Reviewer #2 (Public Review):

This paper reports that neonatal CD43- B cells produce IL-10 upon BCR stimulation, which inhibits TNF-alpha secretion from the peritoneal macrophage. In the neonatal CD43- B cells, the BCR-mediated signal transmitted Stat5 activation and induced IL-6 production, and subsequently, the secreted IL-6 activated Stat3 finally leading to IL-10 production. The authors identified a unique signaling pathway leading to IL-10 production and revealed the different responses between CD43+ and CD43- B cells against BCR crosslinking. A weakness of this study is that the neonatal CD43- B cell subset secreting IL-10 has not been characterized and discussed as well. BCR expression levels between adult CD43- B cells and neonatal CD43- B cells have been overlooked to explain the different reactivity. Clarity on these points would substantially enhance the impact of the manuscript.

Reviewer #2 (Public Review):

The Kaiser lab has been on the forefront in understanding the mechanism of dopamine release in central mammalian neurons. assessing dopamine neuron function has been quite difficult due to the limited experimental access to these neurons. Dopamine neurons possess a number of unique functional roles and participate in several pathophysiological conditions, making them an important target of basic research. This study here has been designed to describe the proteome of the dopamine release apparatus using proximity biotin labeling via active zone protein domains fused to BirA, to test in which ways its proteome composition is similar or different to other central nerve terminals. The control experiments demonstrating proper localization as well as specificity of biotinylation are very solid, yielding in a highly enriched and well characterized proteome data base. Several new proteins were identified and the data base will very likely be a very useful resource for future analysis of the protein composition of synapse and their function at dopamine and other synapses.

Major comment:

The authors find that loss of RIM leads to major reduction in the number of synaptically enriched proteins, while they did not see this loss of number of enriched proteins in the Syt1-KO's, arguing for undisrupted synaptome. Maybe I missed this, but which fraction of proteins and synaptic proteins are than co-detected both in the Syt1 and control conditions when comparing the Venn diagrams of Fig2 and Fig 3 Suppl. 2? This analysis may provide an estimate of the reliability of the method across experimental conditions.

Reviewer #2 (Public Review):

This paper identifies the need for improved pre-clinical models for the study of human primordial germ cells (PGCs) and suggests the common marmoset (Callithrix jacchus) as a suitable primate model. In vitro gametogenesis offers an alternative method to generate germ cells from pluripotent stem cells for study and potential pre-clinical applications. Therefore, the authors aimed to take the first steps toward developing this technology for the marmoset. Here, iPSCs have been derived from the marmoset and differentiated to PGC like-cells (PGCLCs) in vitro that have similarities in gene expression with PGCs identified from single-cell studies of marmoset embryos, as demonstrated through immunofluorescence and RT-qPCR approaches, as well as RNA-sequencing.

The authors have successfully developed a protocol that produces PGCLCs from marmoset iPSCs. These are shown to express key germline gene markers and are further shown to correlate in gene expression with PGCs from the marmoset. This study uses a 2D culture system for further expansion of the PGCLCs. When cultured with mouse testicular cells in a xenogeneic reconstituted testis culture, evidence is provided that cjPGCLCs have the capacity to develop further, expressing marker genes for later germline differentiation. However, the efficiency of generating these prospermatogonia-like cells in culture is unclear. Nonetheless, with the importance of developing protocols across species for in vitro gametogenesis, this paper takes a key step towards generating a robust preclinical system for the study of germ cells in the marmoset.

The claims of the authors are generally justified by the data provided; however, some conclusions should be clarified. In particular, the authors have failed to show convincingly that cjPGCLCs are a distinct cell type to the iPSCs that generated them. cjiPSCs cultured in feeder conditions (OF) with IWR1 are reported to cluster closely with the derived cjPGCLCs using principal component analysis of RNA-Seq data. This contrasts with the cjiPSCs cultured in feeder-free (FF) conditions which maintain a more undifferentiated/less primed state, and are not capable of differentiating to the germline lineage. Therefore, the OF/IWR1 cjiPSCs could rather be an intermediate cell-state between iPSCs and cjPGCLCs.

The reasons behind improved germline competence of iPSCs in the different media conditions are unclear. The authors reject the idea that this is due to the presence of IWR1, since this condition has not affected FF iPSCs. However, the efficiency of differentiation was greatly increased in OF conditions when IWR1 was used, indicating inhibition of WNT does indeed have a positive effect on induction to the germline lineage. This area requires further clarification.

Another area requiring clarification is the reporting of RNA sequencing data as representative of a developmental trajectory, without defining which cell lines produced clusters, or defining the stages of this trajectory. The authors refer to the identification of four clusters representative of a developmental trajectory, however, they provide unclear information as to what this refers to. Importantly, detailed transcriptomic comparisons between in vivo-derived PGCs and in vitro PGCLCs are not provided.

Functional validation of iPSC lines generated in the study is not provided besides confirming that the cells express pluripotency markers OCT3/4, SOX2, and NANOG. It is important to confirm tri-lineage differentiation of iPSCs, e.g., through an embryoid body assay. Since FF cjiPSCs were unable to differentiate into cgPGCLCs, it is even more important to confirm cells are genuine iPSCs.

In summary, although there are issues surrounding clarity, this paper is generally justified in its conclusions. The authors present an optimised protocol for the derivation of PGCLCs from marmoset iPSC-like cells, with defined expansion conditions and evidence of further differentiation to prospermatogonia-like cells.

Reviewer #2 (Public Review):

Many cancers, including pancreatic tumors, host microbes that have the ability to metabolize anti-cancer drugs, thus altering cancer response to these treatments. However, many anti-cancer drugs also are quite toxic to bacteria. Thus, the authors first investigate how a model bacterium that could live pancreatic tumors can become resistant to the pancreatic chemotherapy gemcitabine. Second, they investigate how bacteria that are resistant to gemcitabine impact cancer cell response to this therapy compared to bacteria that are not resistant. By answering these two questions, the authors hope to determine how bacterial evolution to chemotherapy can impact how well chemotherapy works in pancreatic cancer.

To answer the first question, the authors perform both genetic screens and laboratory evolution experiments of E. coli bacteria exposed to gemcitabine. Both the genetic screen and laboratory evolution experiments identified mutation of the bacterial protein nupC as mediating bacterial resistance to gemcitabine. NupC is the transporter protein that bacteria use to take up gemcitabine. Thus, the authors conclude that loss of ability to take up gemcitabine would likely underlay bacterial evolution to gemcitabine in pancreatic tumors.

To answer the second question, the authors take either control of nupC mutant bacteria and expose these to gemcitabine. They then take the bacterial media with its residual gemcitabine and treat mouse colorectal cancer cells with these media. They find the amount of gemcitabine is higher in nupC mutant media and media from these mutants cause correspondingly higher killing of cancer cells.

Thus, the authors conclude that bacteria become resistant to gemcitabine by not taking it up, leaving more gemcitabine around in tumors to kill the cancer cells. The findings of the first question are a major strength of the manuscript - the complementary genetic screen and laboratory evolution experiment convincingly show that loss of nupC is likely a major genetic route for bacteria to become resistant to gemcitabine. Excellent biochemical studies delineate mechanistically how the different mutations including nupC contribute to gemcitabine resistance in the bacteria.

However, a major weakness of the manuscript is the extension to how this laboratory evolved nupC resistance to gemcitabine influences tumor response to gemcitabine. The only experiments done to assess this are performed in colorectal cell culture models in vitro. Importantly, these in vitro models do not recapitulate chemotherapy resistance observed in pancreas cancer and utilize levels of bacteria and gemcitabine that are likely not relevant to tumor physiology. Thus, additional experiments assessing in vivo if nupC mutations become prevalent in the pancreatic tumor microbiome and how much mutations affect tumor gemcitabine levels and response will be necessary to fully answer the authors second question of how bacterial evolution to gemcitabine affects tumor response to this agent.

Reviewer #2 (Public Review):

The paper provides a natural extension of 2D multiphase field models for cell monolayers to 3D, addressing cell deformations, cell-cell interaction, cell-substrate interactions and active components for the cells. As known from 2D, the cell arrangement leads to positional (hexatic) defects and if the elongation of the cells is coarse-grained to define a global nematic order also to orientational (nematic) defects. These defects are characterized, see Figure 2. However, this is done in 2D and it remains unclear if the projected basal or apical side is considered in this figure and the following statistics. The authors identify correlations between orientational defects and extrusion events. In terms of positional defects such statistics seem not to be considered and the relation between positional defects and cell extrusion events remains vague. Also in-plane and out-of-plane stresses are computed. These results confirm a mechanical origin for cell extrusions. However, these are the only 3D information provided. The final claim that the results clearly demonstrate the existence of a mechanical route related with hexatic and nematic disclinations is not clear to me. 3D vertex models for such systems e.g. showed the importance of different mechanical behavior of the apical and basal side and identified scutoids as an essential geometric 3D feature in cell monolayers. These results are not discussed at all. A comparison of the 3D multiphase field model with such results would have been nice.

Reviewer #2 (Public Review):

Skeletal muscle is the main regulator of glycemia in mammals and a major puzzle in the field of diabetes is the mechanism by which skeletal muscle (as well as other tissues) become insensitive to insulin or decrease glucose intake. the authors had proposed in a previous publication that high intracellular calcium, by means of calpain activation, could cleave and decrease the availability of GLUT4 glucose transporters. In this manuscript, the authors identify two additional targets of calpain activation. One of them is GSK3β, a specialized kinase that when cleaved, inhibits glycogen synthase and impairs glucose utilization. The second target is junctophilin 1, a protein involved in the structure of the complex responsible for E-C coupling in skeletal muscle. The authors succeeded in showing that a fragment of junctophilin1 (JPh44) moves from the triad to other cytosolic regions including the nuclei and they show changes in gene expression under these conditions, some of them linked to glucose metabolism.

Overall, the manuscript shows a novel and audacious approach with a careful treatment of the data (that was not always easy nor obvious) that allow sensible conclusions and definitively constitutes a step forward in this field.

Reviewer #2 (Public Review):

This paper investigates the maintenance and function of memory follicular helper T (Tfh) cell subsets using in vitro approaches, murine immunization models and vaccine-challenged humans. Murine Tfh cell subsets (Tfh1, Tfh2, Tfh17) were generated using in vitro polarization (iTfh1, iTfh2, iTfh17), and then tested for support of humoral response following adoptive transfer or adoptive transfer with resting in vivo for 35 days. iTfh17 cells were statistically better than iTfh1 and iTfh2 cells in promoting GC B cell and plasma cell maturation after resting in vivo, although all 3 populations were capable of B cell help. Tfh17 cells were comparatively enriched among blood borne Tfh central memory cells in humans, and were enriched at the memory phase of vaccination with hepatitis B and influenza vaccines, compared to effector phase, suggesting the possibility they are comparatively superior in Tfh cell memory formation, with greater persistence in aged individuals.

Significance<br /> The enrichment of Tfh17 cells in Tfh cell central memory compartment and the dominance of Tfh17 cell population and the Tfh17 transcriptional signature in circulating Tfh cells at the memory phase are nicely demonstrated, and may well be helpful for understanding the heterogeneity of memory Tfh cells and potentially providing clues for vaccine design. The in vitro differentiation system for mouse Tfh cells also provides a strategy for others to build upon in dissection of Tfh cell development and function.

Points to consider<br /> 1. Even though Tfh17 cells are more likely to persist at memory timepoints in mice and in humans, or produce more GC B cells or plasma cells following transfer, all subsets can do this. Is GC output otherwise distinguishable following transfer of the individual subsets, or is their effect (cytokine related perhaps) pre-GC with differential CSR? It is also not clear if the individual subsets populate the GC and assuming they do so, if their respective phenotypes persist when they become GC Tfh cells.

2. iTfh17 cells induce more GC B cells and antibodies after resting and antigen challenge (Figures 1, 2). However, it's not clear whether this effect is a consequence of comparatively enhanced iTfh17 survival during resting (as suggested by latter figures), or better expansion or differential skewing to Tfh differentiation during challenge (as suggested by Figure 1 J,K). The total number of remaining adoptively-transferred cells right before challenge and 7 days post challenge will be helpful to understand that.

3. The authors tried to address whether Tfh17 cells have better ability to survive till memory phase or Tfh17 cells with memory potential are generated at higher frequency at the effector phase of vaccination (Figure 5); however, the experiment is not conclusive. The cTfh population 7 days post vaccination is a mixed population with effector Tph cells and Tfh memory precursors. The increased frequency of Th17 cells at day 28 compared to day 7 could be a consequence of superior survival ability, or Tfh memory precursors with Tfh17 signature are better generated.

4. Experiments to confirm expansion ability of the human subsets or their B cell helper ability were not performed.

Reviewer #2 (Public Review):

This study addresses the ways in which bacteriophages antagonize or coopt the DNA restriction or recombination functions of the bacterial RecBCD helicase-nuclease.

The strength of the paper lies in the marriage of biochemistry and structural biology.

A cryo-EM structure of the RecBCD•gp5.9 complex establishes that gp5.9 is a DNA-mimetic dimer composed of an acidic parallel coiled coil that occupies the dsDNA binding site on the RecB and RecC subunits. The structure of gp5.9 is different from that of the RecBCD-inhibiting DNA mimetic protein phage λ Gam.

Cryo-EM structures of Abc2 are solved in complex with RecBCD bound to a forked DNA duplex, revealing that Abc2 interacts with the RecC subunit. A companion structure is solved containing PPI that copurifies with RecBCD•Abc2.

Whereas the gp5.9 structure fully rationalizes the effect of gp5.9 on RecBCD activity, the Abc2 structure - while illuminating the docking site on RecBCD, a clear advance - does not clarify how Abc2 impacts RecBCD function.

The authors speculate that Abc2 binding prevents RecA loading on the unwound DNA 3' strand while favoring the loading of the phage recombinase Erf.

Does the structure provide impetus and clues for further experiments to elaborate on that question and, if so, how?

Reviewer #2 (Public Review):

The molecular changes of the aged tendon are not well understood. Loiselle et al previously established a mouse model that mimics aging tendon, where they depleted Scleraxis lineage (Scxlin) cells from tendon by injecting diptheria toxin (DT) in mice expressing the DT receptor under the control of the Scx promoter (DTR mice). In this manuscript, the authors demonstrate that the tendons from DTR mice resemble tendons from aged WT mice, in that they both have decreased cellularity, altered collagen organization (via SHG imaging), and impaired biomechanical properties. Proteomic analysis of WT, DTR, and aged WT tendons show that both DTR and aged WT tendons have decreased expression of extracellular matrix proteins (ECM). Corresponding with this, single RNA seq analysis of tendons from these three groups of mice showed that while WT tendons are enriched for genes related to collagen and ECM synthesis and also inflammation, DTR tendons express genes associated with ECM organization and structure and aged tendons express genes that regulate inflammation. The authors point out that this supports designing therapies to prevent tendon cell death to prevent the changes seen in aging tendon.

These data enhances the understanding of the protein and gene changes associated with aging in the tendon and in particular characterizes the importance of Scx+ cells to tendon organization and the aging process. The conclusions are supported by the data presented.

The manuscript would be strengthened by:<br /> 1) Improved clarity of figures presented<br /> 2) More details on the methodology used for biomechanical testing<br /> 3) Clarification if the decrease in ECM protein expression is due to decreased cellularity in the tendons of the DTR and aged mice, or decreased expression per cell<br /> 4) Providing more details on genes that are downregulated in comparison between groups

Reviewer #2 (Public Review):

These discoveries are strongly supported by a large amount of clear and convincing data. Thus, the expression of seven distinct pol III-transcribed genes covering all types of promoter is shown to increase in three cell lines when STAT3 is overexpressed and to decrease when endogenous STAT3 is depleted. The proliferation of HepG2 liver cancer cells can be increased by STAT3 overexpression and decreased by STAT3 depletion. Crucially, proliferative induction by STAT3 is dependent on increased pol III activity, as it can be blocked using a pol III-specific inhibitor at a concentration that allows normal levels of pol III activity, but prevents further elevation. Growth of HepG2 xenograft tumours in mice is also slowed significantly when STAT3 is depleted. The effects of STAT3 on pol III output are indirect, mediated by miR-106a-5p. Thus, the knockdown of miR-106a-5p reverses the drop in pol III product expression following STAT3 depletion; conversely, pol III output is stimulated by a miR-106a-5p mimic. Elevated levels of miR-106a-5p correlate with significantly worse prognosis for patients with liver cancer. A key target for miR-106a-5p is a sequence in the 3'-UTR of the mRNA encoding TP73. Complementarity to this sequence allows miR-106a-5p to deplete the expression of TP73 and this is shown to be crucial for STAT3 to regulate the proliferation of HepG2 cells. Furthermore, TP73 is revealed to be a direct repressor of pol III-mediated transcription, an activity not previously known. TP73 is shown to inhibit the assembly of TFIIIB, the factor that is responsible for recruiting pol III to all of its genetic templates. A clear and convincing causal flow can therefore be traced: STAT3 induces miR-106a-5p, which depletes TP73, thereby removing a brake that limits pol III output and cell proliferation.

Reviewer #2 (Public Review):

Summary:<br /> Dominant mutations in the gene encoding LIS1 cause lissencephaly, a severe developmental brain disorder. LIS1 regulates the multisubunit microtubule motor, cytoplasmic dynein 1, which can exist in an autoinhibited (closed) form and an activatable (open) form. Dynein is only active when bound to another complex, dynactin, and one of several known cargo adaptors. Because dynactin and cargo adaptors only interact with the open form, the local ratio of open to closed dynein can potentially dictate the proportion of "activatable" motors. The current view is that LIS1 stimulates dynein by reducing the autoinhibited closed form, and by recruiting two dynein motors to the active complex, which is thought to increase speeds and run lengths. LIS1 is highly conserved across animal and fungal species. The budding yeast LIS1 ortholog, called Pac1, is around 43% identical to human LIS1. Both Pac1 and LIS1 regulate dynein but there have been intriguing differences in their effect on dynein processivity in assays with purified proteins. The authors of the current manuscript recently published high resolution cryo-EM studies of Pac1 bound to yeast dynein (Gilles 2022). Based on their models they tested several mutations predicted to impact Pac1 binding to dynein and showed these mutations disrupted the single dynein dependent process in budding yeast, translocation of the mitotic spindle. However, mutations in yeast dynein that impacted LIS1 binding apparently only modestly impacted human dynein, prompting the current study that compares cryo-EM studies of human LIS1 bound to human dynein with the previously published studies using yeast proteins. The work points to subtle differences in how yeast and human LIS1 interact with the stem and loop regions of yeast and human dynein heavy chains and reveal an intriguing difference in the residues predicted to be important for the interaction between the two LIS1 propeller structures in the LIS1 dimer. They also report map known disease causing mutations in LIS1 and dynein on the structures and find three that might impact residues involved in protein-protein interaction.

Methods:<br /> This group has been able to use innovative methods to increase the resolution of CryoEM images to 3-4 Å, allowing them to make more accurate predictions about residues involved in protein-protein interactions. They have substantial expertise in the analysis of the resultant data, as demonstrated by past peer review studies. These are very labor-intensive experiments that allow a level of detail not possible with standard biochemical or cell biological analyses.

Results:<br /> The studies revealed subtle, but potentially important, differences between the yeast and human proteins.

Based on their analyses, the authors predicted specific residues that are likely to be important for human LIS1-dynein interactions with the stem region of dynein (sitestem) and with dyneins AAA domain containing ring (sitering). They also predicted specific residues that are likely to be important for an interaction between the two LIS1 beta-propellers, which in the yeast protein is apparently critical for dynein regulation.

The prediction that K147 could be important in the interaction between beta-propellers is very intriguing, given evidence that a K147A mutation disrupts LIS1 binding to dynein, but not to NDEL1, another interacting protein.

Impact

The predictions set out in this manuscript, if they hold up, could inform the design of tools to study LIS1 in the context of human disease. It seems likely from the data that at least some of the indicated residues will be important for human LIS1/dynein interactions

Reviewer #2 (Public Review):

The authors have provided a large dataset of ribosomal RNA sequences to assist in the molecular identification of rare and unstudied medically important mosquitoes in four locations with high biodiversity and mosquito-borne virus circulation, Cambodia, French Guiana, Madagascar, and the Central African Republic. This was accomplished using a non-traditional approach, rRNA seq, which could help in the identification of novel potential vectors of disease in hotspots of transmission. Their method uses previously published insect and non-insect-specific rRNA sequences from multiple locations to perform "depletion" of interfering rRNA. This method allowed the authors to create both 28s and 18s sequences for the identification of novel species of mosquito vectors with high reliability based on phylogenetic analysis and utility where traditional cytochrome oxidase subunit I sequences are not available for systematics.

Strengths:<br /> The non-traditional approach used is well described and provides novel guidance for researchers undertaking similar studies.

The depletion method described allowed the authors to identify mosquito rRNA sequences even in the instance of non-target RNA being present.

Weaknesses:<br /> The author's approach, as with traditional approaches to molecular identification of vector species, relies on expert entomologists capable of identifying mosquitoes in the field which is rare in most places. The authors do not provide citations for the taxonomic keys used for morphological identification, which in many places are outdated or unavailable for specific locations.

While next-generation sequencing is becoming more available, it is still largely unobtainable for researchers lacking resources and infrastructure which is common in locations similar to those the authors provide these data for.

The authors give no explanation as to why they chose rRNA-seq as their method of next-generation sequencing, which is most commonly used for transcriptomics, instead of traditional DNA-based metagenomics which is more commonly used to define community relationships as would be more appropriate for this study.

Reviewer #2 (Public Review):

I agree with the authors (line 421) that their "findings provide a remarkable example of how carbohydrate metabolism dictates the relative importance of different sources of actin filaments for CAR dynamics during cellular division." The scope of the work is very broad, and the manuscript reports dozens of interesting phenotypes with high-quality experimental data. However, most points are not investigated in depth.

My main reservation is the presentation of the work. The writing style is conversational and expansive, which makes it challenging for the reader. Furthermore, long paragraphs shift from one topic to the next rather than using separate paragraphs with strong topic sentences to cover each topic. I suggested a few places to start new paragraphs, but many more paragraphs could be divided. I edited one paragraph to illustrate how the text might be cut in half.

Most of the figures are also overly complicated. I did not attempt to edit one of them, but I am sure that findings will be much clearer with about half of the panels moved to supplemental materials, so the reader can concentrate on the most important data.

Line 873: Fig 1C and many other figures. The legend says the error bars are SD's but they include far less than 2/3 of the measurements, so something is wrong. In Fig 4A and other figures, three data points are insufficient to verify a normal distribution, a prerequisite for using the Student's T-test. Furthermore, the T-test requires equal SD's.

Reviewer #2 (Public Review):

Starrett et al performed whole genome and transcriptome sequencing of bladder cancers from 43 organ transplant recipients. They found that most of these tumors contained DNA from one of four viruses (BKPyV, JCPyV, HPV, and TTV). Viral genomes are most often integrated into the genomes of these tumor cells and the authors provide evidence that the integration utilized the POL theta-mediated end joining pathway. In most cases, viral RNA was detected in tumors with viral DNA. This suggests that the viruses are actively altering the cellular environment. Frequently, this resulted in similarities for overall gene expression patterns in the tumors that were grouped by the type of virus present in the tumor. Moreover, the changes in expression linked with viral gene expression were found in genes relevant to tumorigenesis. Immunohistochemical detection of viral proteins in these tumors also demonstrated active viral gene expression. However, the presence of viral proteins was heterogenous within the tumor, with between 1 and 100% of the tumor staining positive for BKPyV large T antigen. An analysis of mutational signatures in these tumors indicate that the viruses are also shaping the tumor genome by inducing mutations. Evidence that specific viruses are contributing to tumorigenesis in organ transplant patients has fundamental implications for preventing tumorigenesis in these patients.

The conclusions of this paper are generally well supported by the data provided. Indeed, there is little doubt that viral infections are more likely in these tumors. However, there are aspects of the paper that could be improved and or clarified. Most importantly, despite the strong evidence that the viruses are altering the tumor cell environment, it is unclear if these changes are necessary for tumorigenesis or less excitingly the result of an even more immune suppressive environment within the tumor. The heterogeneity of the LT expression suggests that the presence of the viral DNA and RNA may not be enough to assess whether it is actively contributing to the tumor. Is an increased frequency of viral protein staining linked with any evidence of an active contribution to tumorigenesis (fewer tumor-suppressor/oncogene mutations). that they reduced mutations in tumor suppressors. This might be easiest to assess with the tumors that have oncogenic HPV DNA. If those tumors lacked p53 and RB mutations, it would support a causative role for the virus.

Reviewer #2 (Public Review):

Synaptic transmission is a fundamental process of communication in the brain. How and where neurotransmitter release occurs is still an open question. This study addresses an interesting question about the spatiotemporal location of neurotransmitter release in a synapse. This has important implications for postsynaptic signaling and neural excitability in general. The work provides valuable additions to recently uncovered discrepancies in the nanometer scale organization of the two primary forms of evoked vesicle fusion (synchronous and asynchronous) in the synapse from two very different methods. Essentially demonstrating convincingly that synchronous and asynchronous release sites are unshared. The study utilizes tools of super-resolution measurements of synaptic transmission that were previously developed in their lab, which help bridge the discrepancies using a convincing number of experimental paradigms. Limits in the speed of optical resolution opened a few questions of interpretation. However, this study greatly expands our knowledge of synaptic architecture and function of different forms of release. A further claim of different coupling of vesicle fusion and retrieval kinetics is made that at present seems incomplete due to temporal limitation of the super-resolution method.

Reviewer #2 (Public Review):

In this work entitled "Live imaging reveals chromatin compaction transitions and dynamic transcriptional bursting during stem cell differentiation in vivo" the authors use a combination of genetic and imaging tools to characterize dynamic changes in chromatin compaction of cells undergoing epidermal stem cell differentiation and to relate chromatin compaction to transcriptional regulation in vivo. They track this phenomenon by imaging the epithelium at the ear of live mice, thus in a physiological context. By following individual nuclei expressing H2B-GFP along time ranges of hours and up to 3 days, they develop a strategy to quantify the profile of chromatin compaction across different epidermal layers based on normalized intensity profiles of H2B-GFP. They observe that cells belonging to the basal stem cell layer display a considerable level of internuclear variability in chromatin compaction that is cell-cycle independent. Instead, intercellular variability in chromatin compaction appears more related to the differentiation status of the cells as it is stable in the hours range but dynamic in the days range. The authors show that differentiated nuclei in the spinous layer exhibit higher chromatin compaction. They also identified a subset of cells in the basal stem layer with an intermediate profile of chromatin compaction and with the dynamic expression of the early differentiation marker keratin 10. Lastly, they show that the expression of keratin-10 precedes the chromatin compaction establishing relevant temporal relationships in the process of epidermal differentiation.

This work includes a number of challenging approaches and techniques since it is carried out in living mice. Also, it provides nice tools and methods to study chromatin structure in vivo during multiple days and within a differentiation physiological system. On the other hand, the results are descriptive and, in some respect, expected in line with previous observations.

Reviewer #2 (Public Review):

This submission seeks to detect changes in the rate of selfing through pairwise comparison of haplotypes sampled from a population. It begins, as did a previous paper by a subset of the authors (Sellinger et al. 2020), with the well-known theoretical finding that partial selfing increases the rate of coalescence and decreases the rate of crossing-over events in genealogical histories.

I am supportive of pitching this contribution as primarily theoretical, with the very short discussion of the Arabidopsis data provided as a worked example. This perspective increases my enthusiasm, compared to an initial reading. My comments are intended to encourage development.

Some thematic characteristics reduce the impact of the submission. Among these are:<br /> (1) a rather less than a scholarly perspective on previous literature;<br /> (2) tendency to avoid theoretical development in favor of computation;<br /> (3) little interpretation of results of their only analysis of real data.

Reviewer #2 (Public Review):

The paper has two key messages: the discovery and the function of LncSox17. Claims of gene discovery are today untrivial, given the large number of genome-wide datasets. Of course, I understand the authors cannot check everything but I feel some more clear and deep analysis of current databases is lacking. Also, the exact coordinates of the lncRNA are not easy to find in the manuscript.

Many statistical analyses are rather lacking. In particular I did not find details of how the DEGs were identified during differentiation (FDR? How many replicates?).

The results of the smFISH are surprising, since the level of expression seems rather low in comparison to the qPCR (only 4 times less expressed than Sox17) or the RNA-seq.

Reviewer #2 (Public Review):

The X-ray crystal structure of the K. lactis Rad6-Bre1 interaction solved by Shi et al. adds an important piece to the puzzle of how H2B mono-ubiquitination is deposited. The primary strength of this work is the new structural information on the Rad6-Bre1 interaction, which reveals contacts of the E3 (Bre1) to the backside of the E2 (Rad6). Through mutagenesis and biochemical experiments, Shi et al. probe the importance of these contacts for the Rad6-Bre1 interaction, active site accessibility, and Rad6 catalytic activity. In general, the functional data support the structural model and confirm the importance of Bre1 in stimulating Rad6 catalytic activity in vitro and H2Bub1 in yeast. In comparison to the structural data, some of the functional data are not as robust and are at times over-interpreted. However, in general, the conclusions drawn by the authors about the importance of the newly revealed Rad6-Bre1 interface are appropriate and substantiated by the data.

Reviewer #2 (Public Review):

The manuscript by Sun et al., investigates the synaptic plasticity underlying visuo-auditory association. Through a series of in vivo and ex vivo electrophysiology recordings, the authors show that high-frequency stimulation (HFLS) of the cholecystokinin (CCK) positive neurons in the entorhino-auditory projection paired with an auditory stimulus can evoke long-term potentiation (LTP) of the visuo-auditory projection. However, LTP of the visuo-auditory projection could not be elicited by HFLS of the visuo-auditory projection itself or by an unpaired stimulus. They further demonstrate that auditory stimulus pairing with CCK is required to elicit LTP of the visuo-auditory projection as well as visuo-auditory association in a fear conditioning behavioral experiment. As they found elevated expression of CCK in entorhinal neurons which project to the auditory cortex, they conclude that HFLS of the entorhino-auditory projection causes CCK release.

Strengths:

The authors use an elegant approach with Chrimson and Chronos to stimulate different auditory inputs in the same mouse in vivo and also in slice and demonstrate that potentiation of the visuo-auditory projection is dependent on HFLS of the entorhino-auditory projection paired with auditory stimulus. Furthermore, they test several parameters in a systematic fashion, generating a comprehensive analysis of the plasticity changes that regulate visuo-auditory association.

Weaknesses:

In their previous publications (Chen et al., 2019; Li et al., 2014; Zhang et al., 2020), it has been established that HFLS of the entorhino-auditory projection and CKK release are important for visuo-auditory association via electrophysiology and behavioral experiments. The Chrimson and Chronos approach was applied by Zhang et al., 2020, where they already found that the visuo-auditory projection was potentiated through HFLS of entorhino-neocortical fibers. This manuscript extends those findings by testing different parameters of pairing, which may not represent a major conceptual advance. Unlike the electrophysiological recordings, drug infusion is used in behavioral manipulations to show that HFLS of the entorhino-auditory projection is important for visuo-auditory association. While the use of drugs to inhibit CKK receptors is important, it does not directly demonstrate that CCK release from the entorhino-auditory is necessary.

Reviewer #2 (Public Review):

Zhao et al., set out to investigate the molecular mechanisms controlling the timing between training tasks that leads to proactive interference (Pro-I) buildup (i.e. formation) and consequently interference in the retrieval of the newly learned memory.

During the time-dependent stabilization of newly acquired memory (i.e. memory consolidation), the memory traces are vulnerable to disruption by a variety of amnestic influences. When multiple learning events occur in rapid succession, competition occurs between consolidating memories. However, the factors that regulate what memory is remembered or forgotten are unknown. Two interference models of forgetting are proposed in the literature: events occurring prior to learning cause forgetting through proactive interference (Pro-I), or events occurring after learning cause forgetting through retroactive interference (Retro-I).

The most common explanation for Pro-I and its buildup is that this phenomenon emerges due to the competition between two differing task memories (e.g. aversive memories) for storage in overlapping brain areas. The behavioural consequence of this Pro-I buildup is that the recall of newly learned information is impaired when is preceded by a similar learning task. On the other hand, several accounts are used to describe the release from Pro-I (i.e. the reduction of proactive interference): a) having a more distinctive target task compared to the interference task (either different material or relying on different neural circuits), b) prolonging the lag between training tasks and c) contextual changes between the two learnings. Drosophila is an ideal model for the study of these questions, given the detailed knowledge base of how different types of memories are encoded, consolidated, and retrieved and the effects of context changes in these memories.

In this study, the authors use the classic aversive conditioning paradigm, where flies learn to associate an odor A with shock (in the target task), this task is preceded by a proactive task or is followed by a retroactive task, where odor X is paired with a shock. Taking advantage of the known molecular pathways for the more well-characterized model of interference (Retro-I), the authors extended the knowledge for these types of interference models. To uncover the mechanisms underlying the timing of Pro-I, the authors genetically manipulated the activity of a key phosphatase (Corkscrew) and its downstream pathway (Raf/MAPk). This phosphatase was chosen given its known role in controlling the appropriate training intervals for the induction of long-term memory in flies.

A strength of the manuscript is that the authors showed the unique and exclusive role of Corkscrew in regulating Pro-I and its temporal dynamics. Furthermore, the authors described that Corkscrew regulates Pro-I via a single subset (γ) of the intrinsic cells (i.e. Kenyon cells) of the mushroom body, which is the centre of learning and memory in Drosophila. However, the manuscript would have been improved had they characterized the Pro-I task more thoroughly. This is because behaviourally what the authors are observing might look like Pro-I buildup, but other scenarios can also explain the data (e.g. passive decay of the first memory, memory storage limitations, attentional deficits). This would be solved by applying known Pro-I release protocols and, in this way, would be more comparable to the known Pro-I literature.

Interestingly in the mammalian field, phosphatase activity is also known as a key regulator of long-term depression and memory formation. Taken together, this data implies the conserved role of phosphatase activity and its subsequent plasticity during the process of learning a new task. Furthermore, this work shows the importance of phosphatase activity in facilitating memory consolidation of newly learned information, which might occur by suppressing any potential interference from old memories in the same neuronal circuits.

Reviewer #2 (Public Review):

The authors used both pharmacological inhibition and genetic TPL2 kinase dead (KD) mice to test the hypothesis, that inhibition of TPL2 attenuates the microglia inflammatory response to stimuli such as LPS and in the context of chronic (tau mouse model) and acute (optic nerve crush/stroke) neurodegenerative models. The use of TPL2 kinase dead mice rather than KO mice is elegant and important because of the non-enzymatic role of TPL2 in stabilization of its interacting partner ABIN-2. The authors convincingly demonstrated that pharmacological and genetic inhibition of TLP2 in primary microglia reduced the production of pro-inflammatory cytokines, chemokines, and iNOS and consequently reduced neuronal cell death in neuronal-microglial cocultures. Genetic inhibition of TLP2 reduced partially the inflammatory response of microglia in the PS31 tau model. Furthermore, the authors observed reduced infiltration of T cells and dendritic cells. Notably, TLP2 inhibition rescued behavioral deficits in PS31 mice. Overall, these studies support the possibility that inhibition of TPL2 kinase may have translational potential in prevention or treatment of tau-driven neurodegeneration. One aspect of the study that merits further investigation is the alteration in the population structure of myeloid cells in the brain under the various conditions that were evaluated using single cell RNA seq. Very high representation of microglia was observed in TauP301S mice at nine months of age. These findings could reflect bias in recovery of cells for the single cell RNA sequencing assay and independent validation of microglia cellularity by immunohistochemistry would address this question.

Reviewer #2 (Public Review):

Mecp2 is the causative gene for RTT and MDS, but the Mecp2 driven pathogenesis is not clearly defined. While Mecp2 is a regulator of gene expression, identifying downstream genes that are robustly regulated by Mecp2 have been a challenge. The authors utilized computational approach to identify Mecp2 regulated genes using previously published differentially expressed genes in hippocampi of MDS mice treated with Mecp2-specific ASO (Shao et. al., 2021). Through this analysis, the authors shortlisted Gdf11, which also validated in an additional 20 transcriptional profiles for Mecp2 perturbed rat, mouse, and human brain samples.

The transcriptional regulation of Gdf11 by Mecp2 was confirmed using genetic murine models, including Mecp2 -knockout, Gdf11 mutant and Mecp2-tg1.<br /> Finally, the CUT and RUN analysis showed increased Mecp2 binding upstream of the Gdf11 TSS in Mecp2-tg1 hippocampi, which was lost in Mecp2 knockout hippocampus. Mecp2 loss increases H3K27me3, which suggested Mecp2 prevents transcriptional silencing of Gdf11. While these results provide mechanistic insight into the transcriptional control of Gdf11 by Mecp2, it remains unclear how Mecp2, which is generally a transcriptional suppressor increases Gdf11.

The author elegantly demonstrates that normalization of Gdf11 levels in Mecp2-tg1 mice crossed with Gdf11 improves several behavioral deficits in the MDS mice model. In contrast, loss of one copy of gdf11 in mice caused neurobehavioral deficits using a battery of behavioral tests, such as elevated plus maze, rotarod, anxiety tests and shock-tone conditioning.

Finally, the authors show that loss of one copy of gdf11 does not alter proliferation in the adult mouse SGZ or no gross changes in brain anatomy or volume of the dentate gyrus.

Overall, the authors demonstrate that gdf11 is robustly regulated by mecp2, which coup provide new therapeutic options for Mecp2-related diseases, such as RTT and MDS. As discussed in the paper, additional studies are needed to test whether Gdf11 can rescue behavioral deficit in symptomatic RTT murine models.

Reviewer #2 (Public Review):

This manuscript explores the importance of the plastid-hosted SUF iron-sulfur cluster synthesis pathway for plastid maintenance and for the viability of blood stages of the human parasite Plasmodium falciparum. The authors convincingly demonstrate that while most of the proteins of the SUF pathway are essential to P. falciparum survival only one, the cysteine desulfurase SufS, also leads to the loss of the plastid. The authors then explore the possibility that SufS may be providing sulfur to a plastid-localised putative tRNA modifying enzyme, MnmA. They demonstrate that, like when SufS is depleted, specific depletion of MnmA impairs parasite viability and causes plastid loss. They also elegantly complement this phenotype with bacterial MnmA expressed together with a bacterial cysteine desulfurase or even alone, suggesting that SufS from the parasite is able to directly transfer sulfur to the bacterial MnmA.

Overall, this is a well-conducted and well-controlled study, for which I do not have any major criticism, although tRNA purification, identification, and quantification in the SufS and MnmA mutants would bring more compelling evidence that tRNA thiolation is affected in these mutants.

Reviewer #2 (Public Review):

In this manuscript, Li et al. sought to identify tumor suppressor proteins in mesenchymal stem cell conditioned media in which PKA signaling was up-regulated by treatment with a small molecule, and in osteosarcoma-enriched transcripts, to provide alternative treatment strategies to combat osteosarcoma. They identified several proteins that when forcibly expressed both in vitro and in vivo, can suppress osteosarcoma viability, growth, and motility. This manuscript presents a substantial amount of data, is well organized, and provides a novel approach to addressing osteosarcomas. The data is thorough and convincing and provides an alternative approach to developing cancer therapeutics.

Reviewer #2 (Public Review):

The study by Smela et al describes the direct differentiation of human "Granulosa-like cells" via the overexpression of a limited number of transcription factors in pluripotent cells. This approach builds on other contemporary work to produce functional support cells of the mammalian gonad.

The work does succeed to establish cultured cells that retain some characteristics of these ovarian support cells, including the expression of granulosa cell markers, steroid biosynthesis in response to stimulation, and some evidence of acute germline support. The study also marks an important technological development towards the production of in vitro conditions for the production of human gametes from iPS cells. Prior efforts using human germline cells have mostly focussed on xeno-organoid approaches, and so the human-human nature of the present study represents a useful advance. Of particular note, the present study identifies a remarkably fast acquisition of DDX4 and DAZL-positive cells when both germline and support cells are both derived from a human source. This is an intriguing finding, as other groups have reported a substantial delay in acquiring this germline state when cells from mixed species are used. While these findings are of key technological importance towards ongoing efforts to create in vitro gametes, there appear to be some issues of reproducibility, and a lack of deep functional characterisation.

Several conclusions of the paper need to be described in much greater detail. For example, the regulatory effects of the over-expression of transcription factors are stated in Figures 1 and 2, but how this regulatory logic was assembled is not presented, and the methods by which this logic was experimentally probed are not presented. Second, the abstract highlights two transcription factors that are both necessary and sufficient for granulosa-like cell production. While sufficiency is tested through the overexpression of the transcription factors, necessity is not conventionally assessed through a genetic approach. The upregulation of factors in response to transcription factor overexpression does not seem appropriately described. Third, the transcriptional comparison of granulosa-like cells with cancer cell lines that do not reflect normal granulosa cells should be reconsidered.

The study contributes an important step towards the production of functional human granulosa cells from pluripotent cells, though the central conclusions would benefit from a more robust interrogation of the cell status achieved.

Reviewer #2 (Public Review):

This manuscript details the role of the rILN to the DS pathway in the onset of operant behavior that promotes the delivery of a reward and in the ultimate acquisition of that reward. The strengths of the paper are in the detailed fiber photometry study that encompasses several behavioral domains that correlate to the signal observed in the rILN to DS pathway. I am especially interested in how the "encoding" shifts across time as the animals refine their behavior both in a temporal sense and in the magnitude of the signal. Further, the authors demonstrate then that this is dependent on action, as they do not observe signals in a Pavlovian behavioral task, but do observe reward-based signals in a "free consumption" task (the strawberry milk). The examination into devaluation also enhances the understanding of this pathway, even though there were no differences between a valued and devalued task. Finally, the authors examine bi-directional optogenetic manipulation of the pathway, and its impact on how the trials are completed, omitted, or incomplete. They find that manipulation alters the % completed trials and regulates trial omission. This paper really does not have any glaring weaknesses to point out, however, the physiological assessment does seem to have a few strong trends and even though the studies are well powered, and included both sexes, sex as a biological variable was not commented on that I could find. My estimation of the data doesn't suggest strong sex differences in any metric measured. Additionally, the data that included projections to the rILN were very interesting, and future studies looking into the physiology of these neurons, and/or how the physiology of these neurons adapt after operant training may be very interesting to understand plasticity within the adaptation across the training from FR1 to FR5 with time limits.

Reviewer #2 (Public Review):

The present study from Xiaorui Shi's lab investigated the effect of pericyte depletion on spiral ganglion neurons and auditory function. Results in in vitro culture system proposed that pericyte-derived exosomes contain VEGF, and promote not just vascular stability but neuronal survival through Flk1. This study is an extension of their previous study showing pericyte depletion causes auditory dysfunction, which is ameliorated by VEGF gene therapy (Zhang et al., JCI insight 2021). Overall, the data are clear and sophisticated and promote our understanding of the biological roles of pericytes in neuronal function. Several points should be thoroughly discussed or supported by definitive experiments like analysis of neuron-specific Flk1 KO mice.

Reviewer #2 (Public Review):

In this work, Illingworth et al. investigate the effectiveness of ribavirin and favipiravir on the treatment of a paediatric patient with chronic RSV. These drugs cause mutations and the authors tested whether they could observe this effect through deep sequencing viruses from nasal aspirates over the course of treatment. They found an increase in mutations caused by ribavirin but favipiravir appeared to have no additional mutagenic effect. Despite the lack of change in viral load, the authors suggest that the ribavirin reduced viral fitness and did not lead to adaptive escape mutations. The authors modelled how generation time and fitness interacted with mutational load. They also estimated fitness for different haplotypes generated from the mutational data.

Strengths of the paper:

Using mutagenic drugs to treat viruses is generally accepted but results have been mixed with severe viral infections and specific evidence of the precise effects of the drugs is often lacking. This paper is especially valuable for demonstrating that despite in vitro evidence that favipiravir had some effect against RSV, there was no evidence for favipiravir having an effect in a patient. This differs from the authors previous work showing a clear clinical benefit to favipiravir in treating influenza. This paper also appears to be the first to sequence RSV from a patient having been exposed to ribavirin which is important for demonstrating that the drug is having a measurable effect.

Weaknesses in the paper:

I think there is a conceptual problem with the paper. Ribavirin is supposed to increase the mutational rate of the virus which would increase the mutational load. Mutational load has been calculated by summing up the frequencies of minor alleles. However, if a particular mutation rises in frequency, it does not mean that ribavirin has caused additional mutations at the same site but rather viruses containing the mutation have risen in frequency. If a subpopulation containing mutations rises through drift or selection to a relatively high percentage that will bias the mutational load. The authors provide ~75 mutations which were at significant percentages across multiple different timepoints. It seems that these mutations contribute significantly to the mutational load but changes in mutation percentages between samples do not reflect changes in mutational events but changes in viral haplotypes/subpopulations. In a previous study Lumby et al. 2020, the authors removed mutations at >5% from their analysis but there is no indication that they performed this step similarly here. Summing many small changes will give an indication of background mutational rate (though counting only a single mutation at each locus is perhaps the only method to remove the effect of viral clonal expansion).

While ribavirin appears to have shown an effect, many questions remain. Why does the mutational load only increase for 3 points before plateauing? The authors would likely argue that this is the new saturation point for mutation load but they don't test it. Sequencing points from after the cessation of treatment would be expected to show lower mutational load but this data was not collected. Furthermore, questions remain over the methodology. It is thought that Ribavirin should only increase transitions and a transition/transversion ratio for the different samples would have been helpful. The absolute numbers of many mutation classes appear to have increased including transversions e.g AU. There isn't a good reason why nucleoside analogues should have caused this effect and perhaps it is an artefact.

I don't think that the authors can reasonably determine how many haplotypes there are in the population from short read sequencing data. I think that the sequencing data very clearly shows subpopulations due to the large changes in mutation frequencies between different time points. The authors say that their analysis assumes a well-mixed population which is clearly not the case. Therefore, determining fitness of different haplotypes or mutations is likely not accurate.

The authors construct a model to estimate viral fitness and suggest that viral fitness decreased with the drug. This is somewhat problematic to me as viral load has not changed so it would be reasonable to say that viral fitness was likely unaffected by the drug. The authors define fitness in terms of the number of mutations that each virus likely has and assumes that these mutations are deleterious. The authors then use this to claim that mutagenic drugs reduce fitness. This seems very circular to me. If the drugs reduce fitness, it should be observed as a property of the virus population. As the only measure was viral load, which didn't change, it is difficult to claim ribavirin reduced viral fitness. There are other reasons why there could be an increase in the number of mutations e.g. sequencing more subpopulations which would have nothing to do with fitness.

At various points, the paper assumes that there is no selection taking place but immunoglobulin was being applied weekly and palivizumab monthly. The timing of when these drugs were given should be included. How did the palivizumab affect selection? The K272E mutation seems to go up and down but it is not clear if this was in response to drug infusion timing or if this mutation was present in a subpopulation.<br /> I think the main impact of the paper will be that favipiravir will not be used in the future to treat RSV. Given that the EC50 of favipiravir against RSC is ~100x that of influenza, favipiravir was unlikely to reach a therapeutic level in the patient. Nucleoside analogues have a mixed record at treating serious viral infections. Hopefully, this work will spur on future studies to precisely measure the effect that ribavirin has on RSV.

Reviewer #2 (Public Review):

The authors aimed to determine the mode of inhibition of the serotonin transporter SERT as a by-product of MDMA synthesis (ECSI#6). They present a thorough kinetic analysis, using different experimental techniques (binding and transport inhibition) and kinetic modelling. They also test the predicted pharmocophore effect of the compound. In my view, the authors provide compelling evidence for an uncompetitive inhibition mechanism, in which the compound most likely binds to the inward-facing and K+-bound state. Inhibitors of this type may have the potential for therapeutic use.

Reviewer #2 (Public Review):

This manuscript applied the SAXS data analysis of protein self-assembly by implementing the simultaneous fitting of intra- and inter-molecular motions/conformations against SAXS data at a series of oligomerization states/concentrations. Despite several major assumptions hinted, a diverse pool of conformational and oligomeric candidates was generated from CG simulations, and more importantly, these candidates were fitted into these SAXS data to reach a reasonable agreement, suggesting a somewhat convergence (even if the ensemble-fitting could well be at a local minimal). This is considered a technical advance, given the fairly large numbers of both the oligomer fraction phi_i (i=1, ..., N) and the conformational weight w_k (k=1, ..., n), where N is the number of oligomers and n is the number of internal conformational states.

Central is optimizing phi_i and w_k, simultaneously. The former has been illustrated in Fig. 4 and SI-Fig. 7 for the total number of 60-mers. The latter relies on an overfitting-preventing strategy, as shown in SI_Fig. 1, where an effective fraction cutoff was used from 0.1 to 1.0, as opposed to the number of conformational states. What are the numbers of conformational states for these oligomers? This should be quantifiable, e.g., defining the conformational differences by chi_2.

Reviewer #2 (Public Review):

Using live cell imaging, this article describes the oscillation of a tip localized protein, SofT, to hyphal tips during growth of a nematode-trapping fungus, independently of the oscillation of this protein during chemotropic interactions prior to cell fusion. The authors observe oscillation of SofT, which becomes entrained as opposing oscillations at hyphal tips during chemotropic interactions, a process that requires calcium signaling. The authors build on a previously developed mathematical model describing oscillation of proteins to fusion tips during chemotropic interactions with a transition period from single hyphal tip oscillation to coordinated oscillation during chemotropic interactions.

Reviewer #2 (Public Review):

When I was asked to review this paper, I was quite excited, as the analysis seemed very timely. Many of us in biomedical science feel like we are at an inflection point in our field. The combined impact of the pandemic on both people's outlook and on the supply chain, the sharply rising costs of living in major metropolitan areas, and the increasing gap in potential salaries between industry and stipends for graduate students and postdocs are shaking our field. The need to increase salaries for PhD students and postdocs is colliding with a 20+ year stagnation in the size of a non-modular R01, creating major challenges for many basic science labs.

However, having read the piece, I am quite disappointed at what seems to be a missed opportunity. The scientific community at large, and particularly the basic science community is hungry for data like this, to use to try and convince Congress and NIH as a whole to address the issues above. However, as far as I can tell, the authors are not writing for this audience-in fact I was puzzled about their view of for what audience this was intended. I will note several major issues-all could be addressed but would require an effort to tell this story in a much more comprehensible and complete way

1. The manuscript assumes an understanding of both economic terminology and statistical approaches that will not be familiar to most of the audience, if I am a representative example. This begins in the abstract, much of which I found incomprehensible. I still am not sure about the definition of "nominal costs ", and I certainly have no idea what they mean by a "wholly non-parametric machine learning regression". This continues throughout-presenting much of the data as Log10-transformed costs means that many of the graphs become impossible for a normal mortal like me to interpret.

2. The version presented is written like some early outline draft. Rather than using narrative to guide the reader through the data, it reads like a series of Figure legends. For example, I literally thought the text on page 4 were the Figure legends, but they are not. "Figure 2 shows...." "Table 1 shows...". The Discussion is similarly difficult to follow. Given the complexity and importance of the data they present, this is a major missed opportunity

3. What will most interest my own part of the NIH-community is the assertion that "real dollar adjusted" grant funding has not decreased, but has instead remained flat. Few people I know will believe this. The authors address in a less-than-clear fashion some of the reasons for this-solicited versus non-solicited awards, clinical trials, etc, but do not dig into their own data to identify what are likely to be other issues. I doubt any one of the 20+ NIH-funded researchers in my Department (predominantly NIGMS funded) has a grant that reaches the "median level"-I do not after 32 years of continuous NIH-funding. Most new NIGMS-funded researchers, including many in my Department, are coming in funded by MIRA grants, which at $250K are half the median grant size. They do spend a few moments on disparities in Figure 7, but much more could be pulled out of this data set. Digging into issues like this-distributions in different NIH Institutes, at different career levels, etc, would make this work much more impactful.

As one example, this analysis from NIGMS suggests the median grant was likely under $225K, a year when their data suggest the median grant overall was $400k<br /> https://loop.nigms.nih.gov/2016/05/distribution-of-nigms-r01-award-sizes/

My bottom line-this study addresses a key question, but as currently written does so in a way that will minimize its impact

Reviewer #2 (Public Review):

The manuscript aims to define in detail the role of the LIM homeodomain transcription factor isl2 in the acquisition of cardinal spinal motor neuron identities. The authors, by using a number of different and complementary techniques, analyze Isl2 expression in motor neuron subtypes and describe the consequences of its loss on motor neuron generation, positional organization, sensorimotor connectivity, and function. While the importance of Isl2 for the development of axial and visceral motor neurons was already known, the data presented here convincingly show that Isl2 has a previously unappreciated role in controlling differentiation of a subset of motor neurons innervating proximal hindlimb muscles by regulating the expression of the ETS transcription factor Pae3.

Reviewer #2 (Public Review):

Understanding the molecular mechanism of obesity-associated OA is highly in clinical demand. Overall, the current study is well-designed and illustrated that down-regulated GAS6 impairs synovial macrophage efferocytosis and promotes obesity-associated osteoarthritis. Based on the patient's sample, the data indicated synovial tissues are highly hyperplastic in obese OA patients and infiltrated with more polarized M1 macrophages than in non-obese OA patients. Further authors proved that obesity promotes synovial M1 macrophage accumulation and GAS6 was inhibited in synovitis during OA development in mice models. The sample size, data collection, and quality of the IHC and immunofluorescent histological sections are outstanding. The results were well presented with appropriate interpretation. But the following major questions should be addressed.

Major:<br /> 1. Animal model: Ten-week-old animals received DMM surgery and were fed a standard/HFD diet for 4 or 8 weeks prior to specimen harvest. Since Wang J and other studies have shown that male ApoE(-/-) and C57BL/6J wild-type (WT) mice fed with a high-fat diet for 12 or 24 weeks, and the ApoE(-/-) mice gained less body weight and had less fat mass and lower triglyceride levels with better insulin sensitivity and lower levels of inflammatory markers in skeletal muscle than WT (Wang J, et al. Atherosclerosis. 2012 Aug;223(2):342-9. PMID: 22770993; Hofmann SM, et al. Diabetes. 2008 Jan;57(1):5-12. PMID: 17914034; Kypreos KE, et al. J Biomed Res. 2017 Nov 1;32(3):183-90. PMID: 29770778). Thus, it is very important to provide the data on the final body weight gained in your groups and provide a relative background of the animal model chosen in the introduction or discussion. Please explain why ApoE-/- mouse model, and how this animal model is clinically relevant. Does a high-fat diet induced obsess OA available in C57BL/6 WT?<br /> 2. Control group: The DMM surgery was performed on the right leg, and the contralateral knee joint should be used as a baseline to show the level of M1 macrophage infiltration under the obsess microenvironment.

Reviewer #2 (Public Review):

The manuscript from Harrington and colleagues describes the development and characterization of two new mouse resources that report MHC class I and class II expression. In these mice the tomato reporter gene was embedded into the gene encoding beta 2-microglobulin, to report class I expression, and separately in the CD74 gene, to report class II expression. The group highlights the need for such reporters by describing the growing interest in MHC expression by oligodendrocyte lineage cells in inflammatory CNS disorders, and they nicely demonstrate the utility of these reporters using mouse models of multiple sclerosis. There is also an emerging appreciation that immune cell infiltration into the CNS occurs in myriad neurological disorders, such that these models will likely have wide utility. The paper is clearly written and will be of wide interest.

Reviewer #2 (Public Review):

Here the authors tackle the problem of identifying which parts of a TMS-evoked response are local to the stimulation site versus driven by reverberant activity from other regions. To do this they use a dataset of EEG recorded simultaneously with TMS pulses, and examine virtual lesions of a network of neural masses fitted to the data. The fitting uses a very recent model inversion method developed by the authors, able to fit time series directly rather than just summary statistics thereof. And it apparently works rather well indeed, at least after the first ~50 ms post-stimulus. I expect many readers will be keen to try this fitting method in their own work.

Reviewer #2 (Public Review):

The authors use a genetically encoded calcium indicator to measure Ca in flagella to establish that Ca influx correlates with flagellar length. (Despite this correlation, there is so much noise that it is dubious that Ca level can regulate the flagella's length.) Then, they show that reduced Ca decreases the rate of IFT trains entering flagella, which ruins the ion-current model of regulating flagella's length. (Ca can still be one of the factors that sets the target length.) Ca does not seem to change the disassembly rate either. There are also no correlations between Ca influx spikes and IFT injection events. Curiously, these spikes broke pauses of retrograde IFT trains, but that still did not affect IFTs entering dynamics.

Some other possibilities like Ca regulating unloading rates are discussed and convincingly rejected.

The study ends with an interesting Discussion, which talks about other possible models, and concludes that the only model not easily rejected so far is the mechanism relying on diffusion time for kinesins from flagella to the cell body being greater in longer flagella.

The paper is well written, very thorough, contains significant results.

Reviewer #2 (Public Review)

This paper seeks to contribute new empirical insight into the (potential) energetic benefits of schooling. Toward this aim, the authors establish an experimental setup in which brook trout swim in a thrust wake generated by an oscillating airfoil. By combining measurements of body motion and particle image velocimetry, the authors successfully detail how brook trout respond to an incoming thrust wake.

Strengths:<br /> • The idea of using an airfoil that oscillates in the sway and yaw direction is original and a valuable contribution to the simulation of thrust wakes using simplified mechanical systems.<br /> • The experiments are executed with a high level of accuracy and detail, offering important insight into animal locomotion in a thrust wake. In particular, acquiring experimental data on the flow physics (velocity and pressure) for this kind of problem is a major endeavor, which the authors have successfully and originally addressed.<br /> • Performing experiments on the same animals twice is an excellent idea to explore the role of body size, without inflating the number of animals needed for experiments.

Weaknesses:<br /> • The novelty of the robotics-based experimental approach is overstated; several studies have studied the response of live fish to thrust wakes, generated by pitching airfoils or robotic fish.<br /> • The length of the test section for the experiments is very much comparable with the body length of the animals, thereby raising doubts regarding the confounding role of wall interactions. Likewise, the role of 3D effects is elusive; experimental data are in 2D and no discussion is included about the extent to which such an approximation is valid and how it impacts quantitative measurements of vorticity and pressure included in the paper.<br /> • Other sensory modalities (such as touch and the vestibular system) and their integration are not examined in the paper, limiting the understanding of the reader of the way in which fish appraise their surrounding to obtain hydrodynamic advantage from thrust wakes.

Findings of the research can offer valuable insight into the hydrodynamic mechanisms at the basis of schooling, stimulating further interdisciplinary research at the interface of biology and engineering (fluid mechanics and robotics).

Reviewer #2 (Public Review):

- Aim of the study:

Agip et al. studied the structure of respiratory complex I from Drosophila melanogaster, an important model organism with well-developed genetic toolkit and sufficiently close phylogenetic relationship to mammals. They isolated the complex and analyzed its structure by single-particle electron cryo-microscopy (cryo-EM). They also used mass spectrometry to characterize new subunits. So far, the structures of complex I have been reported for several organisms, including mammals, plants, ciliates, fungi and bacteria, but ones from insects have been missing. This study aims to fill this gap and shed light on some of the key questions pertaining complex I biology, such as 1) the conservacy of supernumerary subunits, 2) the mechanisms and physiological relevance of active/deactive transition and 3) the correspondence between the structurally defined closed/open conformations and the biochemically defined active/deactive states.

- Strengths:

The study provides the first structure of complex I from insects, the organisms at an important phylogenetic branch that has diverged from mammals more recently than other eukaryotic species such as plants and fungi. Using purification methods they developed for mammalian enzymes previously, the authors successfully purified the insect enzyme with high quality - a monodisperse peak in gel filtration, the NADH oxidation activity comparable to mammalian enzymes, and the homogenous subunit composition as confirmed by single-particle analyses. It is noteworthy that the authors used state-of-the art tools in model building and validation, such as ISOLDE and MapQ, which makes this model of high standard. In my opinion such careful validation is particularly important for modelling such a gigantic complex, since without cares one can easily misinterpret the density and draw wrong conclusions.

The resolution is 3.3 Angstrom for the best class (Dm1), which allowed modelling side chains and comparing between the observed 3D classes and to the known structures. The model confirms the presence of 43 subunits, akin to mammalinan enzymes, composed of 14 conserved core subunits, 28 supernumerary subunits that have close homologs in mammals, and one supernumerary subunit CG9034 that has not been predicted. They are also structurally similar to mammalian enzymes except for minor local differences. The two supernumerary subunits (NDUFC1 and NDUFA2) that are present in mammals are missing. The authors discuss evidence that NDUFC1 is absent from the Drosophila genome and NDUFA2 is genomically present but its expression is restricted to the male germline. Together, the overall similarity to the mammalian enzyme underlines the use of Drosophila complex I as a model system.

One of the remarkable findings is that common biochemical treatments that are used to deactivate mammalian complex I - heat treatment or NEM treatment - did not reveal deactive state of Drosophila complex I. This is in agreement with their observation that most structural elements are in the active state. The major Dm1 conformation shows all structural features in the active conformation, whereas Dm2 state shows two features in the deactive conformations. Here the author raises an interesting point that the structural elements formerly believed to behave in a consorted manner are actually not coupled, providing new perspective in interpreting complex I structures presented so far and in future. Notably, the authors adopted the same purification procedure for bovine and murine samples. This is a particular strength that they applied a similar procedure for but still observed different behaviors for Drosophila (the absence of the deactive state).

- Weaknesses:

As the authors point out in Discussion, the biochemical statuses of the two described conformations, Dm1 and Dm2, are uncertain. If we assume that Dm1 is a ready-to-go active state, Dm2 could represent several of the possible states; a partially broken state due to delipidation by detergent, a meta-stable state during enzyme turnover, an intermediate towards "full deactiving" structural transition (which the authors argue is unlikely to occur), or a fully reversible state that is in equilibrium to Dm1. Despite these uncertainties, the structure will serve as an excellent starting point to address many open questions in the complex I field in future.

In the final 3D classification the number of classes was set to 3 (K = 3). This is an arbitrary human decision and implicitly forces particles to separate into 3 descrete classes. It would have been great to mention if the authors had tried different classification parameters and, if so, whether that had led to similar classification results. There are different methods available to dissect conformational heterogeneity other than simple 3D classification. For example, focused classification can differentiate local structural features. MultiBody refinement and 3D variabitlity can analyze continuous conformational changes. The simple 3D classification with local angular sampling employed here may lead to over-simplification of the more complex structural heterogeneity.

Although 37 degrees heat treatment and NEM treatment did not reveal any sign of deactivation in Drosophila complex I, it does not rule out the possibility that insect complex I has different ways to deactivate the enzyme, to prevent ROS production. It is probably the limitation of applying existing assays that are originally for mammalian and fungal enzymes to the study of insect enzymes.

- Whether they achieved the aims and whether the conclusions are supported by the results:

Overall, they successfully isolated the active enzyme and determined its structure at 3.3 A resolution, which meets the current state-of-the-art for single-particle cryo-EM and provided an atomic picture of the enzyme composition. The study confirms that the Drosophila complex I is structurally similar to mammalian complex I, but biochemically different in that it does not show the deactive state. It still does not exclude the possibility that Drosophila complex I can transition into a currently unknown state that prevents reverse electron transfer. This question however can be tackled in future by mutagenesis analyses as Drosophila is a genetically tractable organism.

- Impact to the field and utility of the data to the community:

Complex I is important not only for human health but also for understanding universal principles of biological respiration, because of its universal presence in most organisms on Earth. This study provides a basis for relating mammalian complex I with those from other branches of organisms. The current structures will allow Drosophila researchers to interpret and design any mutations that affect complex I functions, and relate them to behavioral, developmental and metabolical changes at tissues, organs and individuals levels.

Reviewer #2 (Public Review):

This work characterizes the diversity of Fruitless-expressing neurons in developing, mid-pupal Drosophila brains using single-cell sequencing. This was a reasonably in-depth effort to characterize sexually specific cell types during neural development. The use of single-cell sequencing tools to understand developmental mechanisms and not just adult function is appreciated. Some of the recent broader efforts, such as a recent whole-head atlas, contained limited numbers of cells for many cell types and have likely missed rare cell types. Sorting cells of an interesting category in order to enrich their representation in the set, with specific questions in mind, is in some ways a stronger and more targeted approach.

I am surprised that the authors observed so much overlap between Fruitless-expressing cells of the same type in males and females and so few sex-specific cell types, which is interesting. Of course, cells of the same overall "type" could have differential wiring and function given the expression of Fruitless. This study suggests that such a modification may not require a wholesale change in gene expression profiles and may be enabled via a restricted set of changes in target gene expression. Overall, while the outcome is a bit descriptive, these efforts produced some interesting biological insights, and this dataset should serve as a resource for future efforts.

Reviewer #2 (Public Review):

The application of AlphaFold to the prediction of the peptide TCR recognition process is not without challenge; at heart, this is a multi-protein recognition event. While Alphafold does very well at modelling single protein chains its handling of multi-chain interactions such as those of antibody-antigens pairs have performed substantially lower than for other targets (Ghani et al. 2021). This has led to the development of specialised pipelines that tweak the prediction process to improve the prediction of such key biological interactions. Prediction of individual TCR:pMHC complexes shares many of the challenges apparent within antibody-antigen prediction but also has its own unique possibilities for error.

One of the current limitations of AlphaFold Multimer is that it doesn't support multi-chain templating. As with antibodies, this is a major issue for the prediction of TCR:pMHC complexes as the nearest model for a given pMHC, TRAV, or TRBV sequence may be in entirely different files. Bradley's pipeline creates a diverse set of 12-hybrid AlphaFold templates to circumvent this limitation, this approach constrains inter-chain docking and therefore speeds predictions by removing the time-consuming MSA step of the AlphaFold pipeline. This adapted pipeline produces higher-quality models when benchmarked on 20 targets without a close homolog within the training data.

The challenge to the work is of course not generating predictions but establishing a functional scoring system for the docked poses of the pMHC:TCR and most importantly clearly understanding/communicating when modelling has failed. Thus, importantly Bradley's pipeline shows a strong correlation between its predicted and observed model accuracy. To this end, Bradley uses a receiver operating characteristic curve to discriminate between a TCR's actual antigen and 9 test decoys. This is an interesting testing regime, which appears to function well for the 8 case studies reported. It certainly leaves me wanting to better understand the failure mode for the two outliers - have these correctly modelled the pMHC but failed to dock the TCRs for example or visa versa?

The real test of the current work, or its future iteration, will be the ability to make predictions from large tetramer-sorted datasets which then couple with experimental testing. The pipeline's current iteration may have some utility here but future improvements will make for exciting changes to current experimental methods. Overall the work is a step towards applying structural understanding to the vast amount of next-generation TCR sequence data currently being produced and improves upon current AlphaFold capability.

Reviewer #2 (Public Review):

A major challenge to studying the ABC transporter dynamics "in situ" is the lack of precise measurement of various structural conformers that correspond to intermediate states during the ATP-catalytic or substrate-transport cycle. The use of the conformation-specific antibody 5D3 has recently enabled structural biology to experimentally visualize a specific structural fold that corresponds to an apo and inward-facing (IF) state of ABCG2. In this study, Gyöngy et al aimed to develop a mammalian cell-based system for ABCG2 to investigate how nucleotide or drug ligands regulate the transporter's alternating nature of its inward- and outward-facing (OF) conformations. The authors exploited the nature of 5D3 to only recognize ABCG2' IF conformers and combined flow cytometry and confocal microscopy to systematically analyze the IF-OF switches in the presence of nucleotides, drug substrates, ATPase inhibitors, and a known ABCG2 inhibitor Ko143. The authors find that nucleotide binding alone is sufficient to decrease the propensity of IF conformation, as well as to drive the high-to-low drug substrate transformation, and subsequently the drug-induced ATP hydrolysis resets the transporter to the IF and 5D3-bound state. These data provide solid cell-based evidence that adds to the ongoing discussion about the allosteric regulation of ABCG2 by both nucleotide and transport substrate ligands. Most importantly, the results support several lines of functional implications that could not be fully addressed by recent high-profile cryo-EM structures of ABCG2.

Strengths:<br /> The development of the methodology is a tour-de-force effort, as well as the biggest strength of this study. The results and the experimental protocol will likely provide a significant impact on how scientists design experiments to address structural questions without using large-scale purified systems and conventional structural biology approaches.

The validity of using the GFP-tagged ABCG2 variant is supported by several lines of functional characterizations, including protein expression, 5D3 reactivity, the responsiveness of nucleotide analogs, and mitoxantrone (MX) accumulation analysis. The application of such a strategy is particularly exemplified by the systematic treatment of various nucleotide analogs, which is sufficient to establish kinetic analysis by looking into apparent nucleotide affinities. These initial works add confidence in performing experiments by using either transport substrates or ABCG2 inhibitors. It is very compelling to see candidly the drug-coupled stimulation of ATP hydrolysis, given that both ATP and ADP decrease the 5D3-bound population.

The development of fluorescence correlation spectroscopy (FCS), the first in such a study, allows the measurement of colocalization of both fluorescence-labeled transporter and transport substrates. As illustrated by MX binding to ABCG2, the data supports the notion that nucleotide binding drives substrate release from the transporters, which in this case, can be explained by the high-to-low substrate binding affinity or IF-OF conformational switch of the transporter. Moreover, such an assay will be likely used as part of a high-throughput pipeline in search of therapeutic drugs against ABCG2.

Weakness:<br /> Although the paper presents solid and compelling cell-based evidence describing the relationship between structural changes of ABCG2 and ligand bindings, the enthusiasm is slightly dampened by the fact that this study seems mostly used to support the hypotheses that were proposed by recent cryo-EM structures. It is unclear from this study whether new insight into ABCG2's working mechanism can be proposed based on the data in this manuscript.

In addition, the IF-OF switch represents the transformation of two extreme conformations in ABCG2. The authors do not address the intermediate states, such as occluded conformers, in this study, which makes one wonder whether this is a limitation of the methodology presented in this manuscript. Moreover, interdomain crosstalk is highlighted in this manuscript to address the communication between NBD and TMD. However, it is not clear how the data could say anything about the crosstalk between NBD and TMD. For example, one limitation of recording 5D3 sensitivity on WT proteins may not allow us to pinpoint how structural motifs at the NBD-TMD interface (e.g., Q-loop, triple-helix bundle, polar relay, etc) transmit signals that cause IF-OF switch. The authors do not address how the strategy described here can address such a gap.

Lastly, the authors illustrate the conformational change of 5D3 epitope in the extracellular domain (ECD) by using atomic models in the presence and absence of the antibody. The dynamic information of how the ECD transforms to non-5D3 reactive is limited through this study; for instance, what the timing is to set loose of antibodies upon nucleotide binding, or to what degree of drug binding, IF starts to transit to OF under the physiological condition. Despite this, it is worth noting that 30% of MX-ABCG2 colocalization was still observed in untreated cells, perhaps suggesting a dynamic equilibrium between substrate-bound IF and other conformers.

Reviewer #2 (Public Review):

"The cellular architecture of memory modules in Drosophila supports stochastic input integration" is a classical biophysical compartmental modelling study. It takes advantage of some simple current injection protocols in a massively complex mushroom body neuron called MBON-a3 and compartmental models that simulate the electrophysiological behaviour given a detailed description of the anatomical extent of its neurites.

This work is interesting in a number of ways:

- The input structure information comes from EM data (Kenyon cells) although this is not discussed much in the paper<br /> - The paper predicts a potentially novel normalization of the throughput of KC inputs at the level of the proximal dendrite and soma<br /> - It claims a new computational principle in dendrites, this didn't become very clear to me

Problems I see:

- The current injections did not last long enough to reach steady state (e.g. Figure 1FG), and the model current injection traces have two time constants but the data only one (Figure 2DF). This does not make me very confident in the results and conclusions.<br /> - The time constant in Table 1 is much shorter than in Figure 1FG?<br /> - Related to this, the capacitance values are very low maybe this can be explained by the model's wrong assumption of tau?<br /> - That latter in turn could be because of either space clamp issues in this hugely complex cell or bad model predictions due to incomplete reconstructions, bad match between morphology and electrophysiology (both are from different datasets?), or unknown ion channels that produce non-linear behaviour during the current injections.<br /> - The PRAXIS method in NEURON seems too ad hoc. Passive properties of a neuron should probably rather be explored in parameter scans.

Questions I have:

- Computational aspects were previously addressed by e.g. Larry Abbott and Gilles Laurent (sparse coding), how do the findings here distinguish themselves from this work<br /> - What is valence information?<br /> - It seems that Martin Nawrot's work would be relevant to this work<br /> - Compactification and democratization could be related to other work like Otopalik et al 2017 eLife but also passive normalization. The equal efficiency in line 427 reminds me of dendritic/synaptic democracy and dendritic constancy<br /> - The morphology does not obviously seem compact, how unusual would it be that such a complex dendrite is so compact?<br /> - What were the advantages of using the EM circuit?<br /> - Isn't Fig 4E rather trivial if the cell is compact?

Overall, I am worried that the passive modelling study of the MBON-a3 does not provide enough evidence to explain the electrophysiological behaviour of the cell and to make accurate predictions of the cell's responses to a variety of stochastic KC inputs.

Reviewer #2 (Public Review):

The paper entitled "International Multicenter Study Comparing Cancer to Non-Cancer Patients with COVID-19: Impact of Risk Factors and Treatment Modalities on Survivorship" by Raad et al. is a multi-center, international, matched cohort, with a relatively large sample size. The aim of this work is to determine independent risk factors that impact survival in the setting of "novel treatment modalities" like Remdesivir. It enrolled patients with COVID-19 and cancer and compared them to cancer-negative controls. The authors conclude that cancer increases mortality from COVID-19 and that Remdesivir can reduce all-cause mortality in a subset of patients receiving low-flow oxygen and the results support their conclusions. Overall, this paper adds to the growing body of literature that implicates cancer as a worse predictor of survival among patients with COVID-19. The use of a matched cohort makes it unique and strengthens the findings of this study. The potential weaknesses of this study are its retrospective nature and lack of data on the effect of vaccination in this population since the study was conducted prior to the introduction of vaccines.

Reviewer #2 (Public Review):

This is a well written manuscript that provides a useful analysis on using PCT for guiding antibiotics use among cancer patients with COVID19, a very common issue with COVID 19 patients in general but more challenging in the cancer population. Analysis is relatively straight forward. Results support the claim that antibiotics for more than 72 hours may be unnecessary for cancer patients with negative cultures and PCT<0.25. This is can be useful clinically to limit unnecessary antibiotic use, however would only apply this as a very broad generalization. It would be interesting to see what outcomes are and if this applies for more specific and challenging but not uncommon clinical scenarios with cancer patients (i.e neutropenic patients, patients undergoing active therapy, ICU admission) where clinicians may favor longer use of antibiotics.

Reviewer #2 (Public Review):

In this paper, Diehl and Redish recorded simultaneously from multiple medial frontal cortical regions while rats are performing a restaurant-row task. Their results provide insights into how neurons in the different regions may represent different aspects of the decision-making process.

The strength of the study is the experimental design. The restaurant-row task is an excellent and rich paradigm for evaluating decision-making, with specific unique components that may be relatable to economic subjective choices. The other strength is the electrophysiological approach, which enables the author to simultaneously record from multiple medial frontal cortical regions. This leads to a large data set of >3,000 single units recorded during behavior. A weakness of this study is the insistence to dissect the results and assign each region to specific behaviors, while the data seem to suggest that similar signals can be observed across multiple regions, albeit to different degrees. The framework of distributed vs. gradient vs. subregions seems like a strawman idea that does not help with the interpretation of the results, whereas the actual data are already quite rich and interesting.

Reviewer #2 (Public Review):

This work by Martis illustrates, in a predator-prey or parasite-host eco-evolutionary context, the classical idea of bet hedging or biological insurance: where a single population would fluctuate and perhaps risk extinction, summing over multiple sub-populations with asynchronous dynamics (some going up while others go down) allows a stabler total abundance.

Here the sub-populations are various genotypes of one predator and one prey species, fluctuations are due to their ecological interactions, their dynamics are more asynchronous when predation is more specialized (i.e. the various predator genotypes differ more in which prey types they can eat), and mutations allow the regeneration of genotypes that have gone extinct, thus ensuring that the diversity of subpopulations is not lost (corresponding to a "clonal interference" regime with multiple coexisting genotypes).

While the general idea of bet hedging has been explored in many settings, the devil is usually in the details: for instance, sub-populations should be connected enough to allow the rescue of those going extinct, but a too strong connection would simply synchronize their temporal dynamics and lose the benefit of bet hedging. In some cases, connections between sub-populations could even be destabilizing (e.g. Turing instabilities in space).

In a recent surge of physics-inspired many-species theories, where fluctuations arise from ecological dynamics, these details are notably starting to be understood in the case of spatial bet hedging, i.e. genetically identical subpopulations in multiple patches connected by migration (see e.g. Roy et al PLoS Comp Bio 2020 or Pierce et al PNAS 2020).

In the non-spatial eco-evolutionary setting considered here, the connecting flux is one of mutations rather than migrations, and a predator genotype can in principle interact with all prey genotypes (whereas in usual spatialized models, interactions cannot occur between different patches). Another possibly important detail here is that similar genotypes do not have similar interaction phenotypes, meaning there is no risk of evolution being confined in a neighborhood of similar phenotypes. According to the author and my own cursory exploration of the relevant eco-evo literature (with which I am less familiar than pure ecology), this setting has yet to see many developments in the spirit of the many-species theories mentioned above.

These differences make this new inquiry worthwhile and I applaud the author for undertaking it. From a theoretical perspective, three results emerging from the simulations stand out in this article as potentially very interesting:<br /> - rather sharp transitions in extinction probability and strain diversity as mutation flux and predator specialization increase.<br /> - how mutation rate and interaction strength combine, notably in power-law expressions for total population abundance<br /> - the discussion of susceptibilities, i.e. how predator and prey populations respond to perturbations, as a key ingredient in understanding the previous results, in particular with counter-intuitive negative susceptibilities indicating positive feedback loops.

It is a bit unfortunate that these more novel points are only briefly explored in the main text: while they are more developed in appendices, these arguments are not always as complete, polished and distilled as they might have been in a main text, so an article focusing entirely on explaining them deeply and intuitively would have been far more exciting to me.

Finally, I will note that I am not convinced by the framing of the current manuscript as a counterpoint to Robert May's idea of destabilizing diversity - in many ways I think this is a less relevant context than that of bet hedging, and it does a worse job at showcasing what is genuinely interesting and original here; I would thus encourage readers to read this paper in the framing I propose above.

Reviewer #2 (Public Review):

Coronary heart disease (CHD) is a major form of cardiovascular disease, the first cause of mortality in the world. The etiology of CHD is multifactorial and polygenic, with atherosclerosis as the main cause of coronary stenosis and ischemic events. Evidence from basic research in small animal models and clinical trials aiming at lowering proinflammatory cytokines such as IL-1β implicated low-grade inflammation in atherosclerosis pathogenesis. Genetic studies in humans report large numbers of risk variants and genes related to macrophages, monocytes and T-lymphocytes biology supporting further immunity and inflammation in CHD risk. The study conducted by this group reports the results of the investigation of the potential association between 22 persistent or frequently recurring pathogen infections with the risk of CHD in a CoLaus|PsyCoLaus study, a prospective population-based and urban cohort of European ancestry. The authors accessed data over 12 years and assessed the association between traditional risk factors through the SCORE2 estimation of risk, a recently validated score specifically developed to predict cardiovascular risk in European countries, genetic risk scores based on GWAS findings, and seropositivity to infections. They were able to confirm the utility of the application of SCORE2 in their population, and report a significant association of the genetic score with the incidence of CHD, both traditional and genetic factors being independent predictors, which was expected. An intriguing result regards reported seropositivity with F. nucleatum to significantly predict incident CHD. This a commensal bacterium that belongs to the normal oral microbiome reported playing an important role in the development and progression of gingivitis (gum inflammation) and periodontitis (infection of the gums). There are several existing lines of evidence connecting oral infections as an independent risk factor for CHD. The results reported by this study provide support for the increased risk of CHD in oral infection through seropositivity to F. nucleatum. However, the direct clinical implications, through the recommendation to search for prior infection with this bacterium as a predicting biomarker of this disease are not on the clinical application agenda yet. The infection seropositivity was measured only at the beginning of the study, with no information on how the oral seropositivity to this pathogen may have evolved over time. And given the novelty of this association, these results need to be replicated in independent cohorts with similar designs (prospective cohorts) before recommendation to screen for seropositivity could be recommended.

Reviewer #2 (Public Review):

Despite previous studies, regulation of the genes required for galactose metabolism in Candida albicans has remained murky. For example, previous work had highlighted Rtg1 and Rtg3 as the key regulator components, an interesting finding given that these factors are important for glucose not galactose regulation in S. cerevisiae. As galactose metabolism is one of the best-understood regulatory systems, the evolutionary difference in the regulation of the galactose response has the potential to teach us about regulatory evolution in general.

The authors initially sought to understand how GlcNAc signaling cross-reacted with galactose gene induction, but they quickly discovered that Reg1, the mediator of GlcNAc signaling was essential for galactose metabolism while Rtg1 and Rtg3 were not. Overturning previous work requires strong evidence, and the authors deliver with a series of growth assays, qPCR, and chromatin IP in wt and mutant backgrounds.

The authors go further to demonstrate that the factor itself interacts with galactose based on isothermal calorimetry (although it would be nice to have seen if this was specific to galactose over glucose or GlcNAc). They show glucose regulation occurs by Reg1 recruiting Cga1 in a manner independent of the activation domain of Reg1 (immunoprecipitation, reporter assays, and chromatin IP). In contrast, Reg1 activation mediated by GlcNAc requires Reg1's activation domain and employs Rgs1. Once again, the experimental evidence for these two regulatory mechanisms is strong.

Evolutionary analysis shows that this specific instantiation of this mechanism, the combination of Reg1 and Cga1, is probably restricted to the CTG clade. While the paper does not explain how these regulatory changes happen, it sets the foundation for future work to tease this apart; work that before this paper would have been unlikely to have been successful.

Reviewer #2 (Public Review):

The study by Nunez et al. builds upon structural work from the MacKinnon lab and the authors' labs to characterize how Ca2+, via calmodulin, interacts with Kv7 channels to mediate redox sensitivity. Using FRET experiments to support electrophysiology, the authors demonstrate an interaction defined by calmodulin, the helixA-helixB fork, and the S2-S3 linker. The experiments are well performed and the conclusions drawn are appropriate. These experiments help further define the redox signaling for Kv7 channels. A weakness is that the model in Figure 7 seems speculative, as the data provided do not appear to explain how the VSD is engaged/disengaged from the pore. Rather, most of the data concentrate on biochemical interactions and structural interpretations (via FRET signals, etc.) of conformational changes in the presence of calcium. Further, the model as presented is not informative. The illustrations do not demonstrate successfully what the authors wish to claim, and the illustrations/models are not sufficiently supported by the data presented.

Reviewer #2 (Public Review):

Kato, Jenkins, et al. investigates cell-intrinsic and environmental determinants of diverse modes of collective cancer cell invasion in mucosal squamous cell carcinoma (muSCC). To explore this large parameter space, the authors develop a Cellular Potts model recapitulating two distinct in vitro muSCC - cancer-associated fibroblast (CAF) co-culture models: an organotypic platform containing an air/extracellular matrix (ECM) interface and a spheroid model mimicking dermal invasion and confinement by 3D ECM. Integrating between in silico predictions and quantitative assessment of the two experimental platforms, the authors make several interesting observations regarding determinants of the mode of collective SCC invasion. Of these, the most significant include the ability of SCCs to invade with deletion of β1 integrin in their organotypic model although invasion phenotype is altered, and identification of a synergistic dependence on cell-cell adhesion and matrix proteolysis for controlling strand width and growth within the invading cohort. Cell-cell adhesions are essential for maintaining supracellular actomyosin coupling to coordinate the invading cohort, while matrix proteolysis is necessary for creating physical space that supports both invasion and cell growth within confined space.

Overall, despite some concerns regarding support for specific claims, alternative considerations, and clarity in presentation, this study is rigorous and of high quality, and should serve as an important technical and conceptual resource that provides new insight into multicellular coordination in SCC invasion. More broadly, it illustrates the utility of coupling computational models with advanced 3D cell culture platforms to parse multifactorial control over complex forms of tissue morphogenesis.

Reviewer #2 (Public Review):

The authors consider the application of Granger causality (GC) analysis to calcium imaging data and identify several challenges therein and provide methodological approaches to address them. In particular, they consider case studies involving fluorescence recordings from the motoneurons in embryonic zebrafish and the brainstem and hindbrain of larval zebrafish to demonstrate the utility of the proposed solutions in removing the spurious links that the naive GC identifies.

The paper is well-written and the results on the chosen case studies are compelling. However, the proposed work would benefit from discussing the contributions of this work in the context of existing and relevant literature and clarifying some of the methodological points that require more rigorous treatment. I have the following comments:

Major comments:

1) I would like to point out recent literature that adapts the classical GC for both electrophysiology data and calcium imaging data:

[1] A. Sheikhattar et al., "Extracting Neuronal Functional Network Dynamics via Adaptive Granger Causality Analysis", PNAS, Vol. 115, No. 17, E3869-E3878, 2018.

[2] N. A. Francis et al., "Small Networks Encode Decision-Making in Primary Auditory Cortex", Neuron, Vol. 97, No. 4, 2018.

[3] N. A. Francis et al., "Sequential Transmission of Task-Relevant Information in Cortical Neuronal Networks", Cell Reports, Vol. 39, No. 9, 110878, 2022.

In reference [1], a variation of GC based on GLM log-likelihoods is proposed that addresses the issues of non-linearity, non-stationarity, and non-Gaussianity of electrophysiology data. In [2] and [3], a variation of GC using sparse multi-variate models is introduced with application to calcium imaging data. In particular, all three references use the sparse estimation of the MVAR parameters in order to mitigate overfitting and also use corrections for multiple comparisons that also reduce the number of spurious links (see my related comments below). I suggest discussing these relevant references in the introduction (paragraphs 2 and 3) and discussion.

2) A major issue of GC applied to calcium imaging data is that the trials are typically limited in duration, which results in overfitting of the MVAR parameters when using least squares (See references [2] and [3] above, for example). The authors mention on page 4 that they use least squares to estimate the parameters. However, for the networks of ~10 neurons considered in this work, stationary trials of a long enough duration are required to estimate the parameters correctly. I suggest that the authors discuss this point and explicitly mention the trial durations and test whether the trial durations suffice for stable estimation of the MVAR parameters (this can be done by repeating some of the results on the synthetic data and using different trial lengths and then assessing the consistency of the detected GC links).

3) The definition of the "knee" of the average GC values as a function of the lag L needs to be a bit more formalized. In Fig. 2H using the synthetic data, the "knee" effect is more clear, but in the real data shown in Fig. 2I, the knee is not obvious, given that the confidence intervals are quite wide. Is there a way to quantify the "knee" by comparing the average GC values as well as their confidence bounds along the lag axis?

4) While the measures of W_{IC} and W_{RC} form suitable guiding principles for the pipeline presented in this work, it would be helpful if the authors discuss how such measures can be used for other applications of GC to calcium imaging data in which a priori information regarding the left/right symmetry or the rostrocaudal flow of information is missing.

5) Removing the "strange" neurons discussed in Section C5 is definitely an important pre-processing step in applying GC. However, the criterion for identifying the strange neurons seems a bit ad hoc and unclear. Could this be done by clustering the neurons into several categories (based on their time courses) and then removing a "strange" cluster? Please clarify.

6) Another key element of existing GC methods applied to large-scale networks is dealing with the issue of multiple comparisons: for instance, in Figures 2, 3, 4, 6, 7, and 8, it seems like all arrows corresponding to all possible links are shown, where the colormap indicates the GC value. However, when performing multiple statistical tests, many of these links can be removed by a correction such as the Benjamini-Hochberg procedure. It seems that the authors did not consider any correction of multiple comparisons; I suggest doing so and adding this to your pipeline.

7) The authors use TV denoising and also mention that it is a global operator, and changes the values of a time series at time t based on both the past and future values of the process. As such, it is not clear how TV denoising could affect the "causal" relations of the time series. In particular, TV denoising would significantly change the \Gamma_{ii} coefficients in Eq. (8). Is it possible to apply a version of TV denoising that only uses the information from the past to denoise the process at time t? In other words, using a "filter" as opposed to a "smoother". Please clarify.

8) The idea of using an adaptive threshold as in Section C8 is interesting; but this problem was previously considered in [30] (in the manuscript) and reference [1] above, in which new test statistics based on log-likelihoods are used that have well-known asymptotic null distributions (i.e., chi-square distributions). In particular, reference [1] above identifies and applies the required rescaling for the asymptotic null distributional assumptions to hold. I suggest discussing your work regarding the adaptive thresholds in the context of these existing results.

9) Related to the previous comment, given that the authors use a shuffling procedure to obtain the null, it is not clear why fitting the F-distribution parametrically and using its quantiles for testing would provide further benefits. In fact, as shown in Figure S9B, the rescaled F-distribution does not fully match the empirical null distribution, so it may be worth using the empirical null to obtain the non-parametric quantiles for testing. Please clarify.

10) In Figure 5C, the values of W_IC for the MV cases seem to be more than 1, whereas by definition they should be less than or equal to 1. Please clarify.

11) Is there evidence that the lateralized and rostrocaudal connectivity of the motoneurons occurs at the time-scale of ~750 ms? Given that this time scale is long enough for multiple synapses, it could be the case that some contralateral and non-rostrocaudal connections could be "real", as they reflect multi-hop synaptic connections. Please clarify.

12) While it is useful to see the comparison of the BV and MV cases shown in Figs. 1 and 2, given extensive evidence in the GC literature on the shortcomings of the BV version of GC, it seems unnecessary to report the BV results in Figs. 3 onward. I suggest discussing the shortcoming of the BV case when presenting figures 1 and 2 and removing the BV results from the subsequent results.

Reviewer #2 (Public Review):

The antiporter AdiC is a member of the amino-acid and polyamine organocation (APC) transporter superfamily. It imports the single-charged arginine (Arg+) and exports the double-charged agmatine (Agm2+). Thus, it increases the intracellular pH, helping some pathogenic enterobacteria survive in acidic environments. The APC transporters are known to sample 4 major conformations in the transport cycle. Monitoring the conformational transitions is important for understanding the transport mechanism, but methods detecting multi-state conformational changes are very limited. The authors use high-resolution polarization microscopy to resolve 4 different states in substrate-free (Apo) or substrate-bound conditions. This work further demonstrates the power of fluorescence polarization microscopy in studying protein dynamics. The authors introduced an interesting normalization step in data processing to average results obtained for different protein particles. However, the 4 states could be identified from single traces and the normalization from trace to trace could not be done without the pre-identified states on single traces. Thus, the improvement provided by the normalization compared to the published work (NSMB 2019a, 2019b, 2019c) is relatively limited.

Reviewer #2 (Public Review):

The manuscript by Park et al. reports a new structure of the mechanosensitive channel MscS of E. coli in the open state and the results of extensive coarse grained and atomistic molecular dynamics (MD) simulations of MscS and the related channel MSL1 of plant mitochondria in presumed closed and open states. The major new finding is that in the closed state, the lipid bilayer contacting the channel is severely distorted. In the open state, this distortion is not present. The MD simulations forming the basis of this finding have been carefully executed and the finding is interesting and relevant for the understanding of channel mechanosensation. The MD simulations are ideally suited to probe the lipid interactions of the channel in a state-dependent manner and to identify possible membrane distortions. However there are some issues that should be addressed.

1) Are the structures stable in the membrane also without the weak restraints on the dihedral angles? Continuing at least one of the atomistic simulations without restraints for about 1 microsecond in a tension-free membrane would address a possible concern that the severe membrane distortion could go away by a more extensive relaxation of the channel structure.

2) Does the observed effect occur also in membranes with physiologically relevant PE lipids? Performing a simulation with a lipid mix closer to that in E. coli (and thus high in PE) would address a possible concern that the observed effect is not physiologically relevant.

3) Please include a figure showing that the lipid positions in the MD simulations match the lipid densities in the cryo-EM maps.

4) Is the reported mobility of helices TM2-TM3 of MSL1, as deduced from a comparison of different cryo-EM structures (ref 18), sufficient to impact the lipid organisation?

5) Did the initial lipid configuration in atomistic MD simulations already contain the deformations of the inner leaflet, or did these form spontaneously both in coarse-grained and atomistic simulations?

6) Did the earlier MD simulations of the closed-state structure 6PWN of MscL give any indications on the membrane deformation?

7) Are there distinct interactions between the headgroups of distorted inner-leaflet lipids with charged amino acids? If so, are these amino acids conserved?

Reviewer #2 (Public Review):

The authors present a set of simulations that show how hippocampal theta sequences may be combined with spike time-dependent plasticity to learn a predictive map - the successor representation - in a biologically plausible manner. This study addresses an important question in the field: how might hippocampal theta sequences be combined with STDP to learn predictive maps? The conclusions are interesting and thought-provoking. However, there were a number of issues that made it hard to judge whether the conclusions of the study are justified. These concerns mainly surround the biological plausibility of the model and parameter settings, the lack of any mathematical analysis of the model, and the lack of direct quantitative comparison of the findings to experimental data.

While the model uses broadly realistic biological elements to learn the successor representation, there remain a number of important concerns with regard to the biological plausibility of the model. For example, the model assumes that each CA3 cell connects to exactly 1 CA1 cell throughout the whole learning process so that each CA1 cell simply inherits the activity of a single CA3 cell. Moreover, neurons in the model interact directly via their firing rate, yet produce spikes that are used only for the weight updates. Certain model parameters also appeared to be unrealistic, for example, the model combined very wide place fields with slow running speeds. This leaves open the question as to whether the proposed learning mechanism would function correctly in more realistic parameter settings. Simulations were performed for a fixed running speed, thereby omitting various potentially important effects of running speed on the phase precession and firing rate of place cells. Indeed, the phase precession of CA1 place cells was not shown or discussed, so it is unclear as to whether CA1 cells produce realistic patterns of phase precession in the model.

The fact that a successor-like representation emerges in the model is an interesting result and is likely to be of substantial interest to those working at the intersection between neuroscience and artificial intelligence. However, because no theoretical analysis of the model was performed, it remains unclear why this interesting correspondence emerges. Was it a coincidence? When will it generalise? These questions are best answered by mathematical analysis of the model (or a reduced form of it).

Several aspects of the model are qualitatively consistent with experimental data. For example, CA1 place fields clustered around doorways and were elongated along walls. While these findings are important and provide some support for the model, considerable work is required to draw a firm correspondence between the model and experimental data. Thus, without a quantitative comparison of the place field maps in experimental data and the model, it is hard to draw strong conclusions from these findings.

Overall, this study promises to make an important contribution to the field, and will likely be read with interest by those working in the fields of both neuroscience and artificial intelligence. However, given the above caveats, further work is required to establish the biological plausibility of the model, develop a theoretical understanding of the proposed learning process, and establish a quantitative comparison of the findings to experimental data.

Reviewer #2 (Public Review):

In 'Molecular characterization of cell types in the squid Loligo vulgaris', the authors study profile cell types of the squid brain, using single cell RNAseq and FISH for anatomical localization. They reveal many different cell types, some of which have correspondences in other organisms and some of which reflect cephalopod-specific innovations. The current study is one of 4 recent preprints (Styfhals et al. 2022, Songco-Casey et al. 2022, Gavriouchkina et al. 2022) profiling cephalopod tissues using scRNAseq and FISH-based anatomical localization. Together these studies begin to reveal the cellular complexity of these fascinating animals.

Reviewer #2 (Public Review):

The authors motivate this study by the medical need to develop brain-machine interfaces (BMIs) to restore lost arm and hand function, for example through functional electrical stimulation. More specifically, they are interested in developing BMI decoding algorithms that work across a variety of "contexts" that a BMI user would encounter out in the real world, for example having their hand in different postures and manipulating a variety of objects. They note that in different contexts, the motor cortex neural activity patterns that produce the desired muscle outputs may change (including neurons' specific relationship to different muscles' activations), which could render a static decoder trained in a different context inaccurate.

To test whether this potential challenge is indeed the case, this study tested BMI control of virtual (on-screen) fingers by two rhesus macaques trained to perform 1 or 2 degree-of-freedom non-grasping tasks either by moving their fingers, or just controlling the virtual finger kinematics with neural activity. The key experimental manipulations were context shifts in the form of springs on the fingers or flexion of the wrist (or both). BMI performance was then evaluated when these context changes were present, which builds on this group's previous demonstration of accurate finger BMI without any context shifts.

The study convincingly shows the aforementioned context shifts do cause large changes in measured firing rates. When neural decoding accuracy (for both muscle and position/velocity) is evaluated across these context changes, reconstruction accuracy is substantially impaired. The headline finding, however, is that that despite this, BMI performance is, on aggregate, not substantially reduced. Although: it is noteworthy that in a second experiment paradigm where the decoder was trained on the spring or wrist-manipulated context and tested in a normal context, there were quite large performance reductions in several datasets as quantified by multiple performance measures; this asymmetry in the results is not really explored much further.

The changes in neural activity due to context shifts appear to be relatively modest in magnitude and can be fit well as simple linear shifts (in the neural state space), and the authors posit that this would make it feasible (in future work) to find context-invariant neural readouts that would result in more robust muscle activity decoders.

An additional novel contribution of this study is showing that these motor cortical signals support quite accurately decode muscle activations during non-prehensile finger movements (and also that the EMG decoding was more negatively affected by context shifts than kinematics decoding); previous work decoded finger kinematics but not these kinetics. Note that this was demonstrated with just one of the two monkeys (the second did not have muscle recordings).

This is a rigorous study, its main results are well-supported, and it does not make major claims beyond what the data support. One of its limitations is that while the eventual motivating goal is to show that decoders are robust across a variety of tasks of daily living, only two specific types of context shifts are tested here, and they are relatively simple and potentially do not result in as strong a neural change as could be encountered in real-world context shifts. This is by no means a major flaw (simplifying experimental preparations are a standard and prudent way to make progress). But the study could point this out a bit more prominently that their results do not preclude that more challenging context shifts will be encountered by BMI users, and this study in its current form does not indicate how strong a perturbation the tested context shifts are relative to the full possible range of hand movement context shifts that would be encountered during human daily living activities.

A second limitation is that while the discrepancy between large offline decoding performance reduction and small online performance reduction are attributed to rapid sensorimotor adaptation, this process is not directly examined in any detail. Third, the assessment of how neural dynamics change in a way that preserves the overall shape of the dynamics is rather qualitative rather than quantitative, and that this implementation of a more context-agnostic finger BMI is left for future work.

Reviewer #2 (Public Review):

Chakrabarti et al. aimed to investigate exocytosis from ribbon synapses of cochlear inner hair cells with high-resolution electron microscopy with tomography. Current methods to capture the ultrastructure of the dynamics of synaptic vesicle release in IHCs rely on the application of potassium for stimulation, which constrains temporal resolution to minutes rather than the millisecond resolution required to analyse synaptic transmission. Here the authors implemented a high-pressure freezing method relying on optogenetics for stimulation (Opto-HPF), granting them both high spatial and temporal resolutions. They provide an extremely well-detailed and rigorously controlled description of the method, falling in line with previously use of such "Opto-HPF" studies. They successfully applied Opto-HPF to IHCs and had several findings at this highly specialised ribbon synapse. They observed a stimulation-dependent accumulation of docked synaptic vesicles at IHC active-zones, and a stimulation-dependent reduction in the distance of non-docked vesicles to the active zone membrane; while the total number of ribbon-associated vesicles remained unchanged. Finally, they did not observe increases in diameter of synaptic vesicles proximal to the active zone, or other potential correlates to compound fusion - a potential mode of multivesicular release. The conclusions of the paper are mostly well supported by data, but some aspects of their findings and pitfalls of the methods should be better discussed.

Strengths:

While now a few different groups have used "Opto-HPF" methods (also referred to as "Flash and Freeze) in different ways and synapses, the current study implemented the method with rigorous controls in a novel way to specifically apply to cochlear IHCs - a different sample preparation than neuronal cultures, brain slices or C. elegans, the sample preparations used so far. The analysis of exocytosis dynamics of IHCs with electron microscopy with stimulation has been limited to being done with the application of potassium, which is not physiological. While much has been learned from these methods, they lacked time resolution. With Opto-HPF the authors were successfully able to investigate synaptic transmission with millisecond precision, with electron tomography analysis of active zones. I have no overall questions regarding the methodology as they were very thoroughly described. The authors also employed electrophysiology with optogenetics to characterise the optical simulation parameters and provided a well described analysis of the results with different pulse durations and irradiance - which is crucial for Opto-HPF.

Further, the authors did a superb job in providing several tables with data and information across all mouse lines used, experimental conditions, and statistical tests, including source code for the diverse analysis performed. The figures are overall clear and the manuscript was well written. Such a clear representation of data makes it easier to review the manuscript.

Weaknesses:

There are two main points that I think need to be better discussed by the authors.

The first refers to the pitfalls of using optogenetics to analyse synaptic transmission. While ChR2 provides better time resolution than potassium application, one cannot discard the possibility that calcium influx through ChR2 alters neurotransmitter release. This important limitation of the technique should be properly acknowledged by the authors and the consequences discussed, specifically in the context in which they applied it: a single sustained pulse of light of ~20ms (ShortStim) and of ~50ms (LongStim). While longer, sustained stimulation is characteristic for IHCs, these are quite long pulses as far as optogenetics and potential consequences to intrinsic or synaptic properties.

The second refers to the finding that the authors did not observe evidence of compound fusion (or homotypic fusion) in their data. This is an interesting finding in the context of multivesicular release in general, as well as specifically for IHCs. While the authors discussed the potential for "kiss-and-run" and/or "kiss-and-stay", it would be valuable if they could discuss their findings further in the context of the field for multivesicular release. For example, the evidence in support of the potential of multiple independent release events. Further, as far as such function-structure optical-quick-freezing methods, it is not unusual to not capture fusion events (so-called omega-shapes or vesicles with fusion pores); this is largely because these are very fast events (less than 10 ms), and not easily captured with optical stimulation.

Reviewer #2 (Public Review):

This manuscript studied potential cellular mechanisms that generate ultrafast oscillations (250-600Hz) in the cortex. These oscillations correlate with sensory stimulation and might be relevant for the perception of relevant sensory inputs. The authors combined ex-vivo whole-cell patch-clamp recordings, local field potential (LFP) recordings, and optogenetic stimulation of thalamocortical afferents. In a technical tour de force, they recorded pairs of fast-spiking (FS)-FS and FS-regular-spiking (RS) neurons in the cortex and correlated their activity with the LFP signal.

Optogenetic activation of thalamic afferents generated ripple-like extracellular waveforms in the cortex, which the authors referred to as ripplets. The timing of the peaks and troughs within these ripplets was consistent across slices and animals. Activation of thalamic inputs induced precisely timed FS spike bursts and RS spikes, which were phase-locked to the ripplet oscillation. The authors described the sequences of RS and FS neuron discharge and how they phase-locked to the ripplet, providing a model for the cellular mechanism generating the ripplet.

The manuscript is well-written and guides the reader step by step into the detailed analysis of the timing of ripplets and cellular discharges. The authors appropriately cite the known literature about ultrafast oscillations and carefully compare the novel ripplets to the well-known hippocampal ripples. The methods used (ex-vivo patch-clamp and LFP) were appropriate to study the cellular mechanisms underlying the ripplets.

Overall, this manuscript develops means for studying the role of cortical ultrafast oscillations and proposes a coherent model for the cellular mechanism underlying these cortical ultrafast oscillations.

Reviewer #2 (Public Review):

This paper focuses on an important topic. It explores how the activation loop conformations affect the type II inhibitor binding in Tyr and Ser/Thr kinases. The comprehensive computational results agree with the available experimental data. It is a remarkably comprehensive, high quality paper.

Reviewer #2 (Public Review):

The goal of this study is to find a minimal model that produces both theta and gamma rhythms in the hippocampus CA1, based on the full-scale model (FSM) of Bezaire et al, 2016. The FSM here is treated as equivalent to biological data. This seems to be a second part of a study that the same authors published in 2021, and is extensively cited here. The study reduces the FSM to a neural rate model with 4 neurons, which is capable of producing both rhythms. This model is then simulated and its parameter dependencies are explored.

The authors succeed in producing a rate model, based on 4 neuron types, that captures the essence of the two rhythms. This model is then analyzed at a descriptive level to claim that the synapse from one interneuron type (CCK) to another (PV+) is more effective than its reciprocal counterpart (PV+ to CCK synapse) to control theta rhythm frequency.

The results fall short on several fronts:<br /> The conclusions rely exclusively on the assumption that the FSM is in fact able to faithfully reflect the biological circuits involved, not just in its output, but in response to a variety of perturbations. Although the authors mention and discuss this assumption, in the end, the reader is left with a (reduced) model of a (complex) model, but no real analysis based on this reduction. In fact, the reduced model is treated in a manner that could have been done with the full one. Thus the significance of the work is greatly reduced not by what the authors do, but by what they fail to do, which is to properly analyze their own reduced model. Consequently, the impact of this study on the field is minimal.<br /> Related to the first point, throughout the manuscript, multiple descriptive findings, based on the authors' observations of the model output, are presented as causal relationships. Even the main finding of the study (that one synapse has a larger effect on theta than another) is not quantified, but just simply left as a judgment call by the authors and reader of comparing slopes on graphs.

Reviewer #2 (Public Review):

In this manuscript, Taylor et al. analyzed the role of the Polo-like kinase PLK-1 during female meiosis in the C. elegans oocyte. By temporally inhibiting an analogue-sensitive PLK-1 mutant (bypassing the PLK-1 requirement for nuclear envelope breakdown) they demonstrate that PLK-1 is involved in meiotic spindle assembly and/or stability, chromosome alignment and polar body extrusion. Consistent with its role in these processes, the authors demonstrate that PLK-1 localizes to multiple regions of the meiotic spindle: the spindle poles, chromosome arms, kinetochores and midbivalent region between the homologous chromosomes during meiosis I. They further dissected the mechanism recruiting PLK-1 to these structures and showed that CENP-CHCP-4 recruits PLK-1 to the chromosome arms while BUB-1 recruits PLK-1 to the midbivalent and kinetochores. The interaction between PLK-1 and its partners is mediated by phosphorylation of a Polo-docking site (consensus STP) in BUB-1 and CENP-CHCP-4. Finally, the authors show that both PLK-1 recruitment pathways are critically required for PLK-1 function in female meiosis.

This fundamental work substantially advances our understanding of PLK-1 function during female meiosis.<br /> Overall, the data presented are of very high quality and support the major conclusions of the paper with one or two exceptions.

Reviewer #2 (Public Review):

The impact of the work will be for yeast researchers in the clear and careful presentation of a case study wherein phenotypes might be ascribed to the knockout of a particular gene but instead derive from effects on a neighboring gene. In this case, a transcript expressed from within or adjacent to a knockout of DBP1 by a selectable marker towards the adjacent gene MRP51 interferes with the adjacent gene's normal transcription start sites. Furthermore, although neighboring MRP51 ORF is present on the longer mRNA isoform that is generated, it is not efficiently translated. The authors expand on this phenotypic observation to demonstrate that a substantial fraction of selectable marker insertions can generate transcription adjacent to or within and going away from, selectable markers.

The strengths of the work are that the derivation of the observed phenotypes for the dpb1∆ alleles is clearly and carefully elucidated and the creation of new selectable marker cassettes that overcome the potential for cryptic transcript emanation from or near to the selectable markers. This is valuable for the community as a clear demonstration of how only the exact right experiments might detect underlying mechanisms for potentially misattributed phenotypes and that many times these experiments may not be performed. While understandable in terms of how the experiments likely played out, the manuscript seems in between biology and tool development, as the biology in question was related to a gene that is not the focus of this lab. The tool development is likely to be useful but potentially non-optimal. The mechanism for interference identified in this example case (via a long undecoded transcript isoform (LUTI) has already been described for other loci and in a number of species, including in work from the Brar lab. The concept of marker interference with neighboring genes has also been increasingly appreciated by a number of other studies.

Reviewer #2 (Public Review):

Activation of SK channels by calcium through calmodulin (CaM) is physiologically important in tuning membrane excitability. Understanding the molecular mechanism of SK activation has therefore been a high priority in ion channel biophysics and calcium signaling. The prevailing view is that the C-terminal lobe of CaM serves as an immobile Ca2+-independent tether while the N-lobe acts as a sensor whose binding activates the channel. In the present study, the authors undertake extensive biophysical/biochemical analysis of CaM interaction with SK channel peptide and rigorous electrophysiological experiments to show that Ca2+ does bind to the C-lobe of CaM and this potentially evokes conformational changes that may be relevant for channel gating. Beyond SK channels, the approach and findings here may bear important implications for an expanding number of ion channels and membrane proteins that are regulated by CaM.

A strength of the study is that the electrophysiological recordings are innovative and of high quality. Given that CaM is ubiquitous in nearly all eukaryotes, dissecting the effects of mutants particularly on individual lobes is technically challenging, as endogenous CaM can overwhelm low-affinity mutants. The excised patch approach developed here provides a powerful methodology to dissect fundamental mechanisms underlying CaM action. I imagine this could be adaptable for studying other ion channels. Armed with this strategy authors show that both N- and C-lobe of CaM are essential for maximal activation of SK channels. This revises the current model and may have physiological importance.

The major weakness is that nearly all biochemical inferences are made from analysis of isolated peptides that do not necessarily recapitulate their arrangement in an intact channel. While the use of MALS provides new evidence of the potentially complex conformational arrangement of CaM on the C-terminal SK peptide (SKp), it is not fully clear that these complexes correspond to functionally relevant states. Lastly, perhaps as a consequence of these ambiguities, the overarching model or mechanism is not fully clear.

Reviewer #2 (Public Review):

This is an extremely thorough investigation of the role of cadherins in generating a functional motor circuit. The work represents a major step forward in the field as it addresses several outstanding questions and verifies anatomical data with functional outcomes. First, the data show that a combination of type I (N) and type II (6, 9, 10) cadherins is needed to generate normal connectivity and function. This is novel as prior work has suggested that the two types do not work collaboratively to generate circuits. Second, the data show that cell body position (in this case) is modulated by N-cadherin but in a manner that is independent from the impact of N-cadherin on connectivity. While position and connectivity have been shown to be separable in some cases, the data support that N-cadherin plays important but separate roles toward both actions, and type II cadherins, mainly in connectivity. These findings also underscore that cadherin roles reported for hippocampus, retina, and spinal cord motor neuron pools are not generalizable across circuits. Third, while the data show that type I and type II cadherins are required for VRG to phrenic motor neuron connectivity, they also show that there are some outcomes controlled only by N-cadherin. Finally, the data reveal much about a very poorly understood and essential circuit. The approaches are sound and range from the standard (in situ, immuno, diI, breathing measurements) to the difficult (rabies-based tracing) to the impressive (challenging ephys preps, and some painstaking mouse crosses), and they incorporated strong and creative strategies for comparison and quantification. Minor questions do not detract from a really impressive piece of work.

Reviewer #2 (Public Review):

This manuscript focuses on the basis of musical expectations/predictions, both in terms of the basis of the rules by which these are generated, and the neural signatures of surprise elicited by violation of these predictions.

Expectation generation models directly compared were gestalt-like, n-gram, and a recently-developed Music Transformer model. Both shorter and longer temporal windows of sampling were also compared, with striking differences in performance between models.

Surprise (defined as per convention as negative log prior probability of the current note) responses were assessed in the form of evoked response time series, recorded separately with both MEG and EEG (the latter in a previously recorded freely available dataset). M/EEG data correlated best with surprise derived from musical models that emphasised long-term learned experiences over short-term statistical regularities for rule learning. Conversely, the best performance was obtained when models were applied to only the most recent few notes, rather than longer stimulus histories.

Uncertainty was also computed as an independent variable, defined as entropy, and equivalent to the expected surprise of the upcoming note (sum of the probability of each value times surprise associated with that note value). Uncertainty did not improve predictive performance on M/EEG data, so was judged not to have distinct neural correlates in this study.

The paradigm used was listening to naturalistic musical melodies.

A time-resolved multiple regression analysis was used, incorporating a number of binary and continuous variables to capture note onsets, contextual factors, and outlier events, in addition to the statistical regressors of interest derived from the compared models.

Regression data were subjected to non-parametric spatiotemporal cluster analysis, with weights from significant clusters projected into scalp space as planar gradiometers and into source space as two equivalent current dipoles per cluster

General comments:

The research questions are sound, with a clear precedent of similar positive findings, but numerous unanswered questions and unexplored avenues

I think there are at least two good reasons to study this kind of statistical response with music: firstly that it is relevant to the music itself; secondly, because the statistical rules of music are at least partially separable from lower-level processes such as neural adaptation.

Whilst some of the underlying theory and implementation of the musical theory are beyond my expertise, the choice, implementation, fitting, and comparison of statistical models of music seem robust and meticulous.

The MEG and EEG data processing is also in line with accepted best practice and meticulously performed.

The manuscript is very well-written and free from grammatical or other minor errors.

The discussion strikes a brilliant balance of clearly laying out the interim conclusions and advances, whilst being open about caveats and limitations.

Overall, the manuscript presents a range of highly interesting findings which will appeal to a broad audience, based on rigorous experimental work, meticulous analysis, and fair and clear reporting.

Reviewer #2 (Public Review):

This is a very interesting paper, in which the authors describe how respiration-driven gamma oscillations in the piriform cortex are generated. Using a published data set, they find evidence for a feedback loop between local principal cells and feedback interneurons (FBIs) as the main driver of respiration-driven gamma. Interestingly, odour-evoked gamma bursts coincide with the emergence of neuronal assemblies that activate when a given odour is presented. The results argue in favour of a winner-take-all mechanism of assembly generation that has previously been suggested on theoretical grounds.

The article is well-written and the claims are justified by the data. Overall, the manuscript provides novel key insights into the generation of gamma oscillations and a potential link to the encoding of sensory input by cell assemblies. I have only minor suggestions for additional analyses that could further strengthen the manuscript:

1. The authors' analysis of firing rates of FFIs and FBIs combined with TeLC experiments make a compelling case for respiration-driven gamma being generated in a pyramidal cell-FBI feedback mechanism. This conclusion could be further strengthened by analyzing the gamma phase-coupling of the three neuronal populations investigated. One would expect strong coupling for FBIs but not FFIs (assuming that enough spikes of these populations could be sampled during the respiration-triggered gamma bursts). An additional analysis to strengthen this conclusion could be to extract FBI- and FFI spike-triggered gamma-filtered signals. One might expect an increase in gamma amplitude following FBI but not FFI spiking (see e.g., Pubmed ID 26890123).

2. The authors utilize the neurons' weight in the first PC to assign them to odour-related assemblies. This method convincingly extracts an assembly for each odour (when odours are used individually), and these seem to be virtually non-overlapping. It would be informative to test whether a similar clear separation of the individual assemblies could be achieved by running the analysis on all odours simultaneously, perhaps by employing a procedure of assembly extraction that allows to deal with overlapping assembly membership better than a pure PCA approach (as used for instance in the work cited on page 11, including the authors' previous work)? I do not doubt the validity of the authors' approach here at all, but the suggested additional analysis might allow the authors to increase their confidence that individual neurons contribute mostly to an assembly related to a single odour.

3. Do the authors observe a slow drift in assembly membership as predicted from previous work showing slowly changing odour responses of principal neurons (Schoonover et al., 2021)? This could perhaps be quantified by looking at the expression strengths of assemblies at individual odour presentations or by running the PCA separately on the first and last third of the odour presentations to test whether the same neurons are still 'winners'.

4. Does the winner-take-all scenario involve the recruitment of specific sets of FBIs during the activation of the individual odour-selective assemblies? The authors could address this by testing whether the rate of FBIs changes differently with the activation of the extracted assemblies.

5. Given the dependence on local gamma oscillations, one might expect that odour-selective assemblies do not emerge in the TeLC-expressing hemisphere. This could be directly tested in the existing data set.

Reviewer #2 (Public Review):

The manuscript documents a thorough and well-validated clinical prediction model for risk of severe child linear growth faltering after diarrheal disease episodes, using data from multiple studies and countries. They identified a parsimonious model of child age and current size with relatively good predictive accuracy. However, I don't believe the prediction rule should be used in it's current form due to the outcome used the danger of missing treating children who require nutritional supplementation.

The outcome used for prediction in a binary indicatory for a decrease in height-for-age Z-score >= 0.5. A child who fails to gain height by future measurements is of concern, but this outcome also misses children who are already experiencing growth failure, and is vulnerable to regression to the mean effect. The two most important predictors were age and current size, with current size having a positive association with risk of growth faltering. As mentioned in the discussion, there is "the possibility that children need to have high enough HAZ in order to have the potential to falter." Additionally, there may be children with erroneously high height measurements at the first measurement, so that the HAZ change >= 0.5 associated with high baseline HAZ is from measurement-error regression to the mean. I recommend also predicting absolute HAZ (or stunting status) as a secondary outcome and comparing if the important predictors change.

In its current form, the results and conclusions from the results have problematic implications for the treatment of child malnutrition. The conclusion states: "In settings with high mortality and morbidity in early childhood, such tools could represent a cost-effective way to target resources towards those who need it most." If the current CPR was used in a resource-constrained setting, it would recommend that larger children should be prioritized for nutritional supplementation over already stunted children who may have reached their growth faltering floor. In addition, with a sensitivity of 80%, the tool would miss treating a large number of children who would experience growth faltering. The results of the clinical prediction tool need to be presented with care in how it could be used to prioritize treatment without missing treating children who would benefit from nutritional supplementation. Including absolute HAZ as an outcome will help, along with additional discussion of how the CPR fits alongside current treatment recommendations. For example, does this rule indicate treating children who aren't currently treated, or are there children who don't need treatment given current guidelines and the created CPR.

In sum, this is a thorough, well done, clearly explained exercise in creating a clinical prediction tool for predicting child risk of future growth faltering. The writing and motivation is clear, and the methods have applicability far beyond the specific use-case.

Reviewer #2 (Public Review):

The authors investigate whether neuronal activity-regulated transcription factor 4 (NPAS4) in the medial prefrontal cortex (mPFC) is involved in stress-induced effects on neuronal spine synapse density (as a proxy for synaptic activity) and reward behaviors. A major strength of the manuscript is that NPAS4 is shown to be necessary for stress-induced reward deficits and pyramidal neuron spine density. In addition, whole transcriptome analysis of NPAS4 target genes identify a number of genes previously found to be regulated in the postmortem brain of humans with MDD, providing translational relevance to these studies. A weakness is that studies were only performed in male mice so its unclear how generalizable these effects are to females. Despite this, the work will likely impact the field of neuropsychiatry by providing novel information about the molecular and cellular mechanisms in mPFC responsible for stress-induced effects on spines synapses and reward behaviors.

Reviewer #2 (Public Review):

In this paper, Osei-Owusu uses a combination of electrophysiology, structure-guided mutagenesis, and molecular dynamics to understand the desensitization of the proton-activated chloride channel (PAC). They show the extent and rate of desensitization is pH-dependent with lower pH promoting faster and more complete desensitization. They identify multiple residues with important roles in desensitization in two clusters at the extracellular end of TM1 and at the interface between the transmembrane and extracellular domains. Together with previously determined structures, the authors offer a model in which interactions between these residues play key roles in stabilizing the desensitized over the open conformation. This work provides important molecular insight into molecular mechanisms underlying the function of this widely expressed ion channel.

Reviewer #2 (Public Review):

This is a well-thought-out, clearly exposed article. It builds upon the platform of 'original antigenic sin' (OAS), a notion first developed from studying individuals infected with influenza. According to OAS, the initial infection will set the dominant immune response targets (antigens) that immune cells will recognize, such that infection with a related strain will cause a strong response focused mainly against the initially infecting strain, that then goes on to protect against the new-infecting strain. This study builds off this idea, showing that as strains become increasingly antigenically distant as inferred by the time between strain appearance, the cross-protection can drop to a point where it needs to be invigorated with a potentially new response. The potential biological mechanisms behind this aren't discussed, but a model is built that conveys the potential for 'relative risk' of an individual over the course of the life, based essentially on when one was born.

The basic premise was to measure from serum influenza haemagglutinin-inhibition (HI) titers of 21 strains of influenza A (H3N2) - related strains causing disease at various times over a period of some 40 years- from a diverse set of ≈800 participants of various ages, at two time points, spaced 2 yr apart. The authors then calculated the HI titer for the 21 strains for each individual. From this, each participant's age, their age at the time of a strain's development, and when a strain emerged were used to assess whether there was periodicity to immune responses by performing a splined Fourier transform for each individual and then examining the composite pattern across time for HI titers. The authors propose that on average there is a 24-year periodicity to immune responses to influenza strains, such that after the initial infection, cross-reactivity reduces to the point where it may be less meaningful for protection over around 24-year, and suggests activation of a 'new' immune response might be required to control the more distant strain involved in the response at that time. The periodicity was longer than would be predicted if age were not a factor involved in the HI titer patterns across time. Further, variability in the periodicity was shown to involve broad cross-reactivity between strains and narrow cross-reactivity in more highly-related (closer in time) strains, individual HI titer, and periodic population fluctuations. In the literature, viral strains are estimated to mutate to the point of losing 50% cross-reactivity with a T1/2 of approximately 2.5 yr, which would make the inferred lifespan plausible but perhaps surprisingly long, implying there are immune feedback parameters that influence periodicity. The authors also use an independent cohort of approximately 150 individuals from a separate, published, study to validate some findings revealed in the primary data set.

Strengths: Overall, the study is well executed and the patterns that are visually apparent in Figure 1A (the 'raw' data) are built on to inform a model of the potential breadth of cross-reactivity in a given individual at any given time after birth, integrated with the influenza strains to which they are most likely to have been first exposed. It is a complex thing to make sense of data involving many individuals who could be infected or vaccinated at any and variable points in time over the course of their life, but the authors derive a model that probabilistically accounts for possible infection events, so controls for this nicely, or at least to a degree that is practicable.

Questions related to the main limitation: The level of math in this paper makes it hard for a basic biologist to critique the approach, but the argued points are intriguing. Foremost, in the final part of the paper the authors move from building a model to testing its potential to predict HI titers in the final quarter strains of the study period, placing individuals into one of four phases: I) early increasing to high titer response, II) waning response phase where they are returning back to the average population-level response against a strain, III) sub-par response against a strain and then reinitiation of HI titers in phase IV. Pleasingly this shows a good correlation between individuals' ages and their predicted phase. However, while the fit predicts phase well in Fig 4C and 4D, it looks to perform less adequately in Fig 4B.

Q1: Why is this?

Another point for consideration is that the time between samplings (2010-2012) is comparatively short, given a 24-yr predicted periodicity. Q2: What would happen to the predictions if the periodicity were 35-yr or 6-yr? Would the model fail to call individuals accurately in these cases?

Q3: Similarly, if the samples were taken further apart, would the model still be effective at predicting phase?

Reviewer #2 (Public Review):

In their manuscript titled "Feature detecting columnar neurons mediate object tracking saccades in Drosophila", Frighetto & Frye study the effect manipulating T3 neurons has on tethered flight saccades. The authors first characterize the responses of T3 neurons to simple visual stimuli, and then manipulate T3 cells (with both Kir2.1 and CsCrimson) and study the effects on the fly's tethered flight behavior, focusing on different types of sharp turns (saccades). Finally, the authors suggest an integrate and fire model to explain how an array of T3-like neurons can produce some of the recorded behavior.

The authors study the elementary, yet challenging, computation of object discrimination. They hone in on a cell type that most likely plays an important role in the circuit. However, the authors do not sufficiently clarify the framework in which they conceptualize T3's role in object discrimination, neither when discussing it in the introduction/discussion nor when explaining experimental results. The authors present the work in comparison to T4/T5 cells. However, T4/T5 cells have been shown to be both local motion detectors and the main cell types to compute motion in the fly's eye. Downstream neurons integrate over these local units to detect different patterns of global and local motion (Authors should cite Krapp 1996 Nature). Are the authors suggesting that T3 neurons perform a similar function only as local object detectors? That is a bold claim that will need to be supported with more experimental results and reconciled with previous results. We already know of other Lobula Columnar neurons (LCs) that respond to different sizes, some even smaller than the optimal T3 stimulus (e.g. Klapoetke 2022 Neuron) and we know of LCs that respond to small objects that do not receive major inputs from T3 cells (e.g. Hindmarsh 2021 Nature).

These differences between T4/T5 cells and T3s also make interpreting the experimental manipulations more challenging. When hyperpolarizing T4/T5 or 'blinding' them with CsCrimson activation, the visual motion circuit is severely disrupted. However, the same cannot be said about inactivating/blinding T3 neurons and the object detection circuit (if it is indeed a single circuit). The authors are justified in deducing a connection between blocking T3 neurons and a reduction in bar tracking, but generalizing the results to object detection requires more experiments and clarifications.

When framing the manuscript in the object detection framework, previous results regarding the definition of an object should also be addressed. Maimon Curr. Biol. 2008 and work from their own lab (Mongeau, 2019) have already shown that tethered flies respond differently to bars and small objects (fixating on the former while anti-fixating on the latter). Previous work has also shown that T3 neurons respond strongly to small objects and suppress responses to long bars (Tanaka Curr. Biol. 2020). Since all the behavioral experiments in the current manuscript and all the visual stimuli are full arena-length bars, it is impossible to tell whether the T3 results generalize to small objects and even how to reconcile the stronger response to small objects with the role ascribed to T3 cells in generating behavioral responses to long bars.

Finally, the authors propose a model for a hypothetical neuron downstream of T3 that would integrate over several T3s and generate saccades. However, given the current knowledge level in the fly vision field, the model should either be grounded more in actual circuit connectivity or produce testable predictions that would guide further research.

The authors should decide whether they would like to address these concerns with more specific experiments that would shed light on the role T3 has to play under different conditions and different definitions of a visual object, or whether they would prefer to limit the scope of their claims.

Reviewer #2 (Public Review):

The burden of cervical cancer worldwide is well recognized. While prevention strategies, including vaccination against human papillomavirus (HPV), cervical cancer screening, and pre-cancer treatment, can reduce the burden of cervical cancer, access to these measures is still limited, especially in low- and middle-income countries. Since the impact of prevention strategies is heavily dependent on the disease's burden on a particular population, we need to know the latter to assess the impact of these context-specific prevention strategies.

However, epidemiological data on cervical cancer are not always available for all geographical areas. This paper uses India as a case study to propose a framework called "Footprinting" to comprehensively evaluate the burden of cervical cancer. The authors applied a three-step analytical strategy to impute cervical cancer epidemiological data in states where this information was unavailable using data from cervical cancer incidence, HPV prevalence, and sexual behaviour from other regions. The findings suggest a high and low incidence of cervical cancer incidence in different parts of India; all Indian states with missing data were classified as low incidence.

The proposed analytical strategy presents an important solution for imputing data from geographic areas of a country where data are missing.

One conceptual limitation of this work is the lack of explanation or evidence that sexual behaviour can be used to approximate cervical cancer and/or HPV rates. Also, full information on the three main indicators is only available in two states. This is used to impute the values for the other states. Moreover, the available data used in this study also present some limitations; for example, cervical cancer incidence data were from 2012 to 2016, while sex behaviour data were from 2006. This large gap is likely to have a significant cohort effect, especially given changes in sexual norms in Western countries over the last few decades, which may have gradually influenced other countries, especially in this age of the internet and social media. Finally, it would be interesting to validate this methodology to confirm its utility.

The proposed framework's strength is difficult to evaluate because the steps and justification for the model variables were not clearly presented, nor were the models validated. Based on the authors' interpretation of the framework findings, this framework may help extrapolate data from one country to another. I'm curious as to whether this framework could be applied across states and countries.

Reviewer #2 (Public Review):

The objective of this work by Masschelin et al. is to investigate the physiological relevance of flavin adenine dinucleotide (FAD). In particular, FAD supports the activity of flavoproteins involved in the production of cellular energy. Mutations in genes encoding flavoproteins often are associated with inborn errors of metabolism (IEMs), thus the clinical interest in investigating in more depth the physiological role of FAD. In this study, the authors first subjected male mice to a vitamin B12 deficient diet (B2D), demonstrating that loss of B12 replicates the phenotypes often observed with IEMs, including loss of body weight, hypoglycemia, and fatty liver. Using a combination of metabolomic phenotyping, transcriptomic analyses, and pharmacology (treatment with fenofibrate, a PPARa agonist), the authors then reach the general conclusion that activation of the nuclear receptor PPARa can rescue the B2D phenotypes, thus revealing that PPARa directly controls the metabolic responses to FAD availability. Although the phenotypic analysis of the mice subjected to B2D increases our knowledge of the physiological impact of depleting the FAD pools on global energy metabolism, not all conclusions and statements made by the authors are totally supported by the data. In particular, the study is overall too descriptive and lacks mechanistic insights. While PPARa is likely an important player in the metabolic response to FAD availability, the molecular details on how FAD controls the activity of PPARa either directly or indirectly are entirely missing. Therefore, the authors are encouraged to directly assess whether B2D directly influences PPARa activity on the genes identified in the study, perform rescue experiments in the liver of PPARa KO mice and explore the possibility that other factors (including nuclear receptors) also participate in the response to B12 deficiency and diminished FAD pools.

Reviewer #2 (Public Review):

This is a nice study that uses cutting-edge MRI measurements in the context of a carefully designed visual experiment. The data would seem to be of high quality and in general, the approach is promising for opening up avenues for non-invasive measurements of cortical myelination.

Unfortunately, this particular study seems to fall into an unhappy middle ground in terms of the conclusions that can be drawn: the relaxometry measures lack the specificity to be considered "ground truth", while the authors claim that the literature lacks consensus regarding the structures that are being studied. The authors propose that their results resolve whether or not stripes differ in their patterns of myelination, but R1 lacks the specificity to do this. While myelin is a primary driver of relaxation times in cortex, relaxometry cannot be considered to be specific to myelin. It is possible that the small observed changes in R1 are driven by myelin, but they could also reflect other tissue constituents, particularly given the small observed effect sizes. If the literature was clear on the pattern of myelination across stripes, this study could confirm that R1 measurements are sensitive to and consistent with this pattern. But the authors present the work as resolving the question of how myelination differs between stripes, which over-reaches what is possible with this method. As it stands, the measured differences in R1 between functionally-defined cortical regions are interesting, but require further validation (e.g., using invasive myelin staining).

Moreover, the results make clear that R1 differences are not sufficiently strong to provide an independent measure of this structure (e.g., for segmentation of stripe). As such, one would still require fMRI to localise stripes, making it unclear what role R1 measures would play in future studies.

The Introduction concludes with the statement that "Whereas recent studies have explored cortical myelination ... using non-quantitative, weighted MR images... we showed for the first time myelination differences using MRI on a quantitative basis". As written, this sentence implies that others have demonstrated that simpler non-quantitative imaging can achieve the same aims as qMRI. Simply showing that a given method is able to achieve an aim would not be sufficient: the authors should demonstrate that this constitutes an important advance.

The study includes a very small number of participants (n=4). The advantage of non-invasive in-vivo measurements, despite the fact that they are indirect measures, should be that one can study a reasonable number of subjects. So this low n seems to undermine that point. I rarely suggest additional data collection, but I do feel that a few more subjects would shore up the study's impact.

The paper overstates what can be concluded in a number of places. For example, the paper suggests that R1 and R2* are highly-specific to myelin in a number of places. For example, on p7 the text reads" "We tested whether different stripe types are differentially myelinated by comparing R1 and R2*..." Relaxation times lack the specificity to definitively attribute these changes purely to myelin. Similarly, on p11: "Our study showed that pale stripes which exhibit lower oxidative metabolic activity according to staining with CO are stronger myelinated than surrounding gray matter in V2." This implies that the study directly links CO staining to myelination. In addition to using non-specific estimates of myelination, the study does not actually measure CO.

I'm confused by the analysis in Figure 5. I can appreciate why the authors are keen to present a "tripartite" analysis (thick, thin, and pale stripes). But I find the gray curves confusing. As I understand it, the gray curves as generated include both the stripe of interest (red or blue plots) and the pale stripes. Why not just generate a three-way classification? Generating these plots in effect has already required hard classification of thin and thick stripes, so it is odd to create the gray plots, which mix two types of stripes. Alternatively, could you explicitly model the partial volume for a given cortical location (e.g., under the assumption that partial volume of thick and thin strips is indicated by the z-score) for the corresponding functional contrast? One could then estimate the relaxation times as a simple weighted sum of stripe-wise R1 or R2.

Reviewer #2 (Public Review):

This paper is a technical tour de force and provides interesting results. This group has indeed contributed to the understanding of membrane potential and firing dynamics of different cortical neuron subclasses during sensation in various previous papers. Yet, the paper falls short in providing a cohesive conclusion and interpretation of their results on pyramidal neurons, PV, SST, and VIP cells in response to free whisking and active touch at different cortical depths. The authors clearly claim that this manuscript aims to extend the current knowledge by investigating Vm dynamics of pyramidal neurons and various GABAergic subtypes across a greater range of cortical depths. The major shortcoming of this paper is indeed a lack of a clear conclusion or picture of how different cortical neuron types are engaged by different states. Overall, I struggle to find a novel message emerging from the present manuscript that hasn't already been described by the same lab. And this is a pity, as the experiments are of the highest quality and the data is definitely hard-won.

Reviewer #2 (Public Review):

Proton-activated chloride channel (PAC or ASOR) is a newly discovered anion channel which has a broad tissue expression and is implicated in important physiological processes, such as regulation of endosomal acidification and macropinocytosis. PAC is also implicated in pathological conditions related to acidosis on the plasma membrane. Since its discovery and initial characterization, several structures were solved in resting, activated and desensitized states, revealing an overall channel architecture and its mechanism of action. However, little is known about modulation of PAC channel by endogenous molecules. In the present manuscript, the authors sought to explore the modulation of PAC by lipids, particularly by PIP2, as this lipid is known to modulate numerous unrelated membrane proteins.

The major strength of the manuscript is the variety of approaches which the authors implement to characterize the mechanism of modulation of PAC by PIP2. Firstly, the authors demonstrate that PIP2 inhibits PAC channel if applied extracellularly. Furthermore, the authors demonstrate that PIP2 acts on the activated/poised towards desensitization, and not on the resting state of the channel. To explore the effect further, the authors tested various PIP molecules, varying in the number of phosphates in the inositol headgroup, and the length of acyl chains. The inhibition of PAC was more potent with the increase of the number of phosphates, and with the lengthening of acyl chains. The lipid chain without inositol, or the inositol without acyl chains, were not as potent in inhibiting PAC. The authors conclude that inositol headgroup together with acyl chains of at least 8 carbons in length are both required to potently inhibit PAC.

To investigate the potential PIP2 binding site, the authors proceeded to solve the structure of PAC in complex with PIP2. Surprisingly, a density representing a putative PIP2 molecule is found on the extracellular side of the protein. This is a rather unusual finding, given that PIP2 is mostly localized to the inner leaflet of the plasma membrane. To further confirm the binding of PIP2 molecule to this site, the authors mutate the residues interacting with PIP2 molecule in their structure, and observe the decrease in inhibition of the channel by PIP2. Furthermore, the authors observe that these residues are not conserved in all PAC homologs. D. rerio PAC channel does not have these residues and is not inhibited by PIP2 as potently as the human homolog (hPAC). Introducing equivalent residues in D. rerio PAC channel endowed it with modulation by PIP2, similar to hPAC, further strengthening the conclusion that the identified site indeed binds PIP2.

Overall, the authors succeeded in identifying and characterizing an endogenous molecule with the potential to modulate PAC channel. The present study is the first case of identifying a modulator, characterizing its binding site and mechanism of action on PAC channel. This opens new exciting avenues for structure-guided drug design for this newly-discovered ion channel. However, the localization of the PIP2 binding site to the outer membrane leaflet is quite unexpected, and it is unclear if PAC could be modulated by PIP2 in a physiological context and whether this would be mediated by another lipid transporter. The work will be of interest to ion channel field and a broader membrane protein community with the emphasis on lipid modulation of membrane proteins.

Reviewer #2 (Public Review):

I would like to congratulate the authors for testing the hypothesis that the gut microbiome from animals that lack myostatin is sufficient to improve muscle-related measures (except treadmill running time). Subsequent experiments should examine if the identified bacteria are sufficient, on their own, to impact muscle, which may open the field to muscle-improving probiotics. Alternatively, data for the SCFA, valerate, may foster approaches aimed at improving muscle with SCFA supplementation. RCTs are needed to test these hypotheses.

Strengths include a translational approach, including findings in pigs, in colonized mice, and in cells.

Weaknesses include the need to normalize muscle-related measures to body weight. Is muscle mass increased, for example, when divided by body weight? If not it would argue against the role of fecal transplantation in increasing muscle mass from myostatin KO pigs.

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

Reviewer #2 (Public Review):

This paper reports a novel measure of biological age derived from machine-learning analysis of retinal imaging data with chronological age as the criterion measure. The resulting algorithm is impressive. Not only can the retinal image data accurately predict chronological age in the training data and record changes over short time intervals, but it also proves accurate in independent test data and appears to contain information related to mortality risk. In addition, the authors report a GWAS of the new measure.

I would like to see a bit more validation data in the UKB - how does EyeAge relate to (a) tests of visual acuity - e.g. does it explain aging-related differences? (b) measures of morbidity and disability - e.g. how is EyeAge Accel associated with at least some of the counts of chronic diseases, self-reported physical limitations, tests of physical performance, measures of fluid intelligence?

But overall, this is a very strong report of an exciting new biomarker of aging. It was unclear to me whether the algorithm to compute the measure would be publicly available. The authors should clarify.

Reviewer #2 (Public Review):

The paper by Ben Yaakov et al. describe a single cell analysis of the mammalian ovary in young, adult and old mice. In comparison with previous studies that used single cell RNAseq to characterize the heterogeneity of cell types in the ovary, this study focuses only on immune cells resulting in much better coverage to characterize the changes that these cells undergo as a function of age. The paper provides a useful dataset and informative data analysis with interesting findings including the increases in DNT cells in the ovary of old mice. Some discussion on how the presented results might be related to reduced fertility with age would be good to tie the results back to the original questions with which the authors start their paper.

Reviewer #2 (Public Review):

Zivanov et al. present a new approach for multi-particle averaging from cryo-electron tomography data. They propose that refining directly against 2D tilt series images instead of the traditional reconstructed 3D subtomograms would simplify and improve structure determination. This would represent the experimental data more faithfully than traditional subtomogram averaging and circumvents the need for missing wedge correction. The authors describe a data structure termed 'pseudosubtomograms' where the tilt images are represented as their Fourier transform pre-multiplied with the CTF, accompanied by an array describing how often each 3D-voxel has been observed and the sum of the squared CTF. They then present a new regularized likelihood target function for cryo-ET particle alignment which uses the pseudosubtomograms data structure. This approach is implemented within the general RELION refinement framework and allows for the use of pseudosubtomograms for 3D classification, initial model generation, and 3D refinement.

The authors also introduce methods for refining optical and geometrical parameters in the tilt series taking advantage of the average map obtained after 3D refinement. This allows for more accurate tilt series alignment, per-particle motion tracking, and calculation of per-particle CTF. They propose that iteratively refining these parameters, extracting new pseudosubtomograms, and realigning the particles should lead to more accurate structure determination. The methods are validated using three different datasets, and the authors show that the iterative refinement within their framework increases the resolution of the 3D reconstruction and that the resulting maps are resolved to the same or better resolution than previously published methods.

The introduction of a more direct representation of the 2D tilt series images is a novel approach to subtomogram averaging, and the authors show that it is as good or better than current approaches. Comparing the subtomogram average to the tilt series to correct for optical and geometrical parameters of the data has already been implemented in the program M. Here, the authors show that their algorithms can reach the same resolution as M for the HIV immature capsid, but discuss that M might be superior at very high resolution, as it models beam-induced rotation of particles. Nevertheless, the new approaches are implemented in a single framework - the popular open-source software package RELION - thereby greatly facilitating their accessibility to uses. This is a very welcome contribution and development in the field.

Reviewer #2 (Public Review):

In this manuscript, Ilmonen H. et al explored potential crosstalk between endothelial cells and fibroblasts in a context of sporadic vascular malformation (venous malformation and angiomatoses of soft tissue). With a high level of evidence, they found that mutated endothelial cells secrete TGFA that will activate surrounding fibroblasts, leading in turn to VEGFA secretion that will stimulate endothelial cell sprouting and vascular malformation development.

Experiments are well-designed and support their hypothesis.

Some controls are missing, particularly in Fig. 2. Indeed, it is mandatory to provide data from healthy skin biopsies (that are available in many laboratories): TGFa, CD31, P-EGFR staining.

Reviewer #2 (Public Review):

This study set out to explore the nature of a previously described non-competitive and selective inhibitor of the human glutamate transporter, EAAT1 and to explore if this mechanism was conserved across the glutamate transporter family. The non-competitive nature of UCHPH-101 inhibition of EAAT1 has previously been demonstrated with both functional analysis and structures of EAAT1. Here, the authors use detailed electrophysiology analysis to confirm this mechanism of inhibition and to demonstrate that the inhibitor slows the steps of the transport cycle associated with substrate translocation, rather than substrate or sodium ion binding. These findings agree with previous studies that have shown that the compound binds at the interface of the transport and scaffold domains in EAAT1, two domains that are required to move relative to each other for the transport process to occur. UCPH-101 also prevents the transporter from entering an anion-conducting state, which agrees with a recent structure and MD simulations of EAAT1 that demonstrate movements of the transport domain relative to the scaffold domain are required for the EAAT1 to move into the anion-conducting state and support the mechanism of UCPH-101 inhibition confirmed in this study (PMID: 35192345; PMID: 33597752).

While UCPH-101 has been shown to be selective for EAAT1 over other human glutamate transporter subtypes (notably EAAT2 and EAAT3), Dong et al., show that this inhibitor can also reduce transport by another member of the SLC1A family, a neutral amino acid exchanger, ASCT2. Using MD simulations and functional analysis, they show that UCPH-101 acts as a partial, low-affinity inhibitor of ASCT2 and identify two amino acid residues in the binding site that appear to be responsible for the different affinities for EAAT1 and ASCT2. Indeed, when these two residues are changed to the corresponding residues in EAAT1, UCPH-101 becomes a full inhibitor of ASCT2 with an increased affinity.

ASCT2 is a neutral amino acid transporter that can transport glutamine and it is known to be upregulated in several cancers. Thus, finding new compounds and novel ways to inhibit ASCT2 is worthy of investigation. In the last section of this study, the authors conduct a virtual screen of 3.8 million compounds to identify other compounds that could bind to this allosteric site in ASCT2. One compound was identified, and while it had relative low affinity it provides the basis for further exploration of this site.

Reviewer #2 (Public Review):

In this work, the authors aim "to assess whether the relationship between neural activity and hemodynamic responses is present" "before the time of normal birth". In other words, they aim at showing that neurovascular coupling is present before term-equivalent gestational age. They use simultaneous EEG and fMRI in preterm infants presented with tactile stimuli.

Neuroimaging methods and stimulation methods are sound and rely on previously published works from the same group using neonatal MRI during somatosensory stimulation. The novelty resides in the use of simultaneous EEG to measure neuronal activity simultaneously with BOLD.

Methodological weaknesses are related to:

- Participant selection and characterization: there is a large variability in gestational age at birth, from very preterm (29 weeks) to late preterm (35 weeks) infants, which produces a large variability in chronological age at measurement (2 to 26 days). Considering how physiology and brain structure change dramatically with these factors, such variability seems an important bias. As stated in the introduction "In the time leading up to full-term human birth, rapid maturational changes are taking place across nearly all of the components which both relate to and occur within the neurovascular coupling cascade". There may be an effective neurovascular coupling in a neonate born at 35 weeks and tested at 2 days, and a very atypical or ineffective neurovascular coupling in an infant born at 29 weeks and tested after a month of intensive care, invasive respiratory support, and medication. This bias is also present in EEG analysis since "microstate basis vectors were derived from periods within the grand average signal that were topographically consistent across trials/subjects": any variability due to prematurity/NICU time is lost with this process.

- Not accounting for sleep states. During sleep, preterm infants alternate between slow and agitated sleep states, the pattern of state cycles changing with gestational age. Although the authors used EEG, they do not report looking for sleep states. Sleep state changes during stimulation would likely affect strongly EEG microstates sequence, duration, and power, as well as BOLD amplitude and distribution (ipsi vs. contralateral). This would be easy to verify and would allow a deeper understanding of the data, such as the variability of EEG and BOLD responses in each participant and among participants.

The main issue with the manuscript is the discrepancy between the stated aims ("to assess whether the relationship between neural activity and hemodynamic responses is present") and the literature available on the topic, on one hand, and between the stated aims and the actual work that was performed and discussed in the manuscript, on the other hand.

Aims vs. literature: The presence of a neurovascular coupling before term-equivalent gestational age has already been shown years ago, including by this group. For example, in: Arichi, T., et al. (2010). Somatosensory cortical activation identified by functional MRI in preterm and term infants. NeuroImage, 49(3), 2063-2071, where the following sentence begins the Conclusion "This is the first description of well-localised somatosensory cortical activation in the premature brain using a fully automated and programmable passive motor stimulus. Predominately positive BOLD signal change during stimulation was seen".

Or in:

Arichi, T., et al. (2012). Development of BOLD signal hemodynamic responses in the human brain. NeuroImage, 63, 663-673.

And by other groups using fMRI:

Heep, A., Scheef, L., Jankowski, J., Born, M., Zimmermann, N., Sival, D., et al. (2009). Functional magnetic resonance imaging of the sensorimotor system in preterm infants. Pediatrics, 123(1), 294-300.

Other examples of neurovascular coupling before term can be found with auditory-evoked BOLD responses in fetuses:

Jardri, R., et al. (2008). Fetal cortical activation to sound at 33 weeks of gestation: a functional MRI study. NeuroImage, 42(1), 10-18.<br /> but also, with various types of stimuli using fNIRS, for example:<br /> Mahmoudzadeh, M., et al. (2013). Syllabic discrimination in premature human infants prior to complete formation of cortical layers. Proceedings of the National Academy of Sciences, 110(12), 4846-4851.<br /> And:<br /> Roche-Labarbe, N., et al. (2014). Somatosensory evoked changes in cerebral oxygen consumption measured non-invasively in premature neonates. NeuroImage, 85, 1-8.<br /> Including simultaneous EEG and fNIRS :<br /> Roche-Labarbe, N. et al., 2007. Coupled oxygenation oscillation measured by NIRS and intermittent cerebral activation on EEG in premature infants. NeuroImage, 36(3), pp.718-727.

Be it in the Introduction or the Discussion, the authors only consider MRI literature whereas neurovascular coupling has been described and used for cognitive studies in premature neonates using fNIRS. There is no reason to restrict oneself to one technology when discussing fundamental physiological or cognitive processes.

Aims vs. actual work: The work that was actually performed is to measure EEG microstates' duration and power following tactile stimulation and to compare BOLD amplitude with these measures. The question being answered is whether the relationship that exists between microstates duration and BOLD amplitude in adults can also be observed in preterm infants. This in itself is an interesting purpose and should be stated as such in the Abstract and Introduction.

The Introduction is short and lacking in essential information. A review of microstates, what they are and what they mean, and how they are described in premature infants (particularly sensory-evoked microstates), is necessary. Previous studies of neurovascular coupling in preterm infants using evoked potentials, or no EEG at all when measuring the hemodynamic (fMRI or fNIRS) response associated with sensory stimuli. The introduction should argue why microstates would be more meaningful than SEP for EEG-fMRI studies, and what relationship with hemodynamics is expected based on previous studies with older participants. A comprehensive review of neurovascular coupling in preterm neonates, including non-MRI studies, is also necessary. The sentence "Here we test the hypothesis that despite the apparent immaturity of the underlying physiology, neurovascular coupling is functional before the normal time of birth." should be replaced by something along the lines of "Here we test whether the relationship between EEG microstates and neurovascular response is similar in premature infants with adults". Then the experimental contribution will make sense and the Discussion can focus on what it entails for understanding neurovascular coupling that amplitude is related to the duration, not power, of EEG microstates.

A Discussion (distinct from the Results) of the scientific and clinical relevance is currently lacking and it is difficult to assess the significance of the experimental contribution. An interesting discussion of microstates in the preterm brain is presented, but because the topic of microstates' relevance in neonates was not mentioned in the Introduction, it is confusing to read results such as "the observed composite progression of microstates indicates that the preterm brain is already capable of multi-level local sensory elaboration in the primary sensorimotor cortices." that does not correspond to any previously formulated hypothesis.

In the results, the authors should report if microstate duration varies among repeated identical stimuli in each child. The authors may look at this variability in terms of gestational age at birth (for example, in the participants who were born the earliest and have stayed the longest in the NICU, are microstates durations after a stimulus more variable than in the late-preterm participants?). The method for microstate analysis does not give clear information to the reader unfamiliar with Ragu other than the fact that one duration value was calculated for each participant. However, it would be informative to see some sort of dispersion range for both Mean BOLD and microstate duration values. It would be interesting to regress this information with gestational age at birth (or chronological age at scan) and sleep state.

After these changes have been made, I expect that the authors may find a more relevant title for their manuscript. "Neurophysiological basis of hemodynamic responses" does not give a precise idea of the experimental findings. Similarly, the abstract should be adjusted by removing sentences like "These results suggest that effective neurovascular coupling is present in the human brain even before the normal time of birth", a long-known fact, and detailing instead "a complex relationship between EEG and fMRI signals underpinned by patterns of activity across distinct neural ensembles."

Details of the stimulation sequence are unclear:

- Why were stimuli varying in duration from 7.5 to 10.5 seconds? The results report "the median BOLD hemodynamic response peaked at 14 seconds after stimulus onset": was it calculated regardless of stimulus duration? It is unlikely that the peak was reached after the same delay for 7 and 10 s stim. Was this accounted for in the MRI analysis?<br /> - There was a maximum of 24 epochs per participant, but how many epochs were kept for each participant after artifact rejection? How were distributed the 76 epochs remaining for analysis, among the participants?

Reviewer #2 (Public Review):

The manuscript by Shepard et al. expands on prior recent publications by the group which demonstrated that silencing long ascending propriospinal neurons (LAPNs) disrupts left-right coordination in certain contexts in uninjured rats but improves locomotion following thoracic contusion. Here, the same reversible silencing strategy is used but instead targeted to the long descending propriospinal neurons (LDPNs). Interlimb coordination and several other locomotor metrics are examined in both uninjured and SCI conditions. The effects of LDPN silencing were quite similar to those of LAPN silencing with a few notable differences. In intact rats, the deficits were observed following silencing on both high and low-friction surfaces. The effects are stronger during the second Dox administration than during the first in intact, and possibly the opposite after SCI. Also, the reversal of deficits by silencing after SCI was more modest.

The major strengths of the study are the methodology and research design employed. The reversible silencing of a specific population of neurons identified by the locations of their somata and terminals is powerful. This also allowed for comparisons of pre-/post-silencing in the same subject both in uninjured and SCI conditions. The primary shortcoming of the study is the lack of histological analysis to demonstrate the degree of loss and/or whether there is any selectivity or bias towards functional subclasses of neurons that are shown to be LDPNs, even at the level of ipsilateral/contralateral and transmitter phenotype.

The presented data support the major conclusions of the study. It is interesting that silencing the LDPNs or the LAPNs, disrupting communication in either direction, has similar effects and that these effects are predominantly related to cross-cord coordination at each girdle. Additionally, the long propriospinal neurons, LDPNs in particular, are thought to be potential targets for relays and adaptive plasticity after spinal cord injury. However, their silencing after SCI leads to locomotor improvements rather than exacerbated of dysfunction. Whether this is due to an imbalance of spared projection neurons, maladaptive plasticity/sprouting, or other mechanism is of interest for future studies targeting spared projections to enhance functional recovery.

Reviewer #2 (Public Review):

The manuscript by Zeng and colleagues aims to investigate how neural representations of sensory cues in two modalities (visual and vestibular) change when conflicts are introduced between the cues. The manuscript convincingly demonstrates that this recalibration process differs between areas MSTd (a multisensory region), where sensory responses recalibrated differently for visual and vestibular cues, following each modality's conflict, and area VIP ( a higher-level region), where responses follow the vestibular cue. More limited insights are present for area PIVC, where visual responses are limited.

The analyses generally support the conclusions of the authors, but I have two major suggestions to strengthen the statistical robustness of the manuscript:

1) The analysis about the lack of visual recalibration in area PIVC would have been more convincing if the authors had used Bayesian statistics instead of regular t tests. In this way it would have been possible to estimate if the lack of visual recalibration in this area, for those few neurons that show visual tuning, can be taken as evidence for the absence of an effect or not. In the absence of this additional analysis, it is in fact difficult to properly interpret the results about area PIVC. Is PIVC more in line with MSTd, in view of the lack of visual responses? Or is there actually no visual recalibration, in contrast to both MSTd and VIP?

2) For all statistical analyses, multi-level statistics would have been more appropriate than simple t-tests. In fact, since recordings come from few subjects, which in turn have relatively few recording sessions, there is a risk that the results are influenced by one subject and do not represent the full population. Admittedly, this is unlikely in view of the apparently large effect size and low p values. Nonetheless, a more appropriate statistical analysis would make the results more robust and convincing.

Once these issues are addressed, I believe that the manuscript would provide relevant evidence supporting the hypothesis that multisensory processing in the cortex is an area-specific phenomenon, and that effects observed in one area cannot be simply expected to operate elsewhere. This will therefore elucidate the mechanisms of multimodal plasticity.

Reviewer #2 (Public Review):

Previous work from the Brown lab showed that SM undergoes proteasomal dependent processing of its N-terminal regulatory region to generate truncSM, which retains catalytic activity. In this manuscript, Hudson and colleagues show that the generation of truncSM correlates with hypoxic conditions. This process appears to be independent of the transcription factor HIF1α and proline hydroxylation. Instead, their data suggest that hypoxia-induced truncSm results from 1) upregulation of the E3 Ub ligase MARCH; 2) accumulation of squalene, the substrate for SM. Finally, the authors have linked these observations to pathologies, such as hypoxic endometrial cancer tissues, arguing that overactive truncSM may contribute to the growth and survival of malignant cells. Overall, this paper provides some interesting concepts on the regulation of the cholesterol biosynthesis pathway upon low oxygen levels. However, the functional consequences of truncSM accumulation under hypoxia have not been addressed.

Another important open question is the role of squalene in promoting truncSM. Any additional information to address these issues would significantly strengthen this study. The analysis and some of the data on the relative abundance of SM and truncSM could also be improved.

Reviewer #2 (Public Review):

This study investigates how thalamic functional MRI activations change across subjects performing many cognitive tasks. The results reveal localised regions in anterior, medial (and potentially posterior) portions of the thalamus that co-activate most consistently across multiple tasks. The authors then try to link these task hubs to cortical association cortices, first by showing that association cortices are most connected to thalamic task hubs. Second, by showing that thalamic activations can predict

The findings are important, mainly because thalamic fMRI activations are largely ignored by the current literature. The major strengths of the study lie in examining thalamic activations under many cognitive tasks and replicating results across two independent datasets.

The findings of thalamic hubs are compelling. However, this current version of the manuscript could be strengthened by providing better links with the wider literature (e.g. with thalamic resting-state networks). The study also falls short in properly quantifying the similarity of findings across the two independent datasets. The subtle discrepancies between the results of the two datasets throughout the manuscript could point to finer-grained fractionations of the identified thalamic hubs. The least compelling set of results (though not necessarily wrong) is the thalamic prediction of cortical activations. This is because the functional connectivity (FC) matrix used to link the thalamus and cortex was derived from the same data after regressing out task-related variance. However, this process might not be clean enough. A stronger test would utilize an FC matrix derived from an independent dataset.

Reviewer #2 (Public Review):

One major enigma in neurodegeneration is why it tends to start many times in the entorhinal cortex. This paper tries to address this issue, by showing the vulnerability of reelin-positive entorhinal cells to inactivation, thus leading to the compelling idea that neurodegenerative processes are initiated by prolonged brain inactivity in specific brain regions. The paper is straightforward and performs a whole set of experiments to demonstrate the specificity of the effect on these cells, trying to partially decipher the underlying mechanisms which lead to the vulnerability of these specific cells.

The paper performs a series of tests on these cells. First, the chemogenetic silencing of layer 2 entorhinal neurons causes cell death and axonal degeneration. Second, this effect is specific to entorhinal neurons and spares other regions. Third, the effect seems to be mediated by synaptic silencing, in addition to general neuronal inactivity, and finally - the effect seems to be governed by neuronal competition and not by a general non-specific change in neuronal activity levels.

I think the paper is a great first step. In the future, more work will be needed in order to better understand the causes of this vulnerability and to connect this work to the cascade of neurodegeneration leading to the known phenomena associated with AD.

Reviewer #2 (Public Review):

In this study, the authors determine the superior cell killing abilities of KLRK1+ IL7R+ (KILR) CD8+ effector T cells in experimental diabetes and tumor mouse model. They also provide evidence that Tregs suppress the formation of this previously uncharacterized subset of CD8+ effector T cells by limiting IL-2.

Strength and Limitation

This study focuses on the relationship between Tregs and CD8+ T cells. They used different experimental diabetes mouse models to reveal that Tregs suppress the CD8+ effector T cells by limiting IL-2. They also found a unique subset of KLRK1+ IL7R+ (KILR) CD8+ effector T cells with superior cell killing abilities through single-cell sequencing, but killing abilities could be inhibited by Tregs. They also tested their theory in in vivo tumor model. The data, in general, support the conclusions; however, some issues need to be fully addressed, as detailed below.

1. This study used the concentration of urine glucose as the standard for diabetes ({greater than or equal to} 1000 mg/dl for two consecutive days). However, multiple reasons may lead to a high level of urine glucose. As a type I diabetes mouse model, authors could use immunohistological analysis of islet to show the proportion of T cells and islet cells in islet, which can display the geographic distribution of immune cells, severity and histology structure of damaged pancreas islet directly. If possible, different subsets of immune cells, especially CD4 vs CD8+ cells should be stained for their location.

2. This article shows that KILR effector CD8+ T cells have strong cytotoxic properties. However, they do not describe the potential proliferation ability vs apoptosis of this subset from islets.

3. Figure 7 shows that the antitumor efficacy of IL-2 depends on CD8+ T cells. But in this part, there is no data to show the change of KLRK1+ IL7R+ CD8+ effector T cells in tumor tissue. Therefore, the article needs to add more data to verify that IL-2 enhances antitumor ability via KLRK1+ IL7R+ CD8+ effector T cells.

4. It is unclear why the authors chose Dox to combine with IL-2/JES6. The authors should provide a more rational introduction to bridge such a combination. Authors should also explain the reason why there is no antitumor effect of IL-2/JES6 treatment alone.

Reviewer #2 (Public Review):

This paper provides a novel approach to quantifying the tradeoff between energetic optimality during walking and the valuation of time to travel a given distance. Specifically, the authors investigated the relationships between walking speed trajectories, distance traveled, and the valuation of (completion) time. Time has been proposed as a potential factor influencing movement speed, but less is understood about how individuals balance energetic optimality and time constraints during walking. The authors used a simple, sagittal-plane walking model to test competing hypotheses about how individuals optimize gait speed from gait initiation to gait termination. Their approach extends literature in the space by identifying optimal gaits for shorter, partially non-steady speed walking bouts.

The authors successfully evaluated three competing walking objectives (constant acceleration, minimum cost of transport at steady speed, and the energy-time objective), showing that the energy-time objective best matched experimental data in able-bodied adults. Although other candidate objectives may exist, the paper's findings provide a likely-generalizable explanation of how able-bodied humans select movement strategies that encompass studies of steady-speed walking.

Overall, this paper provides a foundation for future studies testing the validity of the energy-time hypothesis for human gait speed selection in able-bodied and patient populations. Extensions of this work to patient populations may explain differences in walking speed during clinical assessments and provide insight into how individual differences in time valuation impact performance on assessments. For example, understanding whether physical capacity or time valuation (or something comparable) better explains individual differences in walking speed may suggest distinct approaches for improving walking speed.

Strengths:<br /> The authors presented a compelling rationale for the tradeoffs between energetic optimality and time and their results provide strong support for a majority of their conclusions. In particular, significant reductions in the variance of experimental speed trajectories provides good support for the scaling of speeds across individuals and the plausibility of the energy-time hypothesis. Comparison to theoretical (model-based) reductions across difference time valuation (cT) parameters would further enhance confidence in the practical significance of the variance reductions. Further, while additional work is needed to determine the range of "normal" valuations of time, the authors present experimental ranges that appear reasonable and are well explained. The computational and analytical methods are rigorous and are supported by the literature. Overall, the paper's conclusions are consistent with experimental and computational results.

The introduction of a model-based analytical approach to quantify the effects of time valuation of walking could generalize to test other cost functions, populations, or locomotion modes. Further, models of varying complexity could be implemented to test more individualized estimates of metabolic cost, ranging from 3D dynamic walking models (Faraji et al., Scientific Reports, 2018) or physiologically-detailed models (Falisse et al., Journal of The Royal Society Interface. 2019). The relatively simple set of analyses used in this paper is consistent with prior literature and should generalize across applications and populations.

The authors justified simplifications in the analysis and addressed major limitations of the paper, such as using a fixed step length in model predictions, using a 2D model, and basing energy estimates on the mechanical work of a simple model. It is unlikely that the paper's conclusions would change given additional model complexity. For example, a 3D walking model would need to control frontal plane stability. However, in able-bodied adults, valuation of frontal-plane stability during normal walking would not likely alter the overall shape of the predicted speed profiles.

Weaknesses:<br /> The primary weakness of this work is that alternative objectives may provide similar speed profiles and thus be plausible objectives for human movement. For example, the authors tested an objective minimizing the steady-speed cost of transport. This cost function is consistent with the literature, but (as predicted) unlikely to explain acceleration and deceleration during gait. An objective more comparable to the energy-time hypothesis would be to minimize the net energy cost over the entire bout, including accelerations and decelerations. This may produce results similar to the energy-time hypothesis. However, a more complex model that incorporates non-mechanical costs (e.g., cost of body weight support) may be needed to test such objectives. Therefore, the energy-time hypothesis should be considered in the context of a simple model that may be incapable of testing certain alternative hypotheses.

An experimental design involving an intervention to perturb the valuation of time would provide stronger support for time being a critical factor influencing gait speed trajectories. The authors noted this limitation as an area of future work.

While the results are compelling, the limited sample size and description of participants limit the obvious generalizability of the results. Older adults tend to have higher metabolic costs of walking than younger adults, which may alter the predicted time-energy relationships (Mian OS, et al., Acta physiologica. 2006). As noted in the introduction, differences in walking speeds have been observed in different living environments. General information on where participants lived (city, small town, etc...) may provide readers with insight into the generalizability of the paper's conclusions. Additionally, the experimental results figures show group-level trends, but individual-specific trends and the existence of exceptional cases are unclear.

The authors' interpretation of clinical utility is vague and should be interpreted with caution. A simple pendulum-based walking model is unlikely to generalize to patient populations, whose gait energetics may involve greater positive and negative mechanical work (Farris et al., 2015; Holt et al., 2000). Additionally, the proposed analytical framework based on mechanical work as a proxy for the metabolic cost may not generalize to patient populations who have heterogeneous musculotendon properties and increased co-contraction (e.g., children with cerebral palsy; Ries et al., 2018). Consequently, the valuation of time for an individual could be incorrectly estimated if the estimates of metabolic cost were inaccurate. Therefore, as the authors noted for their able-bodied participants, more precise measures of metabolic rates will be critical for translating this work into clinical settings.

Reviewer #2 (Public Review):

This paper by Tomanek and Guet investigates the evolutionary dynamics of the very earliest steps in the process of evolution through gene duplication and divergence. They use a cleverly designed experimental system where they can tune the benefit of mutations that cause increased expression of a gene, and where they have reporter genes that can be used to distinguish between promoter up mutations and (most) gene duplications.

The major conclusion is that the dynamics of adaptive gene duplications and adaptive point mutations can be very different in different conditions - In "low demand" conditions, where a single mutation (duplication or snp) is enough to achieve the maximum (for that environment) fitness improvement duplications and promoter mutations acts with negative epistasis and become mutually exclusive. Contrary to previous literature that discusses evolution by duplication - divergence, duplications can thus act to prevent or slow down divergence.

The strengths of the paper: The genetic system is simple but cleverly designed. Using a gene (galK) that made it possible to tune the benefit of increased expression (by varying the amounts of galactose in the growth medium) made it possible to make observations that others have missed.

Possible weakness, which this paper has in common with much of the literature on evolution by duplication-divergence: Duplications are very often very unstable and are lost at rates that exceed their rate of formation. This means that in the absence of selection duplications are usually lost very quickly unless selected for, and all experiments and conclusions are based on stable conditions with a continuous selection that may not reflect a natural situation.

The aims of the paper were achieved and the presented data support the conclusions nicely.

This paper provides evidence that evolution by gene duplication is more complex than how it is usually described. Even if two mutations (e.g. gene duplication and promoter mutations) have additive or positive epistasis on a measurable quantity (be it enzyme kinetics, gene expression levels, or some other observable trait) the mutations could show negative (or even sign?) epistasis on the fitness of an organism. Hopefully, this paper will serve as a reminder of this even outside of the duplication-divergence field.

Reviewer #2 (Public Review):

C-type lectin receptors are well-known for their pathogen recognition and their immunoregulatory properties. However, most C-type lectins also engage host-derived ligands. While many microbial targets have been identified, the characterization of endogenous ligands has so far lagged behind. In this paper, Haji et al. identified human Dectin-1 as a bonafide self-ligand for the platelet-specific C-type lectin receptor CLEC-2.

Strengths:<br /> Haji et al. actually identified the first glycan-dependent C-type lectin - C-type lectin interaction, resulting in a 2-way activation cascade downstream of both the Dectin-1 and CLEC-2 receptors. They performed a highly detailed molecular characterization, revealing both the interacting domains with Dectin-1 as well as the interacting glycan sialylated core 1 ligand. Moreover, the authors provide proof of the functional relevance of the Dectin-1 - CLEC-2 interaction in a mouse model deficient for the CLEC-2 ligand podoplanin, demonstrating that human Dectin-1 can rescue the phenotype observed in these podoplanin KO mice.

Limitations:<br /> The main limitation of this work is the use of Dectin-1 and CLEC-2 transfectants. Glycosylation patterns in transfected 2B4 cells (a T cell line) might not mimic the natural glycosylation pattern on Dectin-1 in vivo. A follow-up study should address which human Dectin-1 positive immune cell subsets are recognized by human CLEC-2 and how human Dectin-1 glycosylation is regulated during immune cell activation and differentiation.<br /> In addition, Dectin-1 polymorphisms have been identified in the human population, which strongly decreases Dectin-1 expression. Yet, these individuals mainly suffer from fungal infections and so far have not been shown to have lymphatic defects. This leaves the actual in vivo role of the human Dectin-1 - CLEC-2 interaction yet to be resolved.

Reviewer #2 (Public Review):

Because individuals in most colonies of eusocial insects (i.e., ants, social bees, social wasps, and termites) cannot directly reproduce, theory suggests that natural selection will shape the behavior and physiology of such individuals to be hyper-sensitive to the needs of their colony. In the context of foraging, an individual should make decisions of how often to search for new food based on the "hunger" of the colony that she belongs to. In fact, in previously published work, the authors of this manuscript have confirmed empirically that the frequency of foraging events for individual workers in colonies of _Camponotus sanctus_ carpenter ants is correlated with the amount of food stored within the collection of ants within the nest -- as the colony "satiated" (i.e., the communal stomach of the average nest ant became full), the foraging frequency would decrease (and vice versa). In that work, the authors showed that an individual's decision to leave a nest to return to foraging was predictable from her own communal stomach ("crop") level and how quickly it was being depleted by nest ants receiving it. From that observation, the authors previously suggested that a cognitive process within each individual ant could monitor these two internal variables (crop level and rate of change) and lead an ant to make a decision as to if and when to leave a nest. In the current work, the authors suggest an alternative mechanism that exports the discrete decision making into the nest cavity itself and only requires an individual forager to adjust her movement pattern based on her current level of crop load. In particular, they use computational and mathematical models to show that spatiotemporal statistics similar to real ants emerge when hypothetical modeled foragers move deeper into a nest when their crop level is above a certain threshold and instead move toward the nest exit when their crop level is below that threshold (leaving the nest when randomly encountering it). This simple crop-based rule does not require estimation of depletion rate nor require an ant to deliberate over when to exit. Foragers in "hungry" colonies have shallow penetration in their nests before turning around and quickly returning to foraging while foragers in "satiated" colonies have deeper penetration and may remain in their nests for long periods of time. This proposed mechanism provides the adaptive foraging patterns observed in real carpenter ants with significantly reduced assumptions about individual cognitive abilities when compared to previous mechanistic explanations of this behavior. Broadly speaking, it (combined with other recent work from these authors and others) helps to demonstrate proof of concept of cognitive hypotheses that are embodied in the physical environment around the individual apparently making the decision.

The movement rule proposed by the authors is elegantly simple and produces trajectories that are, at least to the human eye, a good match to the stereotyped trajectories from real ant colonies in terms of their directionality and duration, and the length of these trajectories is modulated by colony hunger-state in exactly the same way as the real ant trajectories. Although the authors do not provide statistics on multiple runs of the simulation (they provide examples of single runs), they do complement their simulation work with both deterministic and stochastic models of statistics of the modeled paths and show that those statistics have the same qualitative relationship to colony hunger-state as the statistics of the real ants. Consequently, the paper provides a compelling argument via the use of multiple types of models for a novel behavioral rule that answers an important question in collective decision making in confined physical spaces.

Much of the authors' argument rests on trajectories and statistics generated from a two-dimensional computational simulation that may be overly simplistic. The computational model simulates a single forager (as opposed to multiple foragers) arriving to a nest that is partitioned into a grid of squares with an immobile ant in the center of every square. Foragers move in discrete steps from square to square, with the guarantee of an interaction in each step. This "grid world" model of ant nest movement is significantly different than the experience of real foraging ants returning to the nest, and the authors even admit that deviations between the empirical data and the computational model may be due to nest-ant clumping and interaction sparsity in the paths of real ants. Continuous-motion agent-based models are commonly used to investigate collective-motion hypotheses, and so the choice of a grid world model instead seems notable and weakens the authors' arguments. Furthermore, whereas the deterministic mathematical model of grid-world forager trajectories seems too simplistic, the stochastic model buried in the appendix that is meant to validate the deterministic model's results seems to have some potential flaws and is itself not validated experimentally against replicated simulation data. Instead of perfecting these models, the authors could have bolstered their arguments using more familiar approaches from statistical mechanics that might help explain the likely depth an ant "diffuses" into such a nest. In the current form of the manuscript, the mathematical models do not add much beyond the simulation models (and the lack of replication of the simulated data may make some readers wonder if the example trajectories are representative).

There are also a few questionable parameters that the authors have chosen in their model, likely for analytical tractability. For example, the authors assume that at each interaction between a forager and a nest ant, the forager offloads enough food to fill 15% of the crop space remaining in the receiving ant. One can assume that this parameter is something like the 63.21% associated with an exponential time constant or may be based on empirical measurements of transfer in real ants, but the actual justification is not completely clear from the manuscript. Because the mathematical models make predictions that depend upon these parameters, their existence (and plausible values) is itself an important assumption that needs to be defended for the argument to be truly compelling.

Beyond these methodological issues, the behavioral model described by the authors assumes that ants are able to choose a direction toward their nest's entrance at any time. This within-nest path-integration ability does not seem cognitively inexpensive, which narrows the cognitive distance between the behavioral model they propose here and the one they proposed in their prior work and weakens the argument for the relevance of this new model. The authors failed to place their work within the context of other simple cue-based motion-switching behaviors discussed in the literature for other taxa - such as "running" and "tumbling" in E. coli bacteria - but if they had, they might have envisioned an alternative crop-based motion rule that would have the same effect as their current rule (i.e., movement toward the entrance on low crop state) without having to assert that the ant moves directly back toward the entrance.

Focusing on the explanatory power of this model specifically for (some) ants, the authors do not address how to empirically reconcile the ambiguity between the more cognitive mechanisms proposed in their previous work (where ants "decide" to exit a nest) and the current proposal (where the nest cavity "decides" when the ant will exit). For this new hypothesis to be useful, it must be empirically discriminable from the previous hypothesis. At first glance, it is difficult to imagine an experiment that would lead to different predicted behavior from the two different hypotheses. In other words, at the moment, it seems impossible to tell whether the "ant decide" or the "nest decide" model is a better predictor of real ant behavior/cognitive architectures. The lack of discriminability becomes even more problematic when considering that the current version of the model actually increases some cognitive demands by assuming (as described above) that ants keep track of the position of the entrance over the trajectory within the nest.

The arguments in the current form of this manuscript could be strengthened by adding realism, connections to related literature in collective motion and motion ecology, and more general models from statistical mechanics, and it is important for the authors to identify potential ways to empirically discriminate between the model introduced here and the behavioral model suggested in their prior work. That said, the salient features of the basic crop-cue-based two-motion-primitive model proposed by the authors are elegant and novel and help to further demonstrate how cognition can be embodied in the physical spaces it is embedded within. The authors focus on a particular example in ants, but it is easy to imagine extending the same model to a variety of other scales and application spaces. For example, there may be microbiological examples of coordination among collectives where individuals face even more stringent cognitive constraints. Moreover, the same methods might be used to build artificial swarms in engineering contexts that allocate to tasks based on demand without significant communication or sensing requirements. Even in industrial organization, there may be ways to use methods like these to ensure an emergent adaptive re-allocation of human workers to tasks based on need. In general, this manuscript provides a new example of how spatiotemporal properties of decision making long thought to be associated with cognitive processes endogenous to individuals can be alternatively generated by simple cue-based behaviors interacting in a non-trivial environment. This is a relatively new perspective that may be useful in both the analysis of natural systems as well as the design of artificially intelligent systems. With the right framing, the example from this manuscript could be very useful not only to ant biologists but to scientists and engineers interested in collective decision making more broadly.

Reviewer #2 (Public Review):

The authors' paper extends their earlier work based on a 2D model of running stability while negotiating sloped terrain of random variable height, extending from a traditional point mass-spring model (SLIP) but with a moment of inertia about the CoM ([19], Dhawale et al. Roy Soc Open Sci 2019). In this study the authors carry out an experimental study of human subjects running over an experimentally-created undulating terrain surface (0.6 m wide x 24 m long) with a known 3D topography, in which they combine a 3D kinematics analysis of foot movement trajectory and placement relative to the terrain topography and in relation to body CoM (hip) movement; with measurements of ground reaction forces to estimate foot-substrate impulses over a subregion of the terrain, and measurements of the runners' metabolic energetics via a portable runner-carried gas analyzer system.

The authors' findings are generally supported by their results, showing that runners do not appear to rely on visual guidance to select foot placement on undulating terrain (this based on computational Monte Carlo simulations of foot placement probabilities favoring level terrain surfaces) and likely achieve stability while running largely by means of limb joint compliance that passively adjusts to variable foot-ground impulses (based on ground reaction force estimates and a collisional multi-segment limb joint model for which joint compliance was varied). As a result, the authors found no significant increase in the metabolic cost of uneven terrain versus level surface running.

However, whereas the authors motivate their study by its relevance to the evolution of human running ability and persistence hunting, which requires running over uneven natural terrain, a weakness is that their in-depth analysis is heavily focused on the mechanics and resulting energetics of running over undulating terrain in the context of foot placement strategies for maintaining stability and whether this depends on visual guidance of foot placement relative to the terrain. The authors claim surprise (Discussion, l.191-192) that the runners do not appear to rely on visual information about unevenness to guide their footsteps. However, based on the nature of their sloped undulating surface, their results were unsurprising to this reviewer.

The authors' study was also motivated to examine the effect of sloped surfaces on running biomechanics, as previous studies have examined step-like terrain comprised if piecewise level blocks or step height transitions, which the authors (correctly) note represent obstacle negotiation rather than how runners may be challenged by undulating sloping terrain. The authors argue (l. 5-6) that a combination of height and slope variations like a natural undulating terrain will be more challenging than one that involves only step height transitions. However, the basis for this statement is not clear. And, indeed, the results the authors find for humans running over a sloped, undulating terrain (height range ~ 40 mm) shows that a sloped, undulating terrain does not actually present a significant challenge, given that it appears to require little or no visual guidance of foot placement and no significant increase in metabolic energy use. To the contrary, this reviewer would argue that obstacle avoidance is the more challenging feature of natural terrains that must be successfully negotiated, which is a common experience for trail runners. The reviewer, therefore, fully agrees with the authors' conclusion (l. 259-261) "Our data thus suggests that terrain-guided foot placement strategies are not required for stability on gently undulating terrain [compared with obstacle avoidance on more complex terrain]".

The principal novelty and value of the authors' study is the analysis of fore-aft impulse and the role of limb joint compliance for adjusting to changes in fore-aft impulse to favor running stability. The authors' paper suffers from overstating the broader relevance of its findings and by merging methods and discussion with the results that it reports. The methods, themselves, are detailed and thorough in their description, and the authors' modeling approaches appear sound, sophisticated and appropriate for the analyses of foot placement strategies and limb compliance in relation to collisional impulse.

Repeatedly in the Results section, however, these methods are summarized when reporting a result (based on the method) and discussion points are mentioned. Specifically:

l. 66-96 This starting section does not present results per se, but a summary description of experimental methods an analytical approach. Actual results findings are not presented until l. 97.

l. 111-117: This summarizes analytical methods; not results per se.

l. 135-145: Summary of methods/analytical approach continues to be blended in with results in these sections.

l. 169 - Comparison of limb retraction rate on uneven vs level terrain of human subjects here with running birds is fine for discussion but not results per se.

l. 170-171: This is a discussion point, not a result.

l. 187-189: Again, discussion not a result.

A final concern is whether and how the requirement that runners repeatedly decelerate, turn and reaccelerate to run back and forth over the 24 m long uneven and level terrains at 3 m/s affects the metabolic measurements? Running at 3 m/s indicates 8 sec to traverse the runway length and, if adding another second for turning to reverse direction and run back = 9 s, this would indicate for a 8 to 10 min metabolic running trial ~53 to 67 turns per trial. Presumably, these would have an effect on running cost.

Reviewer #2 (Public Review):

Vries et al. investigated the mechanism of the color categorical perception and tried to answer the question of whether it develops universally or it is relative to local communication. So they investigated whether a categorical representation of color emerges from a Convolution Neural Network (CNN) that is trained to perform an object recognition task. The results indicate that the CNN has a categorical representation of color, which suggests that the color categorical perception might emerge from the object recognition.

In general, I think the results are interesting. They performed a psychophysical experiment with the CNN, which shows the border of color category was largely invariant to the training colors. Also, further experiments with the evolution algorithm and other experiments confirm this.

However, I think the approaches to address this question are not straightforward. All of the approaches in the paper rely on the retraining of the last layer. I was hoping they would provide more direct evidence to support their claim. Also, if they can show the color categorical information revealed by the CNN is similar to the human's color perception, that would help to strengthen their claim.

Reviewer #2 (Public Review):

In this study, the authors collected and analyzed blood samples from >9,000 participants from two cross-sectional cohort studies in the UK. The ALSPAC cohort only collected data during April and May 2021, whereas the TwinsUK cohort collected data during April and May 2021 and November 2021 to January 2022. They measured anti-Nucleocapsid and anti-Spike antibodies using the collected blood samples. They investigated the variation in antibody levels and risk factors for lower antibody levels following each round of SARS-CoV-2 vaccination across a wide range of socio-demographic, SARS-CoV-2 infection and vaccination, and health factors. Alongside the descriptive analysis, the authors performed some multivariable regression analysis.

Reviewer #2 (Public Review):

Fuhrman et al. explore a fascinating system to study the evolution and genetic architecture of ecological adaptation in marine midges. They use a number of approaches including analyses of whole genome sequences and QTL mapping to explore population structure and the loci associated with the timing and mode of reproduction. I have some concerns about the analyses and interpretations which I outline below.

1) My primary concern is in the design and interpretation of the QTL analysis. The QTL approach used here has low power, both due to the sample size and the number of markers used (it looks like ~8 per chromosome). The authors use an analysis of the sex determining locus as a "control" but because of the complete heritability of this trait in most systems it is more of a straw man to me. The authors conclude that the architecture of the trait is polygenic based on this, but we are missing key information to evaluate this.

2) There are some issues with the presentation and interpretation of the population genetic analyses. Many assumptions are made about whether introgression or ILS occurred and there are statements that are not accurate about it being "impossible" to distinguish between these scenarios.

3) Some of the analyses associated with ecological adaptation that follow on the QTL results struck me as ad hoc and with the potential to lead to spurious results. I am not familiar with the BayPass approach but since it is the approach that explicitly accounts for population structure it seems the one that would be most appropriate for the authors to focus on in a revised manuscript. The use of phylogenetic windows that associate with ecotype is concerning to me as given the level of ILS and gene flow that appears to be present in this system is would be very challenging to distinguish signal from noise.

4) There were issues with the GO analysis that should be addressed. Because the gene universe used for GO enrichment is a subset of the full gene set, GO enrichment results will be biased. This will mostly lead to false positives (i.e. overrepresentation of a GO category due to evaluating a subset of genes that fall in that category).

Reviewer #2 (Public Review):

In this manuscript the authors develop a method, SpecVar, to perform heritability estimation from regulatory networks derived from gene expression and chromatin accessibility data. They apply this approach to public datasets available in ENCODE and Roadmap Epigenomics consortia as well as GWAS phenotype associations in UK Biobank. It promises to be a powerful method to interpret mechanisms from genetic associations. Below are some strengths and weaknesses of the paper.

Strengths

- The method performs heritability enrichment on two major genomic data types: gene expression and chromatin accessibility.<br /> - This method leverages gene regulatory networks to perform the heritability estimation, which may better capture complex disease architecture.<br /> - The authors perform an extensive comparison to other LDSC-based approaches using different tissue datasets.

Weaknesses<br /> - This approach may represent a modest advance over existing LDSC methods when looking at other complex traits.<br /> - The authors only compare with LDSC using different functional annotations as input, which may not be appropriate. A more broad comparison with other heritability methods would be helpful.<br /> - The method seems to be applied to "paired" data, but this is still bulk profiles not paired single-cell RNA/ATAC data.

The authors successfully applied a regulatory network approach to improving the heritability estimation of complex traits by using both gene expression and chromatin accessibility data. While the results could be further strengthened by comparing them to other network and non-network-based methods, it provides important insight into a few traits beyond the standard LDSC model with different functional annotations.

Given that this method is based on the widely used LDSC approach it should be broadly applied in the field. However, the authors should consider adapting this to single-cell data as well as admixed human population genetic data.

Reviewer #2 (Public Review):

The authors described the analysis of a magnesium transporter UEX as a sleep-regulating gene in Drosophila melanogaster. They also proposed the UEX regulates sleep through its downstream Ca2+-dependent CREB signaling and a CNK-dependent ERK pathway. The involvement of UEX in sleep regulation is novel and potentially interesting, but the data presented in the manuscript does not fully support the conclusions the authors proposed. Most of the data are derived from elav-GAL4, which is a non-specific pan-neuronal GAL4 driver. Since as the authors described, UEX functions to alter sleep in various brain regions, the relationship between UEX and other molecules in Ca2+-dependent CREB signaling and a CNK-dependent ERK pathway may be indirect in the sleep-regulating pathway, which means it may involve multiple regions of the brain using different pathways, and the sleep phenotype is the summation of different functions of UEX.

Reviewer #2 (Public Review):

Appropriate brains functions require the precise wiring of vast numbers of synaptic connections in broadly distributed neural circuits. Monosynaptic retrograde rabies virus tracing has become a common approach in neuroscience to assay presynaptic inputs into a given postsynaptic region. However, quantification and interpretation of rabies tracing data is confounded by the lack of uniform and appropriate measuring approaches across different studies and laboratories, as well as the lack of knowledge of the trans-synaptic transfer properties of different rabies viruses in various brain regions.

The current study comprehensively applies mathematical approaches to an example rabies tracing dataset in layer 5 of mouse visual cortex, as well as previously published datasets, to propose more standardized methodologies for rabies data analysis and interpretation. The major strength of the study is the rigorous and unbiased mathematical approaches applied to their data and a range of previously published studies in the field. Inclusion of representative image data would be helpful for readers and would further strengthen the study. Given the ubiquitous use of rabies virus tracing in the field, yet lack of insight into this crucial aspect of its use, this will provide a useful resource for the neuroscience community.

Reviewer #2 (Public Review):

In most organisms, DNA replication is restricted to a relatively few cytologic structures termed replication factories. Studies indicate that such factories contain multiple replication forks. Although these observations suggest that replication fork colocalization has functional significance, the biological rationale for replication factories has remained elusive. To address this issue, the current study utilizes E. coli, a bacterium with a circular chromosome that replicates its DNA bidirectionally from a single origin of replication. During the first half of an E. coli DNA replication cycle, these two forks spatially co-localize into a single "factory." The experimental plan of this study is to block one of the two replication forks at various informative genomic locations and see if such blocks affect the progression and efficiency of the non-blocked fork. Using this approach, the authors find that blocking the progression of one fork at an early point in replication slows the progression of the corresponding unblocked fork and considerably increases its probability of replication fork collapse. This study considerably advances the field by demonstrating for the first time a possible biological purpose behind the replication factory - that factory formation in some yet unknown manner helps coordinate and stabilize bidirectionally oriented replication forks.

Although others have tried to study replication factories using similar experimental logic, this well-written study by Chen et. al. examines the problem with higher sensitivity and resolution using a very elegant and synergistic approach that combines 3-dimensional microscopy, deep DNA sequencing, and old-fashion cell biology with a series of carefully engineered E. coli strains containing a conditional replication fork block in different informative genomic locations. These approaches in combination allow one to make a direct experimental correlation between cytologically defined replication factories (3D fluorescent imaging of labelled replication factors with image deconvolution), and fork progression via an analysis of copy number (genomics). Their experimental approach and accompanying analysis pipeline will be of general interest to the research community.

In addition to a very careful analysis of factory formation that helps resolve several previous discrepancies on this subject, the authors used this approach to show that blocking one replication fork early in DNA replication coordinately decreases both the rate of fork progression and the level of fork stability in the unblocked sister fork. This conclusion is supported by their genomic analysis that shows the velocity of the unblocked fork slows when the other fork is blocked. To further elucidate this observation, the authors examined the likelihood that elevated replication fork collapse contributed to the decreased fork rate. As the restart of a collapsed replication fork depends upon genetic recombination, the role of recombination in fork progression in this situation was examined. Two questions were asked in this system: 1) Is the progression of the unblocked fork specifically reduced in the absence of genetic recombination (with a mutation in RecB)? and 2) Using chromatin IP, does this slow fork specifically recruit binding of a catalytically-dead Holliday-junction resolvase (RuvC)? The results from both experiments strongly support the conclusion that replication factories in some yet unknown manner are needed to stabilize the bidirectionally orientated replication forks. Although this strong conclusion indicates that the unblocked fork specifically creates DNA lesions, this approach does not unambiguously distinguish between damage resulting directly from fork collapse and damage caused by other aspects of defective DNA replication.

Reviewer #2 (Public Review):

Summary

This manuscript re-examines a distractor effect of decoy options on risky choice reported in previous research by re-analyzing data from previously published experiments that reported these effects. The previous studies reported that adding an unavailable decoy option to a choice set consisting of two available risky choices increased the discriminability between the two available risky choices, especially when the expected value difference between the two available risky options was small, by increasing the expected value of the unavailable distractor. The authors argue convincingly that the distractor effect is an artifact of two other confounding factors: one is that there is a covariance between the distractor's expected value and the subjective utility difference between the two targets; the second is that the expected value of the distractor alternative could covary with its relative position in the reward-probability space, and its relative position in the multi-attribute space could induce a well-known context effect. The first alternative explanation was established by comparing binary choice with and without the distractor present and finding the same effect in binary choice without any distractor present. The second was established by showing that the distractor effect was most pronounced when it was close to the higher-value target in the multi-attribute space, inadvertently producing a previously well-known attraction effect. These results clarify the role that an unavailable distractor plays in decisions between two risk alternatives.

Evaluation

This is a very comprehensive and somewhat complex manuscript. It does a good job of detective work to get at the bottom of the distractor effect reported in previous articles (including this journal). It essentially contains two main sections. The first section is designed to establish the conclusion that the distractor effect is an artifact of a confounding variable, the additive utility difference between the two available choices, and generalized linear model analyses were used to make this point. The second section is designed to show that the distractor effect also covaries with a well-known context effect called the attraction effect, and they use mathematical modeling of choice and response time to understand this part. Different hypotheses about how the risk information was integrated tested by varying how the drift rate was calculated in a racing drift diffusion model for choice and response time. In particular, they contrasted a divisive expected value type of integration hypothesis with a selective attention type of additive utility hypothesis. They concluded from these mathematical modeling analyses that an additive utility model for integrating the risk information was used in these experiments to evaluate the risky gambles.

Strengths the manuscript makes a very compelling case for the conclusion that the distractor effect was confounded with the additive utility difference between the available alternatives. This was achieved comparing the binary choice results, with and without the distractor, and finding little or no difference between these two conditions. The manuscript is also commendable for its rigorous mathematical modeling of the context effect of the distractor on the binary choices when the distractor was present.

One weakness is that the contribution is somewhat narrowly focused with respect to the phenomenon that it addresses - the distractor effect in risky choice. However, I do think it is important for understanding this particular phenomenon. The other main weakness is the complexity of the manuscript. The manuscript is very long with numerous detailed statistical analyses and computational modeling analyses. Generally speaking, the authors did a good job describing and summarizing all these analyses, and they made effective use of figures to illustrate the ideas and conclusions. However, there are several spots that are somewhat difficult to follow (see specific comments), and the reader is pressed to think pretty hard and fairly long and with a lot of effort to absorb all the points.

One other major concern I have regards the conclusion that the participants in these studies use an additive rather than a multiplicative rule to integrate the risk information. The additive rule is problematic in general because it fails to predict the reversal in the effect of probability on payoffs when the payoffs change sign. More specifically, increasing the probability of winning increases the probability of choosing an option when the payoff is positive, but the effect reverses when the payoff is negative. One needs to impose some pretty ad hoc assumptions to make the additive model account for this fundamental interaction between probability and payoff. Of course, the experiments reported here did not include negative payoffs, and so didn't run into this problem. In fact, when the payoffs are positive, it is possible to transform the multiplicative model to an additive model by a log transform. This transformation is only possible for the simple type of gamble investigated in this manuscript - a single amount to win with some probability of winning, otherwise win or lose nothing. If the gambles involved more than one outcome, then the theorist needs to deal with a sum of products and the log transform is no longer possible. For these reasons I am very skeptical about the general application of a summation rule for probability and value in risk choice. The authors do address this issue to some extent. They point out the abundance of other research supporting a multiplicative rule, and they speculate that the additive rule may have occurred within the restrictions of this special situation. The latter discussion is a good start, but I suggest that the authors discuss this fundamental issue in more depth.

Reviewer #2 (Public Review):

This paper describes a new concept of "axe-vascular coupling" whereby action potential traffic along white matter axons induces vasodilation in the mouse optic nerve. This is an initial report dissecting some of the mechanisms that are undoubtedly complex as in gray matter NVC. I like the novel AVC concept.

Some minor corrections and suggestions:

1) p3: "The cerebral white matter (WM) in the adult brain is particularly vulnerable to cerebrovascular diseases such as ischemia":this may be misleading since WM is actually far less vulnerable to ischemia than gray matter

2) p4-5: "The ON exhibited a median of 175.8 pc/mm2 {plus minus} 35.7 pc/mm2, more than twice the number of pericytes observed in the corpus callosum [...] and lower than cortex ": this seems incorrect, the density in cortex is not significantly different than ON

3) p5: what is the unit 'pc'? (A cellI I presume but please define at first use)

4) p7 : "To evaluate if pericytes have and retain their contractile properties, we applied the vasoconstrictor U46619 (100 nM) for 15 min followed by acetylcholine (ACh - 100 μM) as a vasodilator": if they saw an effect, how would the authors know these were mediated my pericytes and not smooth muscle cells?

5) in Fig. 3i there is a sharp step after U466... application: is this an artifact or evidence of a delayed constriction? Could a clearer trace be shown that does not confuse?

6) Fig. 4I: what does "20% CAP (norm)" mean? Why not just mV for the y-axis? Also what pulse width was used for stimulation?

7) Fig.5: it would be good to show both the CAPs (at various frequencies) and the vasorespones at 95% vs 20% O2. In particular, are the ONs able to sustain conduction at the higher frequencies (showing overlays as in 4I), and if not, could this at least partially account for the different responses at the two O2 levels?

8) Fig. 6G,H is somewhat misleading as it implies no change in AVC, at odds with 6E. Suggest some clearer labeling to reduce confusion surrounding this very important point.

9) P18 authors state radius of a MON is 150um but on p4 they say "150 μm - 200 μm thickness", pls clarify.

10) p19-20: as part of their second messenger speculation authors may also want to include NO that has been shown to induce important effects in WM. Indeed, testing the tat uncoupling peptides could be interesting to see of oligodendroglial NMDARs have a similar singling arrangement with NOS as do neurons. This may have important implications for WM neuroprotective strategies in stroke that have typically focused on gray matter mechanisms.

Reviewer #2 (Public Review):

This study used serial block face scanning electron in the mouse posterior vermis. The analysis showed that Purkinje cell "naked" spines, are ~5% of all spines after wakefulness but grow to ~10% of all spines after sleep. Additional analysis revealed that the observed sleep-wake difference is best explained by a change in the number of "branched" synapses, Branched spines are proposed to convert to single spines during sleep. It is speculated that sleep promotes the pruning of branched synapses. This is a beautiful study that must have taken considerable effort in addition to expertise. No such data exist in the literature and the observations are interesting in light of the prior data from cortex published by the same group.

Major critique:

• The abstract and in particular the second half is very difficult to follow and should be rewritten. It might be easier to follow if the authors compare to previous work in cortex<br /> • The figures are very well done. However, I am missing a model diagram explaining the model proposed for changes in naked spine during the sleep-wake cycle and the proposed functional consequences.<br /> • The authors have previously studied the effect of sleep on the ultrastructure of glial cells, astrocytes and oligoes. This might be a separate study, but it would be of interest to discuss the role of Bergmann glial cells in synaptic plasticity. One major difference is that Bergmann glia express AMPA receptors, unlike cortical astrocytes and these are important for the proximity of astrocytic processes to synapses.

Reviewer #2 (Public Review):

This is an interesting study with a primary value in generating new transcriptional data sets for zebrafish hair cells and non-sensory cells in the inner ear. The data will, no doubt, be useful for future studies of hair cell function, development, and regeneration. The data also reveal transcriptional differences between similar cell types in different structures and transcriptional similarities between fish and mammalian cell types within analogous structures. Overall the strength of evidence in support of the results is strong.

Reviewer #2 (Public Review):

Amyloid-β precursor protein (APP) regulates synaptic activity in part through the release of secreted APP (sAPP) acting at cell-surface receptors. In 2019 two articles (Dinamarca et al, 2019; Rice et al, 2019) were published showing that sAPP binds with high affinity with GABAB receptors. These receptors regulate neuronal excitability and synaptic release. In the Rice et al. paper, it was concluded that sAPP plays a physiological role by regulating GABAB receptors by modulating synaptic transmission, consistent with the direct activation of these receptors by sAPP. This article has received major attention in the field of Alzheimer's disease and synaptic biology.

The present work was designed to fully explore the functional consequences of sAPP binding to GABAB receptors, in particular, because it was unclear how a conformational change in SD1 - the region of GABAB receptors that binds sAPP - potentially induced by sAPP could increase GBR activity.<br /> The work does confirm that the peptide APP17 which derives from sAPP binds with nanomolar affinity with GABAB receptors. The authors use a diverse range of techniques, ranging from biophysical assays in recombinantly expressed receptors to electrophysiology and live imaging in cultured neurons, slices, and in vivo neuronal activity. In none of these assays, could the authors demonstrate any functional effect of sAPP mediated by an action on GABAB receptors.

This work from a team that has exquisite knowledge of the different aspects of GABAB receptors represents an important and very convincing clarification for the field, and it would therefore be very useful if this information is rapidly available.

Reviewer #2 (Public Review):

In their current manuscript Hussmann et al., present a very detailed phenotypic analysis of the role of svep1 in lymphatic development in zebrafish. They show that svep1 is essential for the development of particular aspects of facial lymphatics (the FCLV and BLECs) in a fashion complementary to VEGF-C. Furthermore, they show that the loss of tie1 phenocopies svep1 mutants not only with respect to lymphatic defects but also in blood vessels (DLAV).

Overall, the manuscript is clearly written, the experiments are carefully executed, and the quality of data is very high and support the author's main conclusions: 1) that Svep1 and Tie1 genetically interact during lymphatic and blood vessel development and 2) that this function is independent and complementary to VEGF-C. 3) The authors confirm and extend on a previous study (Jiang et al. 2020) showing that tie2 (tek) has no overt role in vascular development in zebrafish in blood as well as in lymphatic vessels.

The strength of the paper lies in the careful combination and comparison of different mutant alleles and the use of state-of-the-art imaging. These analyses show that Svep1 and Tie1 interact at the genetic level. In vivo cell tracking experiments show that Tie1 and Svep1 regulate particular aspects of lymphatic cell migration.

An obvious remaining question concerns the epistatic relationship and the molecular mechanism of Tie1/Svep1 interaction. The authors suggest a non-autonomous requirement of Svep1 in the ECM regulating the availability of Tie1 ligands (Ang-1/-2?) in LECs. Since bona fide ligands for Tie1 have not yet been identified in zebrafish further studies will be needed to test this model.

Reviewer #2 (Public Review):

The authors used Mendelian randomisation to study the relationships between metabolic traits and oral/oropharyngeal/head and neck cancers. This study was conducted as the relationships between these traits and cancers are unclear based on observational data. Evidence for relationships between these traits and cancers is inconclusive, which is a relevant finding in the context of previous observational data.

Strengths include using large studies to develop the instrumental variables used in MR and examining multiple metabolic traits. Weaknesses include relatively low power to detect associations and a lack of discussion around any possible pleiotropy of SNPs associated with any of the metabolic traits. Based on these strengths and weaknesses, it is unclear whether the authors achieved their goal and whether the results support their conclusions.

This work is relevant to researchers interested in oral cancers and their etiology. Several issues would need to be addressed to make the evidence more reliable.

Reviewer #2 (Public Review):

The work systematically reassesses fungal mi/miRNA-like characteristics and annotation confidence and identifies that many of the loci fail to meet the key points of the methods developed for animal or plant miRNAs. Therefore the authors establish a set of criteria suitable for the annotation of fungal miRNAs and provide a centralized annotation of identified mi/milRNA hairpin RNAs in fungi based on their established rules.

Here are some comments and suggestions for the manuscript to be improved:<br /> 1. The title mentions "ancestral links", however, the main context of this paper does not include the evolution of fungal mi/milRNAs or show the origins of conserved mi/milRNAs in fungi. The authors are suggested to consider a more appropriate title for this work.<br /> 2. The work proposes a fungal mi/milRNAs hairpin precursor recovery pipeline with three minimal criteria to annotate fungal mi/milRNA loci, which allows nearly half of the loci to pass these rules. To highlight the innovation of this annotation, it is strongly suggested that the authors compare their established pipeline and criteria for fungi with those used in animal or plant miRNAs in detail, and emphasize the advantages of the established pipeline. A figure showing the established pipeline and detailed parameters is needed.<br /> 3. The established "standard rules" for fungal mi/milRNA annotation still require more evaluation. It would be better if there is experimental validation to improve confidence.