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  2. Jun 2021
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  3. May 2021
    1. One solution that fixed this issue with my ISP was that when I went through the first and second line and got in touch with the people that fixed my problem, I asked them if they could give me one of their personal numbers in case the same problem happened again. The problem did occur a couple more times, and I just directly called the same guy.
    2. I find most tech support is filled with inexperienced and frustrated staff who just run off a script. They're not paid well. They are Tier One support to filter out most of the incoming calls. Tech support is designed in tiers.
    1. re beautiful than silence for more than, say, 50% of the time. But here’s a nice surprise: You could exceed that


    1. Reviewer #1 (Public Review):

      Sierra M. Barone developed an automated, quantitative toolkit for immune monitoring that would span a wide range of possible immune changes, identify and phenotype statistically significant cell subsets, and provide an overall vector of change indicating both the direction and magnitude of shifts, either in the immune system as a whole or in a key cell subpopulation. The machine learning workflow Tracking Responders Expanding (T-REX) was a modular data analysis workflow including UMAP, KNN, and MEM. T-REX is designed to capture both very rare and very common cell types and place them into a common context of immune change. T-REX was analyzed data types including a new spectral flow cytometry dataset and three existing mass cytometry datasets.

      The conclusions of this paper are mostly well supported by data, but one aspect need to be clarified and extend. Cytometry tools like SPADE, FlowSOM, Phenograph, Citrus, and RAPID generally work best to characterize cell subsets representing >1% of the sample and are less capable of capturing extremely rare cells or subsets distinguished by only a fraction of measured features. Tools like t-SNE, opt-SNE, and UMAP embed cells or learn a manifold and represent these transformations as algorithmically-generated axes. The advantages of T-REX tool were not very clear.

    1. Reviewer #1 (Public Review):

      In the early days of the pandemic there was unqualified enthusiasm for convalescent plasma therapy. This enthusiasm shifted dramatically as several trials showed no apparent benefit. Although this manuscript does not show a causal relationship between convalescent plasma therapy and prognosis it is provocative and suggests that further work is needed to assess its utility.

      Strengths of the manuscript include the comprehensive review of existing datasets and the use of state-of-the-art statistical methods for examining potential confounders such as patient age, seasonal variation in hospital admissions that might have impacted quality of care, and the emergence of SARS-CoV-2 variants. Weaknesses include lack of data that might have enabled identification of patients who are likely to benefit from convalescent plasma and characteristics of plasma (such as neutralization titers) that may be associated with efficacy. These weaknesses do not indicate a lack of effort on the part of the team; there is simply no way to obtain the data.

    1. Reviewer #1 (Public Review):

      In this paper, Alhussein and Smith set out to determine whether motor planning under uncertainty (when the exact goal is unknown before the start of the movement) results in motor averaging (average between the two possible motor plans) or in performance optimization (one movement that maximizes the probability of successfully reaching to one of the two targets). Extending previous work by Haith et al. with two new, cleanly designed experiments, they show that performance optimization provides a better explanation of motor behaviour under uncertainty than the motor averaging hypothesis.

      Main comments:

      1) The main caveat of experiment 1 is that it rules out one particular extreme version of the movement averaging idea- namely that the motor programs are averaged at the level of muscle commands or dynamics. It is still consistent with the idea that the participant first average the kinematic motor plans - and then retrieve the associated force field for this motor plan. This idea is ruled out in Experiment 2, but nonetheless I think this is worth adding to the discussion.

      2) The logic of the correction for variability between the one-target and two-target trials in Formula 2 is not clear to me. It is likely that some of the variability in the two-target trials arises from the uncertainty in the decision - i.e. based on recent history one target may internally be assigned a higher probability than the other. This is variability the optimal controller should know about and therefore discard in the planning of the safety margin. How big was this correction factor? What is the impact when the correction is dropped ?

      3) Equation 3 then becomes even more involved and I believe it constitutes somewhat of a distractions from the main story - namely that individual variations in the safety margin in the 1-target obstacle-obstructed movements should lead to opposite correlations under the PO and MA hypotheses with the safety margin observed in the uncertain 2-target movements (see Fig 5e). Given that the logic of the variance-correction factor (pt 2) remains shaky to me, these analyses seem to be quite removed from the main question and of minor interest to the main paper.

    1. Reviewer #1 (Public Review):

      The authors first use light sheet microscopy to reconstruct embryonic brain development of O. vulgaris. From these images they note a region adjacent to the eye and the developing brain that initially increases in size and subsequently shrinks. They perform transcriptomics and use phylogenetic analyses to identify 4 classes of genes involved in neurogenesis: those that specify the neuroectoderm, neurogenic genes, and markers for differentiated neurons and mature neurons. They perform spatio-temporal analyses of these genes to demonstrate that the lateral lip is the neurogenic region that harbours neuronal progenitors. This region is distinct from the brain, suggesting that neurons migrate long distances from where they are specified to populate the brain. They perform lineage tracing to provide evidence for this migration and demonstrate that the lateral lip is spatially fated so that regions within it generate neurons specific to parts of the brain.

      In summary, this is an elegant study that provides deep insight into embryonic neurogenesis in O. vulgaris.

    1. Reviewer #1 (Public Review):

      The manuscript has several merits. Most remarkably, Corbett and colleagues developed an alternative to describing biases in decision making by shifting the starting point of evidence accumulation. Instead, they included a linearly increasing urgency buildup rate that was biased by a value cue presented before task onset. Hence, the subsequent evidence accumulation process (labeled the "cumulative bias plus evidence function", p. 5) was affected by this bias in addition to gradually-accumulated stimulus evidence. To allow the estimation of these new model parameters, starting points and urgency buildup rates were constrained to equal the amplitude and temporal slope of the corresponding beta signal captured in simultaneous EEG recordings.

      They tested a set of alternative model implementations and found that the bias in stimulus-evidence accumulation was best represented by a concentrated burst of value-biased activity that mirrored voltage changes in the LRP. In comparison, a model with sustained value-biased activity provided an inferior account of the data. Moreover, the authors found that a model gradually increasing evidence and noise provided a better account of the data than a stationary evidence accumulation function. This systematic comparison of alternative model implementations is a great highlight of the paper, because it allows to narrow down on the neurocognitive processes underlying biased decision making.

      What limits the generalizability of the authors' results is the sample size and composition. With only 18 participants (one of which was a co-author of this manuscript), the robustness of the authors' modeling results remains an open question. Although 18 participants may provide sufficient power to test a simple main effect in a within-subject design, this does not speak to the issue of the reliability and generalizability of modeling results. Moreover, it is important to note that a sample of 18 participants gives only a power of about 50 % to detect a medium-sized effect with α = .05. Nevertheless, I believe that the generalizability of modeling results is a larger issue than the statistical power. It would have been interesting to assess if the best-fitting model identified in Table 2 provides the best account of the data for all participants or only for a certain percentage of the sample.

    1. Reviewer #1 (Public Review):

      Human and animal work over the last couple of years established that fluctuations in pupil size track the activity of a number of neuromodulatory nuclei, including the noradrenergic locus coeruleus, cholinergic basal forebrain, serotonergic dorsal raphe and perhaps the dopaminergic midbrain. In other words, pupil size fluctuations might track a "cocktail" of neuromodulators. The current paper leverages sophisticated data driven analysis techniques to show that pupil size changes can indeed be modulated by different combinations of subcortical nuclei. Doing so, the paper helps laying a solid and nuanced neurophysiological foundation for the interpretation of results from cognitive pupillometry, an area of neuroscience and psychology that is rapidly expanding over the past years. I do have a couple of concerns.

      Major issues:

      The BOLD hemodynamic response function is slower than the pupil impulse response function. It seems that the authors did not correct for the "lag" between the two (as in Yellin et al., 2015, for example). How much does this matter for the results?

      Baseline pupil size was different between the identified clusters. How was pupil size normalized across rats and scanning runs, so that we can meaningfully interpret such a difference?

      A substantial part of the literature focuses on the relationship between task-evoked pupil and neuromodulatory responses. I understand that this paper describes results from a resting state experiment, but even in these conditions one typically observes rapid dilations. Right now, it seems that the analysis is somewhat blind to these. See for example Fig. 2C in which frequencies are plotted only until 0.05Hz. Can we see this on log-log axes, to inspect the higher frequencies? Note that there is some work that indicates that the slower pupil fluctuations more reliably track ACh signaling, and faster fluctuations more reliably track NE signaling (Reimer & McGinley et al., 2016).

      The authors write "Cluster 2 had the strongest positive weights in [...], but also in brainstem arousal-regulating locus coeruleus, laterodorsal tegmental and parabrachial nuclei." However, the voxel size is very large with respect to the size subcortical nuclei. Because of this, here and in other places, I think the authors should use locus coeruleus region or area, to indicate that their voxel captures more tissue than just LC proper. A discussion paragraph on the spatial specificity of their effects would also help.

      The approach is very data driven and the Results section mostly descriptive. I'm personally not at all unsympathetic to this approach, but I do think the authors could aid the reader better by briefly interpreting their results already in the Results section. Related, the authors end each paragraph with "These results verified [...]" or "These results highlight [...]"; however they don't explicitly inform us how.

      Rainbow and jet colormaps are confusing because they are not perceptually uniform (https://colorcet.holoviz.org/). Please consider using something like "coolwarm"?

      Minor issues:

      "Trial" is not well defined. I take this is a 15 minute run?

      How many trials in each cluster (Fig. 2)? It would be nice to see a more zoomed in version of Fig. 5 so that we can actually see the subcortical regions in more detail.

    1. Reviewer #1 (Public Review):

      Previous reports have provided evidence identifying infection of cotton bollworm with a densovirus as resulting in increased fitness. In the current manuscript, the relevance of this infection towards field resistance to transgenic Bt corn is evaluated by comparing its incidence between regions in China growing non-Bt versus Bt cotton. A clear correlation emerges with infection rates being higher in Bt versus non-Bt cotton growing areas, although its effect on resistance to Cry1Ac and Bt cotton is not as clear.


      The manuscript presents evidence for the spread of densovirus infection in field bollworm populations, and that this spread seems to occur at a faster rate in areas of China where Bt cotton is grown versus non-Bt cotton areas. Life table comparisons clearly show increased fitness in bollworms infected with the virus. The study capitalizes on availability of an impressive collection of samples with distinct geographic and historic origin to address relevant evolutionary questions.


      The suggested role for densovirus infection in resistance to Cry1Ac and Bt cotton is supported by association and the data presented does not necessarily support causation. In fact, the confidence intervals in all the comparisons from bioassays overlap substantially and the resulting resistance ratio is not a good estimate of any significant differences the infection may have on ability to survive Cry1Ac. Infection by a virus is expected to activate the immune system, so the larvae used in bioassays should be considered as "primed" and the slight reduction in susceptibility should not be considered as an effect of the virus itself. The life table data clearly shows that fertility and fecundity are probably the most relevant aspects affecting fitness of infected insects. These differences in reproduction (even more than differences in larval growth) could explain why infection is rapidly spreading in the wild. However, most of the research and analyses are focused on the possibility that the viral infection may make the insects more able to survive Cry1Ac or Bt cotton. There are no conclusive data supporting this hypothesis in the current version, other than increased infection rates in Bt-cotton growing areas. This could be explained by effects on reproduction rather than enhanced survival. Related to this aspect, there should be a more clear distinction between the densovirus increasing fitness versus increasing resistance, the data supports the former but is not so clear in the later. It would be useful to provide a map detailing regions were moths were collected.

    1. Reviewer #1 (Public Review):

      The field of genome dynamics is currently very hot and adaptive transposable elements insertions polymorphisms (TIPS) in wild populations are extensively looked for. Here Oggenfuss et al provide evidence that TE activity within a fungus species can vary drastically (1) in different regions of the world and (2) in the same region within a relatively short timeframe (25 years). The data are properly described and both the figures and text are clear. The authors provide examples of candidate TIPS that could adaptive.

      Important findings:

      • A repertoire of TIPS is provided for 284 genomes. A PCA analysis show that a small number of TIPS can better differentiate two samplings 25 years apart on the same area than the same number of SNPs.
      • Increase in TE content is associated with genome size, between areas and within a single area 25 years apart.
      • Interesting candidates for adaptative TIPS are provided and discussed.


      • The TIPS (or a subset of them) are not validated using another technique.
      • The relative expression of the adaptive TIPS is not investigated in this manuscript.
      • For genomicists not familiar with fungal genomes the distinction between core chromosomes and accessories chromosomes might be difficult to appreciate.
    1. Reviewer #1 (Public Review):

      Gupta et al. provide a very detailed and in depth analysis of the dimerization / oligomerization behavior of the protein Survival Motor Neuron (SMN). The protein is able to use a modified glycine zipper motif to form tightly packed dimers and additional hydrophobic amino acids for higher oligomeric states. Mutations in SMN cause Spinal Muscular Atrophy and the authors show that mutations leading to this disease affect the oligomerization state of the protein. Overall, this is a very detailed study using several biophysical techniques and extensive mutagenesis. The data are of high importance for researchers working in the field of SMN proteins.

      A mechanistic link of how these differences in oligomeric states changes the cellular behavior leading to Spinal Muscular Atrophy is unfortunately missing. The authors stress several times that SMN is part of membraneless organelles. Multivalent interactions are characteristic of such organelles, although they are typically based on "fuzzy" interactions involving low complexity regions (and not all dimerization / oligomerization events can be classified as liquid-liquid phase separation). This limits the impact of this detailed analysis.

      While this very detailed analysis is an excellent source for researchers working in this field the interest beyond SMN proteins will be limited. The paper could also be written in a less dense manner, which would make its reading easier. The main weakness is a missing mechanistic model that can explain how differences in the oligomerization behavior relates to the function of the protein and causes Spinal Muscular Atrophy. The impact of oligomerization on the formation of membraneless organelles would be important.

    1. Reviewer #1 (Public Review):

      Breska and Ivry tested the role of the cerebellum in temporal expectation, specifically in how temporal expectation affects perception. The question is interesting, as the neural mechanisms mediating the substantial effects of temporal expectation on perception are not well understood. The authors found that in a perceptual discrimination task, individuals with cerebellar degeneration (CD) showed reduced effects of temporal expectation on discriminability with interval timing cues, but intact effects with rhythmic cues. This shows that the role of the cerebellum in temporal expectation (which had been previously demonstrated by the authors) is not merely one of motor preparation. Rather, the cerebellum appears to play a causal role in bringing about the perceptual consequences of temporal expectation for predictable intervals. It also reveals differences between interval timing and rhythmic manipulations in terms of the mechanisms by which they affect perception.

      This is a straightforward study with a clean experimental approach and clear presentation of the data. However, I felt the manuscript would benefit from a more thorough analysis of the dataset, especially given the rarity of individuals with CD.

    1. Reviewer #1 (Public Review):

      The manuscript aims to identify origins of stochasticity ('noise') in mammalian gene expression focused on the case when a single transcription factor controls the expression of a target gene. It also aims to devise strategies to control mean and variance of gene expression independently.

      The experimental approach uses a light-induced transcriptional activator in two stimulation modes, namely amplitude modulation (AM: time-constant light input) and pulse width modulation (PWM: periodic light inputs in the form of a pulse train). Perturbation experiments target histone-modifying enzymes to influence epigenetic states, with corresponding measurements of single-cell epigenetic states and mRNA dynamics to dissect mechanisms of noise control. Beyond this synthetic setting, the study is complemented by endogenous gene expression noise in human and mouse cells under the same perturbations.

      Major strengths of the study are:

      • The experimental demonstration that, and under which conditions PWM can reduce gene expression noise in mammalian cells; the corresponding data sets could be very valuable for further quantitative analysis.
      • Providing strong evidence via perturbation studies that the extent of gene expression noise is linked to chromatin-modifying activities, specifically opposing HDAC4/5 histone deacetylase activities and CBP/p300 histone acetyltransferase activities.
      • Proposing a positive-feedback model established by these two opposing activities that is consistent with the reported data from perturbation experiments and on chromatin accessibility / modification states.
      • Providing evidence that also in the natural (human and mouse cell) setting, the regulators HDAC4/5 and CBP/p300 contribute to the control of gene expression noise.

      Major weaknesses are:

      • Limited conceptual novelty because noise-reducing effects of PWM have been demonstrated and analyzed previously in synthetic systems in bacteria (with an engineered positive feedback loop; https://www.nature.com/articles/s41467-017-01498-0) and in yeast (with an engineered single transcription factor as in the present study: https://www.nature.com/articles/s41467-018-05882-2#Sec25).
      • Insufficient evidence for the postulated bistability caused by positive feedback on chromatin states in the mammalian system analyzed, which has implications for the mechanistic explanations provided (e.g., if PWM allows rapid cell switching between 'high' and 'low' states as postulated).
      • Limited theoretical support for the proposed (not directly observable) mechanisms that uses a mathematical model illustrating the potential consistency, but the model is not directly linked to the experimental data and hence of limited use for their interpretation.

      Overall, the authors achieved their aim of elucidating mechanisms for noise control in mammalian gene expression by identifying specific, opposing regulators of chromatin states, with clear support in the synthetic setting, and evidence in endogenous expression control. Conceptual advances regarding strategies for the external control of gene expression noise appear limited because of prior work, which includes more in-depth theoretical analysis in simpler (bacterial, yeast) systems.

      Hence, the likely impact of the work will be primarily on the more detailed (in terms of histone regulators, etc.) study of noise control in mammalian cells, while the data sets presented in the study could prove valuable for follow-up quantitative (model-based) analyses because they are unique in combining different readouts such as single-cell protein and mRNA abundances as well as histone and chromatin states.

    1. “Finance is, like, done. Everybody’s bought everybody else with low-cost debt. Everybody’s maximised their margin. They’ve bought all their shares back . . . There’s nothing there. Every industry has about three players. Elizabeth Warren is right,” Ubben told the Financial Times.

      Pretty amazing statement! Elizabeth Warren is right!

    1. Reviewer #1 (Public Review):

      This paper presents evidence that membrane potential excursions called plateau potentials are driven by subthreshold oscillation generated by calcium fluxes in mitochondria. Pharmacological and electrophysiological methods were used to deduce that calcium waves were generated in a bilateral pair of electrically-coupled neurons and spread to additional neurons that were coupled to that pair. The identified neurons in Aplysia allow for the detailed measurements needed to determine this mechanism.

    1. 3No one, when tempted, shouldsay, “I am being tempted by God”; for God cannot betempted by evil and he himself tempts noone. 14But one is tempted by one's own desire, beinglured and enticed by it; 15then, when thatdesire has conceived, it gives birth to sin, and thatsin, when it is fully grown, gives birth todeath. 16Do not be deceived, my beloved.17Every generous act of giving, with every perfectgift, is from above, coming down from theFather of lights, with whom there is no variationor shadow due to change.18In fulfillment of hisown purpose he gave us birth by the word of truth,so that we would become a kind of first fruitsof his creatures.
      • James did not want anyone to think that God sends trials to break down or destroy our faith; therefore, he will come back to this point in James 1:13-18. -James knew that most people have an evil tendency to blame God when they find themselves in trials. Yet by His very nature, God is unable to either be tempted (in the sense we are tempted, as James will explain), nor does He Himself tempt anyone.
    1. Reviewer #1 (Public Review):

      Acyl-homoserine lactone (AHL) based quorum sensing systems are an important form of intercellular communication in bacteria. These systems, minimally comprised of a synthase and a receptor, often involve different types of AHLs. This paper uses covariation analyses to try and tease out the determinants of this AHL specificity. Using the GREMLIN pipeline, they identify a series of coevolving residues in LasR and LasI homologs. This is interesting in its own right, and a strength of the paper, as LasR and LasI don't physically interact, and instead interact and covary indirectly by virtue of sharing the same AHL. Through various reporter and biochemical assays, the authors then demonstrate that the residues identified are important for AHL recognition. In the last part of the manuscript, they attempt to use the covariation analysis to guide the 'rewiring' of LasR-LasI to behave like MupR-MupI. This is mostly successful, although LasR-LasI specificity hasn't been 'rewired' so much as simply broadened. The paper could also be improved by fleshing out the description of the results/data obtained - at times it is difficult to assess how the authors have arrived at certain rather sweeping conclusions.

    1. Reviewer #1 (Public Review):

      This study shows that the Shu complex is critical for 3meC damage tolerance in yeast, supporting the existence of a new pathway for the removal of an important DNA lesion that seems essential in yeast but likely contributes in other organisms. At the same time, it contributes to clarify the distinctive role of homologous recombination in double strand break repair and post-replicative repair.

    1. Reviewer #1 (Public Review):

      Dravet syndrome is a developmental and epileptic encephalopathy resulting from mutations in a sodium channel subunit that is widely thought to cause disease by affecting synaptic inhibition. Here the authors use a well-established mouse model to show that circuit dysfunction results from excess synaptic excitation in the dentate gyrus, potentially providing new insight into the pathological mechanisms underlying seizure activity.

      Strengths of the study include the sophisticated approach of 2P Ca2+ imaging of population activity and whole-cell recording in slices that provide well-supported evidence that circuit dysfunction is independent of GABAergic inhibition. Weaknesses include some oversimplification of the results in the data interpretation such that not all the claims are fully supported and lack of in-depth analysis of the circuit dysfunction with a clear presentation of its developmental time course.

    1. Reviewer #1 (Public Review):

      The dark structure of GtACR1 has been almost simultaneously published at the end of 2018 and beginning of 2019 by the Deisseroth and Spudich groups, respectively. Both groups did not manage to solve a structure with an ion bound and there is very limited information on the open conformation of the channel. Both groups identified a central constriction site as being central for the gating mechanism but the Spudich group proposes two additional constrictions (C1 and C3). In this work Li et al are able to solve the structure of a GtACR1 with a bromide bound near C3, which clearly represents a significant step towards understanding the mechanism of light gated anion channels. The structure reveals that Br binds to the intracellular constriction site (C3) resulting in a small opening of C3. The data support the notion that the partial electropositivity of Pro58 together with two tryptophans play a critical role in anion interaction at C3, which was also confirmed by mutagenesis studies. In addition, there was a noteworthy conformational change in the Bromide bound protein in the extracellular constriction (C1), a 180 degree flip of Arg 94 resulting in a salt bridge to Asp 234 and a slight opening of the C1 constriction.

      While the data and conclusions are sound, the lack of discussion of their data in the context of the work of others is a bit surprising.

    1. Reviewer #1 (Public Review):

      This paper investigates the structural conformation of BtuB, a membrane protein involved in the intracellular transport of vitamin B12 in bacteria, using DEER techniques through the labelling of targeted pairs of amino acids. Using these techniques on whole cells, they detect structural conformations of the transporter upon binding of its substrate vitB12 that were not detected when BtuB is not in a natural environment.

      BtuB belongs to a well-known family of transporters found in the outer membrane of Gram-negative bacteria, called TBDTs (TonB Dependent Transporters). The structure of BtuB has been determined by X-ray crystallography in its apo and vitB12 bound states, as well as interacting with a C-terminal domain of the TonB protein, a periplasmic protein linked to the inner membrane that conveys the energy needed for the transport of vitB12 through BtuB. The TBDTs share a conserved architecture comprising a C-terminal 22 ß-barrel ring occluded by a globular N-terminal domain.

      Using EPR techniques, the Cafiso's lab has shown previously that the BtuB structural states are somewhat different or more dynamic than the X-ray structures would suggest. In the present paper they show that the Substrate Binding SB3 loop of BtuB, upon vitB12 binding, adopts some structural conformations in whole cells that are different than observed with BtuB reconstituted in liposomes, showing that a non-natural environment might alter its functionality. By using a set of mutants that supposedly mimics the BtuB-TonB state, they find dramatic conformational changes of the SB3 loop, which might represent an intermediate conformation of the open state of BtuB, in which vitB12 is allowed to move toward the periplasm, bypassing the need of an energized Ton complex. The data presented are convincing and show that the natural environment of BtuB, i.e., an intact outer membrane, but also probably some periplasmic components such as peptidoglycan and the Ton complex, influence the structural state of this protein. Most importantly these states are not detected when BtuB is reconstituted into liposomes, stressing the importance of studying these transporters in whole cells. However, some of the conclusions are premature, especially concerning the mechanism of action of the Ton complex in the catalyzed transport of vitB12. While the data show clear differences between the apo and vitB12 bound states of BtuB, the conclusions on the actual transport mechanism of vitB12 into the periplasm are more speculative.

      The main concern of this reviewer is the conclusions reached from the data obtained with the R14A and/or D316A mutants. There is a clear dramatic change of conformation for the SB3 loop for these mutants upon substrate binding, and as shown the natural environment of BtuB is important to detect these changes. However, the authors state that "breaking the ionic lock and eliminate the electrostatic interactions of R14, as we have done here, should mimic the TonB bound state" (lines 487-488). The data presented in the manuscript do not support this statement as they do not allow to monitor the structural state of the N-terminal TonB box.

      Later it is proposed that "the movement of SB3 may also drive the movement of substrate" (lines 466-467) and that "this structural change may be sufficient to move the substrate into the periplasm" (lines 501-502). This is highly speculative, as in the structural states observed with the broken ionic lock, it cannot be determined if vitB12 is still bound to BtuB, or released in the periplasm. As noted, the "conversion of the transporter to the apo state does not occur under the conditions of the experiment" (lines 398-399). It is possible that this structural state is locked with a vitB12 bound and unable to complete the transport cycle.

      Nevertheless, these mutants affecting the ionic lock seem to represent valuable tools to investigate the structural intermediates during transport. It remains to be seen if these mutants still promote transport in vivo.

    1. Reviewer #1 (Public Review):

      The study is focused on the role of noncoding RNA (sfRNA) of DENV in mosquito transmission of the virus. The requirement of sfRNA for efficient transmission of flaviviruses by mosquitoes is well-documented, however the exact mechanisms of this effect are not clearly established. In this manuscript, authors demonstrated that DENV sfRNA is secreted into mosquito saliva within the extracellular vesicles (EV) and can facilitate infection of the acceptor human cells when delivered together with infectious virus in mosquito saliva. This is a novel and intriguing finding that has a potential to expand our understanding of flavivirus transmission and functions of sfRNA.

      The data provided are mostly compelling and provide answers to posed questions. However, additional evidence for EV-mediated delivery of sfRNA into acceptor human cells and the effect of this sfRNA on viral replication in acceptor cells are required to further our understanding of mechanistic aspects of how sfRNA is delivered by salivary extracellular vesicles and how it facilitates virus replication in acceptor cells. A number of additional experiments and clarifications has been requested to clarify this.

    1. Reviewer #1 (Public Review):

      After infection, new HIV-particles assemble at the host cell plasma membrane in a process that requires the viral protein Gag. Here, Inamdar et al. showed that a component of the host cell, the membrane curvature-inducing protein IRSp53, contributes to efficiently promote the formation of viral particles in synergy with the viral Gag protein.

      In cells depleted of IRSp53, the formation of HIV-1 Gag viral-like particles (VLPs) was compromised. The authors showed in compelling electron micrographs that the formation of VLPs was arrested at about half stage of particle budding. Biochemical data (co-IPs and analysis of VLPs and HIV particle content), super-resolution nanoscopy (single molecule localization microscopy) data, and in vitro biophysics measurements (in GUVs), all seem to indicate a functional connection between Gag and the iBAR-domain containing protein IRSp53. The combination of the different techniques and approaches is a clear strength of this manuscript. However, to my opinion, the interpretation of some of the experimental data is somehow limited by the lack of some appropriate controls (that are lacking for different reasons, as the authors state in some parts of the text). These are:

      1) Specificity of the IRSp53 siRNA. Although the authors showed that the siRNA used can deplete the expression of the protein (both endogenous and ectopic), they did not presented any rescue experiments of the phenotypes (or corroboration with different siRNA oligoes).

      2) In the co-IPs (IRSp53 IP + Gag co-IP) there is no assessment of the IRSp53 IP efficiency in the different conditions. The authors argued that IgG signal masking precluded them from doing that.

      3) The authors observed an increase in the membrane-bound pool of IRSp53 when Gag is present (Fig. 2c). It is not clear whether this is specific for IRSp53 or other IBAR proteins can also be more membrane-bound as a result of Gag expression.

    1. Reviewer #1 (Public Review):

      Gentile A et al show a novel role of Snai1b in growth regulation of zebrafish myocardial wall. Specifically, authors show that zebrafish lacking Snai1b exhibit cardiac looping defects (~50% penetrance), consistent with previously described morpholino mediated Snai1b knockdown phenotype. Extruding cardiomyocytes away from cardiac lumen, mostly in the atrioventricular canal region were observed in remaining 50% of Snai1b knockout zebrafish. Using RNA-seq, authors identified several dysregulated genes, including enrichment of intermediate filament genes in Snai1b knockout zebrafish. Among these dysregulated genes, authors suggest that increased Desmin expression and its aberrant localization promote cardiomyocyte extrusion in Snai1b knockout zebrafish hearts. Overall, present manuscript describes a novel phenomenon during cardiac development, hence, it is of interest to developmental biologists.

      Major concerns are:

      1) Snai1 is known to affect cushion formation in atrioventricular canal region. It would be helpful to establish cause and effect relationship for Snai1b in this region. Zebrafish lack global Snai1b expression - so it would be helpful to show if defective cushion promotes cardiomyocyte extrusion in atrioventricular canal region. Tnnt2 morpholino experiments provides some insights, however, it does not rule out role of defective atrioventricular cushion (defective EMT).

      2) For Figure 2 - additional histology / immunohistology to show extrusion, cohesion, and orientation of cardiomyocytes at a section level (2D) in Snai1b knockout hearts could help to characterize phenotype at a cellular level. It is assumed that all cardiomyocytes lack Snai1b protein (immunostaining would help), however, only few cardiomyocyte show extrusion. Minor point - Cartoon images in figure 2 are somewhat disconnected from immunostaining images.

      3) It is unclear whether Snai1b knockout hearts exhibit defective contractile phenotype and whether there is a cardiac phenotype in surviving adult zebrafish. It is also unclear whether RNA-seq and SEM from adult zebrafish heart represent embryonic extrusion and intermediate filament defects.

      4) It is unclear why only few cardiomyocytes show extrusion when most of cardiomyocytes, if not all, are overexpressing Desmin gene.

      5) Molecular link connecting Snai1b and cardiac filaments genes is not determined.

    1. Reviewer #1 (Public Review):

      The authors found a mechanosensitive channel gene in T. cruzi, and aimed to characterize the functions. The strength of this manuscript is that the channel has been examined from various aspects: the modelled molecular structures; expression and localization during development; electrophysiological characteristics; cell motility; responses to osmotic stress; regulation of Ca2+ homeostasis; infectivity to host cells. The weakness of this study is the assessment of motility and the nature of the recombinant protein. To conclude, this study provides data sufficient for reporting the discovery and initial characterization of the novel mechanosensitive in T. cruzi. The most significant finding is the correlation with infection, but the involvement in the response to osmotic stress is also interesting in the field of cell biology.

    1. Reviewer #1 (Public Review):

      In prior work, the authors identified a requirement for an ATR-dependent activation of Chk1 for the maintenance of G2 arrest in larval tracheoblasts. Absent the activity of ATR or pChk1, larval tracheoblasts re-enter the cell cycle early. Here the authors were attempting to build on their prior work by determining the mechanism by which ATR is regulated in larval tracheoblasts. In large measure, the authors are successful in this endeavor, finding that ROS generated by Duox are required to activate ATR. However, what regulates the timing of Duox expression and the precise molecular mechanism by which ROS activates ATR remains unresolved. The closely related ATM kinase has previously been shown to be directly regulated by ROS, through the formation of disulfide bridges. The authors' modeling suggest a different mechanism may be at play.

    1. Reviewer #1 (Public Review):

      2.1 Summary of the paper

      The authors' model is an extension of standard disease models (Kermack & McKendrick, 1927; Yang & Brauer, 2008) that track the spread of an infectious disease within a host population. The authors consider the possibility that individuals' level of activity (and thus their probability of contacting others and potentially transmitting or contracting the infectious disease) may vary in time. Importantly, individual activity levels vary according to a stochastic processes that is not in any way affected by the current disease dynamics in the population or by the individuals' own disease states.

      The authors' key result is that if individual social activity levels can spike or crash but then tends to return to their mean value, then synchronous spikes and/or crashes among many in- dividuals' activity levels can lead to corresponding transient changes in the epidemiological dy- namics. Waves take off when many individuals are active, but may peak well before herd immu- nity is reached, because individual activity levels regress to the mean.

      Nowhere in the authors' model does individual behavior depend upon individual disease state or population-level disease dynamics. There are many epidemiological models featuring adaptive host behavior; in these, individuals respond behaviorally to the disease. Those adaptive behav- ior models show disease dynamics that would not be seen in the standard (i.e. constant con- tact rate) Susceptible-Infectious-Recovered (SIR) model (see for instance Epstein et al., 2008; Fenichel et al., 2011; see Bauch et al., 2013 for an extensive review).

      This, then, is the authors' key result: behavioral change that is not responsive to the disease itself can still produce transient plateaus, sub-herd immunity peaks, etc. The authors thus offer a valuable null model that should be considered when responsive behavioral change models are proposed to explain observed epidemiological dynamics.

      I believe that this is an important result, especially in light of the explosion of adaptive behav- ior epidemiology that has accompanied the COVID-19 pandemic thanks to an unprecedented wealth of both epidemiological (e.g. case / hospitalization / death) and behavioral (e.g. Google Mobility) data (Nouvellet et al., 2021). Claims that responsive behavior explains observed epi- demiology will need to improve upon this null model in some way in order to be persuasive. My principal reservation about the paper is that the model is presented less as such a null model and more as a mechanistic explanation of observed COVID-19 dynamics. I did not find the case for this interpretation sufficiently convincing, for reasons I will explain below.

      The authors find a number of other interesting results, including that stochastically time-varying behavior can reduce the likely "overshoot" of the disease attack rate beyond the herd immu- nity threshold, and can produce states of "Transient Collective Immunity". These results are a properties of a previously-presented model developed by the same authors, in which individ- ual activity levels may vary in time but not necessarily according to a defined stochastic process (Tkachenko et al., 2021). In general, given that this paper builds on that work, I would encour- age the authors to be clearer about distinguishing their current results from their prior findings.

      The authors characterize the potential endemic state for a pathogen under their model (in the case that previously-exposed individuals can become once again susceptible on some timescale), and show that time-varying heterogeneous contact behavior again alters the dynamics of the approach to endemicity. Notably, they find that behavioral variation can reduce the amplitude of peaks and troughs on the way to endemicity, potentially avoiding stochastic extinction of the disease during troughs.

      The authors compare their analytical results to stochastic simulations based on the underlying stochastic process, and find good agreement. Finally, the authors fit their model to COVID-19 death data from United States geographical regions and compare predicted model trajectories to observed deaths.

      2.2 Key contribution of the paper

      In my view, the greatest strength of the paper is in providing a plausible null model for how adaptive behavior can modulate epidemiology even when it does not respond directly to disease, and in developing analytical results that give further insight into the origin and magnitude of these effects given the underlying model parameters.

      2.3 Concerns regarding the paper

      My principal concern about the paper is the implicit claim that the model explains the epidemi- ological patterns of COVID-19 in the United States during summer and fall 2020.

      The authors fit their model to US death data by estimating parameters related to the degree of mitigation as a function of time M(t), as well as some seasonality parameters affecting R0 as a function of time. It is not clear whether baseline R0 was also estimated, since it is not listed as a fixed.

      As the authors point out,monotonically increasing R0M(t) in a standard well-mixed SIR far from herd immunity would result in a single peak that overshoots the (ever-increasing) HIT. In the authors' fitted model, deaths in fact initially decline in the northeast and midwest before rising again, and the epidemic in the south displays two peaks separated by a trough.

      But I am not sure this is a particularly convincing demonstration of the correctness of a model as an explanation for the observed dynamics. Official distancing policies may have monotoni- cally become more lax over the period June 1 through to, e.g., the fall. But restrictions were tightened in winter in response to surges, and there was clear signal of behavioral response to incresasing transmission that seems unlikely to have been mere regression to the mean.

      In the model, the mitigation function is fitted; no actual data on deliberate versus randomly- varying behavior change is used. Given clear empirical signals of synchronous and delibate re- sponse to epidemiology, modulated by social factors (Weill et al., 2020), a persuasive demonstra- tion that consideration of random behavioral variation is necessary and/or sufficient to explain observed US COVID-19 dynamics would need to start from mobility data itself, and then find some principled way of partitioning changes in mobility into those attributable to random varia- tion versus deliberate (whether top-down or bottom-up) action.

      My other main concern is that the central result of transient epidemiological dynamics due to transient concordance of abnormally high versus low social activity-stems from the choice to model social behavior as stochastic but also mean-seeking. While I find this idealization plausi- ble, I think it would be good to motivate it more.

      In other words, the central, compelling message of the paper is that if collective activity levels sometimes spike and crash, but ultimately regress to the mean, so will transmission. The more that behavioral model can be motivated, the more compelling the paper will be.


      Bauch, C., d'Onofrio, A., & Manfredi, P. (2013). Behavioral epidemiology of infectious diseases: An overview. Modeling the interplay between human behavior and the spread of infec- tious diseases, 1-19.

      Epstein, J. M., Parker, J., Cummings, D., & Hammond, R. A. (2008). Coupled contagion dy- namics of fear and disease: Mathematical and computational explorations. PLoS One, 3(12), e3955.

      Fenichel, E. P., Castillo-Chavez, C., Ceddia, M. G., Chowell, G., Parra, P. A. G., Hickling, G. J., Holloway, G., Horan, R., Morin, B., Perrings, C., et al. (2011). Adaptive human behav- ior in epidemiological models. Proceedings of the National Academy of Sciences, 108(15), 6306-6311.

      Kermack, W. O., & McKendrick, A. G. (1927). A contribution to the mathematical theory of epidemics. Proceedings of the Royal Society of London, Series A, 115(772), 700-721.

      Nouvellet, P., Bhatia, S., Cori, A., Ainslie, K. E., Baguelin, M., Bhatt, S., Boonyasiri, A., Brazeau, N. F., Cattarino, L., Cooper, L. V., et al. (2021). Reduction in mobility and covid-19 transmission. Nature communications, 12(1), 1-9.

      Tkachenko, A. V., Maslov, S., Elbanna, A., Wong, G. N., Weiner, Z. J., & Goldenfeld, N. (2021). Time-dependent heterogeneity leads to transient suppression of the covid-19 epidemic, not herd immunity. Proceedings of the National Academy of Sciences, 118(17).

      Weill, J. A., Stigler, M., Deschenes, O., & Springborn, M. R. (2020). Social distancing responses to covid-19 emergency declarations strongly differentiated by income. Proceedings of the National Academy of Sciences, 117(33), 19658-19660.

      Yang, C. K., & Brauer, F. (2008). Calculation of R0 for age-of-infection models. Mathematical Biosciences & Engineering, 5(3), 585.

    1. Joint Public Review:

      Strengths & Overall Comments:

      This behavioral study aims to provide an account of the spontaneous behavior of mice as they learn to explore a novel maze in search of a water reward. The authors analyze the trajectories of mice as they adapt to the labyrinth with particular focus on decisions taken at nodes and T junctions. They describe extremely rapid route learning to home and discontinuous exploratory learning or 'light bulb' moments as evident by instantaneous improvements in navigation performance. The authors capture most of the variance in their overall data with a predictive Markov models that could account for the much subsequent actions of the mouse as it moves from one node to the next. The study should be important to anyone who spends their time thinking about decision-making in mice. It highlights the importance of considering ethologically relevant tasks for understanding decision making in rodent species.

      In this submission, the authors introduce a new experimental paradigm for the study decision making in naturalistic contexts, presenting an opportunity to observe these dynamics away from the standard two-alternative-forced-choice paradigm. The application of modern tracking and posture analysis to maze exploration by rodents generates rich and interesting data, and allows the authors to do their experiments with many animals, and with nearly no human interference or specific instructions. The design of the maze is clever, using an underlying tree-like structure (with the tree folded so it precisely and fully occupies a rectangular area), and relatively deep (6 branching points from main trunk to a leaf node). Mice explore this voluntarily, and water-restricted mice learn to find water rewards at a leaf of the maze. The authors thus study truly voluntary and highly interesting complex behavior, and in a high-throughput way. By studying the dynamics of a mouse in a maze, the authors perform a careful set of analyses, describing discontinuous learning dynamics and the effects of history on decision-making. These results should be of interest to a wide group of behavioral neuroscientists that are attempting to understand the neural basis of how animals make decisions in complicated natural environments.

      The data set released with this submission will be of broad use to the community, and we would not be surprised to see dozens of papers using it moving forward.

    1. Assignment

      start giving sample works articles that they can write on Follow suggestions in the doc aRGUMEN, DESCRPITIVE, NARRATVIE Only practice for this month July- one text- 1st, 2nd, 3rd draft each draft will be sent to us - Word doc with all revision history

      Mrinlain needs help with summary wriitng Akshath beats around the bush Avani - is good

      9 grade language- poetry- 1 class

    1. Reviewer #1 (Public Review):

      This work is aiming at the characterization of the molecular and kinetic mechanism of how three members of the SLC6 family of transporters, namely for dopamine (DAT), norepinephrine (NET), and serotonin (SERT), transport substrate across the membrane, and how the transport process is affected by cations. The authors use electrophysiology and sophisticated rapid solution exchange methods, in conjunction with fluorescence recordings from single cells, to correlate flux (from fluorescence) with electrical activity (from currents).

      The strength of the methods is based on the application of a kinetic method with high time resolution, allowing the isolation of fast processes in the transport mechanism, and their modeling using a kinetic multistep scheme. In particular useful is the combination with fluorescence recording from single cells, which allows the authors to measure flux and current in the same cell under voltage clamp conditions. This is an elegant approach to get information on the voltage dependence of substrate flux, which is difficult to obtain with other methods. As to the strength of the results, the data are generally of high quality, showing the kinetic and mechanistic similarities and differences between the three transporters under observation. Another strength is that the results are quantitatively represented by kinetic simulations, which appear to fit the experimental data well.

      The major weakness of the research is related to interpretation of the experimental results. While the authors propose a unified K+ interaction mechanism for the three transporters, DAT, NET and SERT, the proposed K+ association/dissociation mechanism is 1) highly unusual, and 2) not unique in the ability to explain the experimental data. As to point 1), the DAT mechanism (Fig. 7A) proposes a sequence of intracellular K+ association and dissociation steps. Since the intracellular [K+] remains constant, such a sequence requires a change of affinity for K+, which is initially high when K+ associates (33 microM according to the provided rate constants) and then has to be low for K+ dissociation (3.3 mM). Such an affinity change requires input of free energy, to promote K+ dissociation. From the provided rate constants and at room temperature this free energy change can be approximated as 11.4 kJ/mol. This is a large energy amount, in fact larger than what is stored in the physiological concentration gradient for one Na+ ion as a driving force for transport. It appears that the transporter would waste a lot of energy for no apparent benefit, with a futile K+ association/dissociation cycle, that would just generate heat.

      Therefore, while the authors have achieved their aim of quantitatively assessing transporter function and thorough description by a kinetic mechanism, their final proposed mechanism does not support all of the conclusions because it is by far from unique in being able to explain the data (point 2) above). While this may be true for other transport mechanisms proposed in the past, the mechanism proposed here is somewhat odd with respect to energy requirements. Thus, it would require extraordinary experimental proof to propose it in exclusion of other, maybe more plausible mechanisms.

      Despite these shortcomings, the potential impact of the work is high, because a unifying theory of cation interaction and stoichiometry of the monoamine transporter members of the SLC6 family has been missing in the literature. In addition, the elegant method of combining single cell electrophysiology and fluorescence flux measurements is impactful, especially in the whole cell recording method, allowing the control of intracellular ionic composition.

    1. Reviewer #1 (Public Review):

      In this manuscript, Mouat et al. investigated the contribution of viral infection to the severity of arthritis in mice. Epstein-Barr virus (EBV) infection is associated with rheumatoid arthritis (RA). By assessing arthritis progression in type II collagen-induced arthritis (CIA) induced mice with or without latent 𝜸HV68 (murine gammaherpesvirus 68) infection, authors showed that latent 𝜸HV68 exacerbates progression of CIA. Additionally, profile of immune cells infiltrating the synovium was altered in 𝜸HV68-CIA subjects - these subjects presented with a Th1-skewed immune profile, which is also observed in human RA patients. Assessment of immune cells in the spleen and inguinal lymph nodes also showed that latent 𝜸HV68 infection alters T cell response towards pathogenic profile during CIA. Lastly, authors showed age-associated B cells (ABCs) are required for the effects of latent 𝜸HV68 infection on arthritis progression exacerbation. Findings presented in the manuscript provides important insights and resource to clinical RA research.

      There are some statistical analyses that need to be updated for completeness and appropriateness of use. In addition, the authors will need to highlight that all analyses were conducted in young mice, whereas RA occurs in aged individuals.

    1. Reviewer #1 (Public Review):

      This work investigates the structure and maintenance of the blood brain barrier (BBB) in Drosophila. Previous work from this lab and others have shown that the BBB is composed of a specialized type of glia called the subperineurial glia (SPG), which enwrap the entire central nervous system (CNS). Furthermore, they previously identified the Moody G protein coupled receptor (GPCR) as being specifically expressed in SPG and required for BBB formation and maintenance.

      Here they show that Moody protein is localized to the apical membrane domain (facing the CNS) while Protein Kinase A (PKA) is localized to the complementary basal membrane domain (facing the hemolymph of the body cavity). Not only do Moody and PKA have non-overlapping subcellular localization, but genetic interactions show that Moody and PKA act antagonistically in BBB maintenance. They find that both too little and too much PKA activity disrupts the BBB.

      The authors also generate a serial section Transmission Electron Microscopy (TEM) volume to analyze wild type, PKA hyperactivity, and PKA loss of function animals. They find that loss of BBB function is sue to gaps in the BBB, rather than thinning of the BBB. This conclusion is somewhat weak, however, because they did not analyze a genotype that has thin BBB structure but normal BBB function.

      Their work raises the question of how does PKA promote BBB integrity. They analyze two potential PKA targets (myosin light chain kinase [MLCK], and Rho1), finding that reduced Moody levels lead to disrupted subcellular localization of both proteins in SPG; that reducing MLCK or Rho1 levels causes failure of BBB function; and that reducing Moody can rescue these phenotypes. They conclude that Moody acts antagonistically to PKA/MLCK/Rho1 to establish distinct apical and basal membrane domains in SPG which are required for BBB function.

    1. Reviewer #1 (Public Review):

      The paper details a whole genome re-sequencing of 310 accessions of quinoa. This provides a good glimpse of diversity in this orphan crop, plus the GWAS studies are able to help provide the foundations for identifying key genes in quinoa variation. This will certainly advance our knowledge of this increasingly important orphan crop.

      1) One issue that permeates the entire paper is that the analysis is fairly basic and the authors do not make full use of the data. The analysis of population diversity is restricted to PCA, ADMIXTURE and phylogenetic analysis. It would probably broaden the impact of the paper if they can do deeper analysis of quinoa diversity, maybe looking at demographic history, looking at selection of highland vs. lowland, etc.

      2) There is a focus on the rapid LD decay, which the authors attribute to the short breeding history and low selection. That seems like a stretch to make this conclusion based solely on LD decay. As they point out, many other factors could account for this, and the authors should provide other lines of evidence to draw this conclusion.

      3) The GWAS analysis is good and does provide a good foundation for quinoa genetics. The authors discuss possible candidate genes is these GWAS regions. For the thousand seed weight, the relative small span of the GWAS peaks allows for localization of just a few genes in the GWAS region (CqPP2C5 and the CqRING). The GWAS associated with flowering time is larger - 1 Mb with 605 genes - but the authors focus on the GLX2-1 gene. This is again a stretch, as the large region precludes narrowing the candidate list unless there was a compelling mutation (for example a deletion or insertion of a major flowering time gene).

    1. Reviewer #1 (Public Review):

      Overall the analysis is conducted well and is convincing. The characterisation of neural stem cells using 7 markers as well as their morphology and position, is particularly thorough.

      My main criticism is that the study purports to address the effect of aging but the ages analysed only range from 2 months to 12-months. As 12 month-old mice are still middle aged, it is difficult to conclude anything about the process of ageing, which is usually studied in much older mice (18-24 months). Indeed, some of the changes that the authors associate with an "ageing phenotype" appear in microniches already in 2 month-old mice and are predominant at 6 months. This suggest that the authors are documenting the transition from an immature/juvenile state, which is predominant in 2 month-old mice, to a mature/adult state, which already appears at 2 months but becomes predominant at 6 and 12 months. Importantly, this adult state, including the reduced number of neural stem cells, might not be dysfunctional but on the contrary, may perform very well its role of producing small numbers of new neurons as required during adult neurogenesis.

      Another, lesser concern is that, based on antibody staining performed in tissues from 2-month and 12-month-old mice, conclusions are made on the different expression levels of HOPX, MT3 and LaminB1 analysed at different ages. This assumes that the efficiency of antibody staining is the same in different samples analysed in parallel but this is not shown.

    1. Joint Pubic Review:

      Church et al. carry out a mechanistic study focused on regulation of PKA activity at a specific multiprotein complex nucleated by the scaffolding protein AKAP79. The manuscript presents a rigorous biochemical approach combined with computational modeling to address fundamental issues related to PKA signaling. This is a very important but complex system and the authors have nicely addressed it using in vitro approaches. The in vitro data provide evidence that suggests that the phosphatase calcineurin (CaN), by dephosphorylating the PKA regulatory subunit type II (RII), promotes rapid re-association of the PKA catalytic subunit (C) to RII, leading to PKA inactivation. The model proposed is that this modality of PKA inactivation takes place selectively at the multiprotein complex organized by AKAP79, where CaN, PKA and PKA phosphorylation targets are co-localized: the proximity of CaN to RII at the AKAP79 complex would enhances the efficiency of RII dephosphorylation by one order of magnitude, allowing fast re-association of C and RII subunits. This would reduce the proportion of free C subunits and therefore the level of local PKA substrate phosphorylation. Using purified the FRET reporter AKAR4 as a reporter for PKA activity, they further confirm that the level of phosphorylation of this PKA target at a given cAMP concentration depends on the ability of CaN to interact with AKAP79. Based on these findings the authors conclude that CaN anchored to AKAP79 dephosphorylates AKAP79 anchored RII, leading to fast recapturing on C and inhibition of PKA catalytic activity. They then create a kinetic model for this process where cAMP and calcium are working in opposing ways. Notably, the authors also provide an estimate for the concentration of RII subunits in the hippocampal CA1 neuropil layer and find that this falls within the range at which CaM efficiently dephosphorylated RII in vitro.

      In the context of compartmentalized cAMP/PKA signaling, this mechanism would provide yet another regulatory feature to ensure specific control of target phosphorylation at individual subcellular locations. For example, in dendritic spines PKA regulates long-term depression (LTD) of CA3-CA1 hyppocampal synapses via phosphorylation of AMPA-type glutamate receptors, which is facilitated by simultaneous interaction of receptor and kinase with AKAP79. In this context, at a given cAMP concentration, CaN-dependent inhibition of PKA activity would selectively attenuate AMPA phosphorylation and LTD, while PKA may still be able to phosphorylate targets at other sites.

      The paper presents very clear biochemical data but can be further strengthened by some additional attention to the following:

      While the in vitro data convincingly demonstrate the requirement for CaN to be anchored to AKAP79 for efficient dephosphorylation of RII and confirm that phosphorylation of RII at S98 results in more active PKA, the requirement for RII to be anchored to AKAP-79 for this regulation is not investigated, leaving open the possibility that the more efficient dephosphorylation of RII in vitro may be due increased catalytic activity of CaN when the phosphatase is associated to AKAP79c97.

      The authors show convincingly that the pRII subunits are better substrates when the AKAP scaffold is present. However, they need to address the relevance of having the enzyme (CN) and the substrate (pRIIb holoenzyme) scaffolded to the same complex so that diffusion is no longer a rate-limiting factor in the catalytic event. Are MM kinetics relevant for this process? This is a single molecule event that does not necessarily require that the product be released. Instead the product is returned to the active site of the cleft of the C-subunit in the holoenzyme:CN complex where in the cell it is rapidly re-phosphorylated. Also the authors could show what happens when you have a 1:1 concentration of CN and pRIIb. Following this single transfer event does not require dissociation of the holoenzyme and is likely to be more physiologically relevant.

      Do the authors know if calcium vs. Mg influences this process? Calcium stabilizes the product whereas Mg stabilizes the substrate in the case of the kinase. If calcium levels are high following release of the phosphate, would this tend to keep the phosphorylated holoenzyme in a more inhibited state until calcium went down and cAMP went up?

      This process will take place at membranes which may play a significant role in determining whether the A-subunit is released into solution or not.

      Another important question to consider is whether it is even necessary to dissociate the holoenzyme complex at all. Is it sufficient, for example, to simply unleash the linker region of the RII subunit and thereby open up the active site cleft of the C-subunit? Since the tail of the channel is also tethered nearby, it is perfectly reasonable to catalyze this event without dissociating the complex especially given earlier data by Wang, et al showing that the holoenzyme is very stable even when the key arginines in the inhibitor site are mutated. The same motif has access either to the active site of the C-subunit or to the active site of calcineurin in a cAMP/Ca++ dependent cycle. This leaves the phosphorylated tail of the channel free to be dephosphorylated by other phosphatases that are also tethered to AKAP79 and leaves CN committed to recycling of the RII holoenzyme. In principle this does not require dissociation of the RII holoenzyme if CN is tethered nearby. This is a very fundamental question.

      One point that is not addressed in the study and is important for the interpretation of the results is whether interaction of CaN with AKAP79c97 increases CaN activity per se, such that the more effective dephosphorylation of RII is not due to the physical proximity of CaN to RII on the AKAP but to a more active CaN. This could be addressed by testing the dephosphorylation rate of a phospho-substrate other than 32P-RII, in the absence and in the presence of AKAP79c97 or by repeating the experiments shown in Fig 1 in the presence of the AKAP79c97 variant where the PKA (391-400) anchoring site has been removed.

      AKAR4 is a reversible reporter of PKA activity, so it is surprising that the authors find that its phosphorylation is not affected by CaN. One possibility is that AKAR4 is not a good substrate for CaN. However, multiple studies have shown that AKAP4 can effectively be dephosphorylated. The ability of CaN to dephosphorylate AKAR4 should be investigated further to demonstrate more robustly that, in the in vitro experimental conditions used, the observed reduced phosphorylation of AKAR4 is due to less active PKA rather than more active CaN. This could be done, for example, by repeating the experiments summarized in Figure 3-figure supplement 1C & D using a different phosphatase, to ascertain that the experimental conditions allow for detection of AKAR4 dephosphorylation.

      One limitation of the in vitro work is that only AKAR4 is used to measure the level of PKA dependent phosphorylation. AKAR4 is not a natural substrate for either PKA or CaN and the accessibility of the phosphorylation site to these enzymes may be different than for physiological targets. In addition, AKAR4 is not anchored to AKAP79 and may not be the ideal reporter to investigate the effects of CaN-dependent regulation of PKA targets associated to AKAP79.

      Stoichiometry of free RII subunits. The authors have shown convincingly that the RII subunits in particular are present in excess of the C-subunits, and this has led to some new concepts for PKA signaling. There are two questions that need to be addressed here. Perhaps in the discussion is adequate but they do need to be addressed. First is whether there are separate pools of free RII subunits and holoenzymes within single cells. This is essential for the model of PKA signaling taking place in the presence of a 10-fold excess free RII-subunits. Are the dissociated R-subunits in the same subcellular location? Second is whether the free RII subunits are bound to cAMP. The cAMP-free subunits are noticeably less stable and degraded more rapidly that the holoenzymes so are these free R-subunits bound to cAMP? If not, are they bound to something else that keeps them stable? RII subunits do not form membrane-less puncta as was recently reported in Cell by Zhang but is there some other mechanism that allows for the sequestration of large amounts of free RII subunits?

      Do you need to saturate all four sites to have an active C-subunit that can phosphorylate the tail of a channel? This relates to the question above. Perhaps this would not be measured by the AKAR4 reporter but could it be sensed if AKAR4 were fused to the tail of AKAP79 so that it would be tethered close by similar to the tail of the channel.

      Stoichiometry of two calcineurins vs. one RII holoenzyme or one? The authors need to address this stoichiometry question more rigorously. It is quite fundamental for their assays. Does the computational model provide any ability to ascertain stoichiometry of the productive complex?

      While it is true that neither S/A or S/E will be substrates for CN, they will in fact have a different effect on the RII holoenzyme. Ser/Ala and Ser/Glu mutants are, in principle, quite different in terms of their accessibility to the active site of the C-subunit vs. the active site of CN. The Ser/Ala mutant, for example, should be locked into the active site of the C-subunit, and this would be presumably strengthened by ATP since this is a pseudosubstrate. Does the affinity for C-subunit change in an ATP-dependent manner? The Ser/Ala mutant should be a good inhibitor that cannot be regulated by phosphorylation. It could be activated by high concentrations of cAMP but not by the cAMP signaling that is being described here. The Ser/Glu mutation would favor docking into the active site of CN but would be trapped in this state as it also could not be dephosphorylated. Is this consistent with the models proposed by the authors?

      The in vivo work to assess the physiological relevance on this proposed new modality of PKA regulation is very preliminary. By overexpressing S97A and S97E mutants of RII in hippocampal neurons the authors confirm that modulation of PKA sensitivity to cAMP via RII phosphorylation affects spine density. However, no experimental data directly assess the role of CaN-dependent dephosphorylation of RII at the AKAP79 complex and there is no evidence that this mechanism regulates AMPA phosphorylation or phosphorylation of other physiologically relevant targets. Thus, the caveats that are associated with the system and in particular the physiological relevance of the analyses needs to be addressed. Conclusions based on the preliminary 'in cell' data on physiological relevance should be appropriately tempered.

    1. Reviewer #1 (Public Review):

      The authors try to shed light on how plant stem cells located in a ring-like structure in the (the procambial cells or cambium) can generate two distinct differentiated tissues, one filling the interior of the ring (the xylem) and the other one surrounding the ring (the phloem). To achieve this goal, the authors propose different models increasing in complexity, and perform a series of comparisons between the model outcomes and experimental data in the Arabidopsis hypocotyl.

      This work seems to provide for the first time a computational framework to model the radial formation of the cambium, xylem and phloem in the hypocotyl. Some of the features of the wild type and mutants could be qualitatively recapitulated, such as the radial organization of the xylem, cambium and phloem in wild type, and a striking phenotype upon the overexpression of CLE41 transgene.

      Although this work is very well written and understandable at the introduction, when paying careful attention to the presented results, there are different aspects that would require further work and investigation, on both experimental and modelling sides:

      The authors chose to study different models increasing in complexity, reaching a more complete model (Model 3, Figure 5A-D) that the authors claim it is recapitulating the experimental data and the explored experimental perturbations (Figure 5E-F). This model is substantially more complex than Model 1 and Model 2, and it is difficult to understand all the claims by the authors, and the radial pattern formation capabilities of it. Yet, a feature that is clear to the eye, both in the pictures and in the movies, is that this model seems more likely to present a front instability of the cambium front progression, disrupting the radial organization of the different tissues (see Figure 5B), which does not seem to happen in the wild type hypocotyl from Arabidopsis. This effect is even more extreme when looking at the pxy mutant (Figure 5F) and when the xylem cell wall thickness is explored through the simulations (Figure 6). The authors claim this model is able to recapitulate a basic feature of the pxy mutant, which is the fact that the distal cambium appears in patches. Although these patches appear in the simulations, this effect in the model might be produced by the instability of the cambium front progression itself, which might be fundamentally different from what happens in the experimental data. In the experimental data, the PXYpro:CFP cambium does not seem to present such front instability, but rather is the xylem that gets fragmented. To make a link between the Model 3 and the pxy mutant, a careful study of the different stages of this phenotype could be useful to do, both on the modelling and experimental side.

      The authors have a parameter search strategy based on matching the proportion of cell types in Model 3. I am wondering how effective is this strategy in a system where these features are evolving in time, especially in Model 3, which seems to present a front instability. Moreover, this strategy does not tell anything about the model robustness for recapitulating the different features of the pattern.

      In the last model, the authors try to link the cell wall thickness with the radiality of the divisions. Although the idea of looking at the division trajectories seems interesting, more clarity is needed to see how helpful is the radiality measure, and perhaps a better measure is needed - note that the proliferation trajectory in Figure 6C might have the same amount of ramifications than in Figure 6B, and therefore, effectively speaking, the amount of periclinal divisions might be the same in both cases. The authors claim that the increase of xylem thickness contributes in having a more radial growth, but this could be related to the cambium front instability, which seems to be more pronounced as well for higher xylem thickness.

      On the experimental side, the claims about the proximal and distal cambium, together with the cell proliferation data are not very well supported with the presented data in Figures 2, 3A and S1. Moreover, these different figures seem to show different behaviors - are these sections at different stages of the hypocotyl? Also, seeing more of the H4 marker in a region of the tissue not necessarily indicates a higher proliferation rate (it could also simply be that cells are more synchronized in the S phase in that region of the cambium, and/or the cell cycle lasts for longer in that part of the tissue). A quantification and the proper repeats to support these claims is lacking. A quantitative and more extensive study of the pxy mutant would enable a better comparison with the simulated model. Is there PXYpro:CFP expression between the fragmented xylem?

      This work might help progress in the field of understanding radial patterning in plants. The introduction and the first models could attract a more general plant audience, but once the models increase in complexity, the narrative and presented results are more relevant to those scientists more specialized in xylem and phloem formation.

    1. Reviewer #1 (Public Review):

      Mitochondria hyperfission during ishchemia or hypoxia is generally thought as an index of the severity of cytotoxicity, but this group originally identified Cx43 truncated peptide, GJA1-20K, which induces cardioprotection against ischemia/reperfusion injury in mice through promoting mitochondrial fission. Their proposal that GJA1-20K induces mitochodnrial fission independently of Drp1 activation is interesting, but their indirect results are weak to support it.

    1. Reviewer #1 (Public Review):

      Dengue is the most common arboviral infections in humans. Better tools to effectively triage patients at risk for severe dengue are urgently needed to optimize use of healthcare resources. This well written manuscript by Nguyen Lam Vuong and colleagues assessed the associations of a panel of blood biomarkers on day 1-3 from symptom onset with the development of severe or moderate (S/MD) dengue in a large cohort of children and adults. Ten candidate biomarkers were selected, each representing important pathogenic processes in dengue. Overall, higher concentrations of the biomarkers increased the risk for S/MD dengue. Important differences between adults and children were found for the performance of several biomarkers. The performance of the individual biomarkers, as well as the best combination was assessed for children and adults.

      Strengths: Particular strengths of this study are the uniqueness of the prospective cohort with a large number of participants from different countries and the availability of blood samples early in the course of infection.

      Other strengths include the enrolment of both children and adults, which is important given the observed differences in dengue pathology, the consistent data collection and the use of standardized outcome definitions.

      The authors selected the candidate biomarkers based on earlier pathogenesis studies, reflecting different pathogenic pathways in dengue (e.g. activation mononuclear cells, vascular pathology).

      State-of-the-art statistical modelling was used to assess the performance of the biomarkers.

      Weaknesses: The main aim of the study is to identify biomarkers that predict S/MD dengue early in the course of dengue. This requires biomarkers of which the levels change early after symptom onset. However, levels of several of the biomarkers did not change markedly between the two time points (early vs late), suggesting that the levels of these biomarkers had not yet changed on day 1-3, thereby questioning their use as 'early biomarkers'. The authors selected the biomarkers based on earlier pathophysiology studies. An alternative approach might have been to first measure a larger set of candidate biomarkers in a selection of patients and select only those biomarkers showing a clear change in the early phase.

      The predictive values of many of the biomarkers was only modest or absent. In addition, some of the findings appear a bit counterintuitive. Examples include the trend of the association of IP-10 with S/MD dengue that changed from positive to negative in the global model, and the opposite trends of some of the biomarkers (e.g. IL-8, ferritin) in adults and children. The authors acknowledge the existence of differences in dengue pathology between children and adults, but could discuss the possible biological reasons in more detail. For example, why would specifically IL-8 or ferritin have an oppositie effect in children and adults.

      The study does not include a validation cohort. The authors conclude that their findings 'assist the development of biomarker panels for clinical use.' Can the authors put into perspective the performance of their current combined biomarker panel to rule out S/MD dengue.

      Overall, the authors show convincingly in a unique cohort that biomarkers can be helpful to triage dengue patients already in the first days from symptom onset. Identification of the best biomarkers for this goal, validation in other cohorts, and a better understanding of differences between children and adults are required before such panels can be introduced in daily clinical practice.

    1. Reviewer #1 (Public Review):

      This report investigates spontaneous neural activity in the spinal cord of healthy adult male Sprague-Dawley rats under anesthesia. Urethane or isoflurane were used, and the effects were compared.

      This manuscript is presented as a research advance that builds upon a 2014 eLife publication. It aims to address unresolved questions regarding the nature of spontaneous neural activity in the cord that give rise to observed resting state spinal cord networks in humans (and other species).

      The similarity of results across anesthetic agents is important and I agree with the authors' conclusion that this provides strong evidence for persistent synchronous discharges between spinal cord regions during unconsciousness.

      Finally, the authors do an appropriate job of describing the weaknesses of the study and how future experiments may continue this line of investigation.

    1. Reviewer #1 (Public Review):

      There are very few studies on the spatial integration of color signals of V1 receptive fields, which is a striking gap in knowledge given the importance of color to primate vision and the powerfulness that spatial analysis of luminance contrast integration has proven for understanding how V1 works. This paper helps fill this major gap in knowledge. The main take home is that double opponent cells and simple cells are more likely to be linear in how they integrate signals across their receptive fields than a sample of non-double-opponent/non-simple cells. This conclusion is consistent with the limited data presently in the literature, and I wonder if further analysis of the rich dataset could uncover some deeper insights.

    1. Reviewer #1 (Public Review):

      The phase of a signal (similar to its amplitude) is a significant and informative feature that helps for a better representation of time-series data. In Neuroscience, and in the context of neural oscillations, the phase of neural signals (for example EEG and LFP) plays an important role in understanding mechanisms underlying brain rhythms. The author of this paper proposed a novel approach to track the phase of neural signals in real-time. This approach is inspired by [Matsuda and Komaki, 2017] and employs the well-known state-space modeling framework. Using several synthetic data, it was shown that the proposed approach outperforms other methods in the literature which are based on band-pass filtering (not appropriate for broadband rhythms). The simulation studies were designed to demonstrate the strength of the state-space phase estimation approach vs. two recent methods in the context of common confounds such as broadband rhythms, phase resets, and co-occurring rhythms. As well, the state-space phase estimator was applied to in-vivo data including two datasets: (1) rodent LFP and (2) human EEG. Furthermore, the authors made their proposed method available online in the form of MATLAB code as well as a ready-to-use plug-in for the OpenEphys acquisition system. This effort is very much appreciated as it provides the code available for further theoretical and experimental studies.

      While the proposed method is very novel and timely, it would be helpful for the authors to: (i) consider the impact of noise in the phase estimation, (ii) describe specifications of the Kalman filter and its robustness, and (iii) consider the performance of the estimated phase relative to other methods.

    1. Reviewer #1 (Public Review):

      The work by Fujimori et al. addresses the role of downstream WNT signaling in thymus epithelial cell (TEC) differentiation and function. A TEC-specific beta5t-cre driver allowed for the generation of gain of function (GoF) or loss of function (LoF) mouse models. The specificity of the beta5t-cre driver system was key in allowing the authors to focus on TEC effects. Of note, the LoF of beta-catenin showed a smaller thymus with fewer cortical TEC, but generally no changes in the thymus morphology or in the ability to support normal percentages of thymocyte subsets. These results clearly establish that WNT signaling plays a minor role in TEC differentiation and function. Nevertheless, the GoF approach led to thymus dysplasia with a loss of TEC identity, due to a loss of FOXN1 expression, as well as a failure to support T cell development. These results point to a role for WNT signaling in inducing the TEC differentiation into other non-T-cell-development-supporting epithelial subsets.

    1. Reviewer #1 (Public Review):

      This is an excellent manuscript in which Bartel and colleagues use an abundance of approaches to provide compelling evidence relevant to the coupling between poly(A)-tail length and translational efficiency. Without reiterating the results, the data are convincing and the paper is clearly written. Any concerns are too trivial to articulate.

    1. Reviewer #1 (Public Review):


      1) The model structure is appropriate for the scientific question.

      2) The paper addresses a critical feature of SARS-CoV-2 epidemiology which is its much higher prevalence in Hispanic or Latino and Black populations. In this sense, the paper has the potential to serve as a tool to enhance social justice.

      3) Generally speaking, the analysis supports the conclusions.

      Other considerations:

      1) The clean distinction between susceptibility and exposure models described in the paper is conceptually useful but is unlikely to capture reality. Rather, susceptibility to infection is likely to vary more by age whereas exposure is more likely to vary by ethnic group / race. While age cohort are not explicitly distinguished in the model, the authors would do well to at least vary susceptibility across ethnic groups according to different age cohort structure within these groups. This would allow a more precise estimate of the true effect of variability in exposures. Alternatively, this could be mentioned as a limitation of the the current model.

      2) I appreciated that the authors maintained an agnostic stance on the actual value of HIT (across the population & within ethnic groups) based on the results of their model. If there was available data, then it might be possible to arrive at a slightly more precise estimate by fitting the model to serial incidence data (particularly sorted by ethnic group) over time in NYC & Long Island. First, this would give some sense of R_effective. Second, if successive waves were modeled, then the shift in relative incidence & CI among these groups that is predicted in Figure 3 & Sup fig 8 may be observed in the actual data (this fits anecdotally with what I have seen in several states). Third, it may (or may not) be possible to estimate values of critical model parameters such as epsilon. It would be helpful to mention this as possible future work with the model.

      Caveats about the impossibility of truly measuring HIT would still apply (due to new variants, shifting use & effective of NPIs, etc....). However, as is, the estimates of possible values for HIT are so wide as to make the underlying data used to train the model almost irrelevant. This makes the potential to leverage the model for policy decisions more limited.

      3) I think the range of R0 in the figures should be extended to go as as low as 1. Much of the pandemic in the US has been defined by local Re that varies between 0.8 & 1.2 (likely based on shifts in the degree of social distancing). I therefore think lower HIT thresholds should be considered and it would be nice to know how the extent of assortative mixing effects estimates at these lower R_e values.

      4) line 274: I feel like this point needs to be considered in much more detail, either with a thoughtful discussion or with even with some simple additions to the model. How should these results make policy makers consider race and ethnicity when thinking about the key issues in the field right now such as vaccine allocation, masking, and new variants. I think to achieve the maximal impact, the authors should be very specific about how model results could impact policy making, and how we might lower the tragic discrepancies associated with COVID. If the model / data is insufficient for this purpose at this stage, then what type of data could be gathered that would allow more precise and targeted policy interventions?

      Minor issues:

      -This is subjective but I found the words "active" and "high activity" to describe increases in contacts per day to be confusing. I would just say more contacts per day. It might help to change "contacts" to "exposure contacts" to emphasize that not all contacts are high risk.

      -The abstract has too much jargon for a generalist journal. I would avoid words like "proportionate mixing" & "assortative" which are very unique to modeling of infectious diseases unless they are first defined in very basic language.

      -I would cite some of the STD models which have used similar matrices to capture assortative mixing.

      -Lines 164-5: very good point but I would add that members of ethnic / racial groups are more likely to be essential workers and also to live in multigenerational houses

      -Line 193: "Higher than expected" -> expected by who?

      -A limitation that needs further mention is that fact that race & ethnic group, while important, could be sub classified into strata that inform risk even more (such as SES, job type etc....)

    1. Reviewer #1 (Public Review):

      The gist of this work is that the simple concept of a solubility product determines a threshold for phase separation, thereby enabling buffering even in systems where phase separation is driven by heterotypic interactions. The solubility product or SP is determined by the number of complementary interaction sites and the coordination number i.e., the number of bonds one can make per site.

      The work appears to be motivated by two questions: Are concentrations buffered in systems where heterotypic interactions drive phase separation thereby negating the presence of a rigorously definable saturation concentration? This question was motivated by work from Klosin et al., showing how phase separation can enable buffering of noise in transcription. They relied on the concept of a saturation concentration. In a paper that followed a few months after, Riback et al., showed that the concept of a saturation concentration ceases to exist, as defined for systems where phase separation is driven purely by homotypic interactions. This was taken to imply that the formation of multicomponent condensates via a blend of homotypic and heterotypic interactions causes a loss of buffering capacity afforded by phase separation. The second question motivating the current work is the apparent absence of a theoretical framework for "varying threshold concentrations" in systems governed by heterotypic interactions.

      Using two flavors of simulations, the authors propose that the SP sets an upper limit on the convolution of concentrations that determine phase separation. They show this via simulations where they follow the formation of clusters formed by linear multivalent macromolecules and monitor the emergence of a bimodal distribution of clusters. In 1:1 mixtures of multivalent macromolecules they find that SP sets a threshold beyond which a bimodal distribution of clusters emerges. The authors further find that SP sets an upper limit even in systems that deviate from the 1:1 stoichiometry.

      The authors proceed to show that the SP is influenced by the valence of multivalent macromolecules. They also demonstrate that short rigid linkers can cause an arrest of phase separation through a so-called "dimer trap" reminiscent of the "magic number" postulate put forth by Wingreen and colleagues.

      Is the work significant, novel, and timely? Effectively the authors propose that the driving forces for phase separation can be distilled down to the concept of a solubility product. Given prior knowledge of the valence, coordination number, and affinities can one predict concentration thresholds for phase separation? The authors suggest that this can be gleaned from either network based simulations, which are very inexpensive, or through more elaborate simulations. They further propose that it is the solubility product that sets the threshold.

      It is worth noting that the authors are quantifying what is known in the physical literature as a percolation threshold. The seminal work of Flory and Stockmayer dating back to the 1940s showed how one can calculate a percolation threshold by taking in prior knowledge of valence, coordination numbers, and affinities whilst ignoring cooperativity. These ideas have been refined and advanced in several theoretical contributions by various labs. While none of the papers in the physical literature use the concept of a solubility product, they rely on the concept of a percolation threshold because the transition to large, system-spanning clusters is a continuous one and it is debatable if this is a bona fide phase transition. Rather it is a topological transition.

      As for novelty, unfortunately the authors disregard prior work that showed how linker length impacts local vs. global cooperativity in phase transitions that combine phase separation and percolation. Ref. 23 is the work in question and it is mentioned in passing, even though the contributions here are entirely a redux.

      The concept of a solubility product, introduced here to model / understand phase behavior of multivalent macromolecules, is an interesting and potentially appealing simple description. It might make the understanding of phase transitions more accessible, but it has problems: (a) it does not define phase separation; rather it defines percolation transitions; (b) without prior knowledge of the relevant quantities, the solubility product cannot be readily inferred, even from simulations, although one can scan parameter space to arrive at predictions regarding the apparent valence and coordination numbers. (c) the solubility product does not tell us much about properties of condensates, interfaces, or the driving forces for phase transitions that are influenced by the collective effects of interaction domains / motifs and spacers.

      Finally, as for the absence of a theoretical explanation for the apparent loss of buffering in systems with heterotypic interactions, the authors would do well to see the work of Choi et al., published in PLoS Comput. Biol. in 2019. Figure 12 in that work clearly establishes that the concentrations of A and B species in the coexisting dilute phase are set by the slopes of tie lines - the lines of constant chemical potential. These slopes are set by the relative strengths of homotypic vs. heterotypic interactions, and to zeroth order, that is the physical explanation.

      Overall, the two interesting observations are that the percolation threshold can be cast as a solubility product and that this product sets an upper limit on joint concentration thresholds for phase separation, even in systems with heterotypic interactions, thereby rescuing the concept of buffering.

    1. Reviewer #1 (Public Review):

      The authors aimed to develop cell-permeable small molecule probes that can monitor the activity of SARM1, an enzyme that hydrolyzes NAD+ and is thought to be important for axon degeneration. They successfully achieved this goal using the base exchange activity of SARM1 to make a donor-π-acceptor type of fluorophore. The best probe described in the manuscript is PC6. A number of experiments were carried to rigorously test that the probe works as expected. PC6 has a number of nice features. It is cell permeable, gives much stronger signal than any other probes known for SARM1, is specific for SARM1 and does not detect the activity of CD38 (another enzyme that has similar activity), and allows detection of endogenous SARM1 activation in neurons.

      Using this probe PC6, the authors was able to monitor SARM1 activity in neurons treated with vincristine and demonstrated that SARM1 activation precedes axon degeneration and is important but not sufficient for axon degeneration. Most importantly, using this probe to monitor SARM activity, they screened a library of about 2000 drug molecules and discovered that a hypertension drug, nisoldipine, could inhibits SARM1. Surprisingly, further studies showed that a derivative of nisoldipine, dehydronitrosonisoldipine (dHNN, present in the nisoldipine compound used ), is actually the inhibitor of SARM1. They then carried nice mechanistic studies (including mass spectrometry and cryo-EM structures) showing that dHNN inhibits SARM1 by covalently modify Cys311 residue in the ARM domain. The dHNN binding site is similar to the previously established NAD+ inhibitory site.

      Overall, the probe is novel with many useful features, the study is rigorous and rather complete, and the conclusion is well supported. I believe the study will be important for the field and will be well received by the field.

      The only minor thing is that the writing can be further improved, especially in the introduction section.

    1. Reviewer #1 (Public Review):

      This is a very well written and comprehensive paper that is a valuable contribution to the literature of childhood cancers. It shows that some childhood cancers have an inherited component and the risk could be to the mother or to the siblings. Although the relative risks are significant, childhood cancer is fortunately rare and the actual risk to the siblings is small.

      Can we assume this is less than one percent? i think it would be helpful to provide some absolute risk numbers for the siblings so that parents could be reassured that the risk to other children is small.

      Do the authors have a suggestion on what genetic tests should be done on children with cancer? Do you have recommendations to make? i assume that the authors do not recommend screening of siblings for cancer except in rare cases. It would be useful to see what the authors recommend.

      Are there some sites where the risk to siblings is there but not to parents which might suggest recessive inheritance?

      If the childhood cancer is rare and fatal one might not see it in the parents because of loss or reproductive fitness. Please comment.

      Should we assume that the higher risks for Latino children are purely due to genetic influences? Could there be environmental factors at play as well?

    1. Reviewer #1 (Public Review):

      This Research Advance builds on the findings of this group's 2019 eLife paper which showed that conserved acidic and basic helices associate to enable heteropolymer formation by Snf7 and Vps24. This work provides some general structure/sequence relationships among the homologous ESCRT-III proteins that will be of interest to those in the ESCRT field. While there are no new mechanistic principles obtained from this study, the data allow the authors to propose a model of the minimal or core units needed for ESCRT-III membrane remodeling.

      The focus is largely on similarities and differences between the closely related Vps24 and Vps2, where they show that a few key point mutations or chimeric swaps (for Vps4 binding by the C-terminal region of Vps2) can exchange their functions. The last portion of the paper further tests similarities within the subgroups of ESCRT-III proteins to experimentally test functional groupings defined by sequence relationships.

    1. Reviewer #1 (Public Review):

      This study investigates roles of DA modulation in projection neuron ensembles in DA-intact mice and Parkinson's disease mouse model using two-photon calcium imaging of direct and indirect SPNs (dSPNs and iSPNs) simultaneously in head-fixed mice locomoting on a freely rotating or motorized circular treadmill. The study begins with careful validation efforts related to their particular imaging conditions and reporter usage. Major findings are: 1) In DA-intact mice, they found that reducing DA receptor signaling by administration of D1/2R antagonists increased iSPN ensemble size (fraction of imaged iSPN active during locomotion) and decreased dSPNs ensemble size, resulting in an imbalance of striatal outputs in favor of indirect pathway. Consistently, elevating DA receptor signaling by D1/2R agonists yielded a dose-dependent imbalance in favor of direct pathway. Interestingly, at one intermediate dose of D1/2R gonists, iSPN ensemble size remained unchanged while dSPN ensemble size increased, whereas at higher doses, both iSPN and dSPN ensemble sizes shrunk. They also showed that reward-induced and nomifensine-induced DA increase recapitulated the low and high dose effects of DA on SPNs, respectively. 2) In dopamine-depleted Parkinson's disease mouse model, the authors found that 6-hydroxydopamine (6-OHDA) treatment reduced dSPNs ensemble size acutely (within 24h) and chronically (after 30 days) and increased iSPNs ensemble size acutely. However, the active iSPN ensembles returned to pre-lesion levels within one week. Overall, ablation of SNc DA neurons biased the striatum output toward indirect pathway. Lastly, they evaluated the influence of L-DOPA on SPN ensembles in DA-depleted mice and found that l-DOPA increased the dSPNs ensembles by 10 fold and reduced the iSPN ensembles to below pre-ablation levels, resulting in strong bias toward direct pathway, a finding they suggest may relate to levodopa-induced dyskinesias. Together, this study introduces data to support the concept that SPN "ensemble size" may be relevant for long-standing pathway balance ideas concerning striatal circuitry in the control of normal movement and its demise in PD.

    1. Reviewer #1 (Public Review):

      The authors sought to assess the relationship between developmental lineage and connectivity.

      This is a tour de force. It relies on detailed EM reconstructions, knowledge of complete neuroblast lineages thus correlating wiring with lineage, and through genetic manipulations of N gene function correlates developmental programs with wiring. The conclusion is important and provides a well described cellular and genetic system for linking the developmental program of a cell to its connection specificity. It provides a framework for considering how to study these questions in other regions of Drosophila and can be extended to the study of more complex mammalian systems where a similar neuroblast-lineage strategy generates different neuron types.

      There are no major weakness.

      This is an excellent study and, in my opinion, is ready to publish in its current form.

    1. Reviewer #1 (Public Review):

      In this manuscript the authors show that a designer exon containing a Fluorescent Protein insert can be used to edit vertebrate genes using an NHEJ based repair mechanism. The approach utilizes CRISPR to generate DSBs in intronic sequences of a target gene along with excision of a donor fragment from a co-transfected plasmid to initiate insertion of the exon cassette by ligation into the chromosome DSB.

      I like the idea here of inserting FP sequences (and other tags) into introns in this way. Focusing on the N- and C-termini for insertions has always seemed arbitrary to me. In practice these internal sites may even tolerate tag insertions better than the termini. However, this remains to be seen.

      My major reservation with this study is that the concepts here are not particularly novel. The approach is very similar to a concept already well established in gene-therapy circles of using introns as targets for inserting a super-exon preceded by a splice acceptor to correct inborn genetic lesions. The methodology employed is essentially HITI (https://www.nature.com/articles/nature20565).

      What is new is the finding that FP insertions are frequently expressed and at least partly functional as evidenced by their ability to localize to the expected intracellular structures. However, no actual functional data is provided in this study so it remains to be seen how frequently the insertion of FP exons is tolerated. It would help the study substantilly to have functional information for a few insertions.

      The value and utility of this study hinges on whether insertions of this type frequently retain function. The authors speculate that "labeling at an internal site of a gene is feasible as long as the insertion does not disrupt the function of the encoded protein. Many introns reside at the junctions of functional domains because introns have evolved in part to facilitate functional domain exchanges (Kaessmann et al., 2002; Patthy, 1999)." Thus an analysis of how often intron tags are tolerated as homozygotes would be helpful for users who will worry that a potentially "quick and dirty" CRISPIE insertion might not accurately report on the function and localization of their protein of interest.

      Other comments:

      1) Were homozygotes identified and were they viable in each instance?

      2) You say: "The CRISPIE method should be broadly applicable for use with different FPs or with other functional domains, different protein targets, and different animal species." I don't know if you optimized your FP to avoid potential reverse strand splice acceptors, but some discussion of this important point should be made so that those trying to apply the approach will make sure that strong acceptors are not included accidentally in reverse oriented inserts.

      3) Would your mRNA sequencing methodologies detect defective transcripts where the splice acceptor and a portion of the upstream FP exon was inserted causing a frame shifted and mispliced mRNA? Such mRNAs would be unstable due to NMD and thus not detected readily in a PCR based approach. Thus disruption of the mRNA by partial insertion of your donor (or fragments of the other co-injected DNA) might be much more widespread than is measured here. This could be tested by recovering clones that partially inserted the donor in the forward orientation and carefully monitoring for defects in mRNA splicing of the inserted allele. Were such clones detected and how frequently?

      4) You note that in the case of vinculin the coding sequence of the last exon of hVCL was included in the insertion donor sequence, and a stop codon was introduced at the end of the mEGFP coding sequence. This is essentially the strategy for super-exon insertion into targets for gene therapy, instead of a splice donor on the C-terminus you include a stop codon. You should site these previous studies. Inclusion of a stop codon in frame would be expected to cause NMD, did you also include transcription termination signals?

    1. Reviewer #1 (Public Review):

      In this manuscript Lituma et al. provides compelling evidence demonstrating the physiological role of presynaptic NMDA receptors at mossy fiber synapses. The existence of these receptors on the presynaptic site at this synapse was suggested more than 20 years ago based on morphological data, but their functional role was only shown in a single abstract since then (Alle, H., and Geiger, J. R. (2005)). The current manuscript uses a wide variety of complementary technical approaches to show how presynaptic NMDA receptors contribute to shaping neurotransmitter release at this synapse. They show that presynaptic NMDA receptors enhance short-term plasticity and contribute to presynaptic calcium rise in the terminal. The authors use immunocytochemistry, electrophysiology, two-photon calcium imaging, and uncaging to build a very solid case to show that these receptors play a role at synaptic communication at mossy fiber synapses. The authors conclusions are supported by the experimental data provided.

      The study is built on a solid and logical experimental plan, the data is high quality. However, the authors would need to provide stronger evidence to demonstrate the physiological function of these receptors. It is hard to reconcile these experimental conditions with the authors' claim in the abstract: 'Here, we report that presynaptic NMDA receptors (preNMDARs) at hippocampal mossy fiber boutons can be activated by physiologically relevant patterns of activity'. We know that extracellular calcium can have a very significant impact of neurotransmitter release and how short-term plasticity is shaped. For this reason, it would be important to explore how the activity of these receptors at more physiological calcium concentrations contribute to calcium entry and short-term plasticity at these synapses.

    1. (

      Ar. starts by pointing to the importance of voluntary action as a necessary component for either a person to praise or blame another's actions or character.

      1109b30 -1110a1 Since, then, excellence ...forcible correction.

    1. RRID:ZFIN_ZDB-GENO-090729-1

      DOI: 10.1016/j.immuni.2020.10.007

      Resource: (ZFIN Cat# ZDB-GENO-090729-1,RRID:ZFIN_ZDB-GENO-090729-1)

      Curator: @scibot

      SciCrunch record: RRID:ZFIN_ZDB-GENO-090729-1

      What is this?

    2. RRID:ZFIN_ZDB-GENO-070502-1

      DOI: 10.1016/j.immuni.2020.10.007

      Resource: (ZFIN Cat# ZDB-GENO-070502-1,RRID:ZFIN_ZDB-GENO-070502-1)

      Curator: @scibot

      SciCrunch record: RRID:ZFIN_ZDB-GENO-070502-1

      What is this?

    1. Reviewer #1 (Public Review):

      The work by Wang et al. examined how task-irrelevant, high-order rhythmic context could rescue the attentional blink effect via reorganizing items into different temporal chunks, as well as the neural correlates. In a series of behavioral experiments with several controls, they demonstrated that the detection performance of T2 was higher when occurring in different chunks from T1, compared to when T1 and T2 were in the same chunk. In EEG recordings, they further revealed that the chunk-related entrainment was significantly correlated with the behavioral effect, and the alpha-band power for T2 and its coupling to the low-frequency oscillation were also related to behavioral effect. They propose that the rhythmic context implements a second-order temporal structure to the first-order regularities posited in dynamic attention theory.

      Overall, I find the results interesting and convincing, particularly the behavioral part. The manuscript is clearly written and the methods are sound. My major concerns are about the neural part, i.e., whether the work provides new scientific insights to our understanding of dynamic attention and its neural underpinnings.

      1) A general concern is whether the observed behavioral related neural index, e.g., alpha-band power, cross-frequency coupling, could be simply explained in terms of ERP response for T2. For example, when the ERP response for T2 is larger for between-chunk condition compared to within-chunk condition, the alpha-power for T2 would be also larger for between-chunk condition. Likewise, this might also explain the cross-frequency coupling results. The authors should do more control analyses to address the possibility, e.g., plotting the ERP response for the two conditions and regressing them out from the oscillatory index.

      2) The alpha-band increase for T2 is indeed contradictory to the well known inhibitory function of alpha-band in attention. How could a target that is better discriminated elicit stronger inhibitory response? Related to the above point, the observed enhancement in alpha-band power and its coupling to low-frequency oscillation might derive from an enhanced ERP response for T2 target.

      3) To support that it is the context-induced entrainment that leads to the modulation in AB effect, the authors could examine pre-T2 response, e.g., alpha-power, and cross-frequency coupling, as well as its relationship to behavioral performance. I think the pre-stimulus response might be more convincing to support the authors' claim.

      4) About the entrainment to rhythmic context and its relation to behavioral modulation index. Previous studies (e.g., Ding et al) have demonstrated the hierarchical temporal structure in speech signals, e.g., emergence of word-level entrainment introduced by language experience. Therefore, it is well expected that imposing a second-order structure on a visual stream would elicit the corresponding steady-state response. I understand that the new part and main focus here are the AB effects. The authors should add more texts explaining how their findings contribute new understandings to the neural mechanism for the intriguing phenomena.

    1. Reviewer #1 (Public Review):

      The evolutionary conserved Notch receptor cell-cell communication pathway is required in cell fate decisions in many vertebrate and invertebrate cells. In Drosophila, Notch controls (among others) the cell fate decision of the sensory organ precursor cell, SOP. SOPs divides asymmetrically to give rise to an anterior and a posterior cell, pIIb and pIIa, respectively, which ultimately result in the formation of a bristle. In a recent paper form the Schweisguth lab (Trylinsky et al., 2017) is was shown that Notch is found both apical and basal of the midbody at the pIIa/pIIb interface during cytokinesis, and that it is mainly the basal pool of Notch that contributes to signaling.

      Houssin et al. now asked how polarity and signaling proteins involved are distributed during cytokinesis and how this distribution could impact on Notch signaling and hence fate decision. The authors show that during cytokinesis of the SOP several polarity determinants are re-distributed. Bazooka /Par3 becomes enriched at the pIIa/pIIb interface, where it occurs in nano-clusters, both apical and basal to the midbody, while aPKC remains in the apical compartment. Bazooka co-localizes with Notch, Sanpodo, Delta and Neuralised (Neur) in these clusters. In the absence of baz, both the apical and the lateral Notch-positive clusters are decreased in intensity and the number of lateral clusters is reduced at the pIIa/pIIb interface. Strikingly, this only slightly reduces the signaling activity of Notch. Formation of the Baz-Notch clusters depend on the Notch-cofactor Sanpodo: in its absence, the lateral Baz-Notch clusters do not assemble, suggesting that Sanpodo supports Notch signaling by promoting lateral clusters. From the data the authors conclude that the Notch/Baz/Spdo/Neur clusters represent the signaling units at the pIIa/pIIb interface.

      Major strengths and weaknesses

      The authors performed a very detailed analysis to further dissect how Notch signaling at the pIIa/pIIb interface is controlled. They used state-of-the-art live-cell imaging of tagged proteins in wild-type and mutant animals and applied careful statistical analyses of their data. Thereby, they provide a novel link between the role of the polarity protein Bazooka in clustering Notch, and how the particular redistribution of Bazooka/Notch in clusters on the lateral membrane during cytokinesis of the SOP organize putative signaling hubs.

      However, in the discussion the authors fall somewhat short to substantiate their main conclusion that these clusters "represent signaling units at the pIIa/pIIb interface." (line 560). First, although in the absence of Baz the number and size of Notch clusters are decreased, Notch signaling is only slightly affected. Second, no suggestion for any molecular mechanism is provided as to how Baz may organize these clusters, e.g. about the molecular interaction between Baz and Spdo, both of which are required to cluster Notch. And finally, the fact that the clusters are similar in composition apical and basal to the midbody does not help to support (or disprove) the conclusions put forward in Trylinsky et al., 2017, showing that Notch signaling mainly occurs by the lateral clusters.

    1. Reviewer #1 (Public Review):

      In the manuscript by Kymre, Liu and colleagues, the authors investigate how pheromone signals are interpreted by the projection neurons of the male moth brain. While the olfactory neurons and glomerular targets of pheromone signaling is known, the signaling of the projection neurons (output neurons) that carry pheromone signaling to higher regions of the brain remained unknown. The authors utilized a series of technically challenging experiments to identify the anatomy and functional responses of projection neurons responding to pheromone mixtures, primary pheromone, secondary pheromone, and behavioral antagonist odors. By calcium imaging of MGC mALT neurons, the authors identify that odor responses in PNs are broader than the olfactory neuron counterparts (ie, the behavioral antagonist activates OSNs innervating the dma glomerulus, whereas the antagonist actives dma and dmp glomeruli). The authors then perform a series of elegant experiments by which the odor responses of different mALT PNs are recorded by electrophysiology, and the anatomy of the recorded neurons identified by dye fill and computer reconstruction. This allowed analysis of the temporal response properties of the neurons to be correlated with their axonal processes in different brain regions. The data suggest that attractive pheromone signals activate the SIP and SLP regions, while aversive signals primarily active regions in the LH. Finally, the authors present a model of pheromone signaling based on these findings.

      The work presents the first glimpse at the signaling from mALT PNs. The technical challenges in performing these experiments did limit the number of neurons that could be recorded and imaged. As such, the comprehensiveness of the study was not clear, or if additional experiments might alter the findings. The connection of protocerebrum anatomy with functional signaling (as summarized in Figure 6) could have been more clearly articulated.

      The manuscript could benefit by revisions to the text and figure presentations that would make it more accessible to a broader audience.

    1. Reviewer 1 (Public Review):

      In the manuscript by Liu et al., the authors investigate the role of Adgr6 in spine development in mice and dissect tissue specific contributions leading to late onset scoliosis in knockouts. Furthermore, they implicate Adgr6 in regulating gene expression and the mechanical properties of dense connective tissues via cAMP signaling that are linked to de development of scoliosis.

      Overall, this is an interesting and thorough study of the developmental roles of Adgr6 in spine development that contributes both to the understanding of spine morphogenesis and the etiology of common types of scoliosis that are of unknown origin (i.e., idiopathic). Through the use of various tissue specific drivers, the authors generate conditional mouse knockouts that allowed them to dissect the respective contribution of Adgr6's function in each spine associated tissue. In addition to the use of state-of-the-art genetic tools, the authors show beautiful histological and micro-CT data illustrating developmental processes and phenotypes with great detail. Their results also implicate cAMP signaling and CREB activity in the regulation of mechanical properties of dense spine tissues.

    1. Reviewer #1 (Public Review):

      ER retrieval mediated by the KDEL receptor occurs for cargo present from great to minimal abundance and for cargo with different variations of the "KDEL" carboxy terminal sorting signal. Using a detailed structure/function approach, this study provides insight into the mechanism of cargo recognition by the receptor. A significant advance is the new structural data derived from co-crystals of the receptor with TAEHDEL and TAERDEL peptides that is now compared with the previous KDEL co-crystal structure. From there, the investigators use mutation of both receptor and cargo sequences as well as molecular simulation of the binding interaction. Altogether the findings identify charged receptor residues playing a role in specificity based on the -4 position of the signal, a receptor tryptophan that accounts for higher affinity binding to HDEL, and binding pocket arginines that may be sequentially engaged by the carboxy terminus for capture of the three carboxyl groups in the DEL portion of the signal. The work is meticulously carried out and the findings will likely be of significant interest to the field.

    1. Joint Public Review:

      Bohm et al. investigated the operating conditions of the soleus and the vastus lateralis muscle during running. They report different roles for the two muscles. The soleus acts as an energy generator characterized by a high force-length potential and enthalpy efficiency whereas the vastus lateralis acts as an energy conservator, characterized by a high force-length and force-velocity potential. The authors show how the decoupling of the muscle-tendon-unit length and the fascicle length, mainly attributable to tendon compliance, allows both muscles to work at a high, almost optimal , force-length potential. Beside this similarity the soleus shortens throughout stance phase (concentric mode) whereas the vastus lateralis shows almost no length changes (isometric mode) and is activated primarily in the first part of the stance phase. These observations in combination with the calculated enthalpy efficiency for soleus and the estimated force-velocity potential for vastus lateralis clarify the role of the two muscles in the optimization of muscle energy production and force generation during the experimental condition. The authors use a complex methodology and calculate the variables of interest in the most sophisticated way. The results of the present study contribute in a comprehensive way to the ongoing discussion on muscle and tendon interaction during human locomotion. The conclusions of this paper are mostly well supported by measured and modeled data, but some aspects of the experimental setup and data modeling need clarification and a more thorough discussion.

    1. ZDB-ALT-070316-1

      DOI: 10.1016/j.devcel.2020.07.015

      Resource: (ZFIN Cat# ZDB-ALT-070316-1,RRID:ZFIN_ZDB-ALT-070316-1)

      Curator: @Naa003

      SciCrunch record: RRID:ZFIN_ZDB-ALT-070316-1

      What is this?

    2. ZFIN: ZDB-ALT-120117-1

      DOI: 10.1016/j.devcel.2020.07.015

      Resource: (ZFIN Cat# ZDB-ALT-120117-1,RRID:ZFIN_ZDB-ALT-120117-1)

      Curator: @Naa003

      SciCrunch record: RRID:ZFIN_ZDB-ALT-120117-1

      What is this?

    3. ZFIN: ZDB-ALT-071017-1

      DOI: 10.1016/j.devcel.2020.07.015

      Resource: (ZFIN Cat# ZDB-ALT-071017-1,RRID:ZFIN_ZDB-ALT-071017-1)

      Curator: @Naa003

      SciCrunch record: RRID:ZFIN_ZDB-ALT-071017-1

      What is this?

    1. Reviewer 1 (Public Review):

      The manuscript by Pantaleao et. al., describes the effects of maternal diet-induced obesity on lipid composition in maternal and fetal serum and the fetal heart, and in the fetal heart transcriptome. Lipid composition in fetal serum and heart was analyzed in males and females. This study revealed sex-specific effects of obesity during pregnancy. The authors found changes in the lipidome of both mother and fetus in response to obesity. Many of the lipid profiles exhibit sex specific changes in the fetal sera. Similarly, the authors identified sex-specific changes to the lipidome of the fetal heart. Through the use of transcriptomic analysis on the fetal heart, the authors identified changes in the expression of genes regulating lipid metabolism. The results presented provide insight into the still poorly understood processes influencing the long-term health of the fetus.

      The work characterizes an important aspect of the effects of maternal obesity and the results are visually well presented. A limitation is that this is a largely descriptive study. Nonetheless, the authors provide a detailed description of the lipid composition changes in response to maternal obesity and associated with sex.

      The introduction provides key information about the effects of obesity during pregnancy in the offspring, and the relevance of lipids in heart homeostasis. However, cardiac transcriptional regulation and sex-specific responses, which are the other key components of this study, could be more cohesively integrated.

      Some of the results presented can be analyzed in deeper detail to establish correlation between sex and diet with lipid composition and cardiac gene expression.

  4. Apr 2021
    1. Reviewer #1 (Public Review):

      This study reports that deletion of Tsc1 restricted to cerebellar Purkinje cells leads to decreased levels of mRNAs associated with FMRP targets although their ribosomal bindings are increased likely through compensatory mechanisms. However, protein levels of Shank2, one of the core FMRP targets, are decreased, suggesting that the compensatory increases in the ribosomal binding of FMRP target mRNAs do not rescue Shank2 protein expression. The analyses for transcriptional and translational processes were performed carefully and in a balanced manner, and the results are largely convincing and support the key conclusions. Considering the growing importance of mTOR signaling and cerebellar functions in ASD pathophysiology, the present work suggests that FMRP target transcripts are key mediators of Tsc1-related cerebellar dysfunctions, which is an important and timely contribution to the field.

    1. Joint Public Review:

      This well-written manuscript describes a spontaneous autoinflammatory phenotype of STAT1-deficient mice, characterized by myeloid hyperplasia, expansion of Th17 cells, microbiota dysbiosis, and inflammatory bowel disease. A similar autoinflammatory condition is seen in humans deficient in STAT1, and in independent colonies of STAT1-deficient mice, but its mechanistic basis is not understood. STAT1 is a critical transcription factor downstream of type I, II (gamma), and III interferon (IFN) signaling. The authors are able to recapitulate the disease phenotype in mice with combined deficiency in both STAT2 (essential for type I and III IFN signaling) and the receptor for IFN gamma, but not in mice deficient in both the type I and II IFN receptors, implying that the phenotype arises from deficiency of all three classes of interferons. Thus the authors conclude that suppression of spontaneous autoinflammatory disease is a redundant function of type I/II/III IFNs. Disease is ameliorated by IL-17 deficiency, indicating a critical role for type 17 responses in pathogenesis. Disease is also ameliorated by treating STAT1 deficient mice with antibiotics, implying a role for the microbiota in the disease progression. The authors' model is that interferons regulate the composition of the microbiota and that dysbiosis of the microbiota then produces the inflammatory disease. The main limitation of the manuscript is that it is not explained how interferons regulate microbiota composition, or how the altered microbiota then produces inflammation. These issues are likely beyond the scope of what could be expected to be fully addressed for this initial paper. However, analysis of disease-free STAT1/IL17-deficient mice could provide insight into whether dysbiosis and inflammation is upstream or downstream of IL-17 signaling.

    1. Reviewer #1 (Public Review):

      Guo et al. describes interesting experiments recording from various sites along a cortico-cerebellar loop involved in limb control. Using neuropixels recordings in motor cortex, pontine nuclei, cerebellar cortex and nuclei, the authors amass a large physiological dataset during a cued reach-to-grasp task in mice. In addition to these data, the authors 'ping' the system with optogenetic activation of pontocerebellar neurons, asking how activity introduced at this node of the loop propagates through the cerebellum to cortex and influences reaching. From these experiments they conclude the following: the cerebellum transforms activity originating in the pontine nuclei, this activity is not sufficient to initiate reaches, and supports the long standing view that the cerebellum 'fine tunes' movement, since reaches are dysmetric in response to pontine stimulation. Overall these data are novel, of high quality, and will be of interest to a variety of neuroscientists. As detailed below however, I think these data could provide much more insight than they currently do. Thus below I provide some suggestions on improving the manuscript.

      1) Since the loop is the focus of this study, it would be nice if the authors better characterized latencies of responsivity to pontine stimulation through the loop, to address how cortically derived information routed to the cerebellum may loop back to influence cortical function. In the data provided, we know that pontine stimulation modulates Purkinje and deep nuclear firing (but latency to responses are not transparently provided in the main text, if anywhere), while motor cortical responses peak at 120 ms (after stimulus onset?, unclear), and that this responsivity is preferentially observed in neurons engaged early in the reaching movement. Is the idea, then, that cortical activity early in the reach is further modulated by cerebellar processing to (Re) influence that same cortical population? Does this interpretation align with the duration of reaches, the duration of early responsive activity during reach, and the latency of responsivity; or is the idea that independent information from other modalities entering the pontine nuclei modulates early cells? Latency to respond at the different nodes, might aid in thinking through what these data mean for the function of the loop.

      2) Many of the figures need work to aid interpretation. Axis labels are often missing (eg 2F); color keys are often unlabeled (2F); color gradients often used but significance thresholds are hard to evaluate (using same colors for z scores and control / laser is confusing 6, 8); and within-figure keys would be useful (5D-h). These issues occur throughout the manuscript.

      3) Relatedly, but also conceptually, Figure 3B has particular issues, such as identifying where the neuropixel multiunit activity is coming from. I assume that in the gray boxes illustrating the spatio-temporal profile of spiking band activity that the lower part of the box is the ventral direction, upper, dorsal. This is not spelled out. From the two examples it would seem that the spiking band is in different places in the cerebellum, undermining, I think, the objective of the figure. It would be sensible to revisit this entire figure to identify the key takeaways and design figures around those ideas. As it stands, these examples appear anecdotal. Consider moving this to a supplement. Powerband density strength is missing an axis. More importantly, it would be nice to corroborate the interpretation of the MUA with the single unit recordings, since the idea is that many neurons are entraining to the PN activity. Yet, the examples don't seem particularly entrained. Is the activity being picked up on just axonal firing of the PN axons? Fourier analysis of spiking of isolated neurons in cerebellum should be used to corroborate the idea that cerebellar neurons are entraining, rather than the neuropixel picking up entrained PN axons.

      4) The use of the GLM is puzzling. In addressing the question of how cerebellum and motor cortex interact (from the Abstract, "how and why" do these regions interact) it is unclear why these regions are treated separately. I would have expected some kind of joint GLM where DCN activity is used to predict M1 variance (5 co-recordings are reported but nothing to analyze?); or where DCN + M1 activity is used to decode kinematics to see if it is better than one or the other alone. As it stands, we learn that there is more kinematic information in the motor cortex than in DCN. This is not necessarily surprising given previous literature on cerebellar contributions to reaching movements. In principle the idea that 'PN stimulation might perturb reaching kinematics through descending projections to the spinal cord, or by altering activity in motor cortex' is treated as mutually exclusive outcomes, though it is highly unlike to be so.' Analyzing M1+DCN together could address whether DCN activity adds nothing to decoding kinematics that isn't there in M1 or adds something that M1 does not have access to. The main point here is that the physiological datasets could be better leveraged with these fits to derive insight into the interactions of the loop. R2 should be provided in the GLMs (Fig 8) to assess statistically how well they perform relative to one another, not just correlations between the two.

    1. Reviewer #1 (Public Review):

      This paper provides quantitative detailed measurements of how dry mass density varies as a function of the cell cycle in fission yeast cells. They find that density decreases during G2 and increases during mitosis/cytokinesis. They also monitor the effects of cell cycle mutants and a drug that depolymerizes actin, and conclude that while dry mass increases continuously, cell cycle-regulated changes in volume growth in fission yeast create the density oscillations. This supports earlier less precise work in the field, and is therefore unsurprising. Overall, the quantitative data convincingly support these conclusions.

      More interesting is the discovery of intracellular density gradients in G2 cells, with lower density at faster growing ends. The basis for these gradients is not investigated. The gradients persist through mitosis and cytokinesis, giving birth to daughter cells whose mean densities differ. These findings would appear to suggest that density differences might accumulate with each generation, but this is clearly not the case as the density variation in a cell population is very small. This paper will be of interest to researchers working on fission yeast, and raises interesting questions for future investigation.

    1. Reviewer #1 (Public Review):

      In this manuscript entitled "Translation inhibitory elements from Hoxa3 and a11 mRNAs use uORFs for translation inhibition", the authors undertake a series of in vitro translation and in cell experiments to characterize the inhibitory features of previously documented Hoxa11 and Hox3 translation inhibitory elements (TIEs). The presence of TIEs within a subset of Hox mRNAs are thought to mediate repression of cap-dependent translation, enabling downstream IRES-mediated initiation to proceed. In sum, the authors report: (i) the presence of an upstream uORF in the Hoxa3 TIE sequence that dampens translation from the downstream ORF and (ii) the presence of a stem-loop structure that appears to block ribosome migration and results in inhibition of the downstream ORF (even thought the 5' UTR of a11 also has 2 uAUGs - these do not appear to play a determining role in a11 TIE activity).

      Major Strengths: This study is comprehensive and thorough. The manuscript is well written.

      Weaknesses: Some of the experiments lacked internal controls making interpretation of the results preliminary in nature.

      For the most part, the authors have defined the inhibitory features of the Hox a3 and a11 Translation Inhibitory Element. The work was placed in appropriate context (Introduction). The work further supports the known concept that uAUGs and 5' UTR secondary structure is detrimental to eukaryotic translation inhibition.

    1. Reviewer #1 (Public Review):

      Samineni et al. seek to identify and characterize the brain mechanisms responsible for itch-related behaviors. Previous work by this group and others showed that mouse CeA contains itch-responsive neurons. Here the authors set out to determine the molecular and circuit identity of these neurons, their necessity and sufficiency in controlling scratching behavior and itch-related affective components. Using photometry in Vgat-IRES-Cre animals, they show that GABAergic neurons in CeA are active during scratching behavior. In subsequent experiments, scratch-responsive neurons are TRAPed (with scratching behavior elicited by pruritogenic chloroquine injections) and later manipulated using optogenetics and DREADD to test their necessity and sufficiency in scratching behavior and other known CeA-dependent behaviors. Scratching bouts are optogenetically driven with or without chloroquine, suggesting that the neurons are sufficient to elicit this behavior. Optogenetic stimulation is also used in a closed-loop real time assay and zero plus maze to show that chloroquine-TRAPed CeA neurons encode aversive affect and anxiety-related behaviors. Inhibitory DREADD is used to show that TRAPed neurons are required for choroquine-mediated itch behaviors and aversive affect elicited by chloroquine. Appetitive studies show that manipulation of chloroquine-TRAPed neurons does not affect free feeding or food seeking. Viral tracing studies show a connection between the CeA and vPAG and optogenetic manipulations of axon terminals in this circuit reproduces findings with TRAPed CeA neuronal manipulations. Finally, TRAPed neurons are isolated and sequenced in an effort to identify their unique molecular profiles. These results strongly suggest that a subtype(s) of CeA neurons are activated by chloroquine and are important for both scratching behavior and affective aspects of the behavior, while not being involved in appetitive behaviors. However, the use of terms like 'active avoidance' is misleading based on the assays used and interpretation of some of the findings is muddied somewhat by missing or inadequately described control data.

    1. Reviewer #1 (Public Review):

      The standard neutral model, which is our null model for levels of genetic variation, predicts that they should be proportional to census population sizes. In reality census population sizes across metazoan species span several orders of magnitude more than the ~3 orders spanned by levels of genetic diversity. This discrepancy is referred to as Lewontin's paradox, and to resolve it would mean to explain how basic population genetic processes lead to the modest span of genetic diversity levels that we observe. This is a central question in population genetics (which is, after all, concerned with understanding patterns of genetic variation) and is of substantial general interest.

      The manuscript addresses Lewontin's paradox through three main analyses:

      1) It derives novel estimates of census population size across metazoans, which alongside previous estimates of neutral diversity levels, enables a revised quantification of the relationship between diversity levels (\pi) and census populations sizes (Nc).

      2) It quantifies the relationship between \pi and Nc controlling for phylogenetic relatedness.

      3) It revisits the question of whether this relationship can be accounted for by the effects of selection at linked loci (e.g., sweeps and background selection). I address each of these analyses in turn.

      Novel estimation of census population sizes in metazoans: The estimates are derived by: 1) estimating the density of individuals within their range, based on body size and a previously observed linear relationship between body size and density (Damuth 1981, 1987); 2) applying a geometric algorithm (finding the minimum alpha-shape computationally, sometimes adjusting alpha manually) to geographic occurrence data to estimate the area of the range; and 3) multiplying the two.

      The results are sometimes surprising. For example, Drosophila melanogaster is estimated to have a population size > 10^17 (Fig. 1); if the volume of an individual is 1 mm3, this implies a total volume > 1km x 1km x 100 m. Additionally, some species classified as endangered have census estimates > 10^8 (Fig. 3). The author compares his area estimates with estimates for species in the IUCN Red List (focused on endangered species) to find that they largely correlate (although this is not quantified). I think further investigation of the quality of the census size estimates is warranted. Are there are other estimates of census size or biomass that can be used for validation, e.g., for species of economic and biomedical importance (e.g., herring and anopheles)?

      If the proposed method proves to work well, I imagine that the estimates of census size may be of broad interest in other contexts. In the context of Lewontin's paradox, it may be interesting to quantify the difference in the relationship between \pi and Nc suggested by the new estimates vs the proxies used in previous work (e.g., Leffler et al. 2012).

      Quantifying the relationship between \pi and Nc controlling for phylogenetic relatedness: I am unclear about the motivation for this analysis. As Lynch argued (and the author describes), if TMRCAs of neutral loci within a species are smaller than the split time from another species in the sample, its genetic diversity level was shaped after the split, and it could be considered an independent sample for the relationship between \pi and Nc. There may be underlying factors shaping this relationship that are not phylogenetically independent (e.g., similar life history traits) but it is unclear why that would justify down-weighting a sample. In that sense, I am not convinced by the authors argument that finding a 'phylogenetic signal' justifies the correction. Stated differently, it is not obvious what is the 'true' relationship being estimated and why relatedness biases it. One could imagine that the 'true' relationship is the one across extant species, in which case the correction is not needed (with the possible exception of species in which TMRCAs are on the same order or greater than split times). I don't know what an alternative 'true' relationship would be.

      Moreover, I am not sure how a more precise 'quantification' of the relationship between diversity and census size serves us. Regardless of corrections, it is obvious that the null provided by the standard neutral model is off by orders of magnitude. Perhaps once we have alternative explanations for this relationship then testing them may require corrections, but presumably the corrections will depend on the explanations.

      One context in which phylogenetic considerations and quantification may be relevant is the comparison of the \pi - Nc relationship among clades. Notably, one could imagine that different population genetic processes are important in different clades (e.g., due to reproductive strategy) and a comparative analysis may highlight such differences. It is less clear whether the corrections that are applied here are the relevant ones. Separating clades makes sense in this regard, but it is unclear why to correct for non-independence within a clade. Furthermore, it seems that in order to point to different processes one would like to control for the distribution of census population sizes in comparisons between clades (to the extent possible). Otherwise, one can imagine the same process shaping the relationship in different clades, but having a non-linear (in log-log scale) functional dependence on census population size (as in the case of genetic draft studied next). In this regard, I am not sure I follow the argument attributed to Gillespie (1991) and specifically how the current analysis supports it.

      In summary, I find the ideas of clade level analyses and of using phylogenetic comparative methods (PCMs) to look at census population size (and possibly diversity levels) promising. For example, as the author alludes to in the Discussion (bottom of P. 13), PCMs may be informative about the hypothesis that species with large census sizes have a greater rate of speciation. Yet I find the current analyses difficult to interpret.

      Analysis of the effects of linked selection: The author investigates whether the effect of selection at linked sites (e.g., selective sweeps and background selection) can account for the observed relationship between diversity levels and census population size. To this end, he assumes that different species have the same sweeps and background selection parameters inferred in Drosophila melanogaster, but differ in census size and genetic map length.

      As justification for using selection parameters inferred in D. melanogaster, the author argues that this is a "generous" assumption in that the effects of linked selection in this species are on the high end. One issue with this argument is that among reasons for the strong effects in D. melanogaster is its short genetic map length. This is not a substantial caveat, given that the analysis is meant as an illustration and it can be resolved by using appropriate wording. Perhaps more troubling is that the author's estimate of the reduction in diversity level in D. melanogaster is much greater than the reduction estimated in the inference that he relies on (several orders of magnitude and less than one, respectively). This discrepancy is mentioned but should probably be addressed more substantially.

      The results of the analysis are intriguing. The effects of linked selection `shrink' the ~13 orders of magnitude of census population sizes to ~3 orders of magnitude of diversity levels. This massive effect is largely due to the genetic draft (Gillespie 2001) and to a lesser extent to the decrease in map length with increasing census size: when the census population size becomes very large (Nc~10^9) and coalescence rates due to genetic drift decrease accordingly (~1/2Nc), coalescence rates due to sweeps, which increase owing to the smaller map lengths (and would otherwise remain constant), become dominant. In hindsight this is quite intuitive and aligns with Gillespie's original argument, but this is in hindsight, and using this argument in conjunction with data, specifically with census population size and map length estimates, is novel.

      As the author points out, the resulting relationship between diversity levels and census population sizes does not fit the data well. Notably, predicted diversity levels are too high in the intermediate range of census population sizes. Nonetheless, their analysis suggests that linked selection may play a much greater role than previous studies suggested (i.e., the analyses of Corbett-Detig et al. (2015) and Coop (2016) suggests that it cannot account for more than 1 order of magnitude). Maybe the poor fit is due to the importance of other factors (e.g., bottlenecks) in species with intermediate census population sizes?

      I also wonder whether the potential role of linked selection may be clearer if the different effects are shown separately, and perhaps with less reliance on the estimates from D. melanogaster. Namely, the effects of background selection can be shown for a few different values of Udel, e.g., between 0.3-3 (this range seems plausible based on many estimates). They can be shown both accounting and not accounting for the relationship between map length and census size. Similarly, the effect of sweeps can be shown for several values of corresponding parameters, and perhaps even for different models for how the number of beneficial substitutions varies with census size (see Gillespie's work to that effect). I believe that such illustrations will be fairly intuitive and less restrictive.

    1. Reviewer #1 (Public Review):

      In this study, Stephani et al. addresses the question of how ongoing fluctuations in neuronal excitability, as well as stimulus strength, impact the perception of above-threshold tactile stimuli and the subsequent stimulus-evoked brain activity. Specifically, pre-stimulus alpha oscillation amplitude and the N20 component of the SEP are used as a readout of cortical excitability, while signal detection theory quantities - sensitivity and criterion - derived from participant response are used as the behavioral correlates. The authors find that 1) higher prestimulus alpha amplitude is associated with a higher criterion, i.e., participants tend to rate stimuli as "weaker" regardless of the actual intensity, while there was no effect on sensitivity; 2) larger N20 amplitude (more negative) is associated with stronger stimulus intensity; 3) conditioned on actual stimulus intensity, larger N20 amplitude is associated with a higher criterion, similar to prestim alpha; 4) the above effects are confirmed using a multi-level structural equation model while also accounting for peripheral control measures; and finally 5) that the thalamic response, as measured in very early components, have no association with perceptual response and previous findings on later SEP components (N140) is reproduced in this data. The authors offer a physiological interpretation that explains the seemingly contradictory result by accounting for the recruitment level of cortical neurons and their membrane depolarization in excitable stages.

      Overall, I find this study to be very nicely done, well-written, and with informative figures. My expertise in signal detection theory and awareness of the SEP literature are limited, and the following comments will probably reflect that. Considering that, the introduction was very concise yet informative regarding the state of the field, and nicely motivates why suprathreshold stimulation is an interesting question to investigate, and was overall just a pleasure to read. The data and analyses seem convincing in supporting the authors' conclusions. The results are indeed puzzling (in an interesting way), and while the authors provide a nicely parsimonious explanation rooted in the underlying neurophysiology, I think this study has the potential to further motivate many lines of investigation, especially considering that the majority of works done in this field looks at the effect of ongoing neural activity on the detection of near-threshold sensory stimuli (as far as I know). I have some major concerns broadly regarding the interplay between alpha oscillation and the N20 (detailed below), the rest are mostly clarifying comments/questions that I believe may help the authors improve this paper, as well as other interesting points to consider in the discussion to relate to the broader literature.


      N20 and alpha oscillation

      My main technical concern lies in the choice of decomposition filter for SEP and alpha oscillations, and the conclusions the authors draw from that. Specifically, a CCA spatial filter is optimized here for the N20 component, which is then identically applied to isolate for alpha sources, with the logic being that this procedure extracts the alpha oscillation from the same sources (e.g., L359). I have no issues (or expertise) with using the CCA filter for the SEP, but if my understanding of the authors' intent is correct, then I don't agree with the logic that using the same filter isolate for alpha as well. The prestimulus alpha oscillation can have arbitrary source configurations that are different from the SEP sources, which may hypothetically have a different association with the behavioral responses when it's optimally isolated. In other words, just because one uses the same spatial filter, it does not imply that one is isolating alpha from the same source as the SEP, but rather simply projecting down to the same subspace - looking at a shadow on the same wall, if you will. To show that they are from the same sources, alpha should be isolated independently of the SEP (using CCA, ICA, or other methods), and compared against the SEP topology. If the topology is similar, then it would strengthen the authors' current claims, but ideally the same analyses (e.g., using the 1st and 5th quintile of alpha amplitude to partition the responses) is repeated using alpha derived from this procedure. Also, have the authors considered using individualized alpha filters given that alpha frequency vary across individuals? Why or why not?

      In the same vein, both alpha and N20 amplitude relate to perceptual judgement, and to each other. I believe this is nicely accounted for in the multivariate analysis using the SEM, but the analysis that partitions the behavioral responses using the 20% and 80% are done separately, which means that different behavioral trials are used to compute the effect of N20 and alpha on sensitivity and criterion. While this is not necessarily an issue given that there IS a multivariate analysis, I would like to know how many of those trials overlap between the two analyses.

      At multiple points, the authors comment that the covariation of N20 and alpha amplitude in the same direction is counterintuitive (e.g., L123-125), and it wasn't clear to me why that should be the case until much later on in the paper. My naive expectation (perhaps again being unfamiliar with the field) is that alpha amplitude SHOULD be positively correlated with SEP amplitude, due to the brain being in a general state of higher variability. It was explained later in the manuscript that lower alpha amplitude and higher SEP amplitude are associated with excitability, and hence should have the opposite directions. This could be explicitly stated earlier in the introduction, as well as the expected relationship between alpha amplitude and behavior.

      Furthermore, I have a concern with the interpretation here that's rooted in the same issue as the assumption that they are from the same sources: the authors' physiological interpretation makes sense if alpha and N20 originated from the same sources, but that is not necessarily the case. In fact, the population driving the alpha oscillation could hypothetically have a modulatory effect on the (separate) population that eventually encodes the sensory representation of the stimulus, in which case the explanation the authors provide would not be wrong per se, just not applicable. A comment on this would be appreciated in the revision.

      In addition, given how closely related the investigation of these two quantities are in this specific study, I think it would be relevant to discuss the perspective that SEPs are potentially oscillation phase resets. Even though the SEP is extracted using an entirely different filter range, it could nevertheless be possible that when averaged over many trials, small alpha residues (or other low freq components) do have a contribution in the SEP. If the authors are motivated enough, a simulation study could be done to check this, but is not necessary from my point of view if there is an adequate discussion on this point.

    1. Reviewer #1 (Public Review):

      The manuscript by Victorino et al. describes the role of the metabolic adaptor hypoxia inducible factor-1α (HIF1α) in NK cells during viral infection. They first showed that NK cells constitutively express HIF1α and it is upregulated by murine cytomegalovirus (MCMV) infection. Using HIF1α KO mice, they provided evidence that HIF1α is dispensable for normal NK cell development, but important for NK cell dependent virus control and morbidity, NK cell number and their expansion. Although the lack of HIF1α affects the NK cell dependent virus control, it appears that HIF1α is not required for NK cell effector functions. In spite of the fact that proliferation of NK cells in HIF1α KO was not affected, their ultimate number was reduced due to the upregulation of pro-apoptotic protein Bim coupled with increased caspase activity and impaired glucose metabolism. As authors pointed out, the data presented in this manuscript are in sharp contrast to previous finding on the role of HIF1α in NK cell responses to tumors, suggesting the impact of tumor microenvironment.

    1. Reviewer #1 (Public Review):

      This is an interesting and informative study reporting on the molecular features of reversible hair graying in humans and the connection with psychological stress. The study appears to have been very well conducted and the interpretations are generally supported by the data. While the results are primarily correlative at this stage, this work will set the stage for future more mechanistic studies and represents an important conceptual and methodological advance.

    1. Reviewer #1 (Public Review):

      Quantifying the role of the multiple hosts and vector species involved in the transmission dynamics of some vector-borne diseases, such as RRV, remains challenging. Using RRV in Brisbane as a case study, the manuscript develops a 3-step framework (physiological competence, half transmission cycle, complete transmission cycle) to integrate different aspects of host and vector physiological competence (e.g. titer levels) with ecological traits (e.g. abundance and feeding behavior) and rank the contribution of suspected species to RRV community transmission. They use published experimental and observational data when available combined with models mostly based on GLMMs to generalize patterns. The authors found that being a physiologically competent vertebrate host does not seem essential, instead vertebrate host ecology and vector physiological competence are the key traits for community transmission of RRV.

    1. Reviewer #1 (Public Review):

      This manuscript presents a generalizable tool for the comparison of single-cell atlases across species. The work addresses an important problem given the proliferation of such cataloguing efforts across a rapidly increasing diversity of organisms, and the opportunities this presents for comparative and evolutionary biology. The algorithms developed extend the use of self-assembling manifolds to this critical problem by addressing key challenges in the assignment of homologous genes and cell types. The method will be extremely useful for comparative studies to understand the evolutionary relationship of different cell types, and to quickly assign the cell type identity to new single-cell atlases by taking advantage of existing datasets. The authors demonstrate the robustness of the method by comparing cell atlases from diverse metazoans. In the process, the authors arrive at three provocative evolutionary conclusions that will require further investigation to fully support: widespread paralog substitutions, the multifunctionality of ancestral contractile cells, and the existence of a deeply conserved gene module associated with multipotency.


      A key advantage of the approach presented is the relaxation of one-to-one mapping of orthologous genes, instead considering all possible homologous sequences in the alignment of the transcriptomes. Similarly, alignment of cell types is achieved by taking into account the general neighborhood of cell types and not just the closest match. The authors show that the algorithm outperforms existing methods, which were not really developed for the alignment of distantly related cell types. I expect this method will therefore be of general interest to anyone working with diverse organisms.

      Cell types inferred from the use of algorithm could be validated in the poorly studied parasite Schistosoma mansoni. These experiments provide a glimpse into the broad utility of the analysis presented, which can be used as a resource in itself.


      The observation of widespread paralog substitution may be complicated by the use of relaxed gene orthology assignments in the initial alignment of cell types. It will be important to see whether similar levels of paralog substitution are observed when the paralogs in question are excluded during manifold assembly. This would ensure that the apparent paralog substitution is not a consequence of the necessary relaxation of ortholog assignments. Further study of this phenomenon could reveal whether paralogs are more likely to be substituted in cases where they arose more recently, and whether the substitutions are stable within clades-perhaps elucidating different paths of specialization following the ancestral gene duplication event.

      The claim that ancestral contractile cells were multifunctional demands closer exploration of the gene module common to this cell type across species. Cellular contractility is a complex process in any cell and the distribution of the gene module across categories of signaling, actin regulation, and cell adhesion does not in itself imply multifunctionality. The authors also point to a second enriched module within multipotent cells (stem cells) which could be investigated further. Cursory analysis suggests that the gene signature might simply be the consequence of actively dividing cells lacking specialized cell identity markers, as opposed to a more fundamental program of multipotency.

    1. Reviewer #1 (Public Review):

      Ide and colleagues report on an undescribed, pro-inflammatory proximal tubule cell state (DA-PT) in the pathogenesis of acute kidney injury and repair following acute kidney injury. They demonstrate that DA-PT cells accumulate after injury and persist following severe injury, potentially due to alteration of genes related to glutathione metabolism and ferroptosis. Their results are derived from single-cell RNAs sequencing and quantitative microscopic approaches in the mouse kidney. The studies from this work will have a significant impact not only to those studying acute kidney injury but also ischemic injury in other organ systems.

      Major strengths of this work include the comprehensive and complementary nature of the studies with pertinent in vivo models and data analysis of single cell RNA sequencing from kidney cells. The authors have achieved most of the aims of their study and the results mostly support their conclusions. The discussion is a nice summary of their work and compares their results to what is available in the literature.

      A major weakness of this work is the reliance on SOX9+ cells to represent DA-PT cells. This is relevant since their results show that less than 40% of the DA-PT cells express SOX9. SOX9 is not specific to DA-PT cells either, as they are seen in both PT cells and DCT1 cells as well. Additional clarification of these data would be important to enhacne the significance of this work.

    1. Reviewer #1 (Public Review):

      The Signal Peptidase Complex (SPC) processes signal peptides in a wide variety of secretory and membrane proteins that are inserted into the ER membrane in eukaryotic cells. How SPC discriminates transmembrane segments of membrane proteins from signal peptides remains elusive. The work of Kim et al shows that the Spc1 subunit of the SPC enzyme is involved in the quality control function of SPC facilitating accurate cleavage of signal peptides and preventing it from cleaving after transmembrane segments. The work is well executed and the experiments are done in triplicate.

      The approach that Kim et al use is to investigate signal peptide cleavage of carboxy-peptidase Y (CPY) variants with extended amino-terminal regions of various lengths and with low, intermediate or high hydrophobicity of the H region of the signal sequence. The results show that signal peptide processing by Signal Peptidase Complex (SPC) depends on the n-region and the h-region. Signal peptide cleavage of the internal signal sequences is greater in the Spc1 knock out strain.

      In addition, Kim and coworkers study SPC-mediated cleavage after a TM segment of single spanning and a double spanning membrane protein, based on the model membrane protein leader peptidase. Their results (Fig. 4 and Fig. 5) show Spc1 acts as a negative regulator of cleavage of the model single and double spanning membrane proteins when the stretch is quite hydrophobic. Notably, the presence of Spc1 does not completely eliminate SPC cleavage of the artificial membrane proteins. It is not an all or nothing effect, suggesting that the artificial constructs are not faithfully mimicking a membrane protein, which you do not want to be cleaved.

      Given this, it remains unclear what would be observed for physiological membrane proteins that are not normally SP processed but do have a potential signal peptide cleavage site immediately at the C-terminal region. The authors model predicts that such proteins should be cleaved by SPC in the absence of Spc1, and, if this were observed, it would conclusively prove that Spc1 plays a fidelity function and contributes to the accuracy of signal peptide cleavage by SPC.

    1. Reviewer #1 (Public Review):

      Sorrentino et al explore the possible link between 'neuronal avalanches' in resting MEG signal and structural connectivity in the human brain. They estimate neuronal avalanches by applying a threshold to identify large perturbations in the source reconstructed MEG data before binarising the time-series to define 'active' and 'passive' windows in each voxel. Sequences of 'active' voxels are identified starting with any region becoming active and ending when all voxels become passive. The probability of an avalanche transitioning between any two voxels in the MEG data is compared to network structure identified from diffusion imaging in the same individuals. The authors show that brain regions with a high function transition probability are also likely to be structurally connected. Whilst the core finding is interesting, the results are undermined by a lack of controls for confounds.


      This paper utilises a straightforward and intuitive analysis approach to tackle a complex question - how does functional activity spread throughout the brain? The simple thresholding in the neuronal avalanches approach avoids a number of complex steps typically associated with electrophysiology connectivity estimation such as strong filtering and complex frequency transforms. Sorrentino et al are able to show that this simple time-domain measure is able to provide an interesting overview of functional network structure. Moreover, this method naturally works to explore networks structure in transient, aperiodic signals which are often overlooked in favour of an oscillatory perspective.

      The authors consider a range of analysis pipelines to show that the core results are robust to key analysis decisions. Two different parcellations and methods for computing transition probabilities are considered and the results are shown to hold when using diffusion MR data from the HCP project.


      The authors claim that these results are unlikely to be caused or affected by linear mixing or volume conduction - however this is not clear to me based on the presented information. Specifically, if a perturbation arises in one region and is mixed by volume conduction into a second region, part of its shape will be preserved but this will be at a lower overall amplitude. Therefore, as the whole perturbation shape will be scaled down in the second mixed region, it is likely that its rising edge will reach the z-score threshold at a later time than in the original signal. In this way linear mixing by volume conduction has the potential to create spurious time-lagged in this analysis. Previous literature on neuronal avalanches in MEG have included extensive control analyses and discussions on linear signal mixing for this reason (10.1523/JNEUROSCI.4286-12.2013). This point is not tackled in the analysis and not clearly discussed in the paper.

      The correlation in Figure 2 B and C is interesting but is not supported by control analyses to account for confounds. For example, ROI size could potentially lead to more apparent structural connectivity and stronger MEG signal driving an apparent correlation between the modalities. This authors conclusions would be better supported if such effects were ruled out.

      The main results are not well developed from the available data. The group level correlations are visualised and the subject-specific correlations are brieflly shown but not described in detail. It is unclear which regions and connections show the highest correlations. Similarly, there is wide between subject variability in the structure<->function correlation which ranges betwee 0.1 and 0.35 but the analysis does not explore whether this is reproducible, neuronal variability or driven by differences in SNR.

    1. Reviewer #1 (Public Review):


      The authors present a very interesting and appealing approach to relate physiological damages observed after the extreme drought in 2018 to drought resistance genes in the European tree species Fagus sylvatica. Climate change and observed drought damages are a pressing issue for the forestry sector. The species is widespread through Europe and an important timber tree. Sampling took place in Hessen, Germany, in a 90x150km area. The authors used poolGWAS and a recently established reference genome to infer associated SNP loci by contrasting allele frequencies with replicated pools of drought susceptible and resistant trees. The authors also test the detected loci by a linear discriminant analysis based on an additional set of trees from the same region (SNP assay). The authors found systematic and quantitative genomic differences for drought susceptibility in the sampled population based on 7 significant loci located within genes and a few more loci (12) to be located close to genes associated with drought susceptibility in previous studies. The authors conclude that the significant loci found help to accelerate and monitor adaptation of beech to climate change. And they conclude from their results that there is enough genetic variation in beech to adapt to increasing drought and future climate change.


      • The authors used a so-called XP-GWAS or poolGWAS approach, a relatively new (Yang et al. 2015, Zou et al. 2016), time and cost efficient whole genome sequencing method. By using a strictly pair-wise sampling design (XP-GWAS), pitfalls of traditional GWAS studies are avoided. In addition, the authors make use of the recently established reference genome of Fagus sylvatica (however, the used version not yet published). This genetic approach was successfully used in a similar way for crop plants and another broad-leaved tree species (Fraxinus excelsior, Stocks et al. 2020). Sampling effort and sequencing resolution seem to be adequate according to Yang et al. 2015 and yield 106 significantly phenotype associated SNP loci.

      • Environmental variables used in this study contain very detailed climate data from 1950 onwards and mean monthly evaporation potential from 1991 onwards for all sites used for sampling. There are other drought indicators that better correlate with vitality traits such as the ratio of actual versus potential evapotranspiration or minimal site water balance (based on local field capacity) as has been shown for other central European beech forest sites (Braun et al. 2020, Schweiz Z Forestwes 171). But such climate data are difficult to obtain for dense and large-scale samplings without a monitoring background.


      • Small-scale differences in soil water availability and other possible abiotic or biotic factors at the sampling scale of tree pairs are not considered in this study. In the first hypothesis statement, local environmental variation is ruled out by the fact, that the selected trees stand next to each other and, thus, are neighboring trees in the forest. But such small-scale variation should be at least be considered and discussed Literature recommendations: Kätzel 2008, Bolte et al. 2008 (see Sutmöller et al. 2008), Carrière et al. 2019. Furthermore, the (maximum) distance between the pairs of trees is not stated.

      • The selection criteria used for damages versus resistant trees are unclear and the stated selection criteria are not specific to drought stress but rather more general stress indicators (see Wohlgemuth et al. 2020, Schweiz Z Forestwes 171). Traits used seem not to be consistent with protocols from internationally recognized monitoring networks (e.g. ICP forest manual, www.icp-forests.net). Attention should be paid also to the fact that observed stress symptoms have a multivariate background. Modelling analysis of long-term data show that other environmental factors such as N deposition are correlated with the changes in health status observed in central European beech forests and show interactions with drought indicators (Braun et al. 2020, Schweiz Z Forstwes 171, see also Pflug et al. 2018).

      • The authors found only few drought-associated loci (7) to be located within genes and a few more (12) to be located close to genes associated with drought susceptibility in previous studies. Although most of the genes found in this study had putative homologs in other plant species, none were involved in a transcriptomic study on drought response in beech saplings (Müller et al. 2017, see discussion paragraph). It is questionable whether these systematic and quantitative genetic differences are large enough to infer that there is a genomic basis for drought resistance in beech and that genetic variation is large enough in this species to cope with future climate change, also with respect to its distribution across Europe.

      The authors study the genomic basis of drought susceptibility and found systematic and quantitative genomic differences. However, the results seem not to be very strong in supporting the conclusions drawn. It is not clear whether the power of the GWAS study is affected by the precision of phenotyping, pool size, selection intensity, marker density or the depth of sequencing. Moreover, geographic limitations of the study and how that limits conclusions with respect to the species range have not been considered. This could, for example, be based in estimates of genetic variation across the species range such as in Magri (2006) New Phytologist and other newer references.

      This study presents an important issue in forestry and forest ecology and implemented a recently developed, time and cost efficient, genetic approach that has only rarely been applied to woody long-lived species.

    1. Reviewer #1 (Public Review):

      This paper focuses on using liquid chromatography and mass-spectrometry (LC-MS) to compare peptidome of human wound fluid. In this study, uninfected healing wound fluid and infected would fluid were evaluated for potential differences that can predict wound status and infection risk. The authors concluded differences between plasma and wound fluid as well as differences between non-inflamed/non-infected wounds fluid in term of signature of LG-MS peptidome and peptide alignment maps.

      Through their analysis they found many traditional biomarkers associated with wounds such as the cytokines IL-1β, 403 IL-6, IL-8 and TNF-α; the major novel findings come from the vast number of new peptide sequences they described, that could be used as wound biomarkers or drug targets in the future. The major counterargument for their otherwise novel findings is the same group's recent publication on wound biomarkers recently published in Frontiers in Immunology, "Bioinformatic Analysis of the Wound Peptidome Reveals Potential Biomarkers and Antimicrobial Peptides".

    1. Reviewer #1 (Public Review):

      The authors consider the effects of the cilium geometry and motility on its performance in detecting chemicals in the surrounding fluid. They begin by presenting a classic solution of the diffusion equation in an infinite fluid domain at rest, bounded internally by a single cilium. The cilium is modeled as a cylinder of finite length and perfectly absorbing boundary. They compare the capture rate of ambient chemicals at the cilium boundary to that of an absorbing circular patch on a reflecting wall of similar surface area. The latter is another classic solution of the diffusion equation. They find that the capture rate by the cilium exceeds the capture rate by the circular patch. Then, they solve the advection-diffusion equation around the cilium numerically, assuming perfectly absorbing boundary conditions along the cilium and reflecting boundary conditions on the wall. They apply this numerical framework to cases (i) where cilium is at rest in an external shear flow, (ii) where the cilium is actively beating, and (iii) where a bundle of hydrodynamically-interacting cilia are either at rest or actively beating. They observe an increase in capture rate when shear flows and motility are accounted for.

    1. Reviewer #1 (Public Review):

      The primary strength of this paper is the attempt to characterize the neurons injected by Toxoplasma and the electrophysiological changes that ensue. Three major problems are however noted.

      1) Figure 1 attempts to identify regions of the brain more profoundly impacted by Toxoplasma and does so by normalizing the numbers of injected neurons to the size of the region. But since the reporter system used requires the parasite injected protein to interact with a neuron's nucleus, The authors claims can only be valid after normalizing not to size but to density of nuclei in a region. This is especially important in the cortex where different layers have distinct architectures.

      2) The authors claim that inhibitory neurons are significantly less injected than excitatory ones. But how do they know that the inhibitory ones just don't die more quickly.

      3) All of the electrophysiological changes that are reported to happen in the injected neurons can be most easily explained by the fact that they are unhealthy due to the injection. This does not mean that the data are insignificant since increased neuronal damage/death in injected neurons is a critical finding.

    1. Reviewer #1 (Public Review):

      In this manuscript, McLeod and Gandon propose a framework for understanding multidrug resistance (MDR) evolution in a structured population in terms of linkage disequilibrium (LD) dynamics, and apply this framework to three concrete examples of MDR evolution. I was asked to evaluate this manuscript, as well as the authors' response to comments from previous reviewers. My expertise is in epidemiological modelling of antibiotic resistance; I am not hugely familiar with population genetics.

      Overall, I think the authors address an important and interesting question, and I think the approach has the potential to generate valuable insights. I also think the authors addressed the previous reviewers' comments well. However, I have substantial concerns about the modelling framework and the interpretation of the results. In particular: i) there are some problems with the interpretation that LD arises from variation in susceptible density; ii) presenting these results as a re-interpretation and generalisation of Lehtinen et al. 2019 is incorrect; and iii) the modelling of additive transmission costs needs further thought/explanation.

      1) Interpretation of results and re-interpretation of Lehtinen et al. 2019.

      The authors present their results as a generalisation of the effect observed in Lehtinen et al. 2019. Both models show that variation in the strength of selection for resistance between populations can give rise to LD in a model of multiple resistances. In Lehtinen et al., this variation in selection is attributed to variation in clearance rate. The authors re-interpreting the effect as arising from variation in susceptible density instead. This re-interpretation is incorrect: the change in how costs of resistance are modelled (additive here, multiplicative in Lehtinen et al.) changes the evolutionary dynamics, so the two models capture different evolutionary effects. (See points 2 and 3 for further discussion of additive vs multiplicative costs).

      One way to see this is to consider a simple model of single resistance as presented in Lehtinen et al. eqn 1, in which resistance is selected for when: B_r/a_r > B_s/(a_s + tau), where "B" is the transmission rate, "a" the clearance rate and tau the treatment rate. Re-arranging for tau shows how the threshold of selection for resistance depends on the strain's properties (B and a) under different assumptions about cost. With an additive cost in transmission (i.e. B_r = B_s - c), this threshold depends on both transmission rate and clearance rate, predicting LD if populations vary in either transmissibility or duration of carriage. With an additive cost in clearance, this threshold is independent of the strain's properties, predicting no LD. These are precisely the results the authors describe lines 268-277 and Figure 3.

      However, if the costs are multiplicative, this threshold depends on clearance rate only, whether costs are modelled as part of clearance or transmission rate. This is why the model in Lehtinen et al. 2019 predicts LD when populations vary in duration of carriage, even when there is no transmission cost. The author's re-interpretation of the effect in Lehtinen et al. as arising from variation in the density of susceptibles, contingent on an explicit transmission cost, is therefore not correct. More generally, representing one model as a generalisation of the other is misleading.

      I am also not sure about the authors' interpretation that the effects in the model with additive costs arise from variation in susceptible density. Variation in the density of susceptibles can also be generated by variation in the overall population density, so if I understand correctly, this interpretation would predict that LD would arise if the population density was different between populations? And that the selective pressure on single resistance would also depend on overall population density (argument stating line 261)? I am not able to reproduce this dependence of population density in a simple model. I would instead interpret the effect the authors observe as arising because the same additive transmission cost is much more significant if the baseline transmission rate is low (e.g. with c = 1, a strain with B_s 1 would never evolve resistance because B_r would be 0, which would not be the case for a strain with baseline transmission rate B_s = 3).

      The problem with the interpretation in terms of susceptible density is clear in the section on serotype dynamics. The main text refers to serotype-specific susceptibles (S^x) (line 303) and explains observed effects in terms of variation in S^x. In the supporting information however, the authors present a model of serotype dynamics which does not have serotype-specific susceptible classes and the pool of susceptibles is the same for all serotypes (eqn 43). While I absolutely agree this is a better model to study transient effects than introducing a serotype-specific susceptible class, I don't understand what the authors mean by serotype-specific susceptible density in the main text.

      2) The use of an additive transmission cost

      The use of an additive transmission cost requires further consideration/discussion. An additive transmission cost is difficult to interpret epidemiologically and can lead to implausible consequences. For example, if costs are high enough compared to baseline transmission rate, additive costs with no epistasis would lead to a negative transmission rate for the dually resistant strains, which does not make sense (say B_ab = 2 and B_Ab = B_aB = 0.5, then B_AB = -1).

      3) Why is epistasis defined in terms of an additive rather than multiplicative expectation?

      I also have quite a basic question about the overall framework (eqn. 2). In the modelling framework, epistasis is the difference between the actual per capita growth rate of the dually-resistant infections and the expected growth rate, defined as the sum of the difference between the growth rates of the singly-resistant infections and the baseline rate. It was not obvious to me whether the expectation needs to be additive, or whether this is a question of definition (could the expectation be defined, for example, as a multiplicative rather than additive effect?). In particular, I was wondering about this in the context of the authors' suggestion that multiplicative costs are problematic because they give rise to epistasis - this seemed a little tautological to me because epistasis has been specifically defined as deviation from an additive expectation. I think a discussion about why epistasis is defined in terms of additive effects, and the implications for the derivation of the dynamics of D, would be very interesting and also helpful in making the paper more accessible.

    1. Joint Public Review:

      Chen et al. identify LIN37, a member of the DREAM transcriptional repressor complex as a new regulatory factor in DNA double-strand break (DSB) end resection. The study commences with a CRISPR-Cas9 screen for chromatin associated RPA in quiescent pre-B cells that lack DNA ligase 4. In addition to the established anti-resection components 53BP1-Shieldin, findings that validates the screen, the authors identify the transcriptional repression complex LIN37-DREAM. This well executed study makes a number of compelling observations. Namely, that LIN37 limits end-resection only in quiescent cells, that it is not epistatic with 53BP1-Shieldin, and loss of Lin37 allows expression of hundreds of genes including genes involved in DSB end resection and homologous recombination. yielding Rad51 filament formation and HR. All phenotypes were recapitulated by a LIN37 mutant that that does not interact with DREAM. Moreover, generality is shown across human and mouse cell types using either Cas9 breaks or IR.

      The results presented in this manuscript are fascinating and should open a new avenue to study cell cycle dependent regulation of DSB repair. The combination of cell biological and end-seq approaches make a very convincing argument for this unanticipated finding. The conclusions drawn from this work are for the most part well-supported by the data, which are of high-quality, and the experiments are rigorously performed. What is unclear is whether these effects are direct or indirect, including whether other DREAM factors also participate in this end-resection suppression. It would also be nice to know the cellular consequences of dysregulated HR that occurs in quiescent LIN37-deficient cells.

    1. Reviewer #1 (Public Review):

      This paper shows that the sphingomyelin-degrading enzyme SMPDL3B is under transcriptional control of SIRT1 and c-Myc in ESCs, and that loss of SIRT1 lowers sphingomyelin content of ESCs. Sphingomyelin accumulation in SIRT1-deficient ESCs is associated with changes to membrane fluidity and the abundance of several differentiation markers. The paper also includes interesting data showing that maternal HFD feeding increases the SM content of SIRT1 KO embryos. The studies presented are thorough and the data are interesting.

    1. Reviewer #1 (Public Review):

      The authors used EEG-based multivariate pattern analysis and acute stress induction to assess the neural representations mediating a previously demonstrated influence of stress on the balance between goal-directed and habitual responding. They found that stress reduced neural outcome representations and enhanced response representations - results that are consistent with associative structures thought to mediate goal-directed and habitual response strategies, respectively. The study addresses an important and open question, and the combination of clinical, neural and behavioral assays is appealing. However, the interpretability, and thus impact, is threatened by an apparent lack of temporal synchrony between relevant measures, and by the potential effects of social feedback.

      Specifically, it is hard to understand how neural and behavioral devaluation differences between groups can be stress related given that they emerge at a point when differences in stress measures (e.g., cortisol) are no longer present. It seems more likely that, at the time when devaluation insensitivity became more pronounced in the stress group, this group was being released from stress, perhaps experiencing corollary fatigue or buoyancy.

      Another concern is that it is unclear whether the "Error" feedback screen was being employed during devaluation blocks. This is important, because most human psychology experiments use accuracy as the only incentive, and it appears to be a pretty effective motivator. Given that participants in the stress group had just been subjected to an aversive social stressor, they might have found the socially relevant error feedback more painful than the relatively minor response cost.