Reviewer #2 (Public Review):

The goal of this study was to provide in situ measurements of how combined eye and body movements interact with real 3D environments to shape the statistics of retinal motion signals. To achieve this, they had human walkers navigate different natural terrains while they measured information about eyes, body, and the 3D environment. They found average flow fields that resemble the Gibsonian view of optic flow, an asymmetry between upper and lower visual fields, low velocities at the fovea, a compression of directions near the horizontal meridian, and a preponderance of vertical directions modulated by lateral gaze positions.

Strengths of the work include the methodological rigor with which the measurements were obtained. The 3D capture and motion capture systems, which have been tested and published before, are state-of-the-art. In addition, the authors used computer vision to reconstruct the 3D terrain structure from the recorded video. Together this setup makes for an exciting rig that should enable state-of-the-art measurements of eye and body movements during locomotion. The results are presented clearly and convincingly and reveal a number of interesting statistical properties (summarized above) that are a direct result of human walking behavior.

A weakness of the article concerns tying the behavioral results and statistical descriptions to insights about neural organization. Although the authors relate their findings about the statistics of retinal motion to previous literature, the implications of their findings for neural organization remain somewhat speculative and inconclusive. An efficient coding theory of visual motion would indeed suggest that some of the statistics of retinal motion patterns should be reflected in the tuning of neural populations in the visual cortex, but as is the present findings could not be convincingly tied to known findings about the neural code of vision. Thus, the behavioral results remain strong, but the link to neural organization principles appears somewhat weak.

to give out something, especially products, services, or amounts of money 分配、發放

a stringed instrument of the harp class having an approximately U-shaped frame and used by the ancient Greeks especially to accompany song and recitation (https://www.merriam-webster.com/dictionary/lyre) 古希臘的七弦豎琴

an artifice or trick in war for deceiving and outwitting the enemy (https://www.merriam-webster.com/dictionary/stratagem) 計謀、詭計、策略、戰略

英勇possessing or acting with bravery or boldness

有組織的歌唱團（如在教堂禮拜中）an organized company of singers (as in a church service)

通過拉動或拉動使（某物）移動:施加牽引力to cause (something) to move by pulling or drawing : to exert traction on

規模大或宏偉large or magnificent in scale

打破慣有的友好關係a break in accustomed friendly relations

無所畏懼 Courageously resolute especially in the face of danger or difficulty

刺穿 To pierce through with or as if with a pointed weapon

突然的衝動或心血來潮 A sudden impulse or whim

傲慢 Having or showing an attitude of superiority and contempt for people or things perceived to be inferior

a feeling of contempt for someone or something regarded as unworthy or inferior 蔑視

DANS LE CADRE D'UE NOTE CRITIQUE POUR L1 PSYCHOLOGIE IED

Reviewer #2 (Public Review):

In this study, Ippolito and colleagues elucidated the molecular mechanism of CMK-1 shuttling between the nucleus and cytoplasm and its function in the context of regulated thermosensation in C. elegans. This study is built on their previous work that identified a specific Nuclear Export Sequence (NES) required for CMK-1 cytoplasmic localization at 20{degree sign}C, and a specific Nuclear Localization Signal (NLS) to promote prolonged heat (28{degree sign}C)-induced CMK-1 nuclear entry. Here they show additional functional NES and NLS which counteract previously identified elements: the NLS297-307-dependent nuclear entry pathway and the S325-dependent cytoplasmic accumulation. Combined with their previous study, their work suggests a model: upon prolonged FLP neuron stimulation by noxious heat, CaM binding to CMK-1 causes CKK-1-dependent phosphorylation of T179, which in turn has a context-dependent dual effect: it is sufficient for nuclear translocation at 20{degree sign}C in an NLS71-78-dependent manner, and it promotes NES288-294-dependent nuclear export at 28{degree sign}C.

The authors thereby established a direct link between the state of a signal transduction pathway and FLP neuronal activity in response to heat stimulation. They used multiple approaches, including transgenics and reporter quantification analysis to characterize CMK-1 nucleo-cytoplasmic dynamic equilibrium. The experiments are well-designed with appropriate controls and appropriate sample sizes. The data analysis is comprehensive and revealing. The findings expand the functionally relevant intrinsic CMK-1 subcellular localization determinants. The new understanding generated in this study will appeal to readers in the fields of cell biology, signal transduction, and physiology.

Reviewer #2 (Public Review):

In their paper Variation in thermal physiology can drive the temperature dependence of microbial community richness, Clegg and Parwar present a relatively simple phenomenological model for explaining the wide variety of empirically observed relationships between temperature and diversity in the microbial world. Previous theories such as the Metabolic theory of biodiversity (MTB) and the metabolic niche hypothesis have emphasized the role of energy through either more efficient cellular kinetics or temperature-dependent niches. This paper builds on these works by showing that if one accounts for the variation of temperature sensitivity across species, one can get a much richer set of behaviors consistent with empirical observations.

Overall, I find the manuscript quite compelling and the model presented as a very nice summary of how variability in temperature dependence, simple Arrhenius scaling, and arguments based on modern coexistence theory can be combined to explain empirical observations of species abundance distributions and temperature.

Reviewer #2 (Public Review):

Despite high bone mineral density, increased fracture risk has been associated with T2D in humans. In this study, the authors established a model that could mimic some aspects of T2D in mice and then study bone turnover and metabolism in detail.

Strengths<br /> This is an exciting study, the methods are detailed and well done, and the results are presented coherently and support the conclusions.<br /> Previous work from Dr. Long's group over this last decade has established a requirement for glycolysis in osteoblast differentiation. They showed the requirement for glycolysis not only for the anabolic action of PTH but also as an effector downstream of Wnt signaling. Using the T2D mouse model they have generated, they test if manipulating glycolysis and oxidative phosphorylation can rescue some of the detrimental effects on bone in this model.<br /> They use several novel approaches, they use glucose-labeling studies that are relatively underutilized, and it provides some insights into defective TCA cycle. They also utilize BMSCs that have been sorted for performing single-cell sequencing studies to identify specific populations modified with T2D. Unfortunately, the results are modest and need some clarification on what these populations add to the story.<br /> The authors use two approaches: a drug (Metformin) and a number of mouse genetic models to over-express genes involved in the glycolytic pathway using Dox inducible models. The results with overexpressing HIF1 and PFKFB3 show a potential rescue of bone defects with T2D, and Glut1 overexpression does not rescue T2D-induced bone loss.

Concerns<br /> The authors have generated several overexpression models to manipulate the glycolytic pathway to recuse T2D-induced bone loss. The use of DOX in drinking water has been shown to affect mitochondrial metabolism. Did the authors control for these effects? Since both the groups of mice got the DOX in drinking water, there is internal control.<br /> Only one of the rescue experiments had control with the Chow diet. There are some studies that have shown a high-fat diet to be protective of bone loss in TID models.<br /> The use of metformin to correct metabolic dysfunction and, thereby, bone mass is an exciting result. Did the authors test to see if they had in any way rescued this phenotype because of reducing ROS levels? The decrease in OxsPhos seen with the seahorse experiments suggests there could be mitochondrial dysfunction often associated with ROS generation.<br /> All of the experiments used male mice (because STZ use and ease of T2D establishment in males). It would be better if this were made clear in the title.<br /> Is the T2D model presented really represent what is observed in humans? Some experiments to test the other factors implicated in T2D and whether those are modulated in the rescue experiments might help address this.

Reviewer #2 (Public Review):

The underlying toxic species in C9ORF72 FTD/ALS is debated, with evidence for the contribution of both loss of function and gain of function of sense G4C2 repeat-expanded mRNAs and DRPS has been shown. The authors ask what the role - if any - of the antisense C4G2 repeat expanded mRNAs, which are equally abundant in patient brains, in producing toxicity. They convincingly show a role for these, independent of DRP expression, and distinct from sense G4C2repeat-expanded in toxicity in cell lines, neurons, and zebrafish, mediated via PKR activation. The latter is shown through increased p-eIF2alpha and reduced protein synthesis rates, associated with toxic phenotypes, rescued by PKR knockdown. The authors have achieved their aims, where the excellent data strongly support their conclusions.

The mechanism for PKR activation by antisense but sense repeat-expanded mRNAs is not examined, but the authors reasonably propose secondary structure differences in PKR activation. This could be tested in future work.

The work adds to our understanding of mechanisms of toxicity in repeat disorders, and this particular mechanism has implications for therapy via ISR modulation to reverse the effects of PKR activation.

The human data adds to the spectrum of protein-misfolding neurodegenerative diseases that show UPR/ISR activation, again with implications for therapy via ISR modulation.

Interestingly, PKR knockdown only partially rescues cell toxicity in neuronal cells, possibly reflecting other toxic mechanisms at play.

Reviewer #2 (Public Review):

This work continues the exploration of the GspB protein as a cytosolic hub for different cell wall enzymes. In particular, this manuscript presents evidence for the direct interaction of GspB with both FtsZ and PBP4 in Staphylococcus aureus. Structural determination is provided for the N-term region of GspB alone and in complex with the small cytosolic region of PBP4 recognized by GspB.

After previously published works from the same group identifying the connection between GspB and FtsZ, and from another group providing the structural basis for the interaction between GspB and PBPs in different bacterial species; the present work provides incremental information for the S. aureus case. The work is sound, and the experimental evidence supports the presented conclusions.

The main strength of the manuscript is providing pieces of evidence of the protein-protein interaction between GspB and FtsZ and between GspB and PBP4.

However, no structural information is provided for the GspB:FtsZ complex, and the 3D structure of the N-term domain of GspB is very similar to previous ones solved for other bacteria, but with the presence of a three-residues insertion that provides flexibility to the domain, a fact that seems to be important in vivo.<br /> The complex of N-term GspB with the cytosolic micro-domain of PBP4, reveals the interactions involved in the recognition; an interaction network that is similar to the previously reported for GspB and PBPs in bacillus subtilis and in Streptococcus pneumonia.

Reviewer #2 (Public Review):

This study examined the relationship between dopamine synthesis capacity, working memory, impulsivity, and spontaneous eye blink rate. The rationale for the study is sound and well-articulated given the results of prior studies suggesting relations between dopaminergic measures and these behavioral measures. Understanding these relationships is important both for understanding the neural and neurochemical correlates of behavioral traits, but also because it has been proposed that these measures might be used as a proxy for dopamine synthesis capacity, which is extremely expensive to collect and requires exposure to radiation. The study used appropriate methods and a major strength is that it was performed in a larger sample than is typical for PET studies, which are typically underpowered due to the expense of using radioligands. Critically, the study did not find evidence for associations. Although the results can be seen as disappointing in that they failed to confirm hypotheses, the findings nevertheless have substantial implications for the field. Specifically, the results argue against the use of these behavioral constructs as a proxy for dopamine synthesis activity. As such, the findings provide a critical corrective for prior conclusions that were derived from past smaller studies.

Reviewer #2 (Public Review):

This is an interesting study that seeks to deorphanize Tango2, a protein linked to muscle dysfunction but with no known function. It reveals that Tango2 primarily co-localizes with mitochondria, and its loss impacts mitochondrial homeostasis. Tango2-depleted cells also accumulate LDs. Lipidomic analysis indicated a partial depletion of diacyl lipids including PA in Tango2-depleted cells, and an accumulation of lyso-lipids such as LPA. The proposed model suggests that Tango2 plays a role in lipid metabolism, potentially in acyl-CoA trafficking and or delivery to lyso-lipids to generate diacyl-lipids for mitochondrial homeostasis, which is defective in tango2-deficient diseases like rhabdomyslosis. In general, this is a well-conducted and potentially important study. The first section which deals with Tango2 localization and profiling of cellular changes in Tango2-depleted cells is well conducted. However, the latter half which seeks to understand how Tango2 loss impacts lipid homeostasis is more preliminary. Lyso-lipids like LPA are definitely altered with tango2 loss, but additional work is necessary to understand whether this is due to increased lyso-lipid synthesis, a block in their acylation, or some combination of factors. Delineating these possibilities will significantly enhance this study.

Reviewer #2 (Public Review):

Dell'Amico and colleagues examine a C-terminal truncating mutation of WDR62, a gene identified as the 2nd most frequent cause of primary microcephaly. The authors generate neural progenitor cells and neurons from patient-derived IPSCs to examine the cell biological phenotypes of the truncation. This reveals the localization of WDR62 in the Golgi apparatus during interphase and suggests that shuttling from the GA to the spindle poles could be a potential mechanism underlying the effects of WDR62 truncation on cortical development.

Whereas these model systems are useful to study certain cell biological aspects of mutated cells, they do not fully recapitulate all features of the cortical development that the authors study. This model system lacks polarity of the tissue, which is important for a correct cell division of radial glia, which in turn is the key process impaired in microcephaly. Together with the inherent heterogeneity of the differentiation protocols, this poses a major weakness to the authors' approaches. On the other hand, the authors' system is well-suited for the analysis of co-localization and they show compelling evidence of the localization of WDR62 to the GA in interphase, which is the main strength of the study. These data are corroborated by immunostainings in fetal human tissue. Minor experiments are still needed to show a direct interaction of WDR62 with GA proteins and to further assess by immunofluorescence the GA-WDR62 co-localization in the radial glia of fetal human samples. Further, the author's interpretation that premature neurogenesis is not occurring in their system should be better supported by additional immunostaining. Finally, the manuscript is well written and the methods are adequately explained.

Reviewer #2 (Public Review):

The authors attempt to develop an allele-specific editing approach targeting RHO-T17M mutation for potential therapeutic use to treat the mutation associated with autosomal dominant retinitis pigmentosa.

1) The authors reported three sgRNAs for the RHO T17M allele for verification. It would be helpful to describe details of the discovery phase of these sgRNAs, including design, in silico predictions, inclusion criteria, off-target analysis, etc.

2) The authors claim that the targeted gene-editing efficiencies are dose-dependent. However, data were presented from only one mouse for the 5ｘ108 dose group (line 231-237), which might need more explanation.

3) With respect to Fig. 4C, the flat-mount retina is not representative. A better image of flat-mount of retina is preferred.

4) With respect to Fig. 6B & 6C, it seems that T17M protein and RHO-5m protein are likely detected in both cytoplasm and plasma membrane rather than being limited to the cytoplasm alone.

5) The therapeutic efficacy benefit should be supported by data of photoreceptor function and cell preservation after treatment. It is be better to include two more control groups, namely wild-type mice and untreated mutant mice, which may help evaluate improved response after treatment.

6) The mouse lines are confusing. Did the authors generate three lines of mice, including RHOwt/hum, Mut-RHOwt/hum, RHOhum/m-hum mice? Did the authors use the Rhohum/m-hum mice for verification of cutting efficiencies, whereas they use the other two lines of mice for rescue experiments? The authors should clarify.

7) Mut-RHOwt/hum mice have previously been reported to have fundus pigment abnormalities, so the fundus should be examined after rescue. The expression of Rho-5M mRNA was reduced in vitro. Was the expression of RHO mRNA also down regulated after rescue as well as in vitro? Did the subretinal injection of GFP spread to the whole retina? This can be determined with retinal flat mount or panretinal staining using GFP labeling. The authors showed that the cell numbers in the ONL were increased in the treatment group compared with the control group at 9 mpi. Were the other nuclear layers or plexiform layer also affected? Did the other retinal cells develop normally? Figure 8 showed retinal functions with AAV-based SaCas9/17-Sg2 in Mut-Rhowt/hum mice. ERG of Mut-Rhowt/hum mice without treatment are also needed.

The efficiency and safety of RHO T17M allele-specific editing in this paper are well supported by in vitro and in vivo experiments.

The fundamental basis of the study design should be clearly stated, ie which truncation variants in RHO cause disease or not. It is reported that truncation variants occurring before K296 are likely benign, which should be mentioned. This is the key starting point for this kind of study and is not limited to RHO. but as an allele-specific gene editing approach as a potential therapy for dominant mutations in any gene for which heterozygous loss-of-function is tolerated in the whole gene or in part of the gene (mostly at N-terminals). Apart from RHO, in fact, N-terminal truncating variants in several other IRD associated genes have been reported to be benign in heterozygotes, including CRX, TOPORS, RP1, etc. This study verified the efficiency and safety of this approach based on both patient derived iPSC and humanized animal models which are unique compared with other studies on RHO.

Reviewer #2 (Public Review):

In this paper, Pose-Méndez and colleagues have investigated the lifelong ability of zebrafish for functional Purkinje cell regeneration after selective ablation. Previous studies have determined that the adult zebrafish cerebellum lacks the capacity to regenerate Purkinje cells after traumatic injury. The authors use an elegant approach to determine whether selective ablation of Purkinje cells, a scenario closer to neurodegenerative disease, would allow for regeneration. The overall message is, that Purkinje cell regeneration is accomplished at every age after targeted ablation. The authors find in a series of well-executed functional and behavioral experiments that selective loss of Purkinje cells leads to a change in neuronal circuit activity and behaviors. During the regeneration process and interestingly before the full recovery of Purkinje cell numbers compared to controls neuronal activity as well as behaviors are recovered.

Reviewer #2 (Public Review):

In this elegant work,  the authors investigated dopamine release (measured by dLight sensor fiber photometry) in the nucleus accumbens shell, in response to salient luminance change. They show that abrupt visual stimuli - including stimuli not detectable by the human eye - can evoke robust dopamine release in the accumbens shell.

The fact that dopamine signals can be evoked by salient sensory stimuli is not itself novel, but the paper manages to make several important and new findings:

1. The authors show that the dopamine signal is not related to the level of threat evoked by the visual stimuli. <br /> 2. They provide important detail about the stimuli parameters relevant to dopamine release. For instance, they show that the rate of luminance change (or abruptness) is a key factor in evoking dopamine responses.<br /> 3. They show that robust dopamine responses can be evoked by visual stimuli of low intensity,  including stimuli not perceptible by the human eye.<br /> 4. They show that these dopamine responses can be evoked by all wavelengths in the visible spectrum (with some higher sensitivity at certain wavelengths).<br /> 5. Finally, by recording dopamine responses in two knockout mice strains, the authors show that the light-evoked dopamine release critically relies on rod and cone photoreceptors, but not melanopsin phototransduction. 

These results add to a series of recent findings showing that dopamine signals are not restricted to the encoding of reward prediction error, but instead contribute to signaling environmental changes more broadly. The study has been skillfully executed, the results are clear and appropriately analyzed, and the manuscript is very well written. Although the work did not include control mice lacking the dLight sensor, the fact that light-evoked dopamine responses were not observed in mice lacking cone + rod phototransduction is strong evidence that the fiberphotometry signals were not due to direct light artifacts.

Comment/concerns are minor:

1. The authors show that the dopamine response evoked by a brief visual stimulus is drastically reduced when the visual stimulus is repeated in rapid succession (stimulus train). The authors interpret this as evidence for the HABITUATION of this light-evoked dopamine release. An alternative explanation is that it is the prediction of the stimulus that is responsible for canceling the dopamine response (i.e. sensory prediction error). The authors should discuss this alternative explanation for this finding.

2. Although the study largely focuses on dopamine responses to visual stimuli, the results are largely consistent with previous studies showing dopamine signals encoding value-neutral changes in sensory inputs (i.e. sensory prediction errors) in different modalities (taste or odors; cf. Takahashi et al., 2017, Neuron; Howard & Kahnt, 2018, Nat. Comm.). The authors might want to cite those papers (note that I am not affiliated with those papers).

Reviewer #2 (Public Review):

This study adds value in the relatively new field, specifically in the topic of ET-B receptor. In this study the authors provide a new structure in ET-B receptor that might be beneficial to the development of ET-B agonist. However, from the clinical and physiological point of view, the manuscript did not provide sufficient evidence in its current form.

Reviewer #2 (Public Review):

Ribonucleotide reductase (RNR) is crucial for de novo synthesis of the dNTP building blocks needed for DNA synthesis and is essential in nearly all organisms. In the current study, all three E. coli RNRs have been removed and the essential function of the enzyme is bypassed by the introduction of an exogenous deoxyribonucleoside kinase that enables dNTP production via salvage synthesis. This leads to a complete dependency on exogenously supplied deoxyribonucleosides (dNs), loss of control of dNTP regulation, and a highly increased mutation rate. The bacteria could also grow with only supplied deoxycytidine (and no other dNs), indicating that all dNTPs could be synthesized from deoxycytidine. An evolutionary analysis of the recombinant E. coli strain grown in multiple generations showed that mutations accumulated in genes involved in the catabolism of deoxycytidine and deoxyribose-1-P, supporting a model that all the other deoxyribonucleosides can be produced by a phosphorylase using nucleobases and deoxyribose-1-P as substrates and that the deoxycytidine (besides being a precursor of dCTP) could be a substrate to produce the deoxyribose-1-P needed by the phosphorylase working in the opposite direction.

The story is very interesting with novel findings, and the experiments are well performed. There are a few missing pieces of information, but on the other hand, it is many steps to cover if everything is going to be shown in a single paper and I came to the conclusion that the data is enough at this stage. One of the missing points for future research is to check what happens with the dNTP pools. RNR is a very important enzyme to control the dNTP levels and it is likely that it is unbalanced dNTP pools that lead to the increased mutation rates. However, it would be interesting to really measure the dNTP pools and connect them to the mutations reported. Another missing piece is to identify which nucleoside phosphorylase is involved and investigate its substrate specificity to better understand why the cells can live on deoxycytidine but not other dNs.

Reviewer #2 (Public Review):

The aim of this article was to create a biologically plausible model of decision-making that can both represent a choice's value and reproduce winner-take-all ramping behavior that determines the choice, two fundamental components of value-based decision-making. Both of these aspects have been studied and modeled independently but empirical studies have found that single neurons can switch between both of the aspects (i.e., from representing value to winner-take-all ramping behavior) in ways that are not well described by current biological plausible models of decision making.

The current article provides a thorough investigation of a new model (the local disinhibition decision model; LDDM) that has the goal of combining value representations and winner-takes-all ramping dynamics related to choice. Their model uses biologically plausible disinhibition to control the levels of inhibition in a local network of simulated neurons. Through a careful series of simulation experiments, they demonstrate that their network can first represent the value of different options, then switch to winner-takes-all ramping dynamics when a choice needs to be made. They further demonstrate that their single model reproduces key components of value-based and winner-takes-all dynamics found in both neural and behavioral data. They additionally conduct simulation studies to demonstrate that recurrent excitatory properties in their network produce value-persistence behavior that could be related to memory. They end by conducting a careful simulation study of the influence of GABA agonists that provide clear and testable predictions of their proposed role of inhibition in the neural processes that underlie decision-making. This last piece is especially important as it provides a clear set of predictions and experiments to help support or falsify their model.

There are overall many strengths to this paper. As the authors note, current network models do not explain both value-based and ramping-like decision-making properties. Their thorough simulation studies and their validation against empirical neural and behavioral data will be of strong interest to neuroscientists and psychologists interested in value-based decision-making. The simulations related to persistence and the GABA-agonist experiments they propose also provide very clear guidelines for future research that would help advance the field of decision-making research.

Although the methods and model were generally clear, there was a fair amount of emphasis on the role of recurrence in the LDDM, but very little evidence that recurrence was important or necessary for any of the empirical data examined. The authors do demonstrate the importance of recurrence in some of their simulation studies (particularly in their studies of persistence), but these would need to be compared against empirical data to be validated. Nevertheless, the model and thorough simulation investigations will likely help develop more precise theories of value-based decision-making.

Reviewer #2 (Public Review):

The authors made an applaudable attempt to identify druggable cryptic pockets and address a controversy regarding a pH switch of a very large system of significant biological and Pharmaceutical interest. Due to the size of the system and uncertainty in the membrane interactions/curvature the draft produces etc, it is a nontrivial task. By using a previously validated mixed solvent (i.e., benzene mapping) protocol, the authors were able to analyze the potential pockets in the entire system. This is big technical advance and the protocol can be used by other works in the field for studying cryptic pockets.

Reviewer #2 (Public Review):

The authors want to capture the dynamics of CML therapy with TKI and understand why some patients fail to respond to therapy (primary resistance). They develop a mathematical model of hematopoiesis that includes stem cells, progenitor cells, and mature cells linked through feedback mechanisms. They explore parameter space using sophisticated algorithms to reduce this parameter space and the potential models to one final model and then apply it to chronic myeloid leukemia in the chronic phase under therapy with a tyrosine kinase inhibitor. The novelty in the model is the feedback mechanism introduced and the concomitant animal model data to understand the parameters.

The model is tractable and yet captures important physiologic aspects of hematopoiesis that have not been explored previously in CML. The animal data to validate it is also quite important. Finally, the application of the model to clinical data illustrates its applicability to real clinical scenarios and provides interesting insights.

One concern is whether the short-term transplantation experiments truly reflect the steady state of hematopoiesis and how CML develops in humans.

It is possible that the model can be applied to other hematologic conditions such as myeloproliferative disorders since one would expect the dynamics and interactions to be similar.

Reviewer #2 (Public Review):

Throughout the manuscript, the authors aim to distinguish signal from the lack of it. All conclusions depend on the success of this process. In such an endeavor, the sensitivity of the applied methods is critical. Thus, the authors must use the most sensitive tools to draw meaningful conclusions. The latest iGluSnFR has amazing sensitivity allowing the detection of single AP-evoked responses. This is not the case for vGpH, which requires hundred APs to get a meaningful signal. Similar, synthetic Ca2+ dyes have much better dynamic range, linearity and sensitivity compared to GCaMP6f.

The rate of silent boutons at 2 mM [Ca2+]e is lower for a single AP compared to 20 or 200 APs. The overall failure rate cannot be increased with increasing the number of APs. This clearly indicates a technical issue (e.g. insufficient sensitivity of vGpH and GCaMP6f).

The authors used three different measuring tools and used three different stimulation protocols, making the interpretation of the data challenging. It is impossible to tell how the failure rate changes from 1 to 20 APs without knowing the release probability, the pool size, depletion, recovery of SVs, and facilitation. These are all unknown.

The last experiment with the GABAB agonist has little novelty in its present form. The authors demonstrate that GABAB agonism increases the rate of silent terminals. The interesting issue would be to reveal how the effect of GABAB activation depends on the [Ca2+]e. This information is essential to see whether there is indeed a shoulder in its effectiveness curve.

The authors refer to a theoretical set-point in [Ca2+]e below which the function of the terminals is fundamentally different. From the presented experiments, the reviewer does not see any data that is inconsistent with a continuum. 'Thus, as with Ca2+ influx, SV recycling is modulated in an all-or-none manner by modest changes in [Ca2+]e around the physiological set point.' This statement is not supported by the data. The reviewer cannot see a set point.

Reviewer #2 (Public Review):

In this study, Bayliss et al. built a machine learning algorithm that predicts which country an isolate of Salmonella Enteritidis has come from based on its genome sequence. The study used S. Enteritidis isolates taken from clinical infections in the UK with recently reported travel, with the recent travel location being assumed as the source of infection.

The reason for developing this type of algorithm is to use it for source attribution in the case of gastroenteritis cases caused by imported food or cases of gastroenteritis picked up during travel overseas. S. Enteritidis is a major cause of gastroenteritis worldwide. Its transmission is tied in with the food chain, and understanding where it travels and how is key to reducing the burden of these infections. While a country's efforts to reduce the burden of these bacteria within its own borders can have tremendous benefits, imported food can still introduce contaminated meat and produce, and these have indeed become larger proportional risks following control efforts in the UK.

S. Enteritidis shows strong geographical substructuring across its phylogenetic tree. Traditional phylogenetic analysis is time-consuming (particularly to perform repeatedly on a routine basis) and required highly skilled staff to perform. Machine learning should be able to identify genetic markers linked to clades typically found in a single location, without the need to build and interpret a phylogenetic tree.

There is some nice methods development work in this paper, with the employment of a hierarchical structure to the ML modelling pipeline and the use of an array of classifier, resampler, feature selection and parameter optimisation techniques to increase accuracy.

However, the main strength of this paper is how well tailored the model is to a real world use case. Many groups are applying machine learning to genomic data, but often not with a clearly defined use case or realistic training and testing conditions. The results begin by giving the reader an understanding of the current state of this work in a UK context, where all clinically reported cases of Salmonella are sequenced and when appropriate, travel history is recorded. The algorithm is designed to fit into this existing practise and thought has been put into how this would be operationalised. For example, the authors have shown that this work can truly be done in real-time, by developing an algorithm that works directly on raw reads and takes <4 mins to run. A great touch in this work was determining the time horizon over which the model should be retrained to keep up with contemporary geographic distributions of this pathogen. The time horizon itself may not be highly generalizable in genomic epidemiology, but the methods provided make it easier for others to make the same assessment for their pathogen and use case.

A weakness of the work is the areas where predictions are not as accurate, but this relates to the extent of pathogen sequencing today rather than the method itself. Countries with less accurate predictions are ones which few people return from with an infection and if they do, it tends to be a different strain each time, making building an accurate algorithm for these cases impossible without denser sampling outside of clinical infections or more sequencing of infections occurring in other countries. Without proofs of concept like this, there is less of a strong economic argument to justify these investments. Therefore this work represents an important step in demonstrating the feasibility of the method itself and the value in gathering more data. In contrast, a major strength of this work is that it uses data collected routinely from existing practice in the UK, rather than a bespoke sampling strategy that may not be realistic for routine public health. A comparison of the collection to NCBI also found this sampling to be less biased by specific outbreaks of interest, which is encouraging.

The training dataset appears to be only based on infections acquired overseas, while I suspect the model would be more useful in investigating infections due to imported contaminated food. An unresolved question from this work is therefore whether the source of travel-acquired infections and infections caused by food imported from the same places is the same, or whether exported vs domestically consumed food around the world is treated differently in important ways that would affect the relative prevalence and success of strains in causing infections. Looking at clinical infections also may bias Salmonella to those that cause more severe forms of infection, as many people don't report to a doctor when they have food poisoning. The large egg-related outbreak that did not feature much at all in the UKHSA dataset is potentially a nice example of this.

The low accuracy on countries with low infection numbers and high genetic diversity indicates that these algorithms would likely become less accurate over time if food safety is improved, and that individual countries could avoid being confidently attributed as a source of infection by eliminating or controlling major circulating foodborne clones. More clearly communicating when a prediction is uncertain could be helpful in dealing with isolates from countries where it is hard to make a determination.

One final limitation I see is the exclusion of UK Salmonella isolates - in cases where it is uncertain whether a Salmonella infection is due to import or not, it does not seem possible to make this assessment using the ML tool. This also limits the utility of the tool for other countries that might also benefit.

The authors have done an excellent job of demonstrating the feasibility of this approach and honing their machine learning workflow to the specific demands of the task. The work presents a clear and well thought out use case with the overall performance of the algorithm broken down into test cases where the algorithm is successful and unsuccessful which provide useful insight into what we can expect from the performance of these approaches.

Finding a way to better communicate when the source of an outbreak is unclear due to poor representation of a clade or a clade that is found in many countries would be a valuable extension of this work in the future, but as it is the results represent a promising starting point for initiating investigations into the source of Salmonella infections.

Diarrheal disease is a huge health burden worldwide. Previous work to lower the burden of these infections has shown that targeted interventions can make a substantial difference to the burden of disease and success of clonal outbreaks. The availability of a tool that can be used routinely to assess the most likely overseas origin of an infection could potentially highlight previously unrecognised outbreaks or areas of suddenly increased importation rate. In turn, this could lead to better investigations and targeted improvement of food security.

This paper provides an excellent case for the value of collecting recent travel history and including it in metadata for pathogen genomic data. If this were done in more countries with different patterns of travel and the data could be shared, this would provide a valuable global resource and start to capture the flow of strains internationally.

I am curious about the implications of being better able to attribute clinical gastroenteritis cases in the UK (and elsewhere) to food imported or travel to specific countries with respect to trade and regulation. This is well outside the scope of the paper, however the ability to capture isolates commonly picked up from food around the world without the cooperation of these countries raises interesting issues, particularly when factoring in the authors' scenarios of the true country of origin being obscured by uneven travel patterns and complex food supply networks.

Reviewer #2 (Public Review):

The mechanism for early-onset osteoporosis (EOOP) is not well understood. The authors performed PLS3 knockout and characterized its bone phenotype in a rat model. This provides a very useful tool for studying EOOP and the potential treatment for EOOP. The authors did a very nice job of characterizing the phenotype including the assessments of bone turnover markers, bone histomorphometric analyses, and bone biomechanical tests. The results from these assessments led to the conclusion that this PLS3 knockout rat model mimics the human EOOP. In addition, treatment with currently available drugs for osteoporosis is effective in this EOOP model. These results support further clinical investigation of anti-osteoporosis drugs for EOOP management.

Reviewer #2 (Public Review):

The manuscript at hand by Sharma et al. presents new data on neurons of the stellate ganglia that are relevant for autonomic control of the heart. The authors identify stellate ganglionic neurons (SGN) that innervate the heart by retrograde tracing techniques and differentiate them from SGN neurons innervating other organs and tissues (mostly paw is used as a control). They subsequently employ single-cell RNAseq and morphological and functional (electrophysiological) studies. Their main finding is the identification of 3 SGN subtypes that they were further able to stratify into high and low neuropeptide Y cells. These subpopulations differ with regard to gene expression and action potential generation indicating different electrophysiological properties and different roles in the sympathoexcitation of the heart. They validate these findings by in vivo experiments where electrical stimulation of stellate ganglia after NPY-expressing neurons was depleted and find that heart rate change was lower under stimulation with high frequencies for NPY-depleted mice. The research question is very relevant and might have important therapeutic consequences for patients with cardiac diseases. The paper is written clearly. The methods applied are elegant and appropriate and the data support the conclusion.

The authors do report on some experiments in which stellate ganglion was used. Viral administration and physiological studies were performed on the right, while RNA sequencing was done from the right and left stellate ganglion. As there are physiological lateral differences between the effects of the left and right stellate ganglion, it would be useful to thoroughly report which side was used for which experiment throughout the manuscript and to discuss whether any lateral differences are relevant for the obtained results and conclusions.

Reviewer #2 (Public Review):

The authors develop statistical tests for assessing whether two hemispheres of the Drosophila larval brain are bilaterally symmetric, and more generally to develop a framework for comparisons of connectomes. The study is organized in order of increasing complexity of the statistical test, beginning with a simple test of whether or not the two sides of the brain have equal connection density. A more sophisticated approach is applied to a model in which neurons are partitioned into groups defined by preexisting known cell types on the left and right hemispheres and densities are allowed to vary between groups (a stochastic block model). A correction is included for an overall difference in density between hemispheres. Finally, analyses are applied to assess which cell types contribute to differences in the larval connectome. This identifies Kenyon cells as particularly distinct - a density-corrected stochastic block model with Kenyon cells removed results in no significant bilateral asymmetry. Results are also compared across different choices for thresholding of connection weights.

This manuscript tackles an interesting and timely problem. The analyses are largely straightforward applications of standard hypothesis tests for binomially distributed random variables. However, the observation that a density correction is needed to account for the two hemispheres' connection probabilities, and that a stochastic block model is sufficient to describe these probabilities, with the exception of the Kenyon cells, is interesting and makes more precise the notion of bilateral symmetry, at least at the level of connection probabilities, than previous approaches.

There are still several questions that remain about the generality of the results. The first concerns assumptions about the generative model for the graph. As the authors acknowledge, an Erdos-Renyi random network is a strong simplifying assumption. In particular, independent edge weights may be a restrictive model of connectome data given the broad degree distribution, spatial dependencies, and other features that characterize biological connectivity. A second question concerns the issue of statistical power. After partitioning neurons into groups, the most significant difference in connection probabilities comes from Kenyon cells, with the smallest p-value in the density-corrected comparison coming from KC-to-KC connections (Fig. 4B). However, KCs represent a large group of neurons, and the KC-to-KC connection probability is among the highest in the larval brain (Fig. 3B), raising the question of whether the observation of a significant difference specifically for these neurons is simply due to increased power. Third, connection density is only one of the many graph features that may be relevant for evaluating connectome similarity.

In total, although the analyses are straightforward, the study represents a first step toward the evaluation of connectome similarity and should spur further work in this important direction.

Reviewer #2 (Public Review):

The two new micropeptides are well characterized in the manuscript and appear to be functionally important with some chromatin-level consequences of their loss (which can be either direct or indirect), but the finding that lincRNA sequences encode micropeptides is not novel, and the two described in the paper appear to be zebrafish-specific and their function was tested only in zebrafish, which limits the interest in these genes. The use of ribosome profile data along behavioral screening to identify micropeptides is interesting and important, but the scope of the screen, the candidates selected for testing, etc. are not clear enough as presented. The ChIP-seq analysis of the new proteins is very interesting but is not described in any detail. Overall, the experimental part is well designed and the phenotypes reported by the authors appear to be strong and convincing, but the mechanistic understanding of what the two new proteins do and how, and the general interest in the results given the current scope of understanding of micropeptide is limited.

Reviewer #2 (Public Review):

In this work, the authors have carried out an extensive and highly granular survey of Mycobacterium ulcerans carriage by possums who are living on the outskirts of Melbourne Australia, in areas that are known hot spots for cases of Buruli ulcer (BU). The work is the culmination of many years of endeavour by this team, who first identified that the faeces of possums can be highly positive for M. ulcerans DNA, genetically linked to the strains found in BU patients who live in, or have visited, the area.

Surveys across two seasons were performed. Based on qPCR data to identify M. ulcerans carriage, spatial mapping of this, and BU case data, a statistical model was generated using data from the Mornington Peninsula that was better predicted than a null model. This statistical model was then validated using a second independent site at Geelong. As a result of this data, there can now be little doubt that possums play a vital role in the transmission cycles of BU in the region, and will allow mitigation strategies to be designed and tested. As BU is a necrotising skin disease that can cause disability and permanent disfiguration even in a high-resource setting such as Australia, such approaches are urgently needed.

Strengths:

The scale (both in terms of geographic reach/granularity and time) of the surveillance effort to understand the distribution of M. ulcerans DNA in the local possum population is unprecedented.

Since BU is a notifiable disease in Australia, the researchers have access to comprehensive clinical information across the study period.

The statistical model developed had a strongly positive influence over the ability to predict where BU cases will arise, over areas with a small radius (several km) which is the first time this has been achieved. The process by which this model was developed and validated seems robust.

Weaknesses:

In their model, the authors have used an assumed "exposure window" for when patients were infected with M. ulcerans in the Mornington Peninsula. Correctly defining, and assigning, this is absolutely critical to the accuracy of the statistical model, as is "blinding" of researchers assigning mesh boxes to patients to the results of surveillance data (and vice versa). These aspects are not fully clear in the current version. Furthermore, the effects on the model of changing these assumptions are not discussed.

The presence of M. ulcerans DNA in possum excreta and in patient samples is defined by qPCR for IS2404, a multicopy insertion sequence. Greater justification for using this as the sole marker is required, as this insertion sequence is also present in other mycolactone-producing mycobacteria. Moreover, some samples were claimed to be 'positive' with Ct values of 40 without justification for using this value (such as standard curves).

Comparing the summer and winter surveys at the Mornington Peninsula, the distribution of M. ulcerans positive excreta appears to have changed quite substantially, especially given that the possums are reported to be highly territorial with a range of only 100m. This version of the manuscript does not formally compare these spatial distributions, only the averages. Such an analysis would help understand if it is the possums that are moving, whether the possums undergo 'waves' of carriage (or indeed any other explanation), or if these apparent differences are down to chance.

Reviewer #2 (Public Review):

In their manuscript, Francou and colleagues study the delamination of epiblast cells into the mesodermal layers using live imaging of mouse embryos cultured ex vivo. By segmenting the apical area of delaminating cells, they quantify extensively the dynamic behavior of delaminating cells. Using immunostaining and crumbs2 mutants, they propose that apical constriction of cells results from pulsed contractions, which could be guided by crumbs2 signals.

The manuscript is interesting and provides extremely valuable data for our understanding of mouse gastrulation. Occasionally, the manuscript can be a bit confusing and contains a few inaccuracies. However, the main issues I have are with some of the interpretations from the authors, which may be incorrect due to limited time resolution (with a 5 min time resolution that was used, it might be difficult to distinguish pulses from measurement noise) and the analysis of immunostaining data, which would require more rigorous quantification.

Reviewer #2 (Public Review):

This manuscript documents the study of the transcriptome of Borrelia burgdorferi at 1, 2, 3 and 4 days post-feeding in nymphs of Ixodes scapularis. The authors use antibody-based pull-downs to separate bacteria from tick and mouse cells to perform an enrichment. The data presented support that the transcriptome of B. burgdorferi changes over time in the tick. This work is important as until now, only limited information on specific genes had been collected. This is the first study of its kind and is valuable for the field.

The manuscript is overall well written and easy to follow. The data are compelling and support the conclusions.

Reviewer #2 (Public Review):

Mitochondria are essential cellular organelles that generate ATPs as the energy source for maintaining regular cellular functions. However, the degradation of sperm-borne mitochondria after fertilization is a conserved event known as mitophagy to ensure the exclusively maternal inheritance of the mitochondrial DNA genome. Defects on post-fertilization sperm mitophagy will lead to fatal consequences in patients. Therefore, understanding the cellular and molecular regulation of the post-fertilization sperm mitophagy process is critically important. In this study, Zuidema et. al applied mass spectrometry in conjunction with a porcine cell-free system to identify potential autophagic cofactors involved in post-fertilization sperm mitophagy. They identified a list of 185 proteins that might be candidates for mitophagy determinants (or their co-factors). Despite the fact that 6 (out of 185) proteins were further studied, based on their known functions, using a porcine cell-free system in conjunction with immunocytochemistry and Western blotting, to characterize the localization and modification changes these proteins, no further functional validation experiments were performed. Nevertheless, the data presented in the current study is of great interest and could be important for future studies in this field.

Reviewer #2 (Public Review):

The work presented in this manuscript focuses on the role of Cylicins in spermiogenesis and the consequences of their absence on infertility. The manuscript is presented in two parts: the first part studies the absence of Cylicins from KO mouse models and shows in mice that both isoforms of Cylicins are necessary for normal spermiogenesis. The evaluation of double heterozygotes is particularly useful for the second part which looks at the presence of mutations in these genes in a cohort of infertile men. A patient with two hemizygous/heterozygous mutations in the CYLC1 and 2 genes, respectively, was identified for the first time and the results obtained with the KO models support the hypothesis of the pathogenicity of the mutations.

In general, the experiments are perfectly performed and the results are clear. Numerous techniques in the state of the art in male reproduction are used to obtain high-quality phenotyping of the mouse models.

The discovery of two concomitant mutations in an infertile patient is very interesting and the work carried out on mice allows supporting that an absence of CYLC1 and a heterozygous mutation of CYLC2 could lead to a phenotype of complete infertility. However, as the mutation on CYLC2 is not identified as pathogenic, the pathogenicity of this mutation remains in question (the authors note this point in the discussion). It would be interesting to see if the mutated amino acid is conserved between different species. In mice, the authors have shown the importance of these proteins on the morphology of the acrosome. What about in humans?

Reviewer #2 (Public Review):

The manuscript by Gordon-Fennell et al. presents an open-source platform for the analysis of behavior in a head-fixed apparatus (termed OHRBETS). In addition to providing instruction on how to assemble and implement the apparatus itself, the authors validate its use across a set of procedures broadly relevant to the field of behavioral neuroscience - including operant conditioning and fluid consumption protocols run in conjunction with optical manipulation and/or recording of neural activity.

The manuscript is comprehensive and clearly very strong. It also has the potential to have a broad impact in the field as many labs start to move towards effective head-fixed behavior. I also appreciate the fact that this manuscript includes a range of very strong behavioral tests - including experiments where several reinforcer options are available. This could be used for studies assessing taste, preference, reinforcer value, etc. Overall, the manuscript is impactful and my enthusiasm for it is high.

Reviewer #2 (Public Review):

This work describes a new method to create three-dimensional macroscale fat tissues derived from adipocytes cultured in two-dimensional monolayers. By scraping the differentiated adipocytes from the tissue culture plastic and mixing them with an edible binding material, they have created fat tissues that demonstrate similar mechanical properties to native animal tissue. Additionally, using lipidomics, the authors demonstrate that lipid treatment of the cultured adipocytes modifies their fatty acid composition in the triglyceride as well as the phospholipid portions. The fatty acid profiles of the cultured adipocytes are then compared to those of native animal fat tissues.

Strengths:

This paper addresses the relevant issue of the development of a hypoxic and necrotic core during the culture of large three-dimensional structures. The authors describe a straightforward method to bypass the three-dimensional cell culture by assembling their macroscale fat tissues after the adipocytes have fully differentiated in a two-dimensional monolayer.

The authors use two different binders to assemble their fat tissues, alginate, and microbial transglutaminase, both GRAS-registered. As the authors recognized, in the field of cultivated fat production for food consumption, it is essential to use materials that result in an edible product. Importantly, the authors demonstrate with mechanical testing that the binder material is of more significance to the mechanical properties of the macroscale fat tissue than the degree of lipid accumulation of the adipocytes.

The authors describe a detailed fatty acid composition profile of murine and porcine cultured adipocytes, treated and untreated with Intralipid, and native fat tissues. This dataset gives valuable insight into the effect of lipid treatment on fatty acid composition.

Weaknesses:

In the introduction, the authors hypothesize that their approach reproduces the taste of native fat and describe that fatty acid composition provides insight into flavor. The paper does not provide an analysis of taste to test this hypothesis and the lipidomics data does not provide data on the flavor profile of the aggregated macroscale fat tissues. In the abstract, the authors describe that the 3D fats were visually similar based on uniaxial compression tests. However, this test does not describe visual similarity.

The authors describe that detachment of adipocytes during differentiation was avoided by carefully replacing media and adipocytes had to be scraped off the flask even after increased lipid accumulation as a result of Intralipid treatment in the porcine adipocytes. Cell detachment of adipocytes on tissue culture plastic is a common phenomenon limiting the long-term culture of adipocytes in 2D. It could be useful for the field if the authors could describe in more detail how they avoided cell detachment during adipocyte differentiation or if they could hypothesize why they did not observe this phenomenon.

The authors compare the fatty acid composition of cultured adipocytes to that of native animal fat tissue. In the discussion, the authors describe that genetics and diet likely have an influence on the fatty acid composition profile of animal fat tissue. To be able to understand better what the effect is of Intralipid treatment, and to determine if this treatment brings the fatty acid composition of cultured adipocytes closer to their native counterpart, the authors could have cultured adipocytes in vitro from cells derived from the same animals as those that provided the native animal fat tissue.

In the discussion, the authors claim that the aggregate of adipocytes after scraping looked like fat tissue. This claim is not supported by lipid staining of cryosections of these aggregates, which makes it not possible to visually compare to the images of cryosectioned native animal tissue.

At the end of the discussion, the authors imply that their macroscale aggregation concept can be applied to scalable bioreactor-based cell culture strategies. However, the authors do not demonstrate how their method of scraping adipocytes from a tissue culture flask (low degree of scalability) applies to the potential of combining large amounts of adipocytes cultured on microcarriers in suspension bioreactors (high degree of scalability). The authors have not addressed the limited scalability of monolayer cell expansion which is a significant part of their approach.

Reviewer #2 (Public Review):

Guinet et al address the question of whether the divergent lifestyles in hymenopteran insects determine the rates of acquisition and domestication of viral genetic elements. As endoparasitoids are intimately associated with their hosts and often develop as broods herein, they predicted that the acquisition rate is higher compared to free-living and ectoparasitoid hymenopterans. Following viral domestication in the new recipient wasp genome, these viral elements have been shown to contribute to endoparasitism by promoting the delivery of secreted compounds in insect hosts (where immature wasps develop). Because of this functional importance, the authors predicted that the rate of domestication is also higher in endoparasitoid wasps. I was impressed with the solid and rigorous approach that was followed to test these two hypotheses. The authors carefully ruled out confounding factors, including contamination of genome assemblies. Previously characterized hymenopteran genomes were included as positive controls to assess the developed pipelines. There was also great merit in using a Bayesian model to study endogenization within the phylogenetic framework. To summarize, this multi-pronged strategy to mine animal genomes for viral genetic elements has the potential of becoming a new benchmark for future studies.

Although the authors do partially achieve their aim of coupling endogenization with an endoparasitoid lifestyle, I am afraid some of the assumptions and generalizations hinder a more solid conclusion. I feel that categorizing hymenopterans either as free-living, endoparasitoids, or ectoparasitoids is an oversimplification. Many of the authors' arguments to associate endogenization with endoparasitoids also apply to free-living eusocial hymenopterans. Both endoparasitoid and eusocial insects can be relatively more exposed to viruses because of intimate conspecific interactions within confined spaces. As endoparasitoids intimately interact with their host, so do eusocial insects with their social guests (melittophiles, myrmecophiles, and termitophiles). Perhaps, you could even argue that some gregarious insects also fit the bill. I would be interested to see whether the conclusions hold when "free-living" is further subdivided and "eusocial" is a separate category. Second, I wonder why the authors did not include Wolbachia infection as an explanatory variable to explain the endogenization rate. Wolbachia bacteria infect the insect germline and are often associated with phages. These phages could thus be a major source of viral genetic elements. Having said that, I do not see any Symbioviridae, the phylogenetic clade in which these phages reside (https://doi.org/10.1371/journal.pgen.1010227), in Figure 2B - so perhaps this is a minor point.

Finally, in addition to the dsDNA virus - endoparasitoids relationship, the authors also detect a link between ssRNA viruses and free-living hymenopterans. (Maybe eusociality is biasing these results?) In any case, I realize the manuscript is already heavy in content but it would be interesting to also dissect these observations in a bit more detail.

Reviewer #2 (Public Review):

Salas-Lucia et al. investigated two main questions: whether the Thr92Ala-DIO2 mutation impairs brain responsiveness to T4 therapy under hypothyroidism induction and the mechanisms of neuronal retrograde transport of T3. They find that the Thr92Ala-DIO2 mutation reduces T4-initiated T3 signaling in the hippocampus, but not in other brain regions. Using neurons cultured in microfluidic chambers, they further describe a novel mechanism for retrograde transport of T3 that depends on MCT8 and endosomal loading (possibly protecting T3 from D3-mediated cytosolic degradation) and microtubule retrotransport. Finally, they present evidence of retrograde transport of T3 through hypothalamic projections and interhemispheric connections in vivo. The main novelty of this study is the delineation of the mechanism of T3 retrograde transport in neurons. This is interesting from the cell biology perspective. The notion of impaired hippocampal T3 signaling is relevant for the cognitive outcomes of hypothyroidism and its associated therapy. Although the data are exciting and relevant for the community, some issues need to be addressed so that conclusions are more clearly justified by data:

1) The title and the abstract mean that dissecting this novel mechanism of T3 retrograde transport may help improve cognition or brain responsiveness in patients taking T4 or L-T3 therapy. However, how initial results (Figs 1 and 2) connect to later data is not essentially clear. For example, do Thr92Ala-DIO2 mice present altered retrograde transport of T3? Would stimulation of retrograde transport in Thr92Ala-DIO2 mice rescue neurological phenotypes? Can the authors address this experimentally?

2) Although the authors present in vivo evidence of retrograde T3 transport in the hypothalamus and motor cortex, given the select susceptibility of the hippocampus to hypothyroidism, it would be especially interesting to test whether this mechanism also happens in a hippocampal circuit (CA3-CA1 Schaffer collaterals, mossy fibers or perforant pathway).

3) Table 1 should present the raw values for Ala92-DIO2 mice and treatments instead of only displaying the direction of change and statistical significance. From Panels 1E-J, it is unclear if Thr92Ala-DIO2 mice or treatments caused any real change in brain regions other than the hippocampus.

4) The authors put forward the notion that a rapid nondegradative endosome/lysosome incorporation protects T3 from D3 degradation in the cytosol. Their experiments with pharmacological modulation of MCT8, lysosomes, and microtubules are in this direction. However, they do not represent an unequivocal demonstration of this mechanism. Therefore, the authors should be more cautious in their interpretation and discuss the limitations of their approaches.

Reviewer #2 (Public Review):

In this work, the authors tackle the question of how a non-linear decay in a morphogen gradient might affect downstream patterning specificity. In the first section of the paper, they address this theoretically, by examining the nature of morphogen gradients assuming either linear or non-linear degradation of the morphogen, using previously-established equations. Assuming variation in the concentration of morphogen at the source, they show that a linear decay model results in uniform shifts in the location of a threshold concentration of morphogen that only depend on the relative concentration changes, while a non-linear decay model yield shifts with more complex dependencies on concentration.

The next section of the paper addresses gradient patterning precision by accounting for not only variation in the source concentration of morphogen, but also in the parameters that describe the production, degradation, diffusion, and cell size, for both a linear and non-linear decay model. The key finding from this section is that, while non-linear decay can produce some improvements in patterning reliability near the morphogen source, it fares far worse than linear decay in regions far from the morphogen gradient. Simulations that include explicit morphogen-producing cells demonstrate that simpler models that exclude this detail may have overestimated the benefits of a non-linear morphogen decay.

The strength of this work is tackling head-on the question of how a non-linear decay of morphogen affects patterning precision using both theory and simulations. Non-linear decays have been observed in nature, and therefore this question is one of interest. The methods used by the authors provide convincing evidence for their claims, and the results, particularly the importance of simulating morphogen-producing cells, are likely to be of interest to the community interested in the design principles of morphogens and developmental patterning.

Reviewer #2 (Public Review):

In their study the authors aimed to investigate the dissemination of Enterobacterales plasmids between geographically and temporally restricted isolates recovered from different niches, such as human blood stream infections, livestock, and wastewater treatment works. By using a very strict similarity threshold (Mash distance < 0.0001) the authors identified so-called groups of near-identical plasmids in which plasmids from different genera, species, and clonal background co-clustered. Also, 8% of these groups contained plasmids from different niches (e.g., human BSI and livestock) while in 35% of these cross-niche groups plasmids carried antimicrobial resistance (AMR) genes suggesting recent transfer of AMR plasmids between these ecological niches.

Next, the authors set-out to examine the wider plasmid population structure by clustering plasmids based on 21-mer distributions capturing both coding and non-coding plasmid regions and using a data-driven threshold to build plasmid networks and the Louvain algorithm to detect the plasmid clusters. This yielded 247 clusters of which almost half of the clusters contained BSI plasmids and plasmids from at least one other niche, while 21% contained plasmids carrying AMR genes. To further assess cross-niche plasmids similarities, the authors performed an additional plasmid pangenome-like analysis. This highlighted patterns of gain and loss of accessory plasmid functions in the background of a conserved plasmid backbone.

By comparing plasmid core gene or plasmid backbone phylogenies with chromosome core gene phylogenies, the authors assessed in more detail the dissemination of plasmids between humans and livestock. This indicated that, at least for E. coli, AMR dissemination between human and livestock-associated niches is most likely not the result of clonal spread but that plasmid movement plays an important role in cross-niche dissemination of AMR.

Based on these data the authors conclude that in Enterobacterales plasmid spread between different ecological niches could be relatively common, even might be occurring at greater rates than estimated, as signatures of near-identity could be transient once plasmids occupy and adept to a different niche. After such a host jump, subsequent acquisition, and loss of parts of the accessory plasmid gene content, as a result of plasmid evolution after inter-host transfer, may obscure this near-identity signature. As stated by the authors, this will raise challenges for future One Health-based genomic studies.

Strengths<br /> The article is well written with a clear structure. The authors have used for their analysis a comprehensive collection of more than 1500 whole genome sequenced and fully assembled isolates, yielding a dataset of more than 3600 fully assembled plasmids across different bacterial genera, species, clonal backgrounds, and ecological niches. A strong asset of the collection, especially when analyzing dissemination of AMR contained on plasmids, is that isolates were geographically and temporally restricted. Bioinformatic analyses used to discern plasmid similarity are beyond state-of-the-art. The conclusions about dissemination of plasmids between genera, species, clonal background and across ecological niches are well supported by the data. Although conclusions about inter-host plasmid dissemination patterns may have been drawn before, this is to my knowledge the first time that patterns of dissemination of plasmids have been studied at such a high-level of detail in such a well selected dataset using so many fully assembled genomes.

Weaknesses<br /> One conclusion that is not entirely supported by the data is the general statement in the discussion that "cross-niche plasmid in not driven by clonal lineages". From the tanglegram, displaying the low congruence between the plasmid and chromosome core gene phylogeny in E. coli, this conclusion is probably valid for E. coli, but this not necessarily means that this is also the case for the other Enterobacterales genera and species included in this study. For these other genera, the data supporting this conclusion are not given, probably because total number of isolates for certain genera were low, or because certain niches were clearly underrepresented in certain genera.

Furthermore, the BSI as well as the livestock niches were analyzed as single niches while the BSI niche included both nosocomial and community-derived BSI isolates and the Livestock niche included samples from different livestock-related hosts. Given the fact that a substantial number of plasmids were available from cattle, sheep, pigs, and poultry, it would be interesting to see whether particular livestock hosts were more frequently found in the cross-niche plasmid clusters than other livestock hosts and whether the BSI plasmids in these cross-niche clusters were predominantly of community or nosocomial origin.

Reviewer #2 (Public Review):

The authors show how an avian influenza A virus that jumped into dogs is now evolving in real time. Though its evolutionary adaptation to dogs, the virus is gaining properties that are increasingly consistent with the potential to infect humans.

The data are alarming, although it should be emphasized that this dog H3N2 influenza virus has not yet infected humans, and perhaps never will. It is also unknown how pathogenic (medically serious) the virus would be in humans if it were to jump. The authors show preliminary data that prior exposure to human seasonal H3N2 will not render us resistant to this dog virus should it jump to humans.

What is most remarkable about this study is the breadth of experimental approaches taken, and the holistic analysis of what is bound to become a classic tale in virus evolution and emergence through an intermediate host.

Reviewer #2 (Public Review):

In this manuscript, Vias and co-authors develop HGSOC PDOs and characterized their genomes, transcriptomes, drug sensitivity, and intra-tumoural heterogeneity. They show that PDOs represent the high variability in copy number genotypes observed in HGSOC patients. Drug sensitivity was reproducible compared to parental tissues and the ability of these models to grow in vivo.

Overall, the manuscript lacks sufficient novelty. Several pieces of information and a number of conclusions that are presented here have been previously published by other groups (Nina Maenhoudt, Stem cell reports, 2020; Shuang Zhang, Cancer Discov, 2021).

Reviewer #2 (Public Review):

This is a well-written and clear manuscript, in which the authors describe the stepwise development of an approach for loss of function screens in a range of different Leishmania species, culminating in a small-scale screen. The method relies on CRSIPR/Cas9 directed mutation of cytosine bases to generate premature STOP codons. The conclusions of the manuscript are well supported by the data presented and this approach appears to have great potential to facilitate functional studies and discovery biology in a range of different species.

The authors have presented the development of their base editing toolbox in a stepwise manner, showing the optimisation steps they took. They initially used a tdTomato expressing cell line to optimise which base editor to use and examine constitutive versus episomal expression approaches. Before analysing specific proteins - PFR2, IFT88, PF16, MFT. This systematic approach gives confidence in their results and the utility of the system. The primer design resource with primer effectiveness score is great to see and will aid the adoption of this approach.

Line 482 - the authors wrote 'As expected, the proportion of cells showing a motility phenotype in the IFT88 targeted L. infantum population decreased further' Why is this result expected? Presumably, this is due to the fact that cells without a functional IFT system lack flagella and grow slower so can be outcompeted by faster-growing mutants. This speaks to the major caveat highlighted by the authors in the discussion and the final small-scale screen. In a population of cells, those with deleterious mutations in an essential gene or one whose disruption results in slower growth will be outcompeted by cells in which a non-deleterious mutation has occurred, which feeds into the issue of timing.

The authors show with CRK3 this process of non-deleterious mutants outcompeting deleterious mutants does result in a detectable drop in the number of parasites with specific CRK3 guides but not in those with IFT88. Is this due to the fact that the outgrowth of the non-deleterious IFT88 mutants occurs rapidly or that the mutation of the targets in IFT88 was ineffective? The data presented in Figure 5 shows that for some species at least a mutation of the IFT88 gene was possible. This might mean that for certain genes the outgrowth occurs within the first 12 days after transfections so will not be seen using this approach, without a wider study, which is beyond the scope of this manuscript it will be difficult to know.

The ability to readily generate cells resistant to miltefosine, highlight the strength of this approach in identifying the mode of actions/resistance mechanisms for anti-leishmanial drugs. Moreover, any screens using this base editing approach, in which cells expressing proteins without a changed functionality/expression are killed will likely be effective in identifying genes of interest. This could mirror the success that the genome-wide RNAi screens have had in Trypanosoma brucei.

This base editing approach now sits alongside using CRISPR/Cas9 to generate full gene deletion mutants and RNAi to help understand gene function in Leishmania. As discussed by the authors in their balanced discussion there are merits. A major advantage of this approach is the ability to simply generate a library of plasmids that will target the entire genome, whereas both full gene deletions and RNAi in L. braziliensis are more time-consuming and the latter lacks inducible control. However, as part of the LeishGEM project pools of barcoded deletion mutants are being generated, which have the potential to be used in other screens. Moreover, this base-editing approach has the potential to identify the function of essential genes, which is not possible when trying to generate stable deletion cell lines. However, this has only been demonstrated for one gene to date and the ability to detect slower-growing mutants varied greatly between different species.

The authors highlight that this base editing approach will leave potentially functional regions of the NT of proteins, which is true and may mean genes are missed. However, this may also provide extra information about the protein's function/domain structure if STOP codons in certain positions showed an effect on function whereas those in others don't.

Overall, the base editing approach in this manuscript looks to have great utility and in reality, is a complementary approach to the genetic tools we already have to study gene function in Leishmania. However, only time will tell how effective this method is through its adoption and effective use by different researchers.

Reviewer #2 (Public Review):

This umbrella review summarizes the results of systematic reviews about the impact of the COVID-19 pandemic on cancer care. PRISMA checklist is used for reporting. The literature search was performed in PubMed and systematic reviews published until November 29th, 2022 were included. The quality of included systematic reviews was appraised using the AMSTAR-2 tool and data were reported descriptively due to the high heterogeneity of 45 included studies. Based on the results of this paper, regardless of the low quality of included evidence, COVID-19 affected cancer care in many ways including delay and postponement of cancer screening, diagnosis, and treatment. Also, patients with cancer had been affected psychologically, socially, and financially during the COVID-19 pandemic.

Strengths:

This umbrella review has summarized many important aspects of cancer care that were affected during the COVID-19 pandemic.

Weakness:

The main limitation of the current study is that the authors have searched only one database, which might have missed some relevant systematic reviews. Also, most of the included reviews in this paper had low and medium methodological quality.

Reviewer #2 (Public Review):

The authors describe in the nematode C. elegans the effects of perturbed organization of Intermediate filaments (IFs), which form the cytoskeleton of animal cells together with actin filaments. They focus on a previously identified mutant of the kinase SMA-5, which when mutated leads to disorganized IF structure in intestinal cells of C. elegans. The authors found that the phenotypes caused by the mutated SMA-5 kinase concerning gut morphology and animal health can be reversed by removing IF network components such as the protein IFB-2. This finding is extended to other components of the IF network, which also display a certain degree of sma-5 phenotype alleviation when depleted.

Strength:<br /> The finding that suppressing the intestinal phenotypes caused in sma-5 mutants can be suppressed by removing functional IF components is an interesting observation. It confirms a previous study showing that bbln-1 mutation-caused IF phenotypes can be suppressed by depleting IFB-2.

Weakness:<br /> 1) The finding of suppressing the intestinal phenotypes caused in sma-5 mutants can be considered a minor conceptual advancement. However, the study comes short of providing insight into the molecular processes of how deranged IF networks and its consequence can be rescued/suppressed by removing e.g. the IFB-2 filaments. Many statements concerning the relationship between SMA-5 and the IFs are based on assumptions. The study requires protein biochemical analysis to show whether SMA-5 phosphorylates the IF proteins - mainly the IFB-2 polypeptide. The relationship between SMA-5 / IFB-2 is a central aspect of this study but the main conclusions are based on the notion that IFB-2 and other IF proteins may be phosphorylated by SMA-5. Mutating putative phosphorylation sites of IFB-2 without having shown any proof that the modification occurs by SMA-5 is futile. This important open question needs to be addressed. And will allow statements whether the ifb-2(kc20) mutant allele-encoded shorter IFB-2 protein lacks phosphorylation or not.

2) No quantification of the morphological defects such as using fluorescent-labeled IF proteins as in previous studies is provided in the manuscript. The EM pictures are not sufficient to provide information on how often the IF network perturbations and morphology defects occur. Also, the rescue of the actual morphological gut defects was not quantified. The assessment of development time and arrest, body length, lifespan, oxidative stress resistance, and others should be related to intestinal tube defects. They are useful and important but are an indirect measure of intestine defects and rescue.

3) It is not clear how exactly the mutant ifb-2 allele kc20 was identified. In the Materials and methods section, the authors provide information on the specific primers for the ifb-2 locus. But how did they know that the mutation lies within this region? Was there mutation mapping or whole-genome sequencing applied?

Reviewer #2 (Public Review):

In this study, the authors take a multipronged approach to identify the substrate repertoire of calcium-dependent protein kinase, CDPK1 in Toxoplasma that includes quantitative phosphoproteomics, myristoylation, thiophosphorylation, immunoprecipitation as well as proximity-based labeling. Their finding also reveals that CDPK1 functions in parasite invasion and egress by phosphorylating different protein candidates. More importantly, the authors successfully determine one branch of the CDPK1 signaling pathway that regulates invasion through the phosphorylation of the HOOK protein involved in the translocation and secretion of micronemal proteins.

Reviewer #2 (Public Review):

In this manuscript, the authors use an embedding of human olfactory perceptual data within a graph neural network (which they term principal odor map, or POM). This embedding is a better predictor of a diverse set of olfactory neural and behavior data than methods that use chemical features as a starting point to create embeddings. The embedding is also seen to be better for comparison of pairwise similarities (distances of various sorts) - the claim is that proximity of pairs of odors in the POM is predictive of their similarity in neural data from olfactory receptor neurons.

A major strength of the paper is the conceptualization of the problem. The authors have previously described a graph neural net (GNN) to predict verbal odor descriptors from molecular features (here, a 2019 preprint is cited, but a newer related one in 2022 describing the POM is not cited). They now use the embedding created by that GNN to predict similarities in large and diverse datasets in olfactory neuroscience (which the authors have curated from published work). They show that predictions from POM are better than just generic chemical features. The authors also present an interesting hypothesis that the underlying latent structure discovered by the GNN relates to metabolic pathway proximity, which they claim accounts for the success in the prediction of a wide range of data (insect sensory neuron responses to human behavior). In addition to the creativity of the project, the technical aspects, are sound and thorough.

There are some questions about the ideas, and the size of the effects observed.

1. The authors frame the manuscript by invoking an analogy to other senses, and how natural statistics affect what's represented (and how similarity is defined). However, in vision or audition, the part of the world that different animals "look at" can be very different (different wavelengths, different textures and spatial frequencies, etc). It is still unresolved why any given animal has the particular range of reception it has. Each animal is presumably adapted for its ecological niche, which can have different salient sensory features. In vision, different animals pick different sound bandwidths or EM spectra. Therefore, it is puzzling to think that all animals will somehow treat chemicals the same way.

2. The performance index could be made clearer, and perhaps raw numbers shown before showing the differences from the benchmark (Mordred molecular descriptor). For example, can we get a sense of how much variance in the data does it explain, what percent of the hold-out tests does it fit well, etc.?

3. The "fitting" and predictions are in line with how ML is used for classification and regression in lots of applications. The end result is a better fit (prediction), but it's not actually clear whether there are any fundamental regularities or orders identified. The metabolic angle is very intriguing, but it looks like Mordred descriptor does a very good job as well (extended figure 5). Is it possible to show the relation between metabolic distance and Mordred distance in Figure 2c? In fact, even there, cFP distance looks very well correlated with metabolic distance (we are talking about r= 0.9 vs r = 0.8). This could simply be due to a slightly nonlinear mapping between chemical similarity and perceptual similarity (which was used to get POM distance).

4. How frequent are such examples shown in Fig 2d? Pentenal and pentenol are actually very similar in many ways, and it may be that Tanimoto distance is not a great descriptor of chemical similarity. cFFP edit distance is quite small, just like metabolic distance. The thiol example on the right is much better. Also, even in Fig 2C POM vs metabolic distance, the lowest metabolic distances have large variations in the POM values - so there too, metabolic reactions that create very different molecules in 1 step can vary widely in POM distance as well.

5. A major worry is that Mordred descriptors are doing fine, and POM offers only a small improvement (but statistically significant of course). Another way to ask this question is this: if you plot pairwise correlation/distance of pairs of odors from POM against that for Mordred, how correlated does this look? My suspicion is that it will be highly correlated.

6. The co-occurrence in mixtures and close POM distance may arise from the way the embedding was done - with perceptual descriptors used as a key variable. Humans may just classify molecules that occur in a mixture as similar just from experiencing them together. Can the authors show that these same molecules in Fig 4d,e have very similar representations in neural data from insects or mice?

Reviewer #2 (Public Review):

Treatment of human illnesses caused by infection by hantaviruses are currently not available and hence research on new therapies are needed. The manuscript by Engdahl et al describes the characterization of four neutralizing antibodies with potency against hantaviruses using several approaches. This knowledge of these antibodies and where they bind in these studies can be used in the design of vaccines or the development of passive immunotherapeutic approaches and are hence very valuable for the advancement of new treatments. Hence this new knowledge is a major strength of the manuscript. the studies, however, the in vitro studies are limited in the use of pseudotyped viruses and not the actual viruses. Inclusion of the potency and binding of these to their native viruses, and standardization of their use in treatments of hamsters with these viruses, would elevate this approach to stand as a valuable contribution to the development of treatments for hantaviruses.

Reviewer #2 (Public Review):

This study uses behavioral monitoring and cutting-edge calcium imaging approaches to track the activity of cholinergic and noradrenergic axons in cortex of head-fixed mice, and correlate activity with behavioral state. The data confirm that much of this activity is dependent on behavioral state, and in particular is strongly correlated with arousal of the animal and is highly coordinated across axons. They also show that a small fraction of axonal activity is heterogenous, and does not seem to be dependent on global behavioral state. They describe additional details of this activity, such as that whisking activity is the best predictor of cholinergic and noradrenergic axon activity, and that noradrenergic activity is more transient during bouts of arousal (whisking) than cholinergic activity. Altogether this manuscript is generally very thorough analytically, most of the data appear technically sound, and the presentation is largely clear. However, the significance of the findings - exactly how much they enhance what is already known - is less clear.

The main advanced novelty of the approach is the use of mesoscale imaging, giving them the ability to analyze the degree to which neuromodulatory cholinergic and noradrenergic signals are uniform across cortex, or might be correlated with distinct behavioral states or events. They attempt to get at this in Figure 4, by determining how much of their detected signal from cholinergic and noradrenergic axon activity comes from a 'common signal' versus how much of the signal is residual once the common signal is subtracted, so presumably reflects a unique influence. This analysis and the reasoning behind it is very hard to follow, and it is not clear to us that these residual signals are truly meaningful (i.e. not coming just from some source of noise). The authors try to get at this meaning in Figure 4K by plotting partial minus ordinary correlations in different arousal states, but it is not clear to us what exactly this difference means, considering the ordinary correlation itself is different in those comparisons as well. The fact that there is a bigger difference between partial and ordinary correlations during whisking than in other states does not give us real information about where the partial correlation is from.

Reviewer #2 (Public Review):

Franz and colleagues set out to understand the mechanisms and cell types that contribute to melanocyte regeneration in the adult skin. Previously, they used genetics and imaging to identify cell populations (progenitors) in the adult skin that they believe contribute to melanocyte regeneration in adult zebrafish (Iyengar et al., 2015). Here, they use scRNA-seq to understand the molecular nature of these cells following melanocyte ablation with the copper chelator, neocuproine. From these studies, they claim to identify three types of progenitors (called melanocyte stem cells, McSCs): cells that give rise directly to differentiated melanocytes and depend on kit signaling; cells that undergo division before becoming fully differentiated; and cells that express high levels of a xanothophore marker (a yellow pigment cell) that also undergo cell division.

Strengths:<br /> The main strength of this work is the generation of scRNA-seq datasets of cells that express a melanocyte marker (mitfa) at multiple time points in adult skin during regeneration. This is an exciting dataset, and unique. The work gives an idea of the complexity of the regeneration process and paves the road for future studies on how McSC lineages contribute to melanoma. It is interesting to see how many of the processes and zebrafish cell types are conserved during evolution. By studying skin-associated melanocyte progenitors in adults, the authors provide insight into mechanisms poorly understood about melanocyte regeneration.

Weaknesses:<br /> (1) Data Interpretation in context: We have concerns regarding the labelling of the cells of interest "stem cells"; we prefer the term the authors themselves use "progenitors" (Iyengar et al., 2015). The authors do not place their work in the context of the wider field, especially with regards to the work on xanthophores and on regenerating melanocytes and adult McSCs in the embryo that contribute to the adult stripe.

(2) Cell type identity: Zebrafish contain another cell type called xanthophores that can also express mitfa and aox5 (Saunders et al., 2019). Indeed, in their supplementary tables, the authors call many of the mitfa+ aox5+ cells "xanthophores" based on their gene expression. There is no evidence here that these cells give rise to melanocytes. In their studies in Figure 7, we think that based on the shape of the cells, they may be looking at dividing xanthophores or unpigmented xanthophore precursors (McMenamin et al., 2014), rather than melanocyte stem cells. We don't know why these cells are dividing, but perhaps the loss of melanocytes in the adult stripe leads to an expansion of xanthophores.

(3) Analysis: The statistical approaches are not always correct, and some choices in the scRNA-seq analysis should be explained and/or revisited.

Reviewer #2 (Public Review):

The paper is intriguing, but to me, a main weakness is that the imaging experiments are done with overexpressed protein. Another is that the different results for the different subunits of TFIID would indicate that there are multiple forms of TFIID in the nucleus, which no one has observed/proposed before. Otherwise, the experimental data would have to be interpreted in a more nuance way. Additionally, there is no real model of how a TBP-depleted TFIID would recruit Pol II. Do the authors suggest that when TBP is present, it is not playing a role in Pol II transcription, despite being at all promoters? Or that in its absence an alternative mechanism takes over? In the latter case, are they proposing that it is just based on the rest of TFIID? How? The authors do not provide a mechanistic explanation of what is actually happening and how Pol II is being recruited to promoters.

Reviewer #2 (Public Review):

In this manuscript, Roberts et al. present XTABLE, a tool to integrate, visualise and extract new insights from published datasets in the field of preinvasive lung cancer lesions. This approach is critical and to be highly commended; whilst the Cancer Genome Atlas provided many insights into cancer biology it was the development of accessible visualisation tools such as cbioportal that democratised this knowledge and allowed researchers around the world to interrogate their genes and pathways of interest. XTABLE is trying to do this in the preinvasive space and should certainly be commended as such. We are also very impressed by the transparency of the approach; it is quite simple to download and run XTABLE from their Gitlab account, in which all data acquisition and analysis code can be easily interrogated.

We would however strongly advocate deploying XTABLE to a web-accessible server so that researchers without experience in R and git can utilise it. We found it a little buggy running locally and cannot be sure whether this is due to my setup or the code itself. Some issues clearly need development; Progeny analysis brings up a warning "Not working for GSE109743 on the server and not sure why". GSEA analysis does not seem to work at all, raising an error "Length information for genome hg38 and gene ID ensGene is not available". In such relatively complex software, some such errors can be overlooked, as long as the authors have a clear process for responding to them, for example using Gitlab issue reporting. Some acknowledgement that this is an ongoing development would be helpful.

The authors discuss some very important differences between the datasets in the text. Most notably they differ in endpoints and in the presence of laser capture. We would advocate including some warning text within the XTABLE application to explain these. For example, the "persistent/progressive" endpoint used in Beane et al (next biopsy is the same or higher grade) is not the same as the "progressive" endpoint in Teixeira et al (next biopsy is cancer); samples defined as "persistent/progressive" may never progress to cancer. This may not be immediately obvious to a user of XTABLE who wishes to compare progressive and regressive lesions. Similarly, the use of laser capture is important; the authors state that not using laser capture has the advantage of capturing microenvironment signals, but differentiating between intra-lesional and stromal signals is important, as shown in the Mascaux and Pennycuick papers. The authors cannot do much about the different study designs, but as the goal is to make these data more accessible We think some brief description of these issues within the app would help to prevent non-expert users from drawing incorrect conclusions.

The authors themselves illustrate this clearly in their analysis of CIN signatures in progression potential. They observe that there is a much clearer progressive/regressive signal in GSE108124 compared to GSE114489 and GSE109743. This does not seem at all surprising, since the first study used a much stricter definition of progression - these samples are all about to become cancer whereas "progressive" samples in GSE109743 may never become cancer - and are much enriched for CIN signals due to laser capture. Their discussion states "CIN scores as a predictor of progression might be limited to microdissected samples and CIS lesions"; you cannot really claim this when "progression" in the two cohorts has such a different meaning. To their credit, the authors do explain these issues but they really should be clearly spelled out within the app.

We are not sure we agree with their analysis of CDK4/Cyclin-D1 and E2F expression in early lesions. The authors claim these are inhibited by CDKN2A and therefore are markers of CDKN2A loss of function. But these genes are markers of proliferation and can be driven by a range of proliferative processes. Histologically, low-grade metaplasias and dysplasias all represent proliferative epithelium when compared to normal control, but most never become cancer. It is too much of a leap to say that these are influenced by CDKN2A because that gene is inactivated in LUSC; do the authors have any evidence that this gene is altered at the genomic level in low-grade lesions?

Overall this tool is an important step forwards in the field. Whilst we are a little unconvinced by some of their biological interpretations, and the tool itself has a few bugs, this effort to make complex data more accessible will be greatly enabling for researchers and so should be commended. In the future, we would like to see additional molecular data integrated into this app, for example, the whole genome and methylation data mentioned in line 153. However, we think this is an excellent start to combining these datasets.

Memindex dimensions mentioned in a 1904 advertisement<br /> cards: 2 3/4 x 4 1/2 inches<br /> case: 2 3/4 x 4 3/4 inches

Reviewer #2 (Public Review):

This study by Wang et al. examines changes in YAP expression in embryonic avian cultured explants in response to high and low shear stress, as well as tensile and compressive stress. The authors show that YAP expression is increased in response to low, oscillatory shear stress, as well as high compressive stress conditions. Inhibition of YAP signaling prevents compressive stress-induced increases in circularity, decreased pHH3 expression, and increases VE-cadherin expression. On the other hand, YAP gain of function prevents tensile stress-induced decreases in pHH3 expression and VE-cadherin expansion. It also decreases the strain energy density of embryonic avian valve explants. Finally, using an avian model of left atrial ligation, the authors demonstrate that unloaded regions within the primitive valve structures are associated with increased YAP expression, compared to regions of restricted flow where YAP expression is low. Overall, this study sheds light on the biomechanical regulation of YAP expression in developing valves.

Strengths of the manuscript include:<br /> - Novel insights into the dynamic expression pattern of YAP in valve cell populations during post-EMT stages of embryonic valvulogenesis.<br /> - Identify the positive regulation of YAP expression in response to low, oscillatory shear stress, as well as high compressive stress conditions.<br /> - Identify a link between YAP signaling in regulating stress-induced cell proliferation and valve morphogenesis.<br /> - The inclusion of the atrial left atrial ligation model is innovative, and the data showing distinguishable YAP expression levels between restricted, and non-restricted flow regions is insightful.

This is a descriptive study that focuses on changes in YAP expression following exposure to diverse stress conditions in embryonic avian valve explants. Overall, the study currently lacks mechanistic insights, and conclusions based on data are highly over-interpreted, particularly given that the majority of experimental protocols rely on one method of readout.

Reviewer #2 (Public Review):

The idea of using fluorescently labeled tandem SH2 domains to target tagged RTKs is brilliant and could potentially provide a powerful new way to assess the activation of RTKs in situ and in multiple physiological contexts. Thus, it was disappointing that there was insufficient characterization of the system to be able to interpret the data it generates. Although the paper shows that tagging the EGFR appears to have minimal impact on its biological activity, the readout for receptor kinase activity is % clearance of the fluorescent reporter tag from the cytosol. Such clearance is likely to depend on a variety of different factors, including the ratio of tagged receptors to probe, the number of functional pools in which the probe exists, the exchange rate between these pools, and the affinity of the probes for the tagged receptor. Without determining how each of these factors impacts % clearance, it is difficult to interpret either the dose-response curves or response kinetics.

For example, the difference in activation kinetics between EGFR and ErbB2 is very interesting, but the almost instantaneous rise (Fig S4B) is very surprising. The kinetics of activation of the EGFR have been extensively studied by mass-spectrometry and are generally limited by ligand binding, which has a characteristic time of several minutes, not seconds (pmid: 26929352; pmid: 1975591). Thus, such a response is suggestive of a freely exchanging ZtSH2 reporter pool that is mostly depleted in seconds with the slow secondary kinetics reflecting a slowly exchanging ZtSH2 reporter pool. Alternately, the cells could be accumulating an intracellular pool of activated receptors over time. That the authors are using concentrations of EGF >100-fold physiological levels (pmid: 29268862) further complicates the interpretation of these experiments.

There is also insufficient attention paid to either controlling or measuring important parameters, such as expression levels of tagged receptors or levels of endogenous receptors. 3T3 cells, contrary to the statement of the authors, do not have "negligible" numbers of EGFR: they have ~40K, which is typical for mouse fibroblasts. This is much higher than MCF7 cells, which are frequently used as a model system to study EGFR responses. Yet they do not see transactivation of their ErbB2 construct in 3T3 cells without expressing additional EGFR (Fig. 4C), suggesting low sensitivity of the assay. Conversely, they show a significant response mediated by endogenously tagged EGFR in HEK 293 cells, which are frequently used as an EGFR-negative cell line (PMID: 26368334). This indicates that their assay is extremely sensitive. Which is it? As mentioned above, it likely depends on the expression level and affinity of the different components of their system.

A great advantage of using the EGFR system as a test case for the new system is that thousands of investigations have been performed over the last four decades. This provides a strong foundation for determining whether the new technology is working correctly. For example, the dynamics of EGFR activation and trafficking at the single cell level have been documented in many studies, which show a remarkable consistency (e.g. see pmid: 24259669; pmid: 11408594; pmid: 25650738). Unfortunately, instead of using differences between the new results and previously reported data as a basis for refining their technique, the authors attempt to apply their raw data to address complex questions of EGFR dynamics, with less than satisfactory results.

For example, they attempt to use their technique to understand the basis of different signaling dynamics between EGFR ligands. Rather than being a relatively recent observation, differences in EGFR ligand signaling have been explored for over 30 years (pmcid: PMC361851), and are generally ascribed to differences in trafficking (pmid: 7876195). Based on these observations and resulting mathematical models, novel EGFR ligands have been designed with enhanced potency (pmid: 8195228 , pmid: 9634854 ). All this work was done over 20 years ago. Since then, new natural ligands for the EGFR have been discovered from sequence analysis and differences in their potency have similarly been ascribed to differences in their intracellular trafficking patterns (pmid: 19531065 - cited by the authors). An alternate hypothesis was proposed more recently by Freed et al (2017) as described by the authors, but that is what it is: an alternative hypothesis.

Unfortunately, the model that the authors use to test this hypothesis does not even include endocytosis or receptor trafficking but instead uses variable "scaling" factors to see if the data can fit the dimerization hypothesis. In the supplement, they state that "Since our simulations were run on relatively short time scales (~30 min post-stimulation), we did not consider trafficking and degradation of receptors." However, the half-life of EGFR internalization is generally ~3-4min (pmid: 1975591) and degradation ~1hr, so most of the signal shown in Figure 3 is likely to come from internalized rather than surface-associated ligand-EGFR complexes. A further complication is that internalization rates are strongly influenced by receptor expression levels (pmid: 3262110), which are not controlled for here. Thus, the omission of trafficking in their model is not appropriate. This does not mean that the authors are wrong, it simply means that without validation or calibration, their new technology is not ready to resolve current problems in the field.

Reviewer #2 (Public Review):

Mitterer et al investigated the role of the essential ATPase Spb4 in the maturation of the large ribosomal subunit precursor in the nucleolus using a combination of genetics, biochemistry, and cryo-EM. They suggest that the helicase Spb4 promotes limited RNA strand separation to drive reconfiguration of helices H62/H63/H63a at the base of domain IV of the 25S rRNA. The study also couples an in vitro pre-ribosome maturation assay with cryo-EM visualisation of pre-60S particles to recapitulate a major structural transition that is dependent on the recruitment of the AAA+ ATPase Rea1 to Spb4-bound particles. This structural transition is important as it promotes nucleolar exit of the 60S precursor from the nucleolus following the release of a limited set of ribosome assembly factors including the Ytm1-Erb1 complex together with the helicase Has1. The quality of the new cryo-EM maps provides a wealth of structural detail on the architecture of late pre-60S nucleolar maturation intermediates.

The paper is of high quality and clearly written with appropriately detailed methods. The figures are generally well-presented and informative. A strength of the study is that it provides insight into the function and mechanism of action of a poorly understood class of DEAD-box RNA helicases. The study reports the utility of in vitro pre-ribosome maturation combined with cryo-EM analysis to capture additional ribosome maturation intermediates, an approach that may become more widely adopted in the future among the ribosome synthesis community. The biochemical, genetic, and structural analyses strongly support the proposed mechanism for Spb4 function in reconfiguring helices H62/H63/H63a following induced RNA strand separation prior to the release of the Ytm1-Erb1 complex.

The authors suggest that Spb4 "induces" bending and strand separation of the rRNA at the base of ES27. They also suggest that the C-terminal domain of Spb4 "induces" substrate RNA strand disruption. However, an alternative possibility could be that the rRNA is sampling multiple conformations and that Spb4 stabilises one of these conformers. No direct experimental evidence for "induced" bending and strand separation by Spb4 is provided to support the claims.

The findings in the manuscript are generally consistent with a very recently published study on Spb4 function (Cruz et al., https://doi.org/10.1038/s41594-022-00874-9). However, the authors should cite this work and update the text to take account of this report.

Reviewer #2 (Public Review):

This is an intriguing study investigating the molecular mechanisms of the adhesion G-protein coupled receptor latrophilin-2 control of neural circuit developmental organization. Using the model CA1 to subiculum hippocampal circuit with its spatially segregated axon targeting, the authors experiments find that ectopic Lphn2 expression in CA1 neurons that normally do not express it, leads to axon mistargeting. The authors detail these circuitry alterations with Lphn2 genetic manipulations, finding that axon targeting is dependent on its GPCR signaling, likely through Galpha12/13 coupling.

Strengths: Building off the author's previous studies, the experiments are well designed and analyzed. The advance in this study is finding that Lphn2 expression in CA1 cells that normally do not express impacts its axon targeting. They go on to show compelling data that implicates this mistargeting is dependent on Lphn2 GPCR signaling properties, identified as likely Galpha12/13 dependent.

Weaknesses: The system used is a "misexpression system". By forcing cells with ordinally low levels to overexpress Lphn2, circuitry alterations are observed. While this gain of function assay demonstrates the importance as to why Lphn2 is not expressed in certain cell types, it isn't a physiologically relevant system to investigate Lphn2 dependent circuit development.

To strengthen this study, the following specific points could use addressing:<br /> • While the data is strong, some of the terminology used is unclear, including use of terms "repulsive receptor" and "repulsive ligand". The authors use "repulsive receptor" to describe Lphn2 action for axon targeting, but repulsion and attraction processes are simultaneous. Is Lphn2 really by acting as a repulsive receptor, or alternatively, by acting to shift axon attraction to Lphn2 expressing subiculum neurons?<br /> • For their proposed axon guidance model to work, Lphn2 has to be signaling through G12/13 proteins near the axon growth cone to induce its collapse and retraction. By using Flag-tagged Lphn2 constructs in their assays, this should be visible. Clear Flag-Lphn2 signal is observed in the dendrites of infected cells (Figure1-figure supplement 1; Figure5- figure supplement 1). But does Flag-Lphn2 also localize to the pCA1 axons that are projecting to the subiculum?<br /> • With their previous work, pCA1 to dSub circuit patterning is dependent on Ten3+ to Ten3+ homophilic attraction that exists between the two regions. Its unclear how ectopic Lphn2 is able to override this Ten3+ to Ten3+ connection patterning. Does ectopic Lphn2 outcompete Ten3 function in these neurons? Or alternatively, is Ten3 expression/localization impacted by the presence of ectopic Lphn2?

Reviewer #2 (Public Review):

In this work, the authors did a comprehensive model comparison to find the best predictor of where V genes are trimmed during the V(D)J recombination process, using their DNA sequence alone. This is an important step towards characterizing how the diversity of T-cell receptors and antibodies is generated and to better understanding the function of the enzymes involved in the process, such as Artemis.

The authors find that the best model uses a combination of the sequence-specific position-weight matrix, and the GC content of DNA on both sides of the cutting site, which they relate to the DNA's ability to "breathe." Their conclusions are based on a rigorous comparison of log-likelihoods using independent test data from other loci than the one on which the models were trained. The study also includes myriad tests and controls, increasing confidence in their conclusions.

Reviewer #2 (Public Review):

This is an excellent study performed by a world-leading research group in the field of the neural mechanisms of perceptual processing. The strengths of this work are the application of the MEG-fMRI fusion approach that links spatial locations in fMRI and time points in MEG and rigorous model-based analyses. The weaknesses may be a lack of a more concise visual illustration of the main findings and an in-depth discussion of some of the findings. The weaknesses are minor and the authors' conclusions are well justified by their data.

Reviewer #2 (Public Review):

The authors first characterize Siglec-1 clustering on immature and mature DCs and observe that clustering increases in mature DCs. Concomitantly with clustering, the mobility of Siglec-1 reduced. At the cell periphery of mDCs, Siglec-1 was enriched in actin-rich areas. A role for actin, specifically for the formin-nucleated actin was supported using inhibitors. Concomitantly the clustering of Siglec-1 was reduced. The localization of Siglec-1 to actin-rich filopodia was dependent on formin activation and RhoA, ROCK-mediated ERM phosphorylation. With respect to consequences for the binding of HIV particles, forming, and Rho-dependent Siglec-1 nanoclustering, enhanced binding of virus particles indicating that clustering of Siglec-1 provides for better docking sites. On the ligand side, high amounts of GM1 lipids (4%) were needed for liposomes to be captured by Siglec-1, reinforcing the idea of docking sites. Consistent with the important role of actin in the process, time course studies of virus binding to mDCs revealed dramatic changes in the plasma membrane architecture including the emergence of membrane ruffles, shrinkage of the basal membrane, and constriction of the cell membrane where VLPs accumulate on route to the formation of the virus-containing compartment. Overall, the strength of this report is its comprehensive nature, detailed and quantitative imaging analysis, and confirmation of the importance of Siglec-1 clustering (receptor) with liposomes containing the ligand GM1.

Reviewer #2 (Public Review):

Poison frogs are able to sequester alkaloids to make themselves toxic or unpalatable to predators. Despite much research, the proteins that accomplish this sequestering role are not well known. Here, biochemical and proteomic analysis identifies a liver-derived alkaloid binding globulin (ABG) as the main alkaloid binding molecule in the blood of poison frogs. The results are solid and address a major void in our understanding of plasma alkaloid transport in frogs. While some additional analysis of ABG mutants would further enhance the interpretations, the study represents an important starting point that suggests specific new roles for serpins in animal ecophysiology.

Reviewer #2 (Public Review):

Macrophages have been demonstrated to play a role in retinal diseases. Macrophage infiltration in melanomas is predictive of increased changes in metastases, and sub-types of macrophages play a role in diverse diseases including macular degeneration and diabetic retinopathy. Here the authors using a light-induced retinal degeneration model and using retinal explants, and peripheral blood-derived monocytes from patients with AMD show that M2a polarized macrophages drive this phenotype. The authors demonstrate this both in vivo and ex vivo and also demonstrate a role for cell-based and secreted factors. The work is fairly specialized and of interest to the vision research community but also has implications for macrophage biology. The data also connects systemic immunity to retinal cell death in diseases such as macular degeneration.

Reviewer #2 (Public Review):

The manuscript entitled 'Functional membrane microdomains and the hydroxamate siderophore transporter ATPase FhuC govern Isd-dependent heme acquisition in Staphylococcus aureus' investigates the heme transport over the bacterial cell membrane. The novelty of this paper is proving the requirement of a highly structured cell envelope that depends on functional membrane microdomains FMMs for bacterial nutrient acquisition. The authors showed that the heme-specific permease (IsdF) is associated with FMMs, to directly interact with the FMM scaffolding protein flotillin A (FloA) and to co-localize with the latter on intact bacterial cells since IsdF needs an appropriate location within the membrane for functionality.

The strengths of the manuscript:

It provides new evidence on the different mechanisms used by S. aureus to acquire iron. These new findings are essential in understanding the way this bacterium survives nutritional immunity and thus can be a target for novel therapeutic approaches.<br /> All the results were based on the necessary molecular techniques that strongly support the conclusions.

The weaknesses of the manuscript:

More details concerning different strategies of iron acquisition should be mentioned in the introduction.<br /> Additional bibliographic literature is needed for explaining what unknown ATPase partially substitutes for the function of FhuC.<br /> More experiments are needed in order to verify the speculations presented in the last part of the manuscript.

1930s Wilson Memindex Co Index Card Organizer Pre Rolodex Ad Price List Brochure

archived page: https://web.archive.org/web/20230310010450/https://www.ebay.com/itm/165910049390

Includes price lists

List of cards includes: - Dated tab cards for a year from any desired. - Blank tab cards for jottings arranged by subject. - These were sold in 1/2 or 1/3 cut formats - Pocket Alphabets for jottings arranged by letter. - Cash Account Cards [without tabs]. - Extra Record Cards for permanent memoranda. - Monthly Guides for quick reference to future dates. - Blank Guides for filing records by subject.. - Alphabet Guides for filing alphabetically.

Memindex sales brochures recommended the 3 x 5" cards (which had apparently been standardized by 1930 compared to the 5 1/2" width from earlier versions around 1906) because they could be used with other 3 x 5" index card systems.

In the 1930s Wilson Memindex Company sold more of their vest pocket sized 2 1/4 x 4 1/2" systems than 3 x 5" systems.

Some of the difference between the vest sized and regular sized systems choice was based on the size of the particular user's handwriting. It was recommended that those with larger handwriting use the larger cards.

By the 1930's at least the Memindex tag line "An Automatic Memory" was being used, which also gave an indication of the ubiquity of automatization of industrialized life.

The Memindex has proved its success in more than one hundred kinds of business. Highly recommended by men in executive positions, merchants, manufacturers, managers, .... etc.

Notice the gendering of users specifically as men here.

Features: - Sunday cards were sold separately and by my reading were full length tabs rather than 1/6 tabs like the other six days of the week - Lids were custom fit to the bases and needed to be ordered together - The Memindex Jr. held 400 cards versus the larger 9 inch standard trays which had space for 800 cards and block (presumably a block to hold them up or at an angle when partially empty).

The Memindex Jr., according to a price sheet in the 1930s, was used "extensively as an advertising gift".

The Memindex system had cards available in bundles of 100 that were labeled with the heading "Things to Keep in Sight".

Notice the 1 1/4" x 3" cards, 2 1/4 x 4" cards in addition to the 3 x 5" and 4 x 6".

Reviewer #2 (Public Review):

In this work, Ball et al. investigated the possibility to generate a novel set of HepG2 liver cell lines to generate "mitochondrial DNA-personalized" models as novel tools to study idiosyncratic drug-induced liver injury related to mitochondrial variation. This work represents the generation of a comprehensive collection of n=10 HepG2 lines, half reflecting haplogroup H and half reflecting haplogroup J. The authors then assessed their impact on basic mitochondrial function in liver cells. Interestingly, they find a greater respiratory complex activity driven by complex I and II of the haplogroup J lines relative to haplogroup H. Finally, the authors make an attempt at using this novel set of lines to probe the consequential effects of mitochondrial genotype on drug-induced liver toxicity. This work provides an interesting proof-of-concept study and is a starting point towards studying and predicting idiosyncratic drug-induced liver injury in a personalized manner. This technique may be broadly extrapolated to other commonly used liver cell models within the toxicology field.

Strengths:

1) This work presents an exciting initiative to study interindividual variability in idiosyncratic drug-induced liver injury focusing on mitochondrial haplotypes. In further follow-ups, this work could be extended to also represent other different haplogroups to establish a thorough "biobank". The established lines allow for future in-depth characterization and testing of many putative hepatotoxic compounds through a variety of toxicity measures that could shed further light on the impact of mitochondrial DNA variation on (idiosyncratic) drug-induced liver injury.

2) This technique may be broadly extrapolated to other commonly used liver cell lines within the toxicology field (e.g. HepaRG cells or iPSC-derived cells) that are potentially also more metabolically competent. A short discussion on this could be added to the current manuscript.

Weaknesses:

1) The major weakness of the current manuscript is the rather large variation across sample measurements regarding the proof-of-concept experiments to study drug effects (fig. 3-6). This makes much of the data rather hard to interpret and to infer conclusions. As an example, proton leak (fig. 3f/4f) seems to 2-fold increase in the J group even under basal conditions (0 uM flutamide/metabolite), while this is not observed in fig. 2a and this effect seems to be also absent under 0 uM tolcapone (fig. 5f). Unfortunately, the current data do not allow to draw confident conclusions about whether the tested drugs have effects on the mitochondrial respiration of the different haplogroups. This may well be linked to the methods used for measuring mitochondrial activity, but since this is the predominant method needed in the current paper, either increasing the number of experiments (across more lines) or identifying a more rigorous methodological manner to obtain consistencies of experiments would help the authors to make more confident claims about their data.

2) The data on the effects of inhibition of complex I/II activity are not sufficiently convincing to support the claim that haplogroup J is more susceptible to flutamide/metabolite (fig. 6). Both seem to respond rather identical to flutamide or its metabolite, i.e. at higher concentrations complex I/II activity decreases, but with the sole difference that the haplogroups represent different basal activity (not influenced by the drug). Estimating fold changes, for example, for both haplogroups, complex I and II activity decreases ca. 2-fold at the highest concentration of the metabolite (fig. 6c-d), therefore concluding that there is no difference between haplogroup susceptibility unlike the authors claim. It is furthermore unclear what the statistical significance currently represents: it should represent whether at different/increasing concentrations the activity of the complexes significantly differs vs. the previous/basal conditions from the same haplogroup. If it represents (which it seems to be) the significance of the haplogroup J vs. the haplogroup H, it is non-informative as it is obvious that haplogroup J presents with a higher baseline.

3) It would help to mention how many lines per haplogroup H/J were used in the analyses across all figures. This should be clarified, as the error bars for most experiments are rather high and therefore statistical significance is lacking, making data interpretation complex. It could be helpful if the authors present at least for some analyses single plots of data obtained across different lines from the same haplogroup to evaluate the consistency of the effects of the genotypes as supplementary figures. If only 1-2 lines were used per group, it would help to perform additional experiments to assess consistencies across groups.

Reviewer #2 (Public Review):

In their manuscript, "Single-Cell RNA-seq of Heart Reveals Intercellular Communication Drivers of Myocardial Fibrosis in Diabetic Mice", Wei Li et al. study the pathogenesis of cardiac fibrosis in mouse hearts in response to high-fat-diet/streptozotocin-induced diabetes. They infer cellular interactions from single nucleus RNA-seq data and highlight some ligand-receptor pairs including PDGFs and PDGFRa. They further aim to identify fibroblast subtypes associated with fibrosis and to identify factors driving diabetic myocardial fibrosis.

This study addresses an important problem (cardiac fibrosis as a consequence of diabetes), using single nucleus RNA-seq and several follow-up experiments in a diabetic mouse model. While many of the described findings, including PDGFRa involvement in fibrosis and a Postn positive fibroblast population (reflecting activated fibroblasts), are expected, the most exciting novel insight would come from the Hrc+ fibroblast population and its characterization. However, based on the currently presented data and analysis it is not clear if this is indeed a fibroblast subtype or due to technical factors.

1) A major point of the manuscript is the description of Hrc+ fibroblasts (Fibroblast 3) as profibrogenic in diabetes. However, fibroblast 3 expresses several cardiomyocyte markers Nppa, Ryr2, Ttn alongside Hrc which is described to play a role in Ca2+ handling at the sarcoplasmic reticulum in cardiomyocytes (Fig. 4C) and shows a low correlation with other fibroblast clusters (Fig. 4B). A possible explanation is technical, e.g. if two nuclei (one fibroblast, one cardiomyocyte) were captured together in one droplet (barcode collisions or doublets). Unfortunately, this uncertainty makes interpretation of all following snRNA-seq analyses based on this fibroblast subpopulation impossible.

2) To follow the study and be able to appreciate the data quality, individual sample metadata and UMAPs colored based on a sample and/or condition (diabetes or control) would be helpful. The paper would benefit from an analysis to show if the differences in the number of detected genes are due to the number of nuclei per cluster or if the bigger clusters are really also the ones with the most dramatic changes. Instead of showing expression levels of differentially regulated genes in distinct clusters (Fig1 S2), the differential expression could be displayed with violin plots or heatmaps that illustrate values for both conditions. Clusters that did not reveal any differential expressed genes, e.g. Adipo can be removed. Fig 1F these KEGG enrichments are hard to interpret since they can be confounded by highly expressed cardiomyocyte genes that are detected in all clusters (1B) and thus drive the GO enrichment of e.g. "cardiac muscle contraction" in T cells.

3) The study looks into the pathogenesis of cardiac fibrosis in diabetic mice. The authors show that downregulation of Itgb1 with siRNA (Fig 6I) leads to less fibrosis in diabetic mice. This effect might be expected since Itgb1 is an extracellular matrix-linked gene and might indicate that downregulation could be beneficial. Given this, it is confusing to see the following analysis which links several genetic variants associated with Type 2 Diabetes to Itgb1 (one leading to premature stop) and its ligand. This analysis seems out of place in relation to the remainder of the study which focuses to identify the downstream effects of diabetes on cardiac fibrosis.

Reviewer #2 (Public Review):

Using a novel genetic system to conditionally ablate Lepr from Agrp neurons in adults, the authors discovered that leptin-AgRP neuron signaling strongly modulates the DMH and sought to understand the DMH targets and mechanisms of action in the response to AgRP neuron signaling. GABA signaling likely underlies the effects of AgRP neuron-mediated hyperphagia (etc). DMH Mc4R neurons appear to lie downstream of Agrp neurons. GABA in the DMH appears to mediate many of the effects of AgRP neurons on feeding and body weight. Furthermore, Deletion of Lepr from AgRP neurons increases DMH GABA-ARa3, and modulation of this receptor in the DMH alters food intake and the response to leptin.

Unfortunately, there is little quantification or other validation data from many of the systems deployed, and the analysis jumps around a fair amount, without really uniting the results in a way that paints a convincing picture of the final model that they build.

Reviewer #2 (Public Review):

This manuscript presents a thorough set of investigations on the roles of a previously poorly-studied protein, SNX32. SNX32 is a sorting nexin involved in cargo sorting along the endosomal system. SNX32 contains a BAR domain and a PX domain, and the authors have convincingly shown that, by interacting with SNX4 and with phosphoinositides (PI(3)P or PI(4)P), SNX32 localizes to early endosomes and regulates the trafficking of different cargo receptors (transferrin receptor and cation independent mannose-6 phosphate receptor). In a second part, the authors moved to a more physiological context, in which they studied the functions of SNX32 in neuronal differentiation, which they suggest that is linked to the role of SNX32 in mediating the trafficking of Basigin (BSG).

Reviewer #2 (Public Review):

When O. tauri cells are grown under low light, PSI has six classical LHCIs (Lhcas), four on one side of the PSI core and two on another, and three trimers of the "Lhcp" antenna proteins on a third side, thus surrounding the PSI core. Lhcp Trimer 2 consists of 1 Lhcp1 and 2 Lhcp2; Trimers 1 and 3 are solely Lhcp2. Careful examination of carotenoid positions suggested that certain serve as "molecular staples" in holding the three monomers of a trimer together.

The resolution of the structure is high enough to determine the positions of all the chlorophylls and carotenoids and to establish the correct chemical composition. All the proteins determined by LCMS/MS were located and modeled. Of particular interest were the minor polypeptides PsaO, PsaL, PsaH, and PsaK, which are in between the PSI core and the trimers, and are involved in binding the trimers to the core.

There is a very detailed comparison of Lhcp trimers with LHC trimers of plants and Chlamydomonas. One of the conclusions is that Chl b requires a Gln rather than a Glu at a certain position, which may otherwise be occupied by a carotenoid. Another is that the increased distance between Lhca5 and 6 may be responsible for the lack of "red" Chls.

This led to a detailed analysis of potential energy transfer pathways in the holocomplex based on distances between pigments and how the trimers interact with the small PSI subunits PsaO, PsaL, PsaH, and PsaK. This section is unfortunately rather tedious to read because the individual monomers in each different trimer are suddenly designated by capital letters. This is not explained properly in the text or in the legend in Fig. 10.

That being said, my overall judgment of the manuscript up to this point is very favorable - I'm impressed with the high quality of the data and the thoroughness of its analysis. It has long been known that when O. tauri cells are grown under high light, the PSI complex does not have the Lhcp trimers, but just has the Lhca antenna. Returning cells to low light induces the synthesis of the Lhcp trimers and the formation of the holocomplex. This could be looked at as a "low-light acclimation"; in nature, the prasinophytes are found in shallow water and hence high light exposure may be their "normal".

The authors asked if this is related to the situation in higher plants and Chlamydomonas where HL induces phosphorylation of certain LHCII trimers which migrate from the appressed membrane regions and associate with PSI. The common factor of these two phenomena is phosphorylation, but the process referred to as a"State transition" operates in the opposite direction to the situation in O. tauri. The authors did a little experiment to see if the disappearance of the complex was reversible in the same time scale as the "state transitions" of Chlamy and plants, by exposing their normal low light cells to 1 hr of HL, then putting them back in LL. They did show that the amount of phosphorylated Lhcp1 decreased significantly in this time frame and then recovered a significant amount when returned to LL. However, using P700 oxidation to assay Lhcp trimers is not very convincing to my eyes.

In my opinion, this does not provide any evidence for a similar mechanism to "state transitions". A real understanding will have to involve studying PSII and its interaction (if any) with Lhcps. There is no indication of where the Lhcps went in 1 hour of HL--maybe they're just at the top of the gradient, minus any phosphate. I would strongly recommend deleting this section altogether.

My conclusion is that a detailed comparison with plant and Chlamydomonas PSIs shows that there are many different ways in which a photosynthetic eukaryote can evolve an effective antenna system. It gives me great pleasure to see a carefully revealed model of another solution to the light-harvesting problem.

Reviewer #2 (Public Review):

The authors present an interesting study combining deep learning, neuroimaging, and brain stimulation techniques for several neurodegenerative diseases. This has important consequences to understand the connectivity alterations and to design novel therapies to alleviate these changes.

Reviewer #2 (Public Review):

This manuscript by Gao, Penzo and colleagues provides a first pass characterization of PVT neurons using single-cell RNA sequencing. Following identification and characterization of likely unique PVT cell types, the authors use multiplexed in situ hybridization to confirm the existence of differentially expressed genes and their spatial location along the AP, ML, and DV axes of the PVT. Finally, the authors compared their sequencing dataset to an existing single cell sequencing atlas, which includes projection-specific sequencing. Within these experiments, the authors describe the expression and spatial location of unique gene sets that are enriched within the clustered cell types. The authors use hierarchical clustering to suggest the existence of two main cell branches in PVT, with each of those branches having subclassifications for a total of 5 identified cell populations.

Reviewer #2 (Public Review):

This manuscript by Marjaneh et al is an original research article that aimed to understand the genetic complexity of atrial septal defects by using QTL analysis in advanced intercross lines (AIL) QSi5 and 129T2/SvEms mouse strains, which represent mice with extremes of atrial septal phenotypes. This study is built on previous work by the authors (Biben. 2000), in which they developed three quantitative parameters of atrial septal morphology. These quantitative traits were previously proven by the authors to be associated with the prevalence of PFO across a variety of genetic backgrounds. Using an F2 design of the same strains they have previously identified 13 significant or suggestive QTL affecting these quantitative traits, (Kirk. 2006).

The current manuscript extends the previous analysis using the AIL approach at F14. This design, the fine mapping approach, and the rigorous downstream analysis allowed them to refine their previous findings. In addition, several new QTLs were discovered. Remarkably, the resolution was increased and the overlap between QTL for different traits was enhanced. Furthermore, they performed whole genome sequencing of the parental strains and identified high-confidence deleterious variants that are enriched in known human CHD genes as well as the genes within QTL regions that are expressed in the atrial septum, such as SMAD6. They also performed transcriptome analysis of septa at different developmental stages in parental strains and identified networks enriched in the ribosome, nucleosome, mitochondrial, and ECM biosynthesis underlying septal variation.

Overall, the manuscript was built on a clear rationale and employed a suitable genomics approach to address the topic. The results provide a substantial and important extension of the previous work at a larger scale and a higher level of resolution. The findings improve the status of current knowledge and provide valuable resources to unravel the genetic complexity of CHDs, with relevance to human PFO. The significance is deemed to be "Important" given the large-scale approach, the specificity of quantitative measures, and the resolution of the analysis pipeline. Analysis steps are well-designed providing potential candidate targets from their network analysis. Pending functional validation and confirmatory evidence of the causality in future mechanistic studies, the outcomes may lead to novel diagnostic and translational values.

Reviewer #2 (Public Review):

This work recorded neurons in the parahippocampal regions of the medial entorhinal cortex (MEC) and pre- and para-subiculum (PrS, PaS) during a visually guided navigation task on a 'tree maze'. They found that many of the neurons reflected in their firing the visual cue (or the associated correct behavioral choice of the animal) and also the absence of reward in inbound passes (with increased firing rate). Rate remapping explained best these firing rate changes in both conditions for those cells that exhibited place-related firing. This work used a novel task, and the increased firing rate at error trials in these regions is also novel. The limitation is that cells in these regions were analyzed together.

Reviewer #2 (Public Review):

This is a well-written paper that reports that the accumulation of LOOH with age and disuse contributes to the loss of skeletal muscle mass and strength. Moreover, the authors report that LOOH neutralization attenuates muscle atrophy and weakness. The mechanism via which LOOH contributes to these phenotypes remains unclear but seems to be mediated by the autophagy-lysosomal axis. In addition, the paper also reports the efficacy of N-acetylcarnosine treatment in ameliorating muscle atrophy in mice.

The authors should consider the following points to improve the manuscript:

- The authors showed that inhibition of the autophagy-lysosome axis by ATG3 deletion or BafA1 was sufficient to reduce LOOH levels induced by GPx4 deletion, erastin, or RSL3. Moreover, they found that 4-HNE co-localizes with LAMP2. However, it remains unclear the precise mechanism via which LOOH contributes to muscle atrophy and how it is amplified by the autophagy-lysosomal axis. The authors could further test the functional interaction of 4-HNE with LAMP2 with additional experiments such as immunoprecipitation.

- A weak point of the paper is not having performed the experiments on 24-month-old-mice. At 20 months of age, the mice do not display any muscle wasting and myofiber atrophy compared to young mice that have completed postnatal muscle growth (=6-month-old-mice). It would be interesting to see the levels of 4-HNE in 24- or 30-month-old mice, and if N-acetylcarnosine treatment in older mice is able to rescue muscle atrophy induced by aging.

Previous studies have shown that inhibition of autophagy accelerates (rather than protect) from sarcopenia, and that autophagy is required to maintain muscle mass (Masiero 2009, PMID: 19945408; Castets 2013, PMID: 23602450; Carnio 2014, PMID: 25176656). On this basis, the authors should test whether their findings are valid only in the context of disuse atrophy or also in the context of sarcopenia (=24-30-month-old mice).

- In Fig.2 the authors report that GPx4 KD, erastin, and RSL3 reduce the diameter of myotubes. For how long and when was the treatment done? Looking at the images, it seems that there are some myoblasts in the cultures treated with GPx4 KD, erastin, and RSL3. Is it possible that these compounds reduce myotube size by inhibiting myoblast fusion rather than by inducing myotube atrophy?

- MDA quantification was done in the gastrocnemius although all the experiments in this paper were performed in the soleus and EDL. It would be good if the authors could explain the reason for this.

Reviewer #2 (Public Review):

This manuscript dives deeply into the localized binding and potential function of the Histone deacetylase Hdac1, the major HDAC expressed in early frog development. The stage-specific binding of Hdac1 changes during early development, correlating with the binding due to maternal factors, then zygotically generally activated or generally repressed genes, and also genes that can be either activated or repressed depending on their context. The protein appears not to bind to constitutive heterochromatin.

The study pursues how the binding changes on Animal Cap versus Vegetal mass expressed genes, and studies how inhibition of Hdac1 with TSA or VPA affects the degree of acetylation and expression. Perhaps the most interesting finding is that inhibition of Hdac1 has large effects on the acetylation and expression of inactive, but facultatively expressed genes, while it has smaller hyperacetylation effects on already active facultatively expressed genes; despite a modest stimulation of the already stimulatory effects of acetylation, the additional acetylation correlates with inhibition of expression of this subset of genes. This result is clearly documented with embryonic region-specific effects on facultatively expressed genes. The effect on inactive genes fits with the general idea that Hdac1 is repressive, but the effect on already acetylated genes is not so easily explained, though some models are proposed.

The overall findings are important background for developmental and chromatin biologists because they add to the documentation of the correlations between acetylation, deacetylation, and expression of genes in development. The correlations allow the inference of potential functions, though these are not tested other than by pharmacological inhibition of Hdac1.

Reviewer #2 (Public Review):

The study by Tam and colleagues addresses the ion-conducting pathway and selectivity of P2X receptor channels. Recent structures of ATP-bound P2X receptors with the activation gate open revealed the presence of a cytoplasmic cap over the central ion permeation pathway. This prompts the authors to examine if lateral fenestrations are potential pathways for ions to permeate the intracellular end of the channel pore, even although they appear to be largely buried within the membrane. Based on sequence alignment, the authors identified a critical residue E17 within the intracellular lateral fenestrations and found that it is accessible to two thiol reactive reagents. Importantly, mutations of E17 also affect the relative permeability of the channels to cations and anions. The work thus solves an ion-conducting mystery of the physiologically important P2X receptor channels. It demonstrates that lateral fenestrations are part of the internal pore of P2X channels and play a critical role in determining ion selectivity.

The structural and sequence analysis is performed carefully, and the electrophysiological experiments are carried out beautifully. Although the data largely seem to support the conclusions, statistical analysis is required to strengthen the claims. Cysteine accessibility experiments may have alternative interpretations; thus, the rigor can be further improved to include the reversibility of the block by treating it with reducing agents.

Reviewer #2 (Public Review):

The present study aimed to demonstrate the utility of brain signal decoding for the differentiation of asynchronous motor signs in Parkinson's disease (PD). To this end, thirty-one PD patients undergoing deep brain stimulation electrode implantation were recruited to participate in an intraoperative motor task. Task performance was compared to extra-operative experiments in healthy subjects. Neural activity and movement traces were segmented into 7-second windows and attributed tremor and slowness measures. To integrate the two symptom domains an additional decoding state termed effective motor control was introduced, which represented the absence of symptoms. Support vector machine regression was used as the model of choice that was trained on individual recording sessions within subjects. All decoding targets from each neurophysiological modality reached significant prediction performances. This represents an important milestone in the current state of research towards machine learning-based intelligent adaptive deep brain stimulation.

Strengths

1. The present analysis is among the first to demonstrate the potential utility of brain signal decoding for the differentiation of asynchronous motor symptoms in Parkinson's disease. In the future, such approaches may be adopted in clinical brain-computer interfaces that can adapt stimulation in real time to concurrent therapeutic demand.

2. The effort from the research team and patients to acquire this important dataset is commendable. The time pressure in the operation room combined with the current trend of asleep surgery for deep brain stimulation makes such data very rare.

3. No relevant difference in decoding performance was found for subthalamic micro vs. macroelectrode recordings. This has practical significance because current sensing-enabled deep brain stimulation implants only allow for macro-recordings, which according to this study has no severe disadvantage over microelectrode recordings for movement decoding. Note that this question could only be answered in the intraoperative setting, which on the other hand can have disadvantages further described below.

4. Beyond the subthalamic nucleus, the authors corroborate the superiority of electrocorticography over subthalamic activity for movement and symptom decoding in Parkinson's disease. This provides further evidence that additional sensing electrodes may complement the subthalamic signals for adaptive deep brain stimulation.

5. Finally, the idea of decoding the presence of an effective motor state is creative and may inspire future developments in adaptive stimulation control algorithms.

Weaknesses

(Note that I take more words for weaknesses, not because they outweigh the strengths, but because I want to justify my criticism in more detail)

1. One inherent limitation of this study is the intraoperative setting, which demands the patients' skull be fixed to the stereotactic frame. This setting is not naturalistic per se and likely comes with additional perturbations in the brain states that are recorded. Thus, the generalization to real-world scenarios is limited. Given the unique opportunity to record invasive brain signals in humans, this limitation has to be accepted and should be taken into account for the interpretation of the results. As mentioned in the strengths, this is currently the only setting that allows for a comparison of micro- and macroelectrode recordings for brain signal decoding.

2. Similarly, the medication state is defined by the intraoperative scenario, as deep brain stimulation implantations are performed after the withdrawal of dopaminergic medication in the so-called dopaminergic OFF state. In this state, PD symptoms are aggravated, which is used clinically to provide a more reliable assessment of deep brain stimulation-induced symptom alleviation. This may also lead to an overestimation of decoding performances as the difference between the absence and presence of PD motor signs in the dopaminergic medication ON state during activities of daily living could be more nuanced.

3. The task design is very interesting as it allows for a continuous definition of symptom severity and motor performance. The comparison to healthy subjects demonstrated clearly higher tremor scores in PD but no significant differences in movement velocity (depicted as trending but p>0.2). This is somewhat unexpected as slowness of movement, also called bradykinesia, is a defining symptom of Parkinson's disease (PD). By definition, this symptom is present in all PD patients, also indicated in the clinical scores shown in the present study. Action tremor, i.e. the presence of tremulous muscle activity during motor performance, is comparatively rare. To support the clinical relevance of the movement tremor observed during the task, the authors show a correlation with the "resting tremor" score from the clinical assessment. It is unclear to me why resting, instead of action tremor scores are shown, as both are part of the clinical assessment (Unified Parkinson's disease rating scale - UPDRS part III). Ultimately, even though resting tremor is significantly more common in Parkinson's disease, not all patients of the current cohort had resting tremor (as indicated in the clinical score correlation). Thus, it remains somewhat puzzling how precise the 3-8 Hz activity actually captures tremor vs. motor noise or inaccuracy. A more fine-grained analysis comparing patients with clinically diagnosed action tremor (as defined by preoperative UPDRS assessment) and without tremor could have helped to support the clinical claims on symptom-specific decoding. On the other hand, the lack of a significant difference in the slowness of movement in the patient cohort relative to healthy controls questions the ability of the task to capture this symptom. Here, I am not sure whether the normalization procedure may have an influence on the comparability. Finally, movement velocity is an easy target that is distributed across a spectrum, so despite the lack of a significant difference in the healthy cohort, I am relatively confident that the decoding of movement slowness in the present cohort is clinically meaningful.

4. Overall, the pathophysiological framework is well placed in the current state of literature, while almost the entire field of brain signal decoding for adaptive deep brain stimulation was neglected. Successful decoding to address Parkinson's and essential tremor (another disorder with more common action tremor) was achieved by multiple groups in impactful studies representing more naturalistic extraoperative or fully embedded settings (Hirschmann et al., 2017, He et al., 2021, Opri et al., 2021). Additionally, other symptoms, like gait disturbances have been the target of machine learning analyses more recently (Louie et al., 2022 and Thenaisie et al., 2022). Here, the manuscript appears to avoid a discussion of the present endeavour in comparison to the current state of the field. One of our own studies has provided the first demonstration of the superiority of electrocorticography over subthalamic LFP for movement decoding, which I am happy to see replicated for the first time in the present manuscript. Importantly, the referenced study showed modality-dependent model performances, with gradient-boosted decision trees performing significantly better than linear models for electrocorticography, while Wiener filters have been repeatedly shown to perform well for subthalamic local field potentials (e.g. see Shah et al., 2018 IEEE Trans Neural Syst Rehabil Eng). The present study does not compare different machine learning architectures. Thus, decoding performances could potentially be further improved with more refined computational approaches. A more thorough overview of the literature from the many laboratories that are invested in this research across the globe would have improved the interpretation with respect to the broader impacts of the present manuscript.

5. The authors also present analyses of the spatial localization of relative decoding performances. They demonstrate higher tremor decoding performance in the dorsolateral subthalamic nucleus and higher decoding performance for the slowness of movement in the more central and ventral subthalamic regions. The authors interpret this as potential evidence to support clinical decision-making for optimized stimulation control of these symptoms at the respective locations. This is overly speculative and currently not backed by the data. First of all, the results only show the contrast of tremor vs. slowness of movement and not each individually. Thus, the spatial peak with each symptom domain could be very similar, e.g. in the dorsolateral STN, but a reversal of the difference only occurs at relatively low performances, e.g. in the ventral STN. Thus, showing both spatial distributions individually could be more informative. However, the claim that this could also be used to adjust stimulation location to alleviate the respective target symptoms is by no means backed by the data and remains an interesting speculation.

6. Finally, as in many brain signal decoding studies, the presented decoding performances are relatively low. The authors decided to present linear correlation metrics as Pearson's r values. These values are by definition higher than the commonly chosen Coefficient of determination or R² that provides a more interpretable performance metric. The amount of variance in the symptom scores that could be explained by the models ranged between 10% and 30% at a temporal resolution of 7 seconds. Moreover, the validity of the linear score is not entirely clear as Pearson's r can be heavily biased by non-normal distributions which were not assessed or at least not reported for the performance evaluation. These considerations do not severely limit the validity of the results themselves, as the authors have convincingly shown that significant decoding performances are possible and other studies in this field range in similar performance ranks. However, this point should remind us that a short-term clinical adoption of such methods is not yet in sight and further research is warranted. Before machine learning-based clinical computer interfaces can reach the clinical routine, the field has to work on more refined methods. In my opinion, the field will have to provide robust decoding performances with R² > 0.8 without patient-specific training to get into the realm of widespread clinical adoption.

Reviewer #2 (Public Review):

Wong et al. studied how dendrites find specific targets during the wiring process. They used the well-established Drosophila olfactory system to address the question. Specifically, they asked how dendrites of monoglomerulous projection neuron (PN) ensemble form a stereotyped topographic map in antennal lobes. They traced the developmental history of each individual projection neuron from anterodorsal (ad) or lateral (l) lineages and found that birth origin and birth order together specify the initial exploration territory and the terminal target. They then took a step further to ask how about the embryonic-born PNs most of which undergo remodeling during metamorphosis: do they maintain their dendritic target through metamorphosis or do they integrate re-extended dendrites into the adult-specific antennal lobes? They showed that ecdysone signaling simultaneously triggers pruning of the dendrites that formed larval antennal lobes and induces the outgrowth of new dendrites to be integrated into the adult antennal lobes. The methodologies, especially ex vivo explant live imaging, established a powerful paradigm to investigate the dynamics of synapse formation during development.

Reviewer #2 (Public Review):

This is a follow-up study by the senior author, who previously showed in a 2021 JBC paper that levels of Paternally Expressed Gene 10 (PEG10) protein, among many other protein changes, are increased in the spinal cord of Ubqln2 knockout (KO) animals (JBC 2021). In this report, they provide more direct evidence that PEG10 levels are regulated by ubqln2 and that PEG10 can be proteolytically cleaved generating fragments, which when overexpressed, induce alterations in gene expression. Through proteomic analysis of spinal cord tissue from control and ALS patients, they found that PEG10 levels and the signature of genes regulated by its products are increased in ALS, proposing that elevation in PEG10 is a novel marker and driver of ALS.

PEG10 resembles a retrotransposon, encoding virus-like gag-pol products. It is only found in eutherian mammals. Although it has lost its ability to transpose, it still retains the retroviral-like translation frameshifting property generating two main products, gag (reading frame 1, RF1) and gag-pol (RF1/2). PEG10 is essential for survival. It plays an important role in RNA-binding and trophoblast stem cell specification, being required for placental development. It is also expressed in several adult tissues, but its function in them is obscure. A recent study showed PEG10 RF1 and RF1/2 bind the deubiquiting enzyme USP9X, and that loss of USP9X destabilizes RF1 but not RF1/2, suggesting USP9X regulates ubiquitination and proteasomal degradation of PEG10 (Abed et al. PLOS One 2021). Additionally, Abed et al. showed PEG10 products support virus-like particle (VLP) assembly and that both RF1 and RF1/2 localize to the cytoplasm, whereas a portion of RF1/2 is found in the nucleus of some cells. They further showed PEG10 binds and regulates RNA expression, most probably through interaction with the 3'-ends of the RNAs but found no common binding motif suggesting interaction could be with the secondary structure.

As mentioned, the senior author previously reported in a JBC article in 2021 that PEG10 levels are elevated in ubqln2 knock out (KO) mice, but that its levels were slightly decreased in the P497S mouse model of ALS. They validated PEG10 as an interactor of ubqln2 by proximity-dependent biotin labeling. A review of the current manuscript follows.

1. Evidence that ubqln2 regulates PEG10 accumulation (Fig 1). The authors use human embryonic stem cells to investigate how knockout (KO) of different ubqln isoforms (1, 2, and 4) affects PEG10 accumulation, showing that only KO of ubqln2 increases the RF1/2 product.

a) There is considerable variation in PEG10 expression in the duplicate sample sets provided, but this is not reflected by the error bars (fig 1 A and B). For example, RF1/2 is quite different in the two ubqln4 KO lysates, yet the error bars do not capture the variation. Better loading and quantification is needed. Also, in the KO cells, gag levels are slightly increased, which is consistent with alterations in proteasomal degradation. Alternatively, the changes in RF1/2 could also result from changes in read-through translation, but this is not investigated. Also, it would be helpful to include blots showing the lower Mol weight PEG10 products, to see how they change relative to Fig 3.

Fig 1G. The authors examined if removal of the poly proline rich region (PPR) from PEG10 affects RF1/2 regulation by ubqln, confirming its requirement.

b) The mechanism why deletion of the PPR abolished RF1/2 regulation by ubqlns was not examined. Is it from accelerated degradation? Also, it is not clear why the authors use the triple ubqln KO cells and did not perform that tests in the different ubqln KO cells. The latter comment applies for several of their investigations, leading to uncertainty regarding the specificity of ubqln2 in PEG10 regulation. It is possible that removal of most ubqlns stalls protein degradation affecting PEG10 turnover?

2. The authors investigated the phylogenetic relationship between PEG10 and ubqln2 demonstrating that PEG10 levels from marsupials that lack a PPR can be increased by appending a PPR from human PEG10. They used triple ubqln KO cells for these investigations.

a) The change they describe is not obvious in Fig2C and E as they appear quite small. They also conclude that ubqln2 regulates PEG10 by these studies, but really the experiments show it is from loss of all ubqlns, not ubqln2 specifically.

3. The authors show PEG10 is capable of self-cleavage of the RF1 product, generating 2 detectable N-terminal products, and several other fragments, including a C-terminal nuclear capsid (NC) fragment (Fig3). They show expression of HA-tagged NC fragment localizes to mainly the nucleus, whereas several other PEG10 products and fragments localize to the cytoplasm. They provide strong support that PEG10 is capable of self-cleavage by mutation of an aspartate residue (D) in a DSG motif in the protein to alanine (A to → ASG), which abolished cleavage. They also conducted a nice experiment showing the ASG mutant can be cleaved in trans by introduction of WT PEG10.<br /> a) The authors never show evidence for liberation and accumulation of the NC fragment, only for an artificially tagged protein by immunofluorescence. Use of a tag to study its localization and affects is problematic as the could influence its properties. They need to show that the fragment is detectable because of their central claim that it is responsible for inducing changes in genes. Biochemical fractionation studies could also reveal the extent of the partitioning of the fragment in the nucleus and cytoplasm. The mechanism by which the NC fragment induces changes in gene expression is not clear.

4. The authors show differences in gene expression upon transfection of HEK293 cells with PEG10 RF1, RF1/2, and NC expression constructs. They show that two PEG10-regulated genes, DCLK1 and TXNIP, are both increased in the spinal cord in sporadic ALS cases compared to controls.<br /> a) It is not clear from the studies whether the changes found in ALS are related to changes in PEG10 specifically, or for other reasons. Additionally, more rigorous comparison in many more ALS and controls is needed. PEG10 levels increase upon cell differentiation (Abed et al.) so the changes in ALS may reflect a compensatory and protective response.

5. To investigate if PEG10 RF1/1 levels are altered by ALS mutations in ubqln2 they transfected ubqln TKO cells with either wt ubqln2, or with mutants carrying either the P497H or P506T ALS mutations. They show PEG10 RF1/2 levels are reduced by overexpression of both the wt and P497H mutant, but not by the P506T mutant. They claim that P497H expression did not affect RF1/2 levels. The authors conducted a proteomic comparison of extracts from the spinal cord of two controls, one P497H ubqln2 case, and six sporadic ALS cases. They found increased levels of RF1/2 in the ALS cases. They also found neurofilament medium and neurogranin were both reduced in the ALS cases. Based on these changes they speculate that PEG10 is a novel marker for ALS.<br /> a) The conclusion that the P497S mutant did not affect RF1/2 is incorrect. It reduced RF1/2 slightly more than wt ubqln2. In fact, it appears that expression of all three (wt and the 2 ALS mutants) ubqln2 proteins reduce RF1/2 significantly, compared to the TKO cells.<br /> b) The changes in PEG10 found in the ALS cases are difficult to evaluate because too few controls and ALS cases were used for the comparison. Huge variations in the levels of PEG10 and of the other proteins graphed In Fug 6B-F were seen in the two controls. The comparison needs to be done with many more samples for sound statistical comparison. Were the samples compared from the same region of the spinal cord?

General comments

1. In the Discussion the authors write that because ubqln2 is the only ubqln capable of regulating PEG10 RF1/2 levels, the PXX domain that is only present in ubqln2 is likely responsible for the regulation. There is no proof in support of this hypothesis. Only one ALS-causing mutation (P506T) in the PXX domain, but not the P497H mutation in the same PXX domain, affected RF1/2 accumulation, inconsistent with general involvement of the PXX domain in PEG10 regulation.

2. The authors claim that ubqln2 may have specifically evolved to restrain PEG10 expression, but don't mention USP9X as being another regulator. The common theme that emerges from these studies is that PEG10 levels are regulated by any mechanism that interferes with ubiquitination/proteasomal degradation. Indeed, immunoblots of the gag-pol (RF1/2) in the different ubqln KO cells show a smear at high molecular weight consistent with the accumulation of ubiquitinated PEG10. The authors imply that the transcriptional changes caused by the alteration in PEG10 levels by ubqln2 are responsible for ALS (title of the paper), but this is merely speculation as the effects of the changes are not known. The changes found could be protective. They also claim PEG10 may serve as a novel biomarker for ALS, but such a claim is not justified from the limited analysis conducted so far, which will require more extensive proof.

Reviewer #2 (Public Review):

This is an interesting manuscript that explores the hypothesis that inhomogeneities in visual sensitivity across the visual field are not solely driven by cortical magnification factors. Specifically, they examine the possibility that polar angle asymmetries are subserved by differences not necessarily related to the neural density of representation. Indeed, when stimuli were cortically magnified, pure eccentricity-related differences were minimized, whereas applying that same cortical magnification factor had less of an effect on mitigating polar angle visual field anisotropies. The authors interpret this as evidence for qualitatively distinct neural underpinnings. The question is interesting, the manuscript is well written, and the methods are well executed.

1) The crux of the manuscript appears to lean heavily on M-scaling constants, to determine how much to magnify the stimuli. While this does appear to do a modest job compensating for eccentricity effects across some spatial frequencies within their subject pool, it of course isn't perfect. But what I am concerned about is the degree to which the M-scaling that is then done to adjust for presumed cortical magnification across meridians is precise enough to rely on entirely to test their hypothesis. That is, do the authors know whether the measures of cortical magnification across a polar angle that are used to magnify these stimuli are as reliable across subjects as they tend to be for eccentricity alone? If not, then to what degree can we trust the M-scaled manipulation here? In an ideal world, the authors could have empirically measured cortical surface area for their participants, using a combination of retinotopy and surface-based measures, and precisely compensated for cortical magnification, per subject. It would be helpful if the authors better unpacked the stability across subjects for their cortical magnification regime across polar angles.

2) Related to this previous point, the description of the cortical magnification component of the methods, which is quite important, could be expanded on a bit more, or even placed in the body of the main text, given its importance. Incidentally, it was difficult to figure out what the references were in the Methods because they were indexed using a numbering system (formatted for perhaps a different journal), so I could only make best guesses as to what was being referred to in the Methods. This was particularly relevant for model assumptions and motivation.

3) Another methodological aspect of the study that was unclear was how the fitting worked. The authors do a commendably thorough job incorporating numerous candidate CSF models. However, my read on the methods description of the fitting procedure was that each participant was fitted with all the models, and the best model was then used to test the various anisotropy models afterwards. What was the motivation for letting each individual have their own qualitatively distinct CSF model? That seems rather unusual. Related to this, while the peak of the CSF is nicely sampled, there was a lack of much data in the cutoff at higher spatial frequencies, which at least in the single subject data that was shown made the cutoff frequency measure seem like it would be unreliable. Did the authors find that to be an issue in fitting the data?

4) The manuscript concludes that cortical magnification is insufficient to explain the polar angle inhomogeneities in perceptual sensitivity. However, there is little discussion of what the authors believe may actually underlie these effects then. It would be productive if they could offer some possible explanation.

Reviewer #2 (Public Review):

The manuscript "Neural dynamics underlying self-control in the primate subthalamic (STN) nucleus" builds on a substantial literature indicating a role for the STN in impulsive actions, i.e. responding too early in tasks that require patience. The authors trained two monkeys to move a cursor to a target and then hold still, waiting for a reward. A visual cue indicated the reward magnitude and time interval that the monkeys were required to wait on each trial in order to get the reward. Understanding the mechanism by which the STN supports behavioral inhibition is important since the STN is a common target for deep brain stimulation for both neurological and psychiatric disorders. The authors claim that their results indicate that the STN integrates reward and delay information and that this representation is anatomically varied along the axis of the STN.

Plots of "rejection rate" (trials where the monkeys failed to wait until the rewards) as a function of delay and reward size seem to indicate that the monkeys understood the visual cue. The rejection rates were very low (less than 4% for almost all conditions) which indicates that the monkeys did not have a hard time inhibiting their behavior. It also meant that the authors could not compare trials where the monkeys successfully waited with trials where they failed to wait. This missing comparison weakens the link between the neurophysiological observations and the conclusions the authors made about the signals they observed.

The authors examined the STN activity aligned to the start of the delay and also aligned to the reward. Most of the "delay encoding" in the STN activity was observed near the end of the waiting period. The trouble with the analysis is that a neuron that responded with exactly the same response on short and long trials could appear to be modulated by delay. This is easiest to see with a diagram, but it should be easy to imagine a neural response that quickly rose at the time of instruction and then decayed slowly over the course of 2 seconds. For long trials, the neuron's activity would have returned to baseline, but for short trials, the activity would still be above baseline. As such, it is not clear how much the STN neurons were truly modulated by delay.

Another concern is the presence of eye movement variables in the regressions that determine whether a neuron is reward or delay encoding. If the task variables modulated eye movements (which would not be surprising) and if the STN activity also modulated eye movements, then, even if task variables did not directly modulate STN activity, the regression would indicate that it did. This is commonly known as "collider bias". This is, unfortunately, a common flaw in neuroscience papers.

Overall, while the work is potentially interesting, these methodological issues weaken the link between the data and the conclusions of the paper.

Reviewer #2 (Public Review):

The work integrated genomic and transcriptomic data to reconstruct the origin of the svPDE gene from the ancestral ENPP3 gene. The authors also analyzed the expression of svPDE along different snake lineages and different tissues in three species of venomous snakes. Finally, they purified an svPDE from the venom of Naja atra and analyzed its crystallographic structure and enzymatic function. The experiments are adequately designed and carefully planned and the conclusions made by the authors are well supported by evidence.

I have the following suggestions:

I could not find a section where the authors provided information regarding the origin of the analyzed venom and tissues. i.e. muscle tissue from Naja atra and venom for purification of svPDE. It is important to include this information.

The authors mention (Line 156) that "the genomic sequences of svPDE-E1a were present in all species of Serpentes but not in the species of Dactyloidae, Varanidae, and Typhlopidae.". As I understand it, the family Typhlopidae is included in the Suborder Serpentes. The conclusions stand of course, but I believe it is worth revising, for accuracy.

During the discussion (Line 315), it is stated that the expression of svPDE in Lamprophiidae is probably associated with the adaptation of prey selection as a dietary generalist compared to Viperidae and Elapidae. Provided that both of these clades have several species considered dietary generalists, I believe this statement is not strongly supported.

Also in the discussion (Line 320), the authors mention that Colubridae is traditionally regarded as a non-venomous clade. This statement is far from accurate given that Colubridae is a very diverse clade and several species within it have been shown to be at least moderately venomous. Various species have been shown to produce secretions comparable to those of front-fanged snakes.<br /> Furthermore, despite their difference in morphology, I believe there is little to no evidence that suggests Duvernoy's glands in colubrids have any functions differing from the venom glands of front-fanged snakes.

Reviewer #2 (Public Review):

Mahbub et al further elucidate the structural and functional consequences of the ARL15-CNNM2 interaction for divalent cation transport. They show that ARL15 has low GTP binding affinity and could not detect GTPase activity, questioning whether ARL15 functions as a GTPase. Although the interaction of ARL15 and CNNMs has been demonstrated by multiple groups before, this study addresses some of the key questions that are central within the TRPM-CNNM-PRL-ARL15 field. Particularly, the authors have identified residues in both ARL15 and CNNM proteins which are required for their binding to one another. In addition, they have also illustrated how PRL proteins compete with ARL15 for their binding to CNNMs. Lastly, the functional consequences of ARL15 binding to CNNMs are shown by TRPM7-mediated Zn2+ transport assays.

However, the current dataset also comes with limitations. Previous studies demonstrated that PRLs interact with the CBS domains of CNNMs and lock them in their so-called "flat" confirmation. It remains unclear how ARL15 affects the structure of the CBS domains, especially in the presence of ATP. The subcellular localisation of these interactions has not been examined. Moreover, the consequences of ARL15 on TRPM7 activity are not completely elucidated. It remains unclear whether this functional effect is CNNM-dependent. Moreover, how the zinc uptakes translate to other divalent ion transport, such as magnesium, has not been examined. These questions should be answered to confirm the model as presented in Figure 7.

Reviewer #2 (Public Review):

Experiments were designed to determine if the adult offspring of mothers exposed to intermittent hypoxia (IH) during late gestation show reduced compensatory respiratory motor neuron plasticity, which is defined as an increase in respiratory motor system output that persists for a long-time following cessation of the perturbing stimulus. Here, the team uses a clever approach to evoke plasticity, which they term inactivity-induced respiratory motor facilitation. This approach has been shown to be repeatable and robust, and therefore useful for evaluating the impact of experimental interventions on compensatory respiratory motor system responses. The model is a paralyzed, mechanically ventilated, anesthetized rat in which the activity of a phrenic nerve is used as an index of excitability of the phrenic motor neuron population, which drives the diaphragm muscle in mammals. Importantly, the activity of the respiratory control system in the brainstem can be terminated by reducing the pH of the blood and cerebrospinal fluid (CSF) to a value that is unique to each animal. This value is called the central apneic threshold, and it occurs because pH-sensitive receptors in the brainstem provide critical excitatory synaptic input to the respiratory controller. Since the pH of the blood and CSF depends importantly on the corresponding levels of CO2 the pH can be adjusted up or down by manipulating the blood CO2. To evoke inactivity-induced respiratory motor facilitation, the group first sets the mechanical ventilator at a rate sufficient to reduce CO2 below the apneic threshold to stop phrenic motor output and then keeps the ventilator output at this level. Then, CO2 is added to the ventilator to raise the blood CO2 to levels just above the apneic threshold, which establishes the baseline level of phrenic motor neuron output. They then periodically stop adding CO2 to the inspired gas mixture, which allows CO2 to fall below the apneic threshold, which abolishes phrenic nerve activity. After 1 minute of apnea, the CO2 is reintroduced, blood CO2 levels rise and phrenic nerve activity resumes. This sequence of 1 minute of central apnea followed by 5 minutes of phrenic motor activity is repeated 5 times, and the recording continues for 60 minutes after the fifth apneic episode. As shown in figure 1, a progressive and long-lasting increase in phrenic nerve activity is observed in both male and female control animals, consistent with compensatory respiratory neuroplasticity. Interestingly, the neuroplastic response in the male offspring of animals exposed to intermittent hypoxia throughout gestation was abolished but was unchanged in the female offspring.

This striking, sex-dependent loss of respiratory motor neuroplasticity in the offspring of IH-exposed mothers was associated with increased inflammatory response in the cervical spinal cord, but not in the brainstem. In addition, the transcriptomes of both the spinal cord and brainstems from male offspring of IH-exposed mothers differed from control, with upregulation of genes targeting transcription factors involved in the inflammatory response, specifically the NF-kB/STAT pathways. Accordingly, additional experiments were done to demonstrate that blocking STAT transcription factor activation with intrathecally-delivered drugs restored the plastic response in the male offspring of IH-exposed mothers.

These are novel and interesting observations showing that GIH is associated with a strong, microglia-mediated inflammatory response in the spinal cord of adult males, but not female offspring. The inflammatory response was associated with a loss of compensatory neuroplasticity in phrenic motoneurons. The techniques employed include difficult and labor-intensive whole animal physiology experiments to RNA sequencing and microglial functional analyses. These data are thus important and of wide interest, as they link a gestational insult with spinal cord inflammation, microglial dysfunction, and a sex-dependent alteration in the ability to generate neuromotor plasticity that persists into adulthood. The main caveat is that IH does not model either obstructive or central apnea as both are associated with combined episodic hypoxia and hypercapnia. Moreover, whereas excitatory synaptic input to the phrenic motoneurons was periodically silenced to evoke "inactivity", patients with upper airway obstruction during sleep take great breathing efforts. The model used here seems more like central apnea; do pregnant humans typically have central or obstructive sleep apnea? Nonetheless, the experiments provide important insight into the impact of gestational hypoxia on the development of breathing control in male offspring.

Reviewer #2 (Public Review):

The current manuscript presents a new toolbox to apply temporal response functions (TRFs) usable in python. TRFs are becoming more widely used and providing an accessible toolbox for a wider audience is very important and should be promoted. Overall, it also seems that the code accompanying the manuscript provides all the steps to do the analysis and could potentially be very useful. However, in the current version, the toolbox relies on one single way to solve the TRF estimation problem, which is the boosting algorithm. Providing a single algorithm makes it difficult to compare results from this toolbox with outcomes of other toolboxes which rely on different methods to solve the regression. The user is forced to work with this choice and is not provided other options (or easy ways to implement new options). Additionally, it seems unclear whether the toolbox is fully able to provide the means to generate predictors that are typically used in a TRF analysis. The github code provided for generating the predictors does not seem to be fully integrated with eelbrain and relies on code in the trftools toolbox, which contains code that the authors deem not yet stable enough to be released. Finally, the overall logic and idea behind the toolbox could have been explained better to make it more accessible to use.

Reviewer #2 (Public Review):

In this manuscript, Hüsler et al. aimed to evaluate the contribution of LDs, Sey1, and FadL to intracellular replication and palmitate catabolism of L. pneumophila in D. discoideum. The authors found that Sey1 regulates LD proteome composition and promotes Icm/Dot-dependent LCV-LD interactions as well as FadL-dependent fatty acid metabolism of intracellular L. pneumophila. The study is in general well-designed and performed. The data are clearly presented and valuable in enhancing awareness of the mechanisms of L. pneumophila infection. The evidence supporting the claims of the authors is solid, although the inclusion of additional controls and clarifications would have strengthened the study.

Reviewer #2 (Public Review):

The authors describe the derivation of new and stable fly cell lines through a strategy of tissue-specific RasV12 expression and in some cases single cell cloning. Lines with molecular and, in some cases, phenotypic characteristics of the targeted tissue are identified: muscle, neural, glial, epithelial, and macrophage-like. These are (for the most part) karyotypically normal and amenable to genetic manipulation including transient and attP-mediated insertion. This paper reports a publicly available resource that will be of great use to many. The cell lines are ready for the well-established tools available for high-throughput screening using CRISPR, RNAi, and small molecules, and allow scalable biochemistry which has been a limitation of using Drosophila for some research questions. Moreover, the Ras-targeting approach is potentially a general way to make additional tissue-specific cells, and the authors describe several failures as well as successes in deriving tissue-specific lines. Overall it is a highly valuable piece of work. Ways that the paper reporting this work could be enhanced for the reader include 1) a more critical analysis of the limitations of these lines to represent their prospective in vivo tissues; 2) a more explicit comparison of these lines next to existing fly cell lines including but not limited to the workhorse S2, and 3) any information on the ease of use and behavior of these cells in the types of high-throughput/high-volume formats where they are likely to be most valuable.

Reviewer #2 (Public Review):

In this manuscript, the authors investigated the association of household close-range contact patterns with SARS-CoV-2 transmission in the household using proximity sensors deployed after the identification of SARS-CoV-2 in the household. They recruited participants in two urban communities in South Africa, Klerksdorp (North West Province) and Soweto (Gauteng Province) from October 2020 through September 2021. Their analysis suggests the lack of an association between close-range proximity events and SARS-CoV-2 household transmission.

Their study design looks reasonable, with useful household contacts data collected in the study. However, their regression analysis only considered a limited set of contact parameters (i.e., median measurements of duration, frequency, and average duration). It's not clear if this limitation will bias the conclusion regarding the lack of an association between close-range proximity events and SARS-CoV-2 household transmission.

Reviewer #2 (Public Review):

In this manuscript, the authors proposed a mathematical model to describe analog and digital modes of gene regulation using FCA-mediated FLC regulation as a model. Previously, a similar approach revealed that the repression of FLC by vernalisation is digital. The authors utilized allelic variations of fca mutants (fca-1; a strong allele and fca-3; a weak allele), which resulted in the different levels of FLC de-repression. Unlike FLC in fca-1, where FLC is robustly ON or OFF states in the root cells, authors observed "intermediate" FLC-expressed cells (weak ON) in fca-3. The authors argued that these "intermediate" levels of FLC expression in root cells might indicate the presence of the analog mode of gene expression. In addition, the authors used the "age"-dependent FLC repression to validate whether digital mode can occur in fca-3 and concluded that it does happen. However, digital OFF does not occur in fca-1, and the authors speculated that this might be due to a "high" level of FLC transcription. Based on these observations, the authors developed a simple mathematical model to predict the transition from analog to digital gene regulation at the cell population level. It is an intriguing model/conclusion to show the "analog" mode of gene regulation, and FLC regulation has been an excellent model system for understanding various modes of gene regulation.

However, some significant issues need to be addressed.

1. Mechanistic details of how FCA regulates FLC have been extensively studied, and both transcriptional and co-transcriptional regulations occur. I understand that FCA affects the 3'end processing of antisense COOLAIR RNAs, which regulate FLC. FCA also physically interacts with COOLAIR RNAs and other proteins, including chromatin-modifying complexes, which establish epigenetic repression of FLC regardless of vernalisation. In addition, FCA appears to function to resolve R-loop at the 3' end FLC, and FLC preferentially interacts with m6A-modified COOLAIR by forming liquid condensates. FCA is also alternatively spliced in an autoregulatory manner, and fca-1 mutant was reported to be a null allele as fca-1 cannot produce the functional form of FCA transcripts (r-form).

However, I could not find any information on the fca-3 allele, which was reported to exhibit a weaker phenotype in terms of flowering time (Koornneef et al., 1991). In this manuscript, the authors showed that the level of FLC expression is lower than fca-1 and higher than Ler WT, but I could not find any other relevant information on the nature of the fca-3 allele. Given the known details on the function of FCA, the authors should explain how fca-3 shows an "intermediate" phenotype, which is highly relevant to the argument for an "analog" mode of regulation in fca-3. Therefore, the nature of the fca-3 mutant should be described in detail.

2. The authors used a transgene (FLC-venus) in which an FLC fragment from ColFRI was used. Both fca-1 and fca-3 is Ler background where FLC sequence variations are known. I understand that the authors introgressed the transgenic in Ler background to avoid the transgene effect, but it is not known whether fca-1 or fca-3 mutations have the same impact on Col- FLC.

3. Fig. 3A: I understand that Fig 3A is the qRT-PCR data using whole seedlings, and the gradual reduction of FLC from 7 DAG to 21 DAG was used to test the "analog" vs. "digital" mode of gene regulation in fca-1 and fca-3. I am not sure whether this is biologically relevant.

3-a. The authors wrote that "This experiment revealed a decreasing trend in fca-3 and Ler (Fig. 3A)". But, I do also see a "decreasing trend" in fca-1 as well (although I understand that they may not be statistically significant). I also noticed that the level of FLC in fca-1 at 7 day has a greater variation. Is there any explanation?

3-b. The decreasing trend observed in Ler (although the expression of FLC is already relatively low in Ler) may be the basis for the biological relevance. But Fig. 3D shows that the FLC-venus intensity in Ler root is not "decreasing".<br /> The authors interpreted that "root tip cells in Ler could switch off early, while ON cells still remain at the whole plant level that continue to switch off, thereby explaining the decrease in the qPCR experiment."<br /> Does this mean that the root tip system with FLC-venus cannot recapitulate other parts of plants (especially at the shoot tip where FLC function is more relevant)?

The authors utilize the root system with transgenes in mutant backgrounds to observe and model the gene repression (transgene repression, to be exact). If the root tip cells behave differently from other parts of plants, how could the authors use data obtained from the root tip system?

4. I do see both fca-1 and fca-3 can express FCA at a comparable level (Fig. 3B); thus, I guess that the authors are measuring total FCA transcripts and that fca-3 may result in different levels of "functional form" of FCA. But this is not clearly discussed.

5. Quantification based on image intensity needs to be carefully controlled. Ideally, a threshold to call "ON" or "OFF" state should be based on the comparison to internal control and it is not clear to me how the authors determined which cells are ON or OFF based on image intensity (especially in fca-3).

6. In many parts, I had to guess how the experiments were performed with what kind of tissues/samples. The methods section can benefit from a more thorough description.

Reviewer #2 (Public Review):

The authors set out to characterize the genetic architecture for aposematic color polymorphism in a species of tiger moths. It was previously known that the color polymorphism showed a non-sex-linked Mendelian inheritance pattern, and was thus likely controlled by an allelic change at a single autosomal locus. Based on observations in other species that traits with a similar simple inheritance pattern of polymorphic aposematic colors often involve supergenes, which refers to a tightly linked cluster of co-adapted loci, the authors tested the hypotheses that a supergene may be involved here in tiger moth polymorphism. To test this hypothesis, they used a combination of QTL mapping, GWAS, and RNA-seq approaches to identify regions of the genome that showed an association with the color pattern polymorphism. The genetic mapping approaches identified a candidate genomic region that contained >20 genes, including the genes yellow-e, and its paralog, valkea. The RNA-seq data showed these genes to be expressed differently in the developing wings of the different color morphs. The valkea paralog is associated with a duplicated chromosomal region that appears to only be present in the genomes of yellow-colored morphs. A phylogenetic-weighting approach was also used to attempt to distinguish the strength of associations of the yellow-e and valkea genes with the color polymorphism and found evidence suggesting valkea was the likely genetic switch for the color polymorphism. Lastly, the authors provide evidence that the differences in coloration involve a change in melanins, through chemical characterization of pigments extracts. Collectively, the authors provide a comprehensive examination of the color pattern genetics and compelling evidence that the polymorphism in pigmentation is controlled by an allelic change at a single autosomal locus that includes the yellow-e/valkea genes that show different expression patterns in the differently colored morphs.

Strengths:<br /> This study provides a comprehensive mapping effort to identify a locus responsible for modulating adaptive variation in natural populations of the tiger moth. This is an ideal trait and system to study the genetic basis of adaptive variation, as the trait variation has clear impacts on fitness and is under strong selection in natural populations. The genomes of Lepidoptera and their amenability for laboratory research and molecular methods make them well-suited for such mapping efforts. The authors used an impressive number of offspring from genetic crosses to conduct QTL mapping, which was nicely complemented with a population genomic GWAS approach to further narrow the candidate locus. The addition of the RNA-seq provides compelling evidence that genes at this locus are clearly involved in differences in wing pattern development.

The greatest strength of this study is perhaps its finding of "something new, using something old". I am referring to the finding of a novel duplication of the yellow gene being involved in pigment variation. Yellow is well-known to be involved in color pattern development in Drosophila and butterflies, but its role in the tiger moths is completely novel. A recent duplication of yellow being involved in adaptive variation is completely new and quite exciting. With other recent examples of gene duplications being involved in differences in butterfly color pattern development, there are now numerous cases of the rapid evolution of gene duplicates involved in generating wing pattern variation. Thus, the findings here should be of broad interest to those interested in the genetic changes involved in generating adaptive variation in natural populations.

Another strength of the study is the characterization of the melanic pigment changes involved in the polymorphism. Such detailed phenotypic analyses can offer critical insights into how the genetic differences found to be associated with color pattern variation, may function and influence wing pattern development.

Weaknesses:<br /> Despite narrowing the locus to a small number of genes through mapping efforts, the study falls short in identifying the genetic switch and sufficient evidence to confirm valkea's role in the color polymorphism.

The mapping efforts identified a narrow locus covering multiple genes from the yellow gene family and RNA-seq data clearly identified valkea and yellow-e as being differentially expressed between color morphs thereby implicating their involvement in differences in wing color pattern development. However, the type and number of genetic changes at this locus involved in generating the color polymorphism remain unresolved. Tree topology provides only suggestive evidence that genotypes at valkea show a stronger association with color pattern differences than at the other nearby yellow genes, and offers limited further resolution as the where the genetic switch may be (e.g. within coding or non-coding regions across the locus).

I am unconvinced that framing this study as a test for the role of a supergene, or "to test whether the polymorphism is associated with large structural rearrangements controlling multiple phenotypic elements, or the result of a single gene mutation" is most appropriate or strengthens the study. The alternative hypotheses of "large structural rearrangements" versus "single gene mutation" do not necessarily reflect the possible, or most likely hypotheses, and neither are not necessarily clearly supported by the results of the study. In other studies of wing color pattern polymorphisms in butterflies, the genetic changes controlling the variation have been non-coding mutations in putative cis-regulatory elements (CREs) that control the expression of a nearby gene involved in wing pattern development (see examples from Heliconius butterflies). These would be considered changes in CREs, not "single gene mutations". There are instances in which such changes impacting color pattern variation have been captured within structural rearrangements, such as polymorphic inversions of Heliconius numata, the single gene or CRE mutation and structural rearrangements both being involved are not mutually exclusive, thus it is difficult to frame this study as testing them as alternative hypotheses. The data presented in the study celery implicate a genomic region with multiple genes differentially expressed (DE) between color morphs, with one of the DE genes residing within a structural variation (insertion/deletion polymorphism). However, the study is unable to resolve if the large structural rearrangement is involved, or if a single versus multiple genes or CRE changes may be involved. Thus, I find it challenging and perhaps a weakness of the paper to frame the study as a test of these alternative hypotheses that are not necessarily mutually exclusive or able to be distinguished using the data in the study. I have similar concerns with the focus on supergenes (i.e. co-adapted gene complex) being a weakness for the paper, as the results of the study don't directly test for the presence or role of a co-adapted gene complex at the locus identified.

Reviewer #2 (Public Review):

In this manuscript, Hoffmann et al. introduce a novel and innovative method to validate and study the mechanism of action of essential genes and novel putative drug targets. In the wake of many functional genomics approaches geared towards identifying novel drug targets or synthetic lethal interactions, there is a dire need for methods that allow scientists to ablate a gene of interest and study its immediate effect in culture or in xenograft models. In general, these genes are lethal, rendering conventional genetic tools such as CRISPR or RNAi inept.

The ARTi system is based on expression of a transgene with an artificial RNAi target site in the 3'-UTR as well as a TET-inducible miR-E-based shRNAi. Using this system, the authors convincingly show that they can target strong oncogenes such as EGFRdel19 or KRasG12 as well as synthetic lethal interactions (STAG1/2) in various human cancer cell lines in vivo and in vitro.

The system is very innovative, likely easy to be established and used by the scientific community and thus very meaningful.

Reviewer #2 (Public Review):

The authors aimed to test the effects of smoking on the methylome while controlling for genetics to test for evidence of whether previous studies on genetically-unrelated individuals were confounded by genetics.

The strengths of this study of genetics-independent associations between smoking exposure and DNA methylation using an epigenome-scale approach are (1) its moderate sample size for a twin study (50-100 ) to detect some of the larger effects sizes (10-15%) found in this study; (2) the thorough EWAS methodology including adjusting for cellular heterogeneity and the use of Bonferroni correction; (3) the use of a within identical twin pair design; (4) the strong overlap between the results and those of previous similar studies in genetically unrelated individuals. Weaknesses include the use of methylation arrays that although targeted to putative regulatory regions, cover only around 2.5% of genomic CpGs, and the use of only a single tissue (blood). Both are acknowledged by the authors.

The authors achieved their aims and were able to test all their hypotheses. In general, the authors' claims were supported by their data, but they could empirically test for an association between methylation and expression at all top CpGs rather than just stating that a subset significantly associated.

This is an important set of findings for the field because genetic confounding has been levelled as a criticism of epigenomewide association studies. It therefore strengthens the evidence that environment (smoking) can change the methylome, assuming that the methylomes of each pair were similar prior to exposure.

Reviewer #2 (Public Review):

The authors explored non-redundant, and potentially contrasting, roles of the Hippo effector transcription factors, YAP and TAZ, in the epithelial regenerative response to non-infectious lung injury. The strength of the work is the use of genetic mouse models that explored inducible loss of function of YAP and/or TAZ in an alveolar epithelial type 2 (AT2) specific manner. The main weakness of the work is that gene(s) inactivation was performed prior to lung injury and, therefore, does not take into account the contextual and dynamic nature of YAP/TAZ signaling; for example, work by other groups have shown that YAP/TAZ is activated early following injury followed by a decrease in activity, thus balancing proliferation and differentiation of AT2 cells (for review, see PMID: 34671628).

Reviewer #2 (Public Review):

The report was based on three nation-wide cancer screening programs (breast, bowel, and cervix cancer). This paper attempts to simulate the potential impact of screening disruption on the cancer detection. The authors raised an important concern; that the screening disruption by COVID-19 pandemic would led to an increase in cervical cancer but a reduction in detection of breast and bowel cancer.

There are some issues that must be addressed to ensure the analysis and conclusions can be clearly studied. Importantly, it is not entirely clear if the simulation methodology applied to arrive at a scientific conclusion. The authors could provide more insights on how they will address not only the change of cancer detection but also the driving some improved methods for screening helping return to pre-pandemic levels.

1. A quasi-experimental before and after design as the methodological intention should be stated in the article. Although there are equally powerful alternatives with arguably less-stringent requirements that are appropriate and well-tested for natural experiments such as that intervened by the COVID-19 pandemic given the simulation methods, as of now obtaining the actual stage distribution of cancer and the cancer-specific mortality rates before and after the pandemic is possible for making scientifically valid conclusions based on observed data to support the simulation study.

2. The screening disruption is the only concerned parameter in modelling the change of cancer progression in this study. But delayed diagnosis after screening as another concern could be possibly affected by the pandemic. This should be taken into consideration in the simulation. The authors also claimed the cancer treatment could be also be affected by the pandemic, the evaluation on mortality is therefore not feasible. However, the impacts of COVID-19 pandemic on the delayed treatment and cancer treatment are important issues which should be covered by simulation study.

3. By simulations, the confident intervals for the outcomes should be provided as the requirement to determine the required reliability for the estimates.

Reviewer #2 (Public Review):

The authors aimed to explore the relationship between life course SES and BMI trajectories. They achieve the aim partially, and they could present the results more clearly. The work is interesting and will inform China's obesity public health programs and policies, but it is also interesting for other countries and communities. The exploration of life course exposures is relevant in many ways, and the authors did a good job conceptualizing the BMI and SES trajectories. However, some issues need to be improved, such as the discussions about bias and improvements in the writing and presentation of results.

Reviewer #2 (Public Review):

The authors try to introduce the encoding time factor into theories of optimal encoding of information in the nervous system

The major strength is in the rigorous analysis and in the simple yet important take home message.

The authors achieved their aim by proving their point with rigorous analyses and the results support their conclusions

The paper makes a simple yet important addition and will likely call for neuroscientists to include more carefully the importance of stimulus encoding time in their formulations of models of neural coding and in the interpretations of results.

ez a rész egyetlen mondat, képzeletbeli párbeszéd zajlik Radnóti és egy bombázó repülőgép pilótája között. a költő érveket sorakoztat fel, miért ne pusztítsa el hazáját. a szerkesztési elv roppant egyszerű: a pilóta fentről szemláli a tájat; csak egy térképet lát, míg a költő lentről figyeli a tájat, látja az apró életképeket, melyek a térképet élettel töltik meg. a költő ellentétpárokkal dolgozik: háborús célpontok állnak szemben a békés mindennapok képével (vad laktanya - szelíd tanya; gyárat - dolgozót; gyárüzem - gyerek). a pusztítandó célpontok Radnóti számára a hazát jelentik, amelyet ismer és szeret. visszatérnek az első rész képei is: erdő, füttyös gyümölcsös, sírok közt anyóka, bakterház udvarán játszó gyermekek. végül személyes emlékeket idéz fel: szerelmeit, egy apró követ mely szerencsét hozott neki diák korában. egyszóval felidézi a még háború előtti szelíd és békés gyermek- és fiatalkorát. mindez fentről nem látható, de talán átérezhető

Reviewer #2 (Public Review):

Endothelial cells mediate the growth of the vascular system but they also need to prevent vascular leakage, which involves interactions with neighboring endothelial cells (ECs) through junctional protein complexes. Buglak et al. report that the EC nucleus controls the function of cell-cell junctions through the nuclear envelope-associated proteins SUN1 and Nesprin-1. They argue that SUN1 controls microtubule dynamics and junctional stability through the RhoA activator GEF-H1.

In my view, this study is interesting and addresses an important but very little-studied question, namely the link between the EC nucleus and cell junctions in the periphery. The study has also made use of different model systems, i.e. genetically modified mice, zebrafish, and cultured endothelial cells, which confirms certain findings and utilizes the specific advantages of each model system. A weakness is that some important controls are missing. In addition, the evidence for the proposed molecular mechanism should be strengthened.

Specific comments:

1) Data showing the efficiency of Sun1 inactivation in the murine endothelial cells is lacking. It would be best to see what is happening on the protein level, but it would already help a great deal if the authors could show a reduction of the transcript in sorted ECs. The excision of a DNA fragment shown in the lung (Fig. 1-suppl. 1C) is not quantitative at all. In addition, the gel has been run way too short so it is impossible to even estimate the size of the DNA fragment.

2) The authors show an increase in vessel density in the periphery of the growing Sun1 mutant retinal vasculature. It would be important to add staining with a marker labelling EC nuclei (e.g. Erg) because higher vessel density might reflect changes in cell size/shape or number, which has also implications for the appearance of cell-cell junctions. More ECs crowded within a small area are likely to have more complicated junctions.<br /> Furthermore, it would be useful and straightforward to assess EC proliferation, which is mentioned later in the experiments with cultured ECs but has not been addressed in the in vivo part.

3) It appears that the loss of Sun1/sun1b in mice and zebrafish is compatible with major aspects of vascular growth and leads to changes in filopodia dynamics and vascular permeability (during development) without severe and lasting disruption of the EC network. It would be helpful to know whether the loss-of-function mutants can ultimately form a normal vascular network in the retina and trunk, respectively. It might be sufficient to mention this in the text.

4) The only readout after the rescue of the SUN1 knockdown by GEF-H1 depletion is the appearance of VE-cadherin+ junctions (Fig. 6G and H). This is insufficient evidence for a relatively strong conclusion. The authors should at least look at microtubules. They might also want to consider the activation status of RhoA as a good biochemical readout. It is argued that RhoA activity goes up (see Fig. 7C) but there is no data supporting this conclusion. It is also not clear whether "diffuse" GEF-H1 localization translates into increased Rho A activity, as is suggested by the Rho kinase inhibition experiment. GEF-H1 levels in the Western blot in (Fig. 6- supplement 2C) have not been quantitated.

5) The criticism raised for the GEF-H1 rescue also applies to the co-depletion of SUN1 and Nesprin-1. This mechanistic aspect is currently somewhat weak and should be strengthened. Again, Rho A activity might be a useful and quantitative biochemical readout.

Reviewer #2 (Public Review):

This work aims to understand genomic imprinting in the mouse and provide further insight to challenges and patterns identified in previous studies.

Firstly, genomic imprinting studies have been surrounded by controversy especially ~10 years ago when the explosion of sequencing data but immature methods to analyze it lead to highly exaggerated claims of widespread imprinting. While the methods have improved, clear standards are not set and results still have some inconsistencies between studies. The authors first do a meta-analysis of previous studies, comparing their results and doing a useful reanalysis of the data. This provides some valuable insights into the reasons for inconsistencies and guides towards better study designs. While this work does not exactly set a common standard for the field, or provide a full authoritative catalog of imprinted loci in mouse tissues, it provides a step in that direction. I find these analyses relatively simple and straightforward, but they seem solid.

Previous studies have described a relatively common pattern of subtle expression bias towards one parental allele, rather than the classical imprinting pattern of fully monoallelic expression. This work digs deeper into this phenomenon, using first the meta-analysis data and then also targeted pyrosequencing analysis of selected loci. The analysis is generally well done, although I did not understand why gDNA amplification bias was not systematically corrected in all cases but only if it was above a given (low) threshold. I doubt this would affect the results much though. To some extent the results confirm previously observed patterns (bimodal distribution of either subtle or full bias, and effect of distance from the core of the imprinted locus). The novel insights mostly concern individual loci, with discovery and validation of some novel genes, typically with a subtle or context-specific parental bias.

The study also provides some insights into mechanisms, especially by analysis of existing mouse models with a deletion of the ICR of specific loci. The change in the parental bias pattern was then used to infer potential methylation and chromatin-related mechanisms in these imprinted loci, including how the subtle bias further away is achieved. There are interesting novel findings here, as well as hypotheses for further research. However, this is an area where the conclusions rely quite heavily on published research especially as this study doesn't include single-cell resolution, and it's not entirely clear how much of e.g. the Figure 7 mechanisms part is based on discoveries of this study.

Imprinting is a fascinating phenomenon that can be informative of mechanisms of genome regulation and parental effects in general. It is a bit of a niche area though, and the target audience of this study is likely going to be limited to specialists doing research on this specific topic. As the authors point out, the functional importance of the findings is unknown.

Reviewer #2 (Public Review):

Previous work from the authors' lab has shown that the classical 'Minute' phenotypes in Drosophila depend on the ribosomal protein Rps12, suggesting that Rps12 is a sensor of deficits in other ribosomal proteins (Rp). Increasing the dose of Rps12 enhances 'Minute' phenotypes, while loss of Rps12 suppresses them. However, Rps12+/- heterozygous flies do not display 'Minute' phenotypes.

In the current manuscript, the authors examine the consequences of deleting Rps12 in mice to explore its potential role in translational regulation and hematopoiesis. Homozygosity for an Rps12 null mutation is embryonic lethal, while heterozygous Rps12+/- mutant mice exhibit defects in growth, skeletal abnormalities, hydrocephalus and stroke. Consistent with other mouse Rp mutants, Rps12+/- mutant mice have a block in erythroid maturation and reduced spleen size. Hematopoietic stem and progenitor cell (HSPC) numbers are reduced in the bone marrow and are defective in repopulation transplant assays. Unexpectedly, Rps12+/- mutants show loss of HSC quiescence associated with AKT/MTOR and ERK pathway activation and increased global translation, a phenomenon that has not previously been reported in other Rp mutants. The authors conclude that Rps12 is critical for the maintenance of HSC quiescence and function.

Strengths<br /> The data reported in this manuscript nicely complement the existing literature on the functional effects of Rp mutations in mammalian hematopoiesis and development with loss of HSC quiescence and increased global translation in the Rps12 deficient mice. These unexpected findings will be of broad interest to scientists working in the field of ribosome assembly, ribosomopathies and hematopoiesis.

Weaknesses<br /> It remains unclear mechanistically how Rps12 haploinsufficiency activates the AKT/MTOR and ERK signaling pathways. It is also unclear to what extent the reported phenotypes might be indirect consequences of perturbing the expression of two small nucleolar RNA genes that are present in Rps12 introns 4 and 5 or a consequence of TP53 activation, which is known to influence the phenotype in other examples of Rp deletion mouse models. To fully justify the conclusions that the authors wish to draw, it would be important to assess the effect of the heterozygous Rps12+/- mutation on Rps12 protein expression, ribosomal subunit assembly and rRNA processing.

Reviewer #2 (Public Review):

Weaver et al. used video analysis of flies that were feeding in their previously developed FLIC assay to begin to dissect the mechanisms of feeding. FLIC or Fly Liquid Interaction Counter records electrical signals that are generated when a fly touches a liquid food substrate with its legs or proboscis or both. Using video data of the liquid food interactions in the FLIC assay allowed the authors to precisely identify what a fly is doing in the feeding chamber and what the relationship is between the flies' behavior and the electrical signal recorded in the assay. This analysis produced the first detailed behavioral profile of feeding flies and allowed the authors to categorize different types of feeding in the FLIC assay, from tasting food (using their legs) to fast and long feeding bouts (using their proboscis).

After establishing what FLIC signals correspond to the different types of feeding, they used these signals to examine the food choices of starved and sated flies when presented with a sugar-rich (2% sucrose) or protein-rich (2% yeast + 1% sucrose) liquid food source. To represent hedonic feeding, they also presented flies with a choice between super sweet (20% sucrose) food or protein-rich (2% yeast + 1% sucrose) liquid food. Although fully fed flies show no difference in the number of times they visit either food choice, the flies spend more time feeding during their visits on 20% sucrose food than they do on regular sugar and on the yeast food source, suggesting that 20% sucrose is a more pleasurable food source. To make sure this was not due to the higher caloric content of 20% sucrose, they also offered flies food with the same sweetness as 20% sucrose (2% sucrose + 18% arabinose) but without caloric content and food with the same caloric content but the sweetness of 2% sucrose (2% sucrose + 18% sorbitol). This experiment showed that sweetness was the driver for the longer feeding bouts, confirming that sweeter food is apparently perceived as more pleasurable. They also looked at the effect of starving flies on the hedonic drive and found that starvation increases the time spent feeding on pleasurable food, consistent with findings in mammals that homeostatic feeding affects the hedonic drive.

To begin dissecting circuits underlying hedonic drive, the authors used CaMPARI expression in all neurons. CaMPARI is a green fluorescent reporter that turns red in the presence of Ca2+ (a measure of neuronal activity) and UV exposure. Fully fed flies in the super sweet food choice condition showed more red fluorescence in the mushroom bodies. Inhibiting a subset of these neurons acutely shows that horizontal lobes are required for the increased duration of feeding bouts on super sweet food. These lobes are innervated by a cluster of DA neurons and inhibiting them also blocks the increased super sweet feeding times.

The data in the paper largely support the conclusions. The application of this tool to distinguish between homeostatic and hedonic feeding is innovative and very compelling. As proof of principle of the strength of their paradigm, the authors identify a distinct brain circuit involved in hedonic feeding. The methods established in the paper make a deeper understanding of feeding mechanisms possible at both a genetic and brain circuit level.

Some of the data presentation is dense and could be improved to make this paper easier for readers to understand.

1) The dissection of feeding into distinct behavioral elements and its correlation with electrical FLIC signals that allow interpreting feeding types is a fundamental new method to dissect feeding in flies. However, the categories of micro-behaviors in Table 1 are not intuitive.

2) The details for the behavioral data analysis are not clear and should be made more obvious. For example, how many males and females were used in each experiment? Were any of the females mated or were they all virgins? If all virgins, why not use mated females? Mating status may have an effect on the feeding drive. If mated and virgin females were used, are there any differences between them? Similarly, for diurnal feeding experiments, it is not immediately clear from the graphs how many animals were used and how the frequencies were obtained (Fig. 1F, presumably averages for each category per fly but that is inconsistent with the legend in the supplement for this figure). Why does the transition heat map not include all micro-behaviors (Fig. 1E, no LQ data which are significant in diurnal feeding)?

3) The CaMPARI images do not look great, particularly in the pan-neuronal condition (Fig. 5A). It would be useful to include the movie of the stack. Did any other brain regions show activity differences, such as SEZ or PI? These regions are known to be involved in feeding so it seems surprising they show no effect.

Reviewer #2 (Public Review):

This paper explores the possibility of integrating diverse and multiple DNA fragments in the genome taking advantage of plasmids in arrays, and CRISPR-Cas.

Since the efficiency of integration in the genome is low, they, as others in the field, use selection markers to identify successful events of integration. The use of these selection markers is common and diverse, but they use a couple of distinct strategies of selection to:

– Introduce bar codes in the genome of individuals at one specific genomic site (gene for Hygromycin resistance with bar code in an intron with homology arms to complete a functional gene);

– Introduce promoters at two specific genomic landing pads downstream of fluorescent reporters.

The strengths of the study rely on the clever design of the selection markers, which enrich the collection of this type of markers. The weaknesses are the lack of novelty in the field in theoretical or practical terms. In fact, they do not show any innovative application of these approaches. Moreover, they show a limited number of experiments in the manuscript, or at least insufficient in my opinion for an article that is based on a methodology.

This work adds to other recent studies, e.g. from Nonet, Mouridi et al., and Malaiwong et al, that use the integration of single and multiple/diverse DNA sequences in the C. elegans genome, and thus is not as groundbreaking as claimed. The real test of this method will be its use to address biological questions.

Reviewer #2 (Public Review):

In this work, the authors used machine learning techniques to predict chronological age in the large UK Biobank dataset using structural neuroimaging measures of regional brain volumes and cortical thickness in sex-stratified models. From these predictions, the authors calculated the brain-age delta, which is thought to reflect biological brain aging. The authors applied these models to four independent cohorts and calculated brain-age delta, which they then associated with several markers of Alzheimer's disease pathology, neurodegeneration, and cerebrovascular disease. The aim of these analyses was to validate brain-age delta as a clinically relevant marker of AD.

Strengths<br /> This is a well-written manuscript that explains a well-powered study of multiple deeply-phenotyped cohorts. An impressive amount of work went into this manuscript and that is evident from reading it. The manuscript was enjoyable to read and easy to follow, and the authors provided an informative summary figure visualizing the analysis plan of this work. More specifically there are five key strengths in this present work.<br /> First, instead of aiming for a brain-predicted age model with optimal predictive accuracy, as is typically the case in studies using brain-age delta measures, the authors used a model with a restricted feature set and a limited age range to allow for better neurobiological interpretability and to increase the relevance of this model to ageing cohorts.<br /> Second, the authors corrected for the proportional bias that is seen in brain age models and controlled subsequent analyses (i.e. associations between brain-age delta and markers of AD pathology, etc.) for chronological age. This is an important and necessary step when working with brain-age delta but is not always implemented across studies.<br /> Third, the authors computed Shapley Additive explanation values (SHAP) which quantified the contribution of different brain regions to the brain age prediction. This ensured that the model had neurobiological interpretability which is not always the case with brain-age prediction models. This was further improved by using a relatively restricted feature set that is often used in brain-age prediction studies as the most important regions could be easily visualized and therefore more readily interpreted. This is in contrast to other models that use a large number of smaller brain features, which are less easily vizualised and less interpretable.<br /> Fourth, importantly, the authors used sex-stratified models as they generated the brain-age delta measures separately in men and women. This allowed for sex-specific analyses of the associations between brain-age delta and markers of AD pathology, cerebrovascular disease, and neurodegeneration, which is important given evidence of sex differences in AD. These sex-stratified models also enabled the authors to compare the most relevant brain regions in the brain age prediction models. While previous work has reported sex differences in brain-age delta, the sex-specific contribution of specific brain features is important information that is not usually reported.<br /> Finally, in addition to investigating the association of brain-age delta with specific markers of AD pathology, cerebrovascular disease, and neurodegeneration, the authors also analyzed the association between brain-age delta and amyloid and tau status stages which provides important clinically relevant information. This information is important if future work aims to further investigate the use of brain-age delta in the field of AD.

Limitations<br /> There are three important weaknesses in this present work. First, the conclusion that "These results validate brain-age delta as a non-invasive marker of biological brain aging related to markers of AD and neurodegeneration" (from the Abstract) may be overstated. While we assume that brain-age delta reflects an accelerated ageing process, this is still a cross-sectional measure and the results show cross-sectional associations with markers of AD and neurodegeneration. For true validation of this measure as a non-invasive marker of biological brain aging with respect to markers of AD and neurodegeneration, we would need longitudinal data to show that changes in brain age are longitudinally associated with changes in markers of AD and neurodegeneration.<br /> Second, the authors reported that brain-age delta was not related to longitudinal brain change ('aging signature change'), which supports a recent finding that cross-sectional brain-age delta was not associated with longitudinal brain change but was associated with birthweight and polygenic risk scores for brain-age delta (Vidal-Pineiro et al., 2021 eLife). This previous finding led to the conclusion that brain-age delta may reflect early-life factors more so than longitudinal brain change or 'accelerated brain ageing'. This is a critical issue to contend with if we really wish to pursue further validation of the brain-age delta as a potential marker of aging<br /> Third, the analyses for the associations between brain-age delta and other variables are not corrected for multiple comparisons, even though a large number of comparisons are conducted. This means that some of the apparently significant results could be false positives. Appropriately correcting these analyses for multiple comparisons would strengthen the results, allowing for greater confidence in the significant results, and would avoid mistaken interpretations of false positive findings.

Appraisal<br /> The authors developed accurate and generalizable sex-specific measures of the brain-age delta. The authors demonstrated that brain-age delta was associated with measures of AD pathology and neurodegeneration. These have the potential to be useful findings that may promote the use of the brain-age delta in AD research. However, as these results are not corrected for multiple comparisons it is possible that some of these results may be false positives. Moreover, the finding that brain-age delta was not associated with longitudinal brain change may undermine the conclusions, as it could suggest that brain-age delta is not reflective of accelerated brain ageing.

Impact<br /> I believe that this work has two important impacts. First, the methods demonstrated in the present study highlight that sex-stratified models may be necessary for future brain-age delta studies, and given that the models were externally validated in four separate cohorts, a key impact is that future researchers will be able to apply the well-described brain-age models here in their own work. Second, the finding that brain-age delta was not related to longitudinal brain change or atrophy, supports previous similar findings and could suggest that brain-age delta does not, as previously assumed, reflect accelerated brain ageing. This may indicate that the brain-age delta is not a satisfactory marker of brain ageing and therefore could discourage future work with this metric that attempts to validate it is a clinical marker of brain ageing. If this issue could be alternatively explained or if brain-age delta is, in fact, shown to reflect brain ageing, then an additional potential impact is that it may support the future investigation into the use of brain-age delta in longitudinal studies of brain ageing and neurodegeneration.

Reviewer #2 (Public Review):

Wilson et al. investigated the development of thalamocortical tracts in the fetal brain using in vivo diffusion magnetic resonance imaging (dMRI). In their results, fiber tracts terminating in the prefrontal, superior parietal, and visual cortex connect to discrete areas of the thalamus in an anterior-to-posterior manner. The reported fetal thalamus parcellation is remarkably consistent with parcellation observed in adults, which has significant implications for the development of experience-expectant vs. experience-dependent neurocircuitry. Using along-tract analysis, the authors also identify distinct trajectories of tissue maturation along tracts connecting the thalamus to the medial prefrontal cortex, visual cortex, and superior parietal cortex. Next, these maturation maps were segmented using a histologically defined fetal atlas, which revealed unique maturation within fetal neural compartments across gestation. The study introduces an exciting analytical model for bridging the gap between histology and dMRI, enhancing both the interpretability of dMRI metrics in the fetal brain and validating dMRI as a sensitive tool that can reveal organizing principles of fetal brain development. The sample size is impressive for fetal imaging and analyses were completed in individual subject spaces, which helps to minimize the warping of dMRI data.

The conclusions of the paper are largely well-supported by the data, but some aspects of sample composition and data analysis require clarification and extension to ensure the generalizability of the results.

1. Sociodemographic makeup of the sample is insufficiently considered. The authors provide information about fetal gestational age and fetal sex, but no other information about the sample is provided. Readers familiar with the developing human connectome project will know the data was collected in the United Kingdom, but this is not stated explicitly in the manuscript. There is no other information provided about the sample, so it is unclear whether the included 140 maternal-fetal dyads are representative of the broader population. Complex social experiences that vary as a function of income, racial and ethnic identity, and education are potent influences on the developing brain, and there is notable meta-analytic work demonstrating the sociodemographic makeup of a sample alters trajectories of brain development. Brain development in utero has also been shown to vary among fetuses who are later born preterm, yet there is no information about pregnancy complications or delivery (e.g., gestational age at birth) reported in the manuscript. This lack of sociodemographic and health information significantly impedes inference regarding result generalizability.

2. Over half of the collected data were discarded because of failing data quality checks. This is common in fetal data, but it is unclear what thresholds were used to determine exclusion and whether the excluded cases fall evenly along the age spectrum. Typically, MRI data from younger fetuses show greater motion artifacts compared to data collected in older fetuses, which presents a significant confound for the present study that requires careful consideration. It is also unclear whether the motion correction strategies employed in the present study work equally well for all fetal ages. In short, additional analysis and information are required to ensure age-related motion is not unduly impacting the present results.

3. Given that the youngest age group was much smaller than the other groups (n=13), more data is also needed to assess the robustness of the tissue maturation trajectories reported for this young age group.

4. Sensitivity analyses that illustrate the findings are robust to different preprocessing choices would enhance analytic rigor.

Reviewer #2 (Public Review):

Harada et al. investigated the mechanism by which high mannose levels inhibit cellular proliferation and enhance chemotherapy. The authors used CRISPR-Cas9 to delete mannose phosphate isomerase (MPI), a key enzyme for metabolizing mannose, in human cancer cells. They found that MPI knockout leads to decreased proliferation of cancer cells when challenged with supraphysiologic concentrations of mannose. Mannose challenge increased sensitivity to both cisplatin and doxorubicin chemotherapy. It also induced slow cell-cycling with impaired entry into the S phase and progression to mitotic phase. Proteomic analysis revealed down-regulation of cell-cycle related proteins following mannose challenge. Specifically, MCM2-7 proteins are decreased, indicating a failure of replication fork progression. The authors show that high mannose conditions disengage dormant origin sites from DNA synthesis during replication stress induced by cisplatin, confirming relevance to induced chemotherapy sensitivity. Metabolic analysis revealed decreased glycolytic activity, increased oxidative phosphorylation, and depleted nucleotides. Finally, pharmacologic inhibition of de novo dNTP biosynthesis using hydroxyurea treatment produced similar effects on cell-cycle progression, chemotherapy sensitivity, and inhibition of DNA synthesis from dormant origins, indicating that high mannose induced depletion of dNTP pools may be the major mechanism behind the anti-cancer effects of mannose.

Strengths: Overall, the authors used a robust approach with several techniques showing consistent results. The use of multiple clones and cell lines increases confidence in the reported findings. Additionally, the re-expression of MPI in MPI-KO cells eliminated the sensitivity to high mannose conditions, increasing confidence that the findings are not due to off-target effects. The authors are thorough in characterizing the defects in cell-cycle progression and have robust molecular evidence to support the failure of DNA synthesis from dormant origins during chemotherapy-induced replication stress. The use of both proteomics and metabolomic techniques generates a robust picture of molecular effects of mannose challenge. Lastly, the demonstration of similar mechanistic effects by pharmacologic inhibition of de novo dNTP synthesis provides support that depletion of dNTPs is a major cause for the anti-cancer effects of high mannose.

Weaknesses: While the conclusions of this paper are supported by strong and consistent evidence, there are limitations in the relevance of the models used. The study was conducted using cancer cells genetically engineered to not express MPI. However, cancer cells ubiquitously express MPI. Drawing conclusions about metabolic remodeling based on metabolite pool sizes alone is not recommended, as pool sizes can increase or decrease due to changes in production or consumption. Isotope labeling studies would reconcile the reasons for accumulation or depletion of metabolite pool sizes. Lastly, in Figure 3, the authors show down regulation of cell cycle progression genes in response to mannose challenge. However, there is also upregulation of proteins related to various cell death mechanisms including ferroptosis and necrosis, suggesting there may be additional mechanisms to explain the effects of mannose challenge. It is unclear why the cell-cycle explanation was pursued without addressing other possibilities.

Reviewer #2 (Public Review):

In this study, Levakov et al. investigated brain age based on resting-state functional connectivity (RSFC) in a group of obese participants following an 18-month lifestyle intervention. The study benefits from various sophisticated measurements of overall health, including body MRI and blood biomarkers. Although the data is leveraged from a solid randomized control set-up, the lack of control groups in the current study means that the results cannot be attributed to the lifestyle intervention with certainty. However, the study does show a relationship between general weight loss and RSFC-based brain age estimations over the course of the intervention. While this may represent an important contribution to the literature, the RSFC-based brain age prediction shows low model performance, making it difficult to interpret the validity of the derived estimates and the scale of change. The study would benefit from more rigorous analyses and a more critical discussion of findings. If incorporated, the study contributes to the growing field of literature indicating that weight-reduction in obese subjects may attenuate the detrimental effect of obesity on the brain.

The following points may be addressed to improve the study:

Brain age / model performance:

1. Figure 2: In the test set, the correlation between true and predicted age is 0.244. The fitted slope looks like it would be approximately 0.11 (55-50)/(80-35); change in y divided by change in x. This means that for a chronological age change of 12 months, the brain age changes by 0.11*12 = 1.3 months. I.e., due to the relatively poor model performance, an 80-year-old participant in the plot (fig 2) has a predicted age of ~55. Hence, although the age prediction step can generate a summary score for all the RSFC data, it can be difficult to interpret the meaning of these brain age estimates and the 'expected change' since the scale is in years.

2. In Figure 2 it could also help to add the x = y line to get a better overview of the prediction variance. The estimates are likely clustered around the mean/median age of the training dataset, and age is overestimated in younger subs and overestimated in older subs (usually referred to as "age bias"). It is important to inspect the data points here to understand what the estimates represent, i.e., is variation in RSFC potentially lost by wrapping the data in this summary measure, since the age prediction is not particularly accurate, and should age bias in the predictions be accounted for by adjusting the test data for the bias observed in the training data?

3. In Figure 3, some of the changes observed between time points are very large. For example, one subject with a chronological age of 62 shows a ten-year increase in brain age over 18 months. This change is twice as large as the full range of age variation in the brain age estimates (average brain age increases from 50 to 55 across the full chronological age span). This makes it difficult to interpret RSFC change in units of brain age. E.g., is it reasonable that a person's brain ages by ten years, either up or down, in 18 months? The colour scale goes from -12 years to 14 years, so some of the observed changes are 14 / 1.5 = 9 times larger than the actual time from baseline to follow-up.

- The questions above should be investigated and addressed in the context of potential challenges with using brain age as a marker (see e.g., https://onlinelibrary.wiley.com/doi/full/10.1002/hbm.25837, https://onlinelibrary.wiley.com/doi/full/10.1002/hbm.26144).

RSFC for age prediction:

1. Several studies show better age prediction accuracy with structural MRI features compared to RSFC. If the focus of the study is to use an accurate estimate of brain ageing rather than specifically looking at changes in RSFC, adding structural MRI data could be helpful.

2. If changes in RSFC is the main focus, using brain age adds a complicated layer that is not necessarily helpful. It could be easier to simply assess RSFC change from baseline to follow up, and correlate potential changes with changes in e.g., BMI.

The lack of control groups

1. If no control group data is available, it is important to clarify this in the manuscript, and evaluate which conclusions can and cannot be drawn based on the data and study design.

Reviewer #2 (Public Review):

This work by Bray et al. presented a customized way to induce small electrolytic lesions in the brain using chronically implanted intracortical multielectrode arrays. This type of lesioning technique has the benefit of high spatial precision and low surgical complexity while allowing simultaneous electrophysiology recording before, during, and after the lesion induction. The authors have validated this lesioning method with a Utah array, both ex vivo and in vivo using pig models and awake-behaving rhesus macaques. Given its precision in controlling the lesion size, location, and compatibility with multiple animal models and cortical areas, the authors believe this method can be used to study cortical circuits in the presence of targeted neuronal inactivation or injury and to establish causal relationships before behavior and cortical activity.

Strengths:

Great presentation of design considerations that addressed the gaps of current lesioning and neuronal inactivation methods, especially the cross-compatibility that allows this method to be used across different cortical regions and in different animal models, making it easy to be adopted into a variety of electrophysiology studies.

This method can induce lesions that are highly precise and repeatable in size and location, allowing for robust investigation of neuronal circuit function. When combined with the ability to record without disruption both in the acute and chronic phase after lesioning, this would create a great tool to study neural adaptation and reorganization.

The customized current source is simple, low-cost, yet effective in delivering precise, controllable current for electrolytic lesioning, and thus easy to adopt for a range of neuroscience applications.

Extensive ex vivo testing and validation were performed before moving into in vivo and eventually nonhuman primate (NHP) experiments, successfully reducing animal use.

Weaknesses:

In many of the figures, it is not clear what is shown and the analysis techniques are not well described.

The flexibility of lesioning/termination location is limited to the implantation site of the multielectrode array, and thus less flexible compared to some of the other termination methods outlined in Appendix 2.

Although the extent of the damage created through the Utah array will vary based on anatomical structures, it is unclear what is the range of lesion volumes that can be created with this method, given a parameter set. It was also mentioned that they performed a non-exhaustive parameter search for the applied current amplitude and duration (Table S1/S2) to generate the most suitable lesion size but did not present the resulting lesion sizes from these parameter sets listed. Moreover, there's a lack of histological data suggesting that the lesion size is precise and repeatable given the same current duration/amplitude, at the same location.

It is unclear what type of behavioral deficits can result from an electrolytic lesion this size and type (~3 mm in diameter) in rhesus macaques, as the extent of the neuronal loss within the damaged parenchyma can be different from past lesioning studies.

The lesioning procedure was performed in Monkey F while sedated, but no data was presented for Monkey F in terms of lesioning parameters, lesion size, recorded electrophysiology, histological, or behavioral outcomes. It is also unclear if Monkey F was in a terminal study.

As an inactivation method, the electrophysiology recording in Figure 5 only showed a change in pairwise comparisons of clustered action potential waveforms at each electrode (%match) but not a direct measure of neuronal pre and post-lesioning. More evidence is needed to suggest robust neuronal inactivation or termination in rhesus macaques after electrolytic lesioning. Some examples of this can be showing the number of spike clusters identified each day, as well as analyzing local field potential and multi-unit activity.

The advantages over recently developed lesioning techniques are not clear and are not discussed.

There is a lack of quantitative histological analysis of the change in neuronal morphology and loss.

There is a lack of histology data across animals and on the reliability of their lesioning techniques across animals and experiments.

There is a lack of data on changes in cortical layers and structures across the lesioning and non-lesioning electrodes.

Reviewer #2 (Public Review):

The manuscript presents a computational model of how an organism might learn a map of the structure of its environment and the location of valuable resources through synaptic plasticity, and how this map could subsequently be used for goal-directed navigation.

The model is composed of 'map cells', which learn the structure of the environment in their recurrent connections, and 'goal-cell' which stores the location of valued resources with respect to the map cell population. Each map cell corresponds to a particular location in the environment due to receiving external excitatory input at this location. The synaptic plasticity rule between map cells potentiates synapses when activity above a specified threshold at the pre-synaptic neuron is followed by above-threshold activity at the post-synaptic neuron. The threshold is set such that map neurons are only driven above this plasticity threshold by the external excitatory input, causing synapses to only be potentiated between a pair of map neurons when the organism moves directly between the locations they represent. This causes the weight matrix between the map neurons to learn the adjacency for the graph of locations in the environment, i.e. after learning the synaptic weight matrix matches the environment's adjacency matrix. Recurrent activity in the map neuron population then causes a bump of activity centred on the current location, which drops off exponentially with the diffusion distance on the graph. Each goal cell receives input from the map cells, and also from a 'resource cell' whose activity indicates the presence or absence of a given values resource at the current location. Synaptic plasticity potentiates map-cell to goal-cell synapses in proportion to the activity of the map cells at time points when the resource cell is active. This causes goal cell activity to increase when the activity of the map cell population is similar to the activity where the resource was obtained. The upshot of all this is that after learning the activity of goal cells decreases exponentially with the diffusion distance from the corresponding goal location. The organism can therefore navigate to a given goal by doing gradient ascent on the activity of the corresponding goal cell. The process of evaluating these gradients and using them to select actions is not modelled explicitly, but the authors point to the similarity of this mechanism to chemotaxis (ascending a gradient of odour concentration to reach the odour source), and the widespread capacity for chemotaxis in the animal kingdom, to argue for its biological plausibility.

The ideas are interesting and the presentation in the manuscript is generally clear. The two principle limitations of the manuscript are: i) Many of the ideas that the model implements have been explored in previous work. ii) The mapping of the circuit model onto real biological systems is pretty speculative, particularly with respect to the cerebellum.

Regarding the novelty of the work, the idea of flexibly navigating to goals by descending distance gradients dates back to at least Kaelbling (Learning to achieve goals, IJCAI, 1993), and is closely related to both the successor representation (cited in manuscript) and Linear Markov Decision Processes (LMDPs) (Piray and Daw, 2021, https://doi.org/10.1038/s41467-021-25123-3, Todorov, 2009 https://doi.org/10.1073/pnas.0710743106). The specific proposal of navigating to goals by doing gradient descent on diffusion distances, computed as powers of the adjacency matrix, is explored in Baram et al. 2018 (https://doi.org/10.1101/421461), and the idea that recurrent neural networks whose weights are the adjacency matrix can compute diffusion distances are explored in Fang et al. 2022 (https://doi.org/10.1101/2022.05.18.492543). Similar ideas about route planning using the spread of recurrent activity are also explored in Corneil and Gerstner (2015, cited in manuscript). Further exploration of this space of ideas is no bad thing, but it is important to be clear where prior literature has proposed closely related ideas.

Regarding whether the proposed circuit model might plausibly map onto a real biological system, I will focus on the mammalian brain as I don't know the relevant insect literature. It was not completely clear to me how the authors think their model corresponds to mammalian brain circuits. When they initially discuss brain circuits they point to the cerebellum as a plausible candidate structure (lines 520-546). Though the correspondence between cerebellar and model cell types is not very clearly outlined, my understanding is they propose that cerebellar granule cells are the 'map-cells' and Purkinje cells are the 'goal-cells'. I'm no cerebellum expert, but my understanding is that the granule cells do not have recurrent excitatory connections needed by the map cells. I am also not aware of reports of place-field-like firing in these cell populations that would be predicted by this correspondence. If the authors think the cerebellum is the substrate for the proposed mechanism they should clearly outline the proposed correspondence between cerebellar and model cell types and support the argument with reference to the circuit architecture, firing properties, lesion studies, etc.

The authors also discuss the possibility that the hippocampal formation might implement the proposed model, though confusingly they state 'we do not presume that endotaxis is localized to that structure' (line 564). A correspondence with the hippocampus appears more plausible than the cerebellum, given the spatial tuning properties of hippocampal cells, and the profound effect of lesions on navigation behaviours. When discussing the possible relationship of the model to hippocampal circuits it would be useful to address internally generated sequential activity in the hippocampus. During active navigation, and when animals exhibit vicarious trial and error at decision points, internally generated sequential activity of hippocampal place cells appears to explore different possible routes ahead of the animal (Kay et al. 2020, https://doi.org/10.1016/j.cell.2020.01.014, Reddish 2016, https://doi.org/10.1038/nrn.2015.30). Given the emphasis the model places on sampling possible future locations to evaluate goal-distance gradients, this seems highly relevant. Also, given the strong emphasis the authors place on the relationship of their model to chemotaxis/odour-guided navigation, it would be useful to discuss brain circuits involved in chemotaxis, and whether/how these circuits relate to those involved in goal-directed navigation, and the proposed model.

Finally, it would be useful to clarify two aspects of the behaviour of the proposed algorithm:

1) When discussing the relationship of the model to the successor representation (lines 620-627), the authors emphasise that learning in the model is independent of the policy followed by the agent during learning, while the successor representation is policy dependent. The policy independence of the model is achieved by making the synapses between map cells binary (0 or 1 weight) and setting them to 1 following a single transition between two locations. This makes the model unsuitable for learning the structure of graphs with probabilistic transitions, e.g. it would not behave adaptively in the widely used two-step task (Daw et al. 2011, https://doi.org/10.1016/j.neuron.2011.02.027) as it would fail to differentiate between common and rare transitions. This limitation should be made clear and is particularly relevant to claims that the model can handle cognitive tasks in general. It is also worth noting that there are algorithms that are closely related to the successor representation, but which learn about the structure of the environment independent of the subjects policy, e.g. the work of Kaelbling which learns shortest path distances, and the default representation in the work of Piray and Daw (both referenced above). Both these approaches handle probabilistic transition structures.

2) As the model evaluates distances using powers of adjacency matrix, the resulting distances are diffusion distances not shortest path distances. Though diffusion and shortest path distances are usually closely correlated, they can differ systematically for some graphs (see Baram et al. cited above).