that the most dramatic variation in transcriptional/cellular spatial variability corresponds to oral mucosal tissue depth. The comparison of the list of genes with altered expression in gingival inflammation with the ones highlighted from the GWAS analysis related to patients with periodontitis is very interesting and will help to generate new hypotheses for future studies. Together with the recent publication from Williams et al., 2021, these studies are of particular interest and a valuable resource for researchers who study oral mucosa, especially gingiva in healthy conditions and periodontal diseases.

Reviewer #2 (Public Review):

In the paper, the authors aimed to repurpose a previously developed Variational Autoencoder (VAE) trained on adult rsfMRI data to characterise the in vivo foetal-neonatal brain development. Although the attempts to understand both healthy and aberrant early functional development are becoming increasingly popular, the processing and interpretation of the foetal-neonatal rsfMRI remain challenging due to methodological difficulties and the extremely fast and complex nature of the early brain development itself. For this reason, the non-linear computational models, such as the proposed VAE, have the potential to represent the rsfMRI data and capture the early neurodevelopmental trajectories with higher accuracy compared to more prevalent linear methods such as ICA.

In this vein, the authors successfully apply the adult-trained VAE to compress the spatial representation of foetal-neonate rsfMRI cortical patterns into 256 latent features. Due to the non-linear nature of the VAE, this latent representation has the potential to yield more informative brain representations of rsfMRI data compared to other available methods making it a strength of the article.

Nevertheless, one important limitation is that the direct application of the model trained on adult data to early functional connectome and more importantly, the interpretation of the reconstructed latent space-based maps rests on a strong assumption that the adult connectome features are stable and recognisable in the very early period. Moreover, such a model trained on the adult data would also be incapable to reveal possible network structures that would be present in the developing but not in the adult brain.

The attempt to validate the method and assess its generalisability on two independent, fairly large datasets that include foetuses, and preterm- and term-born infants is commendable. However, the interpretation of the results in light of the subject, image acquisition, and processing (which is widely recognised to be very difficult, especially in foetuses) heterogeneity requires caution. For example, the VAE reconstruction error is positively correlated with the age at scan in dHCP, and DBI full-terms, but the relationship is very strong in the reverse direction in DBI foetuses. This suggests differences between the subgroups of subjects which might be driven by factors other than age. Thus, we cannot exclude the possibility that the high age-predictive power of the models based on the latent features is partly driven by those differences in addition to the age-dependant features of the infant functional connectome.

The approach for the extraction and mapping of the group-level brain resting state networks is interesting and has the potential to uncover new insights into the early connectome. However, some of the current results are rather surprising and put into question their biological plausibility. For example, the authors suggest observing the precursor of the default-mode network in the DBI but not the dHCP dataset. This is rather strange given the DBI subjects (including foetuses) were on average scanned earlier than the dHCP subjects. Also, the pattern similarity of the best matched extracted independent component ('brain network') in the full-term dHCP vs full-term DBI comparison is 0.6 which is rather low if expecting the same networks to be extracted in the age-matched comparison. Additionally, the network visualisations show large heterogeneity of the distribution of activation/deactivations within extracted independent components between the datasets (even after ordering them for pattern similarity) which contradicts the expectation that the extracted networks (if real) should be stable, if not along the whole development, then at least between the narrower age ranges within the datasets.

Overall, the interpretation of the current work is somewhat limited, and careful analysis of the latent representations derived from foetal-neonate data might be required to dissociate the effects of potential confounders from biological/developmental mechanisms. This might be difficult in the context of the highly complex and mostly black-box strategy such as VAE (this applies not only to the current method but to all novel methods proposed to study rsfMRI). Despite these limitations, the proposed approach could be very interesting methodologically with a potential impact on the future analysis of rsfMRI data. Overall, the authors achieved their aim of applying a novel VAE method to foetal-neonatal functional data and demonstrated that the extracted latent variables are predictive of brain age. However, careful evaluation of the latent representations and differences in predictive results and the mapped networks between the two datasets might be necessary to support the conclusion that the VAE-derived representations of foetal-neonatal rsfMRI carry informative neural signatures.

Reviewer #2 (Public Review):

This study combines molecular analysis of human melanoma cells with in vivo functional experiments in zebrafish. ChIP-seq analysis of A375 melanoma cells stimulated with TGFB revealed a TGFB enhancer. The human enhancer was a clone and a zebrafish transgenic line driving GFP by this enhancer (TIE:EGFP) revealed that TIE:EGFP was only expressed in late melanomas. TIE:EGFP+ cells showed downregulated IFN response but upregulation of novel chronic GHB target genes. AP-1 transcription factor is required for the activation of this enhancer. Expression of the chromatin remodeller SATB2 promoted activation of TIE:EGFP in early melanomas. Finally, in vivo imaging, flow cytometry and scRNA seq showed that macrophages preferentially phagocytosed TIE:EGFP+ melanoma cells.

The identification of this novel TGFB enhancer is important since most studies focused on acute TGFB effects in melanoma. However, the present study identified a set of chronic TGFB target genes that may be relevant in melonoma and probably other tumors. Therefore, this study paves the way for future studies aiming at revealing the importance of this enhancer in different tumor histotypes and the novel identified chronic TGFB target genes.

Most conclusions are supported by the data, with the exception of the ones related to macrophages that are not fully convincing.

Reviewer #2 (Public Review):

There is currently much discussion about the function of several viral proteins hypothesized to be "viroporins", especially specific proteins within SARS-CoV-1 and CoV-2, such as Orf3a. While some prior studies suggest that Orf3a exhibits ion channel activity, others disagree on this important topic. In the present study, compelling evidence is presented that Orf3a does not function as an ion channel, and suggestions are made as to its actual function. The study combines imaging to delineate Orf3a location in the cell, extensive functional analyses that demonstrate a lack of ion channel activity beyond endogenous currents, and compelling structural evidence that Orf3a does not take the form of an ion channel - lacking a clear conduction pathway and also having a basic aqueous vestibule that would not be predicted to support cation channel activity. Finally, co-assembly with trafficking proteins suggest, instead, functioning of Orf3a as a host cell trafficking disruptor that could contribute to immune cell evasion or even viral exit.

The authors present exhaustive, high-quality data to support their conclusions that Orf3a proteins from SARS-CoV-1 and SARS-CoV-2 do not exhibit ion channel activity. They clearly show Orf3a at the cell membrane and fail to detect ion channel activity using multiple modalities. I believe this work closes the book on the question of Orf3a as a viroporin. It is difficult to find any deficiencies in the experimental work. The parts about a role disrupting trafficking are a little more speculative but nevertheless appropriate and serve as a guidepost for future studies to fully elucidate the true role of Orf3a.

Reviewer #2 (Public Review):

The manuscript presents a very simple and clear result. It demonstrates that neither place-cell nor time-cell presence is a constant in the rat hippocampus, but that both of these modes of activity are engaged flexibly depending on task demands. This result fits into a growing body of published work showing similar examples of flexibility in hippocampal representations; the authors do a fair job in relating their results to these studies. The innovative aspect of their manuscript is that it specifically addresses place cells and time cells, which have been different, and sometimes confusing, ways of thinking about hippocampal activity. By showing that the hippocampus shifts between distance and time encoding, the authors fit place cells and time cells into a more general framework of flexible representations.

The manuscript uses somewhat unusual and not very well-motivated criteria for classifying cells as distance or time cells. To detect the timing of neural activity on each trial, the authors look at the earliest onset of firing prior to the peak. It seems that this method would be highly susceptive to noise, and it is unclear why it would be better than the more standard methods like detecting the actual peak of firing or fitting a stretchable template to the entire firing pattern on each trial. This is a minor weakness of the manuscript, since the main conclusion shouldn't depend on the exact method used to classify cells. The difference between fixed-time and fixed-distance trials reported by the manuscript appears to be large and statistically robust.

Reviewer #2 (Public Review):

In their manuscript "Growth cone advance requires EB1 as revealed by genomic replacement with a light-sensitive variant", Dema et al. showcase a CRISPR-based strategy to introduce a photo activatable EB1 variant into cultured cells in a single genome engineering step. Upon photoactivation this EB1 variant, which they term π-EB1, dissociates, thus severing the connection between the microtubule tip and +TIP proteins. They demonstrate this technique in human induced pluripotent stem cells, verifying that this genetic engineering procedure neither influences the cells beyond the EB1 gene nor hinders their ability to differentiate into neurons. Subsequently, they nicely verify that dissociation of π-EB1 leads to hindered microtubule growth, which subsequently leads to growth cone retraction. Accordingly, π-EB1 expressing axons cannot grow into an area illuminated with blue light, demonstrating the system's usefulness in circuit engineering. Finally, the authors try to specifically redirect growth cones by illuminating defined sections of the growth cone. This however leads mainly to growth cone retraction, in 70% of axons as the authors note, but succeeds in the remaining axons. Sadly, the authors do not further investigate the mechanism at the bottom of the observed axon retraction. Nevertheless, this study adds a valuable tool to the optogenetic toolbox of neurobiologists in the axon growth as well as circuit engineering fields.

Besides a few small writing and figure-editing faux pas, the study is well-written and robustly designed. The conclusions drawn by the authors are well supported by the data, which itself is technically well-prepared and controlled.

Reviewer #2 (Public Review):

Previous studies have shown that the transcription factor Emx2 controls mirror-image PCP along the line of polarity reversal (LPR) by regulating the trafficking of an orphan receptor GPR156. However, the underlying mechanism is unknown. Here, the authors provide evidence that Emx2 represses transcription of Stk32a, which, in turn, negatively regulates GPR156 surface expression, thereby coupling cell-intrinsic and tissue-level PCP in the vestibular sensory epithelia.

Overall, the data are clearly presented and largely convincing. Using RNA-seq and ISH and both loss- and gain-of-Emx2 in vivo, the authors show that Stk32a is expressed in a complementary domain to Emx2 via Emx2-mediated repression. Gain- and loss-of-Stk32a experiments demonstrate that Stk32a is required for hair cell PCP in the Emx2-negative regions and is sufficient to reorient PCP in the Emx2-positive region. Moreover, Stk32a negatively regulates GPR156 localization to apical junctions without affecting core PCP proteins or Emx2 expression. However, there are several notable weaknesses, including a) because transcripts of the Stk32a mutant allele were still present, the nature of the Stk32a mutation is unclear; b) Mechanisms by which Emx2 represses Stk32a transcription were not addressed or discussed; c) Mechanisms by which Stk32a regulates GPR156 surface expression were not addressed. Addressing these issues at least partially would provide stronger support for the proposed model and improve the paper's impact.

Reviewer #2 (Public Review):

This study combines data from different experiments to provide a detailed and conclusive mechanism of how transition metal ions are transported by a prokaryotic member of the SLC11 family. Although insight into this process was already provided in previous investigations, the novelty here concerns the presentation of X-ray structures at high resolution which, in combination with previously determined structures of the same protein, show three relevant conformations on the transport cycle in the presence and absence of substrate. For the interpretation of mechanisms, the conclusions derived from these structures are supported by complementary functional experiments from isothermal titration calorimetry and transport assays. Finally, a series of molecular dynamics simulations illustrate the stability of the investigated conformations and the interaction network that was proposed to be relevant for conformational transitions.

The strength of the manuscript lies in the thoughtful experimental design of the study and the high quality of the data. The X-ray structures are as good as they probably can get for a delicate membrane protein and the interaction with ions was confirmed by anomalous scattering experiments. Although the structure of the outward-facing conformation has relied on a mutation that stabilizes this state, the conformation is similar to known outward-facing conformations of other family members. The presented complementary ITC experiments are of high quality and the experimental design is intriguing.

A comparably smaller weakness concerns a shortage in the critical assessment of the data and their relation to previous findings in the field. This is in no way meant to question major conclusions drawn from this study, but it might help the reader to better understand the limits of the results and their interpretation. This weakness can be addressed by better documentation of the data and some revision of the text.

Reviewer #2 (Public Review):

As described in the manuscript, gaze following is a dynamic process that should be investigated with similarly dynamic stimuli (wherever possible). In this case, the authors used videos, rich with visual information, that could be deemed an appropriate example of such stimuli. By constructing scenarios where actors gazed toward 1) a target person, 2) distractor or 3) nothing, the authors were able to easily study observers' eye movements. First, they were able to determine a baseline for how observers follow gaze in each of the three aforementioned conditions which is an important reference for future studies of this nature. Further, they suggest that eye movements are affected by how gaze following interacts with peripheral information (i.e., processing gaze-related information from the actor is combined with peripheral information about the presence/absence of a target person). Second, the authors also determined that eye movement behavior is affected by gaze information (i.e., changes in the gaze of the principal actor), in an anticipatory manner. This was verified using a DNN approach (using only the gazer's head direction) and then, confirmed through human observers' ratings. Lastly, the authors noted the presence of subsequent, reverse saccades (in the direction of the gazer and then, toward the target), which were shown to play a role in correcting an initial inference based on a slow head velocity of the gazer (confirmed with an SVM approach). While these are important first inquiries related to understanding eye movement behavior elicited in response to gaze following, a few items remain to be further elucidated, including what additional, peripheral information (besides target/distractor absence and presence) drives eye movements during gaze following. Overall, the dynamic videos used by the authors, in combination with their investigations, provide an important first step toward studying gaze following in more realistic conditions.

Reviewer #2 (Public Review):

In mammalian genomes (with some exceptions), the location of recombination hotspots is driven by the PRDM9 zinc-finger protein that recognizes some specific DNA motifs and recruits the machinery inducing double-strand breaks (DSBs) initiating recombination. As DSBs are repaired with the homologous chromosome, "hot motifs" can be rapidly eroded through gene conversion occurring during the repair. This led to the "hotspot paradox" question and to the development of red queen models of hotspot evolution where the lack of enough DSB motifs can select for new PRDM9 alleles recognizing new sets of motifs, which in turn are eroded. However, this model fails to explain some observations, in particular, that the number of DSB seems not limited by PRDM9 sites. Recent findings also showed that PRDM9 played a central role in the symmetrical binding of homologous chromosomes.

In this study, the author incorporated this new finding (and more realistic assumptions compared to previous models) in a model of hotspot evolution. Their main result is that it affects the evolution dynamics and in particular the causes of selection on new PRDM9 alleles. Instead of selection pressure to increase the number of DSB targets, they showed that selection likely occurred instead to limit the number of hotspots to the hottest and symmetrical ones. These results are important as they changed our view and understanding of the evolution of mammalian hotspots and should have general implications for the study of recombination. The article focuses on complex mechanisms and can appear rather specific and technical. However, it nicely exemplifies the importance of taking molecular mechanisms into account to model genome evolution.

Overall, the model is sound with no apparent flaw and should be an important contribution to the field. The model is rather complex but the authors focused on a few key parameters while fixing others based on empirical knowledge. This allows for highlighting the novelty of the results without being lost within too many scenarios and hypotheses. However, two main issues should be addressed but they mostly concern the way the model and the results are presented and do not. First, partly due to the complexity of the mechanisms, the core of the manuscript is rather difficult to follow and would deserve a more careful and explicit presentation to guide the reader, as detailed below. Second, the implications of the model and the practical and testable predictions it makes could be developed more, in particular, to compare with previous models. The main comments are listed below.

1) The introduction reads very well and clearly explains complex mechanisms. It is a bit long and could be reduced a bit.<br /> 2) It is quite helpful to analyze the model step by step. However, the objective of each step is not clearly explained, and it is left to the reader to understand where the authors want to go. At first read, it is not clear whether the authors present an analysis of the model or simulation results and why they do that. So, the results part deserves rewriting and re-organization to guide the reader.<br /> - In the two first parts (Fitness with one heat and two heats) it should be stated more explicitly that it corresponds to an analysis of the fitness landscapes generated by the molecular mechanisms than results on the evolutionary dynamics<br /> - The part "Dynamics of the two-heat model" corresponds to simulations and it is only at this point that mutation on PRDM9 is introduced.<br /> - In the present form, the presentation of the results describes many mechanisms (which is fine). However, as the model is complex, stressing the main conclusion for each part could be useful as then making a clear link between the different steps of the reasoning.<br /> 3) The choice of key parameters is well justified with a detailed review of the literature and it is well justified to fix most of them to focus on the key unknown (or not well-known) ones. However, in a few cases, additional simulations or at least better justification would be welcome, in particular on the mutation dynamics of PRDM9.<br /> 4) The model clearly gives new insights into the evolution of recombination hotspots and appears better to explain some results. However, it is not clear what are the predictions of the model that could be properly tested with data, in particular against previous models. Some predictions are proposed but remain mainly qualitative. For example, can one quantify that this model predicts a skewer distribution of hotspots compared to previous red-queen models? How good is the model at predicting the number of PRDM9 alleles in human and mouse for example? Only the diversity at PRDM9 is given, it may be interesting to also give the number of alleles to compare to observations. The discussion on this remains a bit vague. Finally, are there additional predictions of the model that could be used to test it?<br /> 5) The Penrose stair metaphor is appealing but it seems to be dependent on the definition of hotspot, so not to represent a real biological process. Related to metaphors, it is also not very clear whether the authors suggest abandoning the red-queen metaphor for the benefit of the Penrose stair one. Actually, we can still consider that it is a red-queen dynamics but with a different underlying driver.

Reviewer #2 (Public Review):

This paper studies how relative values are encoded in a learning task, and how they are subsequently used to make a decision. This is a topic that integrates multiple disciplines (psych, neuro, economics) and has generated significant interest. The experimental setting is based on previous work from this research team that has advanced the field's understanding of value coding in learning tasks. These experiments are well-designed to distinguish some predictions of different accounts for value encoding. However there is an additional treatment that would provide an additional (strong) test of these theories: RN would make an equivalent set of predictions if the range were equivalently adjusted downward instead (for example by adding a "68" option to "50" and "86", and then comparing to WB and WT). The predictions of DN would differ however because adding a low-value alternative to the normalization would not change it much. Would the behaviour of subjects be symmetric for equivalent ranges, as RN predicts? If so this would be a compelling result, because symmetry is a very strong theoretical assumption in this setting.