Reviewer #1:

The manuscript by Sachella examines the role of the lateral habenula (LHb) in learning to associate a context and a cue with an aversive event. The methods use pharmacological and optogenetic modulation of LHb function. The data show that inactivation of the LHb impairs contextual fear conditioning (CFC) as well as cued fear conditioning (when testing occurs in a novel context). The disruption in context but not cued FC is also obtained when testing occurs in the context of conditioning (A) 7 days after training but the deficit in both is evident when testing occurs 21 days after training. Overall, similar results are obtained with cue-specific optogenetic inhibition using ArchT and more sustained optogenetic excitation across the entire training session with oChiEF. Finally, exposure to the context and tone 24hrs prior to the test rescued cued but not contextual fear.

The present paper provides an interesting set of studies looking at the role of the LHb in fear conditioning. There are many strengths to the paper. The variation in testing and training conditions is great. It allows to examine memory to the conditioning context when it is the only stimulus the animals learn about, as well as to examine the memory for the cue when tested in a novel context in the absence of influence from the conditioning context (i.e., cue test in context B), as well as in the context of conditioning (i.e., context A). This allows the authors to rule out overshadowing as an interpretation. For example, the LHb-inactivated animals do not present an augmented case of overshadowing in the cued and contextual fear training conditions. If that was the case in the CFC alone experiment, LHb inactivation would not have disrupted learning, but it did. Further, if the LHb had a specific role in summation of context and cued fear (this could account for the data in Fig 3 as ceiling levels could mask performance differences in 3B), then it would not modulate contextual and cued FC when examined independently (Fig 1 and 2). The authors allude to this briefly in line 226. Other strengths of the manuscript include excellent anatomical controls.

Despite the strengths, there are a number of weaknesses that need to be addressed. The major one, I believe, lies in the necessity for additional data to support the conclusions. Although there are a lot of data presented in the manuscript, together they are not a convincing set that speaks to one interpretation. Specifically, the idea that LHb inactivation/stimulation leads to weakening of the memory strength is interesting, but it also requires additional investigation to show that under conditions when the CFC is strengthened, LHb inactivation has a less devastating effect. Further, the authors concede on line 252-253 that more experiments are needed to determine whether LHb inactivation disrupts the associative or representation components of CFC. I agree but feel this should have been done in the present paper instead of the reconsolidation studies which are also incomplete. The authors argue 'under inactivation of the LHb, a cued FC memory is formed whose retrieval depends on the context in which the cue is presented'. However, the disruption of contextual fear makes this interpretation difficult to accept. If the correct context is needed for cued fear to be expressed then this suggests either a possible generalization decrement effect that is ameliorated by being placed in the same context or a context-gating effect. Both require some knowledge of the context where the cued fear learning occurred. Yet, this is difficult to reconcile with the consistent disruption in context fear.

The reconsolidation experiments, although interesting, lack clarity and the vehicle controls. A systematic investigation of exposure to the conditioned context or the conditioned cue (in context B) on fear to the conditioned context, the cue and both would help dissociate how retrieval-based reconsolidation acts in the current preparation. This may warrant an independent investigation/publication.

Some other arguments that I didn't find convincing: The equivalent reduction in exploration in the OF for the vehicle and muscimol animals is argued to suggest that similar contextual representation are formed between the groups and therefore the CFC differences are unlikely to be due to deficits in context encoding. The OF data are insufficient to argue this. Many aspects can modulate activity in the OF from the traditional anxiety argument (here similar reduction in anxiety) to a sense of familiarity. There is no evidence for similar contextual encoding.

Some additional comments:

The way the 24hr and 7d data are presented is a little odd. While the authors justify this, it seems strange from the reader's perspective to see the 7d test data before the 24hr test data. In addition, the 24hr tests data are referred to as long term memory, which can be perceived as odd relative to the longer 7d test. This section just needs to be revised for clarity in the presentation.

Does the difference in cued fear at the 24hr interval persist if conditioning differences are used as a covariate in the analysis and if a difference score is calculated from the baseline difference?

Reviewer #1:

The paper tackles an important aspect of neuroanatomical and language research concerning the lateralization differences related to functional lateralization of language. No clear cut results are currently available nowadays and methodological limitations of previous approaches are here addressed with a new type of analysis. Despite this new angle in the tractography analysis is of interest, the differences in the tasks that are used to address language lateralization are also as important. This may also explain possible differences in previous studies and also with the current one. This aspect seems to be missed in this work.

Although the Letter fluency task implies the use of language, this task is commonly considered in neuropsychological assessments as an executive function task. A more appropriate task would have been a Semantic Fluency task or as in previous work (Vernooij et al 2007) a verb generation task. There is a close relationship between executive function and many aspects of language production, there is not doubt about this. But this does not mean they are the same. Actually the Forceps minor has been found to be associated with individual differences in executive functions in language function (Mamiya et al 2018; Farah et al 2020). This is a limitation of the study and should be acknowledged since the results may differ with a more purely linguistic task, limiting the scope of the study and its conclusions in terms of language lateralization. I do believe the data are worth publishing and the methodological approach is novel but the reader should be clearly aware of the limits in terms of the conclusions the authors can draw from the selection of the sample that may correspond to lateralization of executive function for language more than language lateralization per se.

Reviewer #1:

The work by Pipitone et al. is a very carefully performed and technically sophisticated elucidation of the establishment of the thylakoid membrane system in Arabidopsis chloroplasts upon first illumination of cotyledons. Its charm is the three-dimensional resolution during a time course that allows it to follow the rapid changes occuring during the short time window in which the greening occurs. In addition, the authors included proteomics and lipidomics approaches complementing the morphological observations by sound molecular data. All together the study provides a very detailed catalogue of the processes that trigger chloroplast biogenesis that is highly useful for the community as it provides important numbers of size and development.

Improvements:

Actually the work has been performed very carefully and there is not much to improve.

The introduction could contain more references (e.g. lines 77, 83, 90, 93, 98,, 131, 132)

SBF-SEM should be spelled out at first mentioning (line 146) and maybe a bit more background about the technology would be helpful for the reader to understand it.

Line 244: The occurrence of starch granules is of course caused by the continuous illumination. It however may also have an impact on the final size of the plastid. It would be interesting to know whether chloroplasts at the end of a night phase are smaller than at the end of a light phase. This is not mandatory for the current manuscript but an interesting question to follow in future and maybe to be discussed.

Line 251: The surface area.... please define what is meant since membranes have two sides.

Lines 256-261: There is another study done in cell culture that has a similar design (Dubreuil et al ), are the two studies compatible with each other in their conclusion and if not, what are the differences?

Lines 549-551: This sentence is not perfectly clear to me. Maybe the authors can explain this a bit more in detail using examples.

Lines 564-573: I think it is worth noting that the interactions between PSII complexes located in neighbouring thylakoid membranes trigger the stacking of the grana. It is therefore tempting to speculate that stroma lamellae are established first and that these membranes are then stacked after PSII complexes are inserted into the membrane because they provide the adhesion points between them.

Reviewer #1:

The study by Lyengar et al describes age- and temperature-dependent changes in the neurophysiology of the giant fiber (GF) system in adult wild type and superoxide dismutase 1 mutant flies (SOD[1]). While the main GF circuit and downstream circuits exhibit little change when flies are reared at 25C, GF inputs and other circuits driving motoneuron activities show age-dependent alterations consistent with earlier studies. Rearing flies at 29C temperatures had no additional effects except that age-dependent progression of defects were accelerated, as it was expected from previous studies. In SOD[1] mutants, which are short lived, changes in the neurophysiology of the GF system were different from those induced by high temperature.

Overall this technically challenging, and well executed study provides a nice description of the effects of aging, high activity (induced by higher temperature), and loss of SOD function on the neurophysiology of the GF system. However, most of the described effects have been observed in other systems and are thus not entirely novel. Moreover, the study does not provide any insight into the mechanisms underlying the age-dependent alterations of the examined neurons. Thus, the overall significance of the described findings is limited.

Reviewer #1:

This manuscript compares the effects of a novel versus a classical augmented acoustic environment protocole on partial improvement of congenital hearing loss. The new protocol is based on the idea that temporal structure, and in particular auditory gaps in the augmented environment should improve perception of temporal features in sounds, in particular of auditory gaps.

Technically sound, the study describes how the encoding of gap in the auditory midbrain (inferior colliculus, IC) of a mouse hearing loss model is affected by the novel temporally enriched paradigm with respect to control mice and to the classical paradigm. The study clearly confirms that augmented acoustic environments improve spectral tuning, and detection of sound features with respect to control animals in IC. IC neurons also appear to show a more robust increase of sensitivity to amplitude changes (onsets and offsets) when the animals have gone through the temporal augmented sound environment, both in the presence and in the absence of background noise, as compared to the classical paradigm, at least if one considers the magnitude of the effects with respect to control. However, only few measures show a significant difference when directly testing between the classical and the temporally enriched paradigm. Thus, there is an overall impact of the temporal paradigm which is worth emphasizing as a small but likely useful increment of the auditory enrichment approach for improving hearing loss. This is a definitely interesting, even if somewhat expected result which could drive further studies on clinical practice. It seems however too specialized for broader readership. A few things in the presentation of the results could be improved, and behavioral data could eventually reinforce the message although it is not mandatory to make these results interesting :

1) A figure of the auditory enrichment setup would be nice, to better understand how this works. Are mice constantly submitted to the sounds? Are control mice in a more silent environment than normally housed mice?

2) The lack of behavioral data opens the question whether IC changes have actually an impact on perception. Although it is likely, it would be interesting to measure the magnitude of this impact.

3) What makes the study interesting is the tendential bias in favor of the temporal paradigm with respect to the classical one. This is however rarely significant in one to one comparisons for each sensitivity measure. To reinforce their point the authors could consider a multivariate statistical analysis (e.g. two way ANOVA) to show that over all their measures there is a significant improvement with temporal against classical.

Reviewer #1:

This report makes a logical connection between depressive-like behaviors induced in mice following LPS-injection to mimic bacterial infection and the down regulation of phospholipid transporting enzyme, ATP8A2, in the prefrontal cortex. The intermediary is IFN-gamma. The work is quite convincing that LPS down regulates ATP8A2 by upregulating IFN-gamma and that this has some limited effects on behavior. However, the impact of the findings is limited by several factors.

1) The use of FST and TST as measures of depression is increasingly falling out of favor as there is no face validity to humans. It is understood that these tests have been long in use and were in the past considered the best measures of "depressive-like" behaviors in mice but the field has moved on to much more relevant constructs such as social defeat, anhedonia etc. As it stands the behavioral analysis here is limited and the effects are modest at best.

2) The use of LPS as a model to induce depression also has limitations. The injection paradigm used is likely to have caused massive inflammation, as evidenced by the increase in cytokines, but what this is modeling is unclear and how the impact would be specific to depression later in life is equally unclear. Indeed, the references the authors cite for the LPS regime they use offer completely different mechanisms and impacts of the inflammation. This is not to say the current findings aren't important, they are, but rather this pathway may be one among many that is invoked following massive inflammation during early development which then has many non-specific effects.

3) There is no functional connection between down regulation of ATP8A2 developmentally and adult neural activity. Clearly a membrane phospholipid transporting enzyme is important, but exactly how it is important here, meaning what enduring impacts there are on neuronal function, is unknown.

4) The experiments were designed to test the relationship between IFN-gamma and ATP8A2 but then conclude that the behavioral effects are mediated by this connection. There could be many other effects of IFN-gamma that are not considered here but would be nonetheless blocked by the neutralizing antibody approach used. Thus the main conclusions of the manuscript are not supported in terms of the role of ATP8A2 in LPS-induced depression.

Reviewer #1:

Mackay et al. present a study on the phenotype of neurons from YAC128 mice, an HD model expressing mHTT with 128 CAG repeats. They show (i) that cultured cortical YAC128 neurons exhibit increased mEPSC rates transiently during development in vitro (i.e. between DIV14-18 but not at DIV7 or DIV21), (ii) that calcium release from ER by low-dose ryanodine increases mEPSC rates only in WT but not in YAC128 cells, and (iii) that blocking SERCA to deplete ER calcium stores reduces mEPSC rates in YAC128 neurons as compared to WT controls. These data are interpreted to indicate that a presynaptic ER calcium leak increases mEPSC rates in YAC128 neurons. Using rSyph-GCaMP imaging, the authors then show (i) an increase in longer-lasting AP-independent calcium signals in synaptic boutons of YAC128 neurons as compared to WT, (ii) less profound increases in calcium signals upon ionomycin-mediated equilibration to 2 mM extracellular calcium, (iii) less profound increases in calcium signals upon caffeine treatment in YAC128 boutons, and (iv) less AP-related calcium events in YAC128 boutons. A final dataset shows that evoked synaptic transmission in YAC128 striatum as assessed by iGluSnFR imaging is inhibited by ryanodine in WT but not in YAC128 mice. The authors conclude that the overexpression of mHTT with 128 CAG repeats in the YAC128 mutant causes aberrant calcium handling (i.e. calcium leak/release from the ER), which leads to increased cytosolic calcium concentrations, increased AP-independent release events, but reduced AP-evoked glutamate release.

Comments:

1) I think the authors show convincingly that (presynaptic) calcium handling is perturbed in YAC128 cortical presynaptic boutons. What is conceptually unclear to me at the outset is whether this specific phenomenon is related to HD pathology. The phenomenon is transient during the development of cortical neurons in culture and gone at DIV21. In contrast, the first subtle behavioural defects of YAC128 mice arise at about 3 months of age, overt behavioural defects at 6 months of age, and striatal and cortical degeneration still later.

2) The issue discussed above (1) could have been addressed in part with the slice experiments, which were conducted with tissue from 2-3 months old mice, but the corresponding data are too cursory at this point. They indicate a small defect in evoked glutamate release in the YAC128 model, but it is unclear whether mEPSC rates are altered. It seems important to test this as the increased mEPSC rates are proposed to be at the basis of the phenotype described in the present study. Indeed, the authors ultimately conclude that the YAC128 mutation causes increased mEPSC rates at the expense of evoked glutamate release. This is generally unlikely to be true as the mEPSC rates in question are very likely overcompensated by the vesicle priming rate.

3) The phenomenon of altered calcium handling in YAC128 neurons is shown convincingly. However, this finding is not unexpected given that previous studies indicated such increased calcium release from endoplasmic reticulum in HD models in other subcellular compartments, and it remains unclear how this defect is caused by the mutant HTT.

4) As already outlined above (2) it remains unexplained how the calcium handling defects increase mEPSC rates but decrease evoked transmission. The corresponding part of the discussion reflects this uncertainty. This is aggravated by the fact that several of the drugs used have complex dose-dependent effects that cannot easily be reduced to specific effects on calcium handling by the ER. For instance, it is unclear whether caffeine effects on adenosine receptors or PDEs have to be taken into consideration. In general, the sole reliance on partly 'multispecific' pharmacological tools is a bit worrisome.

5) There are several other aspects of the paper that are not immediately plausible. For instance, I have difficulties to understand why a calcium transient minutes before ionomycin treatment would affect the calcium signal triggered by ionomycin in the presence of 2 mM extracellular calcium (Figure 4); after all, the example trace shows that the calcium levels return to baseline within seconds. And more generally, in this context: Can differences in calcium buffers and the like be excluded? A direct assessment of absolute cytosolic calcium concentrations would be the ultimate solution.

Overall, the present paper describes a phenomenon in presynaptic boutons of an HD model, key aspects of which (e.g. increased ER calcium handling defects) have been described in other subcellular compartments of HD models. The connection of this phenomenon to HD is unclear as the developmental timelines of the appearance and disappearance of the cellular phenotype and the disease progression do not match. The opposite phenotypes caused at the level of presynaptic boutons on AP-independent and AP-dependent release remain disconnected. The mechanism by which mutant HTT causes these defects remains unexplored. The pharmacological tools used do not always allow unequivocal conclusions regarding the targets affected. I think some more work is needed to generate a clear picture of what exactly happens presynaptically in YAC128 neurons, and to show how this might relate to HD.

Reviewer #1:

Deng et al. studied the mechanisms underlying the wide propofol effect-site concentration range associated with loss of responsiveness. Data was acquired from two centers (MRI, Canada; Auditory, Ireland). This is a well conducted study. The results could also explain why older patients (with presumably smaller gray matter volume) are more sensitive to propofol. My major concerns relate to precision in language.

1) The authors studied mechanisms underlying why patients lose consciousness at a wide range of propofol effect-site concentration. This behavioral phenomenon is known and well described (Iwakiri H, Nishihara N, Nagata O, Matsukawa T, Ozaki M, Sessler DI. Individual effect-site concentrations of propofol are similar at loss of consciousness and at awakening. Anesth Analg. 2005;100:107-10). I would suggest that the. authors position their paper as such. They did not study general anesthesia per se, and the allusions to awareness under anesthesia may not be relevant.

2) Per comment 1 above. Please reword the intro and discussion section i.e., " Anaesthesia has been used for over 150 years to reversibly abolish consciousness in clinical medicine, but its effect can vary substantially between individuals." What type of anesthesia are you referring to? Anesthetic vapors? Please provide a reference for this statement or make it propofol specific. Awareness under general anesthesia is related to numerous factors, many of which are iatrogenic as detailed in the NAP 5 study "The incidence of awareness rose from 1 out of 135,000 general anaesthetics to 1 out of 8,200 general anaesthetics when neuromuscular blockers were used" (https://pubmed.ncbi.nlm.nih.gov/25204697/). Further, it is unclear when dreaming occurs (during induction which is reasonable to expect/during emergence which is also reasonable to expect versus during the anesthesia). My suggestion is to qualify your statements by stating that this should be further studied in the context of possible genetic predisposition to awareness (Increased risk of intraoperative awareness in patients with a history of awareness. Anesthesiology 2013;119:1275-83).

3) The term "moderate anaesthesia" is confusing to me, and would be to most clinicians. Please cite the description of what comprises moderate anesthesia. My interpretation is that the study was about sedation. Did you mean moderate sedation? (https://www.asahq.org/standards-and-guidelines/continuum-of-depth-of-sedation-definition-of-general-anesthesia-and-levels-of-sedationanalgesia).

4) "the antagonistic relationship between the DMN and the DAN/ECN #and# was reduced during moderate anaesthesia, with a stronger and significant result in the narrative condition relative to the resting state." Anticorrelation?

5) The suggestion that fMRI can be used to improve the accuracy of awareness monitoring is, in my opinion, not necessary and a stretch.

Reviewer #1:

This article proposes that the assembly of the Sars-CoV-2 capsid is mediated by liquid-liquid phase separation of the N protein and RNA. The strength of the manuscript is a series of in vitro experiments showing that N protein can undergo liquid-liquid phase separation (LLPS) in a manner enhanced by RNA. The authors also identify nilotinib as a compound that alters the morphology of assemblies consisting of RNA and the N protein. The primary weakness of the manuscript is that there is little data connecting the in vitro observations to intracellular events, or viral assembly. Taken together, I find the experiments interesting but, as detailed below, premature.

Major comments:

1) A key issue with any in vitro assembly process such as LLPS is a demonstration that same process occurs in the cell. This is an issue since many molecules can undergo LLPS in vitro in a manner unrelated to their biological function. In this work, the authors show that the N protein can undergo LLPS in vitro in a manner a) stimulated by RNA, b) enhanced by the R2 domain, and c) changed in morphology by nilotinib.

Their argument that this LLPS is relevant to the viral life cycle rests on: a) the observation that over-expressed N protein forms foci in the cytosol, and b) the number of these foci (but not necessarily their morphology as seen in vitro) is somewhat reduced by nilotinib. In my opinion, this is not a very convincing argument for two main reasons.

First, it is unclear why the N protein is forming foci in cells. Specifically:

a) Is it being recruited to P-bodies, or some other existing subcellular assembly? (Which could be examined by staining with other markers).

b) Is it forming a new assembly with RNA as they have proposed? (Which could be addressed by staining for either specific or generic RNAs, or purifying these assemblies and determining if they contain RNA)

Second, it is unclear that the foci seen in cells are related to the LLPS they observe in vitro or relevant to the viral life cycle. Specifically:

c) Is the assembly related to the LLPS they have observed in vitro beyond a poorly understood alteration with nilotinib ? (Which could be addressed by examining if the deletions they observe affect LLPS in vitro also affect the formation of N protein foci in cells).

d) Is the nature of this assembly relevant to the viral life cycle? (Given the difficulty of working with COVID, this is hard. My suggestion here is at a minimum to discuss the issue, and ideally do an experiment with a related coronavirus to test their hypothesis). Frankly, the idea that coronavirus would trigger a LLPS of multiple viral RNAs would seem to be inhibitory to efficient packaging of individual virions. A discussion of how the virus would benefit from such a mechanism, as opposed to a cooperative coating of a viral genome initiated at a high affinity N protein binding site would be important to put the work in context.

2) The manuscript would be improved by examining the presence of RNA in each LLPS, and the ability of RNA to undergo self-assembly under the conditions examined in the absence of the N protein. As it stands, in some cases, the authors could be studying RNA based self-assembly, that then recruits the N protein to the RNA LLPS by RNA binding (see Van Treeck et al., 2018, PNAS for specific example of this phenomenon). This may be particularly likely for some of the longer viral RNAs that can form more stable base-pairs and thereby promote more "tangled" assemblies (e.g. Tauber et al., 2020, Cell).

3) I found the CLMS to not fit well in this manuscript for two reasons:

a) As I understood the methods, the CLMS experiment is looking at cross linking in high and low salt, with some LLPS occurring under low salt. However, since the cross linking was not limited to the dense phase of the low salt condition, a significant fraction (perhaps majority?) of the N proteins will not be in the dense phase. Because of this, the cross linking is essentially mapping interactions that change between high and low salt. If the authors really want to do this experiment, they should separate the phases and examine the crosslinks forming in the dense and dilute phases under the same salt conditions.

b) A second issue with this cross-linking experiment is that the regions that dominate the changes in cross linking are not ones that appear to be important in driving LLPS in vitro based on their deletion analysis. If the authors want to include this data, it should be related to the deletion experiments and connected to the work in a manner to make it meaningful.

4) The work would be improved by comparing how alterations that impact LLPS affect specific biochemical interactions of the relevant molecules. In these experiments, the authors are examining assemblies that form through N-N, N-RNA, RNA-RNA interactions. In each case, biochemical assays could be used to examine which of these interactions are altered by deletions or compounds. By understanding the underlying alterations in molecular interactions, a greater understanding of the mechanism of the observed LLPS, and its relevance to the viral life cycle could be revealed.

Reviewer #1:

This study is based on previous work that exposure to valproic acid (VPA), which is used to model autism spectrum disorders, produces excess local synaptic connectivity, increased seizure susceptibility, abnormal social behavior, and increased MMP-9 mRNA expression in Xenopus tadpoles. VPA is an interesting compound that is also used as an antimanic and mood stabilizing agent in the treatment of bipolar disorder, although the therapeutic targets of VPA for its treatment of mania or as a model of neurodevelopmental disorders have remained elusive. The authors validate that VPA exposed tadpoles have increased MMP9 mRNA expression and then test whether the increased levels of MMP9 mediate the effects of VPA in the tadpole model. The authors report that overexpression of MMP-9 increases spontaneous synaptic activity and network connectivity, whereas pharmacological and genetic inhibition with antisense oligos rescues the VPA induced effects, and then tie the findings to experience dependent synaptic reorganization.

1) What is the exact nature of "increased connectivity"? Is there an increase in synapse numbers or solely an increase in dendritic complexity coupled with a functional plasticity? The authors should document properties of mEPSCs and mIPSCs recording in TTX to isolate synaptic properties. Coupling this "mini" analysis to quantification of synapse numbers will address whether the changes are solely due to structural plasticity or also due to a functional potentiation of transmission. These experiments should at least be conducted in MMP-9 overexpression, VPA treatment and VPA treatment+MMP-9 loss-of-function cases to validate the basic premise that there is an increased connectivity.

2) It is unclear why the authors focused on MMP-9 compared to other genes dysregulated by VPA. This point should be further discussed.

3) How does VPA alter MMP-9 levels? Is this through an HDAC dependent mechanism? Granted VPA has been proposed to work through a variety of mechanisms including HDAC inhibition.

4) Does SB-3CT rescue the expression levels of MMP-9?

5) How is increased MMP-9 produces the synaptic and behavioral effects? What is the downstream target (specific receptor?) that would produce the broad changes in synaptic and behavioral phenotypes? Or is this a rather non-specific effect of extracellular matrix? Based on years of data on MMP-9 function its impact on "structural plasticity" in general terms is not surprising but further mechanistic details and specific targets would help move this field forward.

Reviewer #1:

This manuscript has novelty in it’s approach. The authors use an animal model to abolish the circadian rhythm in mice to study the impact on susceptibility to challenge with LPS. The experimental approach they use involves both wild-type mice subject to sudden stop of the light-dark (LD) cycle and mice knocked-out for the Clock system (KO). I have some points of concern:

• The investigators show that mice shift from LD to DD become more lethal to LPS. If this is due to abolishment of the circadian rhythm, similar lethality should appear with the challenge of the KO mice. The opposite was found. Please explain.

• LPS is acting through TLR4 binding. Can the author provide evidence that TLR4 expression is down-regulated in transition from LD to DD? Does the same apply for the expression of SOCS3?

• TLR4 is a receptor for alarmins with IL-1alpha being one of them. Can the authors comment, based on their IL-1alpha findings, if this may be part of the mechanism?

Reviewer #1:

This manuscript uses simultaneous fMRI-EEG to understand the haemodynamic correlates of electrophysiological markers of brain network dynamics. The approach is both interesting and innovative. Many different analyses are conducted, but the manuscript is in general quite hard to follow. There are grammatical errors throughout, sentences/paragraphs are long and dense, and they often use vague/imprecise language or rely on (often) undefined jargon. For example, sentences such as the following example are very difficult to decipher and are found throughout the manuscript: "if replicated, an association between high positive BOLD responsiveness and a DAN electrophysiological state, characterized by low amplitude (i.e., desynchronized) activity deviating from energetically optimal spontaneous patterns, would be consistent with prior evidence that the DMN and DAN represent alternate regimes of intrinsic brain function". As a result, the reader has to work very hard to follow what has been done and to understand the key messages of the paper.

Much is made of a potential power-law scaling of lifetime/interval times as being indicative of critical dynamics. A power-law distribution does not guarantee criticality, and could arise through other properties. Moreover, to accurately determine whether the proposed power-law is indicative of a scale-free system, the empirical property must be assessed over several orders of magnitude. It appears that only the 25-250 ms range was considered here.

The KS statistic is used to quantify the distance between the empirical and power-law distributions, which is then used as a marker of the degree of criticality. It is unclear that this metric is appropriate, given that transitions in and out of criticality can be highly non-linear. Moreover, the physiological significance of having some networks in a critical state while others are not is unclear. Each network is part of a broader system (i.e., the brain). How should one interpret apparent gradations of criticality in different parts of the system?

The sample size is small. I appreciate the complexity of the experimental paradigm, but the correlations do not appear to be robust. The scatterplots mask this to some extent by overlaying results from different brain regions, but close inspection suggests that the correlations in Fig 6 are driven by 2-3 observations with negative BOLD responses, the correlations in Fig 7A-B are driven by two subjects with positive WMSA volume, and Fig 7B is driven by 3 or so subjects with negative power-law fit values (indeed, x~0 in this plot is associated with a wide range of recall scores). Some correction for multiple comparisons is also required given the number of tests performed.

Figure 1 - panel labels would make it much easier to understand what is shown in this figure relative to the caption.

Figure 2- the aDMN does not look like the DMN at all. It is just the frontal lobe. Similarly, the putative DAN is not the DAN, but the lateral and medial parietal cortex, and cuneus.

P6, Line 11 - please define "simulation testing"

Reviewer #1:

Using two behavioral experiments, the authors partially replicate known effects that rotated faces decrease the benefit of visual speech on auditory speech processing.

As reported by the authors, Experiment 1 suffers from a design flaw considering that a temporal drift occurred in the course of the experiment. This clearly invalidates the reliability of the results and this experiment should be properly calibrated and redone. There is otherwise well-known literature on the topic.

Experiment 2 should be discussed in the context of divided attention tasks previously reported by researchers so as to better emphasize how and whether this is a novel observation.

Additionally:

-The question being addressed is narrowly and ill-construed: numerous authoritative statements in the introduction should reference existing work. For instance, seminal models of Bayesian perception (audiovisual speech processing especially) should be attributed to Dominic Massaro. Such statements as "studies fail to distinguish between binding and late integration" are surprising considering that the fields of multisensory integration and audiovisual speech processing have essentially and traditionally consisted in discussing these specific issues. To name a few researchers in the audiovisual speech domain: the work of Ruth Campbell, Ken Grant, and Jean-Luc Schwartz have largely contributed to refine debates on the implication of attentional resources to audiovisual speech processing using behavioral, neuropsychology, and neuroimaging methods. In light of the additional statements of the kind "The importance of temporal coherence for binding has not previously been established for speech", I would highly recommend the authors to do a thorough literature search of their topic (below some possible references as a start).

-What the authors understand to be "linguistic cues" should be better defined. For instance, the inverted face experiment aimed at dissociating whether visemic processing depends on face recognition (i.e. on holistic processing) or whether it depends on featural processing (and it does constitute a test, as suggested by the authors, of whether viseme recognition is a linguistic process per se).

Some references:

-Alsius, A., Möttönen, R., Sams, M. E., Soto-Faraco, S., & Tiippana, K. (2014). Effect of attentional load on audiovisual speech perception: evidence from ERPs. Frontiers in psychology, 5, 727.

-Chandrasekaran, C., Trubanova, A., Stillittano, S., Caplier, A., & Ghazanfar, A. A. (2009). The natural statistics of audiovisual speech. PLoS Comput Biol, 5(7), e1000436.

-Jordan, T. R., & Bevan, K. (1997). Seeing and hearing rotated faces: Influences of facial orientation on visual and audiovisual speech recognition. Journal of Experimental Psychology: Human Perception and Performance, 23(2), 388.

-Grant, K. W., & Seitz, P. F. (2000). The use of visible speech cues for improving auditory detection of spoken sentences. The Journal of the Acoustical Society of America, 108(3), 1197-1208.

-Grant, K. W., Van Wassenhove, V., & Poeppel, D. (2004). Detection of auditory (cross-spectral) and auditory-visual (cross-modal) synchrony. Speech Communication, 44(1-4), 43-53.

-Schwartz, J. L., Berthommier, F., & Savariaux, C. (2002). Audio-visual scene analysis: evidence for a" very-early" integration process in audio-visual speech perception. In Seventh International Conference on Spoken Language Processing.

-Schwartz, J. L., Berthommier, F., & Savariaux, C. (2004). Seeing to hear better: evidence for early audio-visual interactions in speech identification. Cognition, 93(2), B69-B78.

-Tiippana, Kaisa, T. S. Andersen, and Mikko Sams. (2004) "Visual attention modulates audiovisual speech perception." European Journal of Cognitive Psychology 16.3: 457-472.

-van Wassenhove, V. (2013). Speech through ears and eyes: interfacing the senses with the supramodal brain. Frontiers in psychology, 4, 388.

-Van Wassenhove, V., Grant, K. W., & Poeppel, D. (2007). Temporal window of integration in auditory-visual speech perception. Neuropsychologia, 45(3), 598-607.

Reviewer #1:

This work claims to show that learning of word associations during sleep can impair learning of similar material during wakefulness. The effect of sleep on learning depended on whether slow-wave sleep peaks were present during the presentation of that material during sleep. This is an interesting finding, but I have a lot of questions about the methods that temper my enthusiasm.

1) The proposed mechanism doesn't make sense to me: "synaptic down-scaling of hippocampal and neocortical language-related neurons, which were then too saturated for further potentiation required for the wake-relearning of the same vocabulary". Also lines 105-122. What is 'synaptic down-scaling'? what are 'language related neurons'? ' How were they 'saturated'? What is 'deficient synaptic renormalization'? How can the authors be sure that there are 'neurons that generated the sleep- and ensuing wake-learning of ... semantic associations'? How can inferences about neuronal mechanisms (ie mechanisms within neurons) be drawn from what is a behavioural study?

2) On line 54 the authors say "Here, we present additional data from a subset of participants of our previous study in whom we investigated how sleep-formed memories interact with wake-learning." It isn't clear what criteria were used to choose this 'subset of participants'. Were they chosen randomly? Why were only a subset chosen, anyway?

3) The authors do not appear to have checked whether their nappers had explicit memory of the word pairs that had been presented. Why was this not checked, and couldn't explicit memory explain the implicit memory traces described in lines 66-70 (guessing would be above chance if the participants actually remembered the associations).

Reviewer #1:

In the present manuscript, Evans and Burgess present a computational model of the entorhinal-hippocampal network that enables self-localization by learning the correspondence between stimulus position in the environment and internal metric system generated by path integration. Their model is composed of two separate modules, observation and transition, which inform about the relationship between environmental features and the internal metric system, and update the internal metric system between two consecutive positions, respectively. The observation module would correspond to projection from hippocampal place cells (PCs) to entorhinal grid cells (GCs), while the transition module would just update the GCs based on animal's movement. The authors suggest that the system can achieve fast and reliable learning by combining online learning (during exploration) and offline learning (when the animal stops or rests). While online learning only updates the observation model, offline learning could update both modules. The authors then test their model on several environmental manipulations. Finally, they discuss how offline learning could correspond to spontaneous replay in the entorhinal-hippocampal network. While the work will certainly be of great interest to the community, the authors should improve the presentation of their manuscript, and make sure they clearly define the key concepts of their study.

Online learning is clearly explained in the manuscript (e.g. l.101). Both environment structure (PC-PC connections) and the observation models (PC->GC synapses) are learned online, and this leads to stable grid cells. Then, the authors suggest that prediction error between the observation and transition models triggers offline inference that can update both models simultaneously. However, it is hard to figure out what offline learning is exactly. The section "Offline inference: The hippocampus as a probabilistic graph" is quite impossible to follow. Before explicitly defining offline learning the authors introduce a spring model of mutual connection between feature locations, but it is not clearly explained if this network is optimized online or offline.

The end of this section is particularly difficult to follow (line 180): "In this context, learning the PC-GC weights (modifying the observation model) during online localization corresponds to forming spatial priors over feature locations which anchor the structure, which would otherwise be translation or rotation invariant (since measurements are relative), learned during offline inference to constant locations on the grid-map.".

What really triggers offline inference is only explained much further in the manuscript, l. 366. Interestingly, this section refers to Fig. 1G for the first time, and should naturally be moved at the beginning of the manuscript (where Fig.1 is described)

Along the same lines, the role of offline learning should be made much more explicit in Fig. 2.

The frequent references to the method section too often break the flow of paper and make it difficult to follow. The authors should start their manuscript with a clear and simple definition of the core idea and concepts, almost in lay terms and only introducing a few annotations, using Fig. 1 (perhaps with some modification and focusing especially on panels A and F) as a visual support, and to move mathematical equations such as Eq. 3 to the supplementary information.

The authors have tested their model on various manipulations that have been previously carried out in freely moving animals, such as change in visual gain and in environmental geometry. These sections are interesting but, again, would be much clearer if presented after a clear explanation of online and offline learning procedures, not in between.

Finally, the authors discuss the relationship between offline inference and neuronal replay, as observed experimentally in vivo (Figs 6&7). This is interesting but would perhaps benefit from some graphical explanation. It is not immediately obvious to understand the fundamental difference between message passing (Fig. 6A) and simple synaptic propagation of activity among connected PC in CA3. Fig. 7 is actually a nice illustration of the phenomenon and should perhaps be presented before Fig. 6.

Reviewer #1:

The authors present a workflow based on targeted Nanopore DNA sequencing, in which they amplify and sequence nearly full-length 16S rRNA genes, to analyze surface water samples from the Cam river in Cambridge. They first identify a taxonomic classification tool, out of twelve studied, that performs best with their data. They detect a core microbiome and temporal gradients in their samples and analyze the presence of potential pathogens, obtaining species level resolution and sewage signals. The manuscript is well written and contains sufficient information for others to carry out a similar analysis with a strategy that the authors claim will be more accessible to users around the world, and particularly useful for freshwater surveillance and tracing of potential pathogens.

The work is sufficiently well-documented and timely in its use of nanopore sequencing to profile environmental microbial communities. However, given that the authors claim to provide a simple, fast and optimized workflow it would be good to mention how this workflow differs or provides faster and better analysis than previous work using amplicon sequencing with a MinION sequencer.

Many of the June samples failed to provide sufficient sequence information. Could the authors comment on why these samples failed? While some samples did indeed have low yields, this was not the case for all (supp table 2 and supp figure 5) and it could be interesting to know if they think additional water parameters or extraction conditions could have affected yields and subsequent sequencing depth.

One of the advantages of nanopore sequencing is that you can obtain species-level information. It would therefore be helpful if the authors could include information on how many of their sequenced 16S amplicons provided species-level identification.

While the overall analysis of microbial communities is well done, it is not entirely clear how the authors define their core microbiome. Are they reporting mainly the most abundant taxa (dominant core microbiome), and would this change if you look at a taxonomic rank below the family level? How does the core compare, for example, with other studies of this same river?

This is a page note. I can write overall comments about the pre-print here.

Tags can also be added below.

Reviewer #1:

This study takes two existing models of hippocampal theta rhythm generation, a reduced one with two populations of Izhikevich neurons, and a detailed one with numerous biophysically detailed neuronal models. The authors do some parameter variation on 3 parameters in the reduced model and ask which are sensitive control parameters. They then examine control of theta frequency through a phase response curve and propose an inhibition-based tuning mechanism. They then map between the reduced and detailed model, and find that connectivity but not synaptic weights are consistent. They take a subset of the detailed model and do a 2 parameter exploration of rhythm generation. They compare phenomenological outcomes of the model with results from an optogenetic experiment to support their interpretation of an inhibition-based tuning mechanism for intrinsic generation of theta rhythm in the hippocampus.

General comments:

1) The paper shows the existence of potential rhythm mechanisms, but the approach is illustrative rather than definitive. For example, in a very lengthy section on parameter exploration in the reduced model, the authors find some domains which do and don't exhibit rhythms. Lacking further exploration or analytic results, it is hard to see if their interpretations are conclusive.

2) The authors present too much detail on too few dimensions of parameters. An exhaustive parameter search would normally go systematically through all parameters, and be digested in an automated manner. For reporting this, a condensed summary would be presented. Here the authors look at 3 parameters for the reduced model and 2 parameters in the detailed one - far fewer than the available parameter set. They discuss the properties of these parameter choices at length, but then pick out a couple of illustrative points in the parameter domain for further pursuit. This leaves the reader rather overwhelmed on the one hand, and is not a convincing thorough exploration of all parameters of the system on the other.

3) I wonder if the 'minimal' model is minimal enough. Clearly it is well- supplied with free parameters. Is there a simpler mapping to rate models or even dynamical systems that might provide more complete insights, albeit at the risk of further abstraction?

4) Around line 560 and Fig 12 the authors conclude that only case a) is consistent with experiment. While it is important to match data to experiment, here the match is phenomenological. It misses the opportunity to do a quantitative match which could be done by taking advantage of the biological detail in the model.

5) The paper is far too long and is a difficult read. Many items of discussion are interspersed in the results, for example around line 335 among many others.

Reviewer #1:

Studies in mouse models and humans show synapse loss and dysfunction that precede neurodegeneration, raising questions about timing and mechanisms. Using longitudinal in vivo 2-photon imaging, Jackson et al., investigate pre- and post-synaptic changes in rTg4510 mice, a widely used mouse model of tauopathy. Consistent with cross sectional studies, the authors observed a reduction in density of presynaptic axons and dendritic spines in layer 1 cortex that relate to degeneration of neurites and dendrites over time. Taking advantage of an inducible model to overexpress tau p301L, they show that reducing expression of tau by DOX early in disease progression, resulted in amelioration of synapse loss, also consistent with other studies. Interestingly, the authors observed a significant reduction of dendritic spines less than a week before dendrite degeneration. In contrast, they observed plasticity and turnover of presynaptic structures weeks before axonal degeneration, suggesting different mechanisms.

Overall the results are interesting and largely consistent with previous findings. The new findings shown in Figures 5 and 6 address the timing of pre and postsynaptic loss and structural plasticity and reveal interesting differences; however, the data are highly variable and there are several issues that diminish enthusiasm as outlined below. Moreover, this study does not include new biological or mechanistic insight into the differences in pre- and post-synaptic changes from previous work in the field.

The main weakness relates to the significance and relevance beyond this specific mouse model and brain region. I appreciate the strengths but also technical challenges of in vivo longitudinal imaging, including a small field of view. Thus, the rationale and choice of model and brain region, and validation of key findings is critical to support conclusions. In this case, the tau model, although used by others, has several caveats relevant to the investigation of synapse loss (see point 2 below) that weaken this study and its impact.

1) Most of the work in the model related to synapse loss and dysfunction have been carried out in hippocampus and other regions of cortex in this model and tau and amyloid models. Here the authors focused on layer 1 of (somatosensory) cortex and followed neurites of pyramidal cells labeled with AAV:GFP, an approach that does not enable one image and track axons and dendrites from large numbers of neurons. They observed divergent dynamics in spine and presynaptic TBS of individual dendrites and axons. Given the small number of neurons sampled, significant noise in their imaging data, these findings need more validation using other approaches. This is particularly important for the data and conclusion drawn from Figures 5 and 6 (see point 3).

To estimate the overall effect of genotype the authors fitted Generalized Additive Mixed Models (GAMMS) to their data given the variability in the data within animals and genotype. It would be helpful to those less familiar to provide more comparisons of data using additional statistical tests and analyses along with power analyses calculations.

2) Major caveat with inducible Tau mode Tg4510. While this inducible model has the advantage of controlling timing of tau overexpression in neurons, a recent study by Gamache et al (PMID: 31685653) demonstrated that there are issues with the transgene insertion site and factors other than tau expression are actually what is driving the phenotype. Thus, differences in synaptic and behavioral phenotypes are based on the mouse line used and this needs to be carefully controlled. This was not addressed or discussed. See https://pubmed.ncbi.nlm.nih.gov/31171783/ and https://pubmed.ncbi.nlm.nih.gov/30659012/

3) The interesting new findings presented in Figures 5 and 6 that address timing and differences in axonal and dendritic/spine plasticity and loss need to be validated with more neurons and animals. The sample size is small ( i.e. n= 18 axons from 7 animals and not clear how many neurons. Given the significant variability of the data even within animals, these experiments and data are considered preliminary.

4) How does anesthesia influence these changes in structural plasticity observed? This was not addressed or discussed.

Reviewer #1:

Xu and colleagues compared the intersubject correlation (ISC) and intersubject functional connectivity (ISFC) of participants listening to narrative and argumentative texts while undergoing fMRI. Replicating earlier findings, they show that ISC in the DMN was greater when participants listened to an intact narrative than when they listened to a sentence-scrambled version of the same narrative. Listening to a sentence-scrambled argument elicited ISC in language and control regions of the brain, though interestingly, there was no region in the brain where ISC was greater when participants listened to an intact version of the argument. Instead, there was greater ISFC between the IPS and language areas of the brain when participants listened to the intact argument than when they listened to the scrambled argument. The authors interpret their results as suggesting that listening to the intact argument did not recruit additional brain systems, but instead promoted the cooperation between regions that were already involved in processing the argument.

Most prior work using "naturalistic stimuli" has examined the neural responses to narratives. This manuscript extends this work in an important way by examining how the brain responds to arguments, which comprise a non-trivial proportion of the linguistic content people are exposed to on a daily basis. The ISFC results (Fig. 7) are particularly noteworthy and novel. My main concerns have to do with the possibility that ISC for the scrambled argument seems to be stronger and more extensive than that for the intact argument, and how this might affect the authors' interpretation of their results. Below are some suggestions and comments which I think the paper could benefit from considering further:

1) I think it would be helpful to run the Scrambled Argument > Intact Argument ISC contrast. Visual inspection of Figure 2 suggests that ISC for the scrambled argument might be stronger than that for the intact argument, especially in control regions. If this is truly the case, I think the authors should discuss what this might imply about what is happening during the scrambled condition and if this affects thinking of the scrambled condition as a control for low-level linguistic features. In particular, the 2.97 out of 5 comprehensibility rating of the scrambled arguments suggests that participants might have understood the scrambled arguments. If participants are actively trying to make sense of the scrambled argument text, it seems like this could then drive observed differences in ISFC between the intact and scrambled arguments as well (e.g., decreased connectivity between control and language regions when trying to make sense of scrambled text, rather than increased connectivity between control and language regions when processing an intact argument).

2) More broadly, I think the authors need to make sure their effects aren't driven by the scrambled conditions. For example, for Figure 2 - figure supplement 2, the (Intact Narrative - Scrambled Narrative) > (Intact Argument - Scrambled Argument) contrast can be driven by high ISC in the Scrambled Argument condition, which would suggest a different interpretation of the results. My suggestion would be to run the contrast as (Intact Narrative - Scrambled Narrative) > max((Intact Argument - Scrambled Argument),0) to make sure that the contrast isn't driven by a negative value on the right hand side of the inequality.

3) Point 2 also applies to Figures 6 and 7. Relatedly, the rightmost panel of Figure 6C suggests that the analysis is indeed capturing some edges where the SES of the Scrambled Argument is greater than that of the Intact Argument.

4) How well do the vertexes identified in Figure 7D overlap with the Intact Argument > Resting map? Given the authors interpretation that the ISFC results suggest cooperation between areas involved in processing the intact stimulus, I think this should be properly assessed.

5) Both ISC and ISFC capture only signal that is shared across participants. Most narratives are crafted such that all listeners have a similar interpretation. This is unlike arguments, where different listeners might agree with an argument to a different extent. If listeners had differing interpretations of the argument, ISC/ISFC would miss brain activity/connectivity involved in processing an argument. I think this possibility should be considered and discussed, especially given the null DMN finding for the argumentative texts.

6) For the t-tests on the behavioral ratings , it looks like the authors collapsed over the two texts within a category. This doesn't seem right, given that the ratings for each text are dependent. A mixed model approach would be more appropriate. I doubt this will change the results, but I think it would be good to follow best practices when possible.

Reviewer #1:

Major issues:

I have two major comments on the work.

1) The authors motivate the work from the use of naturalistic speech, and the application of the developed method to investigate, for instance, speech-in-noise deficits. But they do not discuss how comprehensible the peaky speech in fact is. I would therefore like to see behavioural experiments that quantitatively compare speech-in-noise comprehension, for example SRTs, for the unaltered speech and the peaky speech. Without such a quantification, it is impossible to fully judge the usefulness of the reported method for further research and clinical applications.

2) The neural responses to unaltered speech and to peaky speech are analysed by two different methods. For unaltered speech, the authors use the half-wave rectified waveform as the regressor. For peaky speech, however, the regressor is a series of spikes that are located at the timings of the glottal pulses. Due to this rather different analysis, it is impossible to know to which degree the differences in the neural responses to the two types of speech that the authors report are due to the different speech types, or due to the different analysis techniques. The authors should therefore use the same analysis technique for both types of speech. It might be most sensible to analyse the unaltered speech through a regressor with spikes at the glottal pulses a well. In addition, it would be good to see a comparison, say of a SNR, when the peaky speech is analysed through the half-wave rectified waveform and through the series of spikes. This would also further motivate the usage of the regressor with the series of spikes.

Reviewer #1:

The authors studied the over-representation of imprinted genes in the mouse brain by using fifteen single-cell RNA sequencing datasets. The analysis was performed at three levels 1) whole-tissue level, 2) brain-region level, and 3) region-specific cell subpopulation level. Based on the over-representation and gene-enrichment analyses, they interpreted hypothalamic neuroendocrine populations and monoaminergic hindbrain neurons as specific hotspots of imprinted gene expression in the brain.

Objective:

Though the study is potentially interesting, the expression of imprinted genes in the brain and hypothalamus is already known (Davies W et al., 20005, Shing O et al. 2019, Gregg et al, 2010 including many other studies cited in the paper). However, the authors put forth two objectives, the first being whether imprinted gene expression is actually enriched in the brain compared to other adult tissues, where they did find brain as one of the tissues with over-represented imprinted genes. Secondly, whether the imprinted genes are enriched in specific brain regions. The study objectives cannot qualify as completely novel as it is the validation of most of what is already known using scRNA-seq datasets.

Methods and Results

Pros:

-15 scRNA-seq datasets were analysed independently and they were processed as in the original publication.

-Two enrichment methods used to find tissue-specific enrichment of imprinted genes and appropriate statistics applied wherever necessary.

Concerns:

-It is not clear how the over-representation using fisher's exact test was calculated? It would be appropriate to include the name of the software or R package, if used, in the basic workflow section of Materials and methods.

-Why did authors particularly use Liger in R for GSEA analysis?

-GSEA plots generated using Liger and represented for each analysis in the paper by itself does not look informative. For eg. in figure 4 and other GSEA plots in the paper- i) Which 'score' does the Y-axis represent? Include x-axis label and mention corrected GSEA q value either in the legend or the figure. ii) Was the normalized enrichment score (NES) calculated? What genes in the cluster represent maximum enrichment? A heat map of the imprinted genes contributing to the cell cluster will add more clarity to the GSEA plots.

-Apart from the tissue-specific enrichment of gene sets, a functional GO/pathways enrichment of the group of imprinted genes will strengthen the connection of these genes with feeding, parental behavior and sleep.

-Are these imprinted genes coexpressed across the analyzed brain structures, as the authors repeatedly stress on the functioning of imprinted genes as a group?

-A basic workflow schematic might be necessary for an easy and quick understanding of the methods.

Overall, the study gives some insight into the brain regions, particularly cell clusters in the brain where imprinted genes could be enriched. However, the nature of the study is preliminary and validates most of previous studies. The authors have already highlighted some of the limitations of the study in the discussion.

Reviewer #1:

The manuscript “A computationally designed fluorescent biosensor for D-serine" by Vongsouthi et al. reports the engineering of a fluorescent biosensor for D-serine using the D-alanine-specific solute-binding protein from Salmonella enterica (DalS) as a template. The authors engineer a DalS construct that has the enhanced cyan fluorescent protein (ECFP) and the Venus fluorescent protein (Venus) as terminal fusions, which serve as donor and acceptor fluorophores in resonance energy transfer (FRET) experiments. The reporters should monitor a conformational change induced by solute binding through a change of the FRET signal. The authors combine homology-guided rational protein engineering, in-silico ligand docking and computationally guided, stabilizing mutagenesis to transform DalS into a D-serine-specific biosensor applying iterative mutagenesis experiments. Functionality and solute affinity of modified DalS is probed using FRET assays. Vongsouthi et al. assess the applicability of the finally generated D-serine selective biosensor (D-SerFS) in-situ and in-vivo using fluorescence microscopy.

Ionotropic glutamate receptors are ligand-gated ion channels that are importantly involved in brain development, learning, memory and disease. D-serine is a co-agonist of ionotropic glutamate receptors of the NMDA subtype. The modulation of NMDA signalling in the central nervous system through D-serine is hardly understood. Optical biosensors that can detect D-serine are lacking and the development of such sensors, as proposed in the present study, is an important target in biomedical research.

The manuscript is well written and the data are clearly presented and discussed. The authors appear to have succeeded in the development of D-serine-selective fluorescent biosensor. But some questions arose concerning experimental design. Moreover, not all conclusions are fully supported by the data presented. I have the following comments.

1) In the homology-guided design two residues in the binding site were mutated to the ones of the D-serine specific homologue NR1 (i.e. F117L and A147S), which lead to a significant increase of affinity to D-serine, as desired. The third residue, however, was mutated to glutamine (Y148Q) instead of the homologous valine (V), which resulted in a substantial loss of affinity to D-serine (Table 1). This "bad" mutation was carried through in consecutive optimization steps. Did the authors also try the homologous Y148V mutation? On page 5 the authors argue that Q instead of V would increase the size of the side chain pocket. But the opposite is true: the side chain of Q is more bulky than the one of V, which may explain the dramatic loss of affinity to D-serine. Mutation Y148V may be beneficial.

2) Stabilities of constructs were estimated from melting temperatures (Tm) measured using thermal denaturation probed using the FRET signal of ECFP/Venus fusions. I am not sure if this methodology is appropriate to determine thermal stabilities of DalS and mutants thereof. Thermal unfolding of the fluorescence labels ECFP and Venus and their intrinsic, supposedly strongly temperature-dependent fluorescence emission intensities will interfere. A deconvolution of signals will be difficult. It would be helpful to see raw data from these measurements. All stabilities are reported in terms of deltaTm. What is the absolute Tm of the reference protein DalS? How does the thermal stability of DalS compare to thermal stabilities of ECFP and Venus? A more reliable probe for thermal stability would be the far-UV circular dichroism (CD) spectroscopic signal of DalS without fusions. DalS is a largely helical domain and will show a strong CD signal.

3) The final construct D-SerFS has a dynamic range of only 7%, which is a low value. It seems that the FRET signal change caused by ligand binding to the construct is weak. Is it sufficient to reliably measure D-serine levels in-situ and in-vivo? In Figure 5H in-vivo signal changes show large errors and the signal of the positive sample is hardly above error compared to the signal of the control. Figure 5G is unclear. What does the fluorescence image show? Work presented in this manuscript that assesses functionality and applicability of the developed sensor in-situ and in-vivo is limited compared to the work showing its design. For example, control experiments showing FRET signal changes of the wild-type ECFP-DalS-Venus construct in comparison to the designed D-SerFS would be helpful to assess the outcome.

4) The FRET spectra shown in Supplementary Figure 2, which exemplify the measurement of fluorescence ratios of ECFP/Venus, are confusing. I cannot see a significant change of FRET upon application of ligand. The ratios of the peak fluorescence intensities of ECFP and Venus (scanned from the data shown in Supplementary Figure 2) are the same for apo states and the ligand-saturated states. Instead what happens is that fluorescence emission intensities of both the donor and the acceptor bands are reduced upon application of ligand.

much more positive/optimistic outlook than hobbes

If women corrupted the corruption will grow in society, because women shape the half of society, beside they playing an important role in families. so it shows that when a women corrupted then his son can also follow his path.

what does Krishna meant by three world? is it the three world that they believe to the life after death?

Arjuna stated that there are all my kinsman such as: teachers, fathers, sons i do not want to go the battle and kill them. is Krishna meant only his kinsman the reason to not fight or he was not able to do it?

Krishna state that if i want kingship, it is not because of victory or pleasure. then what Krishna meant by delight and life itself in the statement?

Arjuna stated in this part to Krishna about his weakness that he is able to fight, he do not have power to fight in the battle.

This helps to address the institutional type question

Dominance through Elites. This is a grievous danger. We've seen a constant perversion of Genesis 1:27-28 (fruitful, multiply, dominate earth) by those who see this charge as an exclusive office rather than a "law" to be governed through 3rd density complexes! Dominion was designed to be a service to 2nd density and the way toward 4th Density for those in 3rd: NOT SERVICE TO SELF!

DOI: 10.1111/bph.15156

Resource: ZFIN_ZDB-GENO-170316-1

Curator: @Naa003

SciCrunch record: RRID:ZFIN_ZDB-GENO-170316-1

What is this?

DOI: 10.1111/bph.15156

Resource: ZFIN_ZDB-GENO-130722-1

Curator: @Naa003

SciCrunch record: RRID:ZFIN_ZDB-GENO-130722-1

What is this?

DOI: 10.1111/bph.15156

Resource: ZFIN_ZDB-ALT-171010-1

Curator: @Naa003

SciCrunch record: RRID:ZFIN_ZDB-ALT-171010-1

What is this?

DOI: 10.1111/bph.15156

Resource: ZFIN_ZDB-ALT-130409-1

Curator: @Naa003

SciCrunch record: RRID:ZFIN_ZDB-ALT-130409-1

What is this?

DOI: 10.1016/j.celrep.2020.108054

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

Curator: @Naa003

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

Curator comments: allele name: c264Tg Danio rerio ZFIN Cat# ZDB-ALT-070316-1

What is this?

DOI: 10.1016/j.celrep.2020.108054

Resource: ZFIN_ZDB-ALT-141023-1

Curator: @Naa003

SciCrunch record: RRID:ZFIN_ZDB-ALT-141023-1

What is this?

DOI: 10.7554/eLife.52160

Resource: (IMSR Cat# KOMP_VG12793-1-Vlcg,RRID:IMSR_KOMP:VG12793-1-Vlcg)

Curator: @evieth

SciCrunch record: RRID:IMSR_KOMP:VG12793-1-Vlcg

What is this?

DOI: 10.1016/j.celrep.2020.03.024

Resource: (ZFIN Cat# ZDB-ALT-110310-1,RRID:ZFIN_ZDB-ALT-110310-1)

Curator: @ethanbadger

SciCrunch record: RRID:ZFIN_ZDB-ALT-110310-1

What is this?

DOI: 10.1016/j.celrep.2020.03.024

Resource: (ZFIN Cat# ZDB-ALT-110308-1,RRID:ZFIN_ZDB-ALT-110308-1)

Curator: @ethanbadger

SciCrunch record: RRID:ZFIN_ZDB-ALT-110308-1

What is this?

DOI: 10.1016/j.celrep.2020.03.024

Resource: (ZFIN Cat# ZDB-ALT-110308-1,RRID:ZFIN_ZDB-ALT-110308-1)

Curator: @ethanbadger

SciCrunch record: RRID:ZFIN_ZDB-ALT-110308-1

What is this?

DOI: 10.1016/j.celrep.2020.03.024

Resource: ZDB-ALT-180625-1

Curator: @ethanbadger

SciCrunch record: RRID:ZDB-ALT-180625-1

What is this?

DOI: 10.7554/eLife.55913

Resource: (ZFIN Cat# ZDB-GENO-060919-1,RRID:ZFIN_ZDB-GENO-060919-1)

Curator: @Naa003

SciCrunch record: RRID:ZFIN_ZDB-GENO-060919-1

What is this?

(Gilgamesh) lets (no) girl go free to (her bridegroom) What the author meant by this sentence?

(he was the vanguard) Gilgamesh was brave.

DOI: 10.1016/j.cels.2020.02.007

Resource: (ZFIN Cat# ZDB-ALT-100402-1,RRID:ZFIN_ZDB-ALT-100402-1)

Curator: @ethanbadger

SciCrunch record: RRID:ZFIN_ZDB-ALT-100402-1

What is this?

variant id lookup result: http://localhost:8001/test.html

Monarch lookup result: http://localhost:8001/test.html

DOI: 10.7554/eLife.47699

Resource: (ZFIN Cat# ZDB-ALT-100721-1,RRID:ZFIN_ZDB-ALT-100721-1)

Curator: @evieth

SciCrunch record: RRID:ZFIN_ZDB-ALT-100721-1

What is this?

DOI: 10.2337/db19-0508

Resource: (IMSR Cat# KOMP_VG15351-1-Vlcg,RRID:IMSR_KOMP:VG15351-1-Vlcg)

Curator: @Naa003

SciCrunch record: RRID:IMSR_KOMP:VG15351-1-Vlcg

What is this?

DOI: 10.7554/eLife.48914

Resource: (ZFIN Cat# ZDB-ALT-130514-1,RRID:ZFIN_ZDB-ALT-130514-1)

Curator: @evieth

SciCrunch record: RRID:ZFIN_ZDB-ALT-130514-1

What is this?

DOI: 10.7554/eLife.48914

Resource: (ZFIN Cat# ZDB-ALT-141008-1,RRID:ZFIN_ZDB-ALT-141008-1)

Curator: @evieth

SciCrunch record: RRID:ZFIN_ZDB-ALT-141008-1

What is this?

DOI: 10.7554/eLife.54935

Resource: (ZFIN Cat# ZDB-ALT-120412-1,RRID:ZFIN_ZDB-ALT-120412-1)

Curator: @evieth

SciCrunch record: RRID:ZFIN_ZDB-ALT-120412-1

What is this?

DOI: 10.1016/j.devcel.2020.03.017

Resource: (ZFIN Cat# ZDB-ALT-110705-1,RRID:ZFIN_ZDB-ALT-110705-1)

Curator: @ethanbadger

SciCrunch record: RRID:ZFIN_ZDB-ALT-110705-1

What is this?

DOI: 10.1016/j.devcel.2020.03.017

Resource: (ZFIN Cat# ZDB-ALT-150904-1,RRID:ZFIN_ZDB-ALT-150904-1)

Curator: @ethanbadger

SciCrunch record: RRID:ZFIN_ZDB-ALT-150904-1

What is this?

DOI: 10.1016/j.devcel.2020.03.017

Resource: (ZFIN Cat# ZDB-ALT-110421-1,RRID:ZFIN_ZDB-ALT-110421-1)

Curator: @ethanbadger

SciCrunch record: RRID:ZFIN_ZDB-ALT-110421-1

What is this?

DOI: 10.7554/eLife.54937

Resource: (ZFIN Cat# ZDB-ALT-080625-1,RRID:ZFIN_ZDB-ALT-080625-1)

Curator: @evieth

SciCrunch record: RRID:ZFIN_ZDB-ALT-080625-1

What is this?

DOI: 10.7554/eLife.54937

Resource: (ZFIN Cat# ZDB-ALT-080528-1,RRID:ZFIN_ZDB-ALT-080528-1)

Curator: @evieth

SciCrunch record: RRID:ZFIN_ZDB-ALT-080528-1

What is this?

DOI: 10.7554/eLife.54937

Resource: (ZFIN Cat# ZDB-ALT-080528-1,RRID:ZFIN_ZDB-ALT-080528-1)

Curator: @evieth

SciCrunch record: RRID:ZFIN_ZDB-ALT-080528-1

What is this?

DOI: 10.7554/eLife.54937

Resource: (ZFIN Cat# ZDB-ALT-160120-1,RRID:ZFIN_ZDB-ALT-160120-1)

Curator: @evieth

SciCrunch record: RRID:ZFIN_ZDB-ALT-160120-1

What is this?

DOI: 10.1016/j.cub.2020.04.020

Resource: (ZFIN Cat# ZDB-ALT-130506-1,RRID:ZFIN_ZDB-ALT-130506-1)

Curator: @ethanbadger

SciCrunch record: RRID:ZFIN_ZDB-ALT-130506-1

What is this?

DOI: 10.1016/j.cub.2020.04.020

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

Curator: @ethanbadger

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

What is this?

DOI: 10.7554/eLife.53995

Resource: (ZFIN Cat# ZDB-ALT-181113-1,RRID:ZFIN_ZDB-ALT-181113-1)

Curator: @evieth

SciCrunch record: RRID:ZFIN_ZDB-ALT-181113-1

Curator comments: ZFIN Cat# ZDB-ALT-181113-1

What is this?

DOI: 10.1016/j.celrep.2020.107790

Resource: (ZFIN Cat# ZDB-ALT-121009-1,RRID:ZFIN_ZDB-ALT-121009-1)

Curator: @ethanbadger

SciCrunch record: RRID:ZFIN_ZDB-ALT-121009-1

Curator comments: Zebrafish: Tg(hcrt:nfsB-EGFP)

What is this?

This poem is a sonnet with 3 quatrains (lines of 4) and a couplet (set of lines), so in order to help your comprehension, you want to divide the stanzas by the structure.

Themes in poetry show up in the last lines or last stanza. A theme is a universal statement about what the author believes.

If we consider that poems are either a MEMORY or an EMOTION we can use word choice to figure out the theme. This poem is about emotion, particularly about not giving in to an enemy.

So universal theme would be...

symbolism - McKay calls his enemies "monsters", but he doesn't seem to be fighting fictional beasts in the poem, so not literal monsters.

Poetry 101:

Step 1 - Read this poem. Consider this just your first run through. Take notice of punctation (periods, comma, etc.). That's where you stop when reading a poem.

Step 2 - Read the poem again - But now you want to think in Costa's Level 2. So, notice rhetorical devices and what they are doing in the text. Divide your stanzas so you can chunk information and analyze in pieces.

Step 3 - Find the theme. Theme is a universal statement that tells us how the author feels about a topic. This is not a subject - like the beach - but what does the beach, or the setting, mean to the author. Themes are found in the last lines or the last stanza of a poem.

The world continues to change, warp, consume, ebb, and flow around us - good and bad directions.

So if we write a universal theme...

It's easy to ignore the word "but"; however, this is a conjunction that tells you the author is about to flip everything they've been saying.

It's a tiny word with a major impact. So this is a good place to make a division in a poem. To see what was being established, and how the author now wants to change it.

DOI: 10.1016/j.cub.2020.05.016

Resource: (ZFIN Cat# ZDB-ALT-150717-1,RRID:ZFIN_ZDB-ALT-150717-1)

Curator: @ethanbadger

SciCrunch record: RRID:ZFIN_ZDB-ALT-150717-1

What is this?

We mus examine life to be able to choose. We are born taught things that sometimes we don't understand but we just know because it was passed down to us, but it is up to us to experience these things t be able to decide for ourselves.

definition

• Point = That of which there is no part.
• Line = a length without breadth.

Ahuja, A. (2020, June 16). The two-metre rule and other imperfect Covid-19 risk calculations | Free to read. https://www.ft.com/content/30adbfa1-178f-47e2-97a8-bd41ca590999

the reason why the author wrote this article

Avis personnel de l'auteur et vision assez limitée du champ des possibles qu'offre une (des) rencontre(s) qu'elle soit virtuelle ou non.

L'auteur ne va t-il pas un peu vite dans sa déduction , le communautarisme comme il est évoqué ici appartient à un autre débat

Perception personnelle et réductrice de l'auteur qui ne représente pas la réalité. Les utilisateurs doivent-ils justifier d'une attente particulière pour motiver leur inscription ?

L'auteur se confère des qualités d'expert en évoquant une série d'hypothétiques troubles névrotiques liés à l'utilisation des sites de rencontres. Il vulgarise et banalise des pathologies sérieuses.

L'usage pathologique d'internet est réel, mais l'auteur invoque ici un problème de taille sans s'appuyer sur une source solide illustratrant la réalité des risques encourus par les utilisateurs des sites de rencontres.

Voici le premier argument. En effet, il nous est dit que ce phénomène de dispersion atteint son paroxysme avec les femmes actives qui doivent gérer vie professionnelle et vie de famille, mais il serait bon d'approfondir d'avantage. Nous pouvons nous demander pourquoi cela se produit chez les femmes actives. Nous pouvons donc réfléchir si cela n'est pas dû à ce qu'on appelle la charge mentale, puisque ce sont majoritairement les femmes qui s'occupent du foyer et des enfants. A l'inverse, nous pouvons nous demander si la dispersion n'atteint pas son paroxysme parce qu'elles sont d'avantage multitâches que les hommes. En effet, elles sont capables de faire plusieurs tâches simultanément, et cela peut aussi engendrer une dose supplémentaire de travail. Ce phénomène de multitâche peut donc entraîner d'avantage de dispersion de leur part.

I would hazard that US is far above optimal state size for wellbeing and wisdom.

But why does it rain money on them? And who else does that?

This is the scope of Test 2.

Figaro est sarcastique sur la censure

Il y a du mouvement. Il s'assoit et se lève

Il est dégoûté de lui-même et veut avoir une carrière honnête

Il parle de malhonnêteté et de ses avantages

Il parlait de ses différentes professions.

Et ainsi commence le plaidoyer de l'auteur et de son point de vue rhétorique, mettant bien en avant la puissance du numerique sur le biologique dans l'idée collective

optimal questions

YES I THOUGHT THE EXACT SAME FUCKING THING

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000218

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0002591

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0011968

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000189

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000463

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0003196

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000457

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0005280

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000369

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000358

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000316

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0002553

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000574

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0012368

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0011220

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000268

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0002167

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0001263

variant id lookup result: https://www.ncbi.nlm.nih.gov/clinvar/variation/72912/

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0002591

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000463

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0003196

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000369

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000316

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000574

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0012368

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000268

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0002167

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0011344

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0003391

allele id lookup result: https://reg.clinicalgenome.org/redmine/projects/registry/genboree_registry/by_caid?caid=CA414193321

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0001166

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0012385

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0001388

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0001533

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000768

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000767

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0002650

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000098

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0001631

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000400

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000194

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000322

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000276

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0001290

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0001249

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0001263

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0004942

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0001643

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0001629

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0001631

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0001653

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000718

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0007018

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0012743

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000028

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0001762

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0001166

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0002650

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000767

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000768

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000322

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000400

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0011800

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000194

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000276

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0001290

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0000098

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0001249

Monarch lookup result: https://monarchinitiative.org/phenotype/HP:0001263

DOI: 10.7554/eLife.46275

Resource: (ZFIN Cat# ZDB-GENO-090127-1,RRID:ZFIN_ZDB-GENO-090127-1)

Curator: @evieth

SciCrunch record: RRID:ZFIN_ZDB-GENO-090127-1

What is this?

DOI: 10.7554/eLife.46275

Resource: (ZFIN Cat# ZDB-GENO-071218-1,RRID:ZFIN_ZDB-GENO-071218-1)

Curator: @evieth

SciCrunch record: RRID:ZFIN_ZDB-GENO-071218-1

What is this?

DOI: 10.7554/eLife.42455

Resource: (ZFIN Cat# ZDB-ALT-090917-1,RRID:ZFIN_ZDB-ALT-090917-1)

Curator: @evieth

SciCrunch record: RRID:ZFIN_ZDB-ALT-090917-1

What is this?

DOI: 10.1111/bph.14614

Resource: (IMSR Cat# KOMP_VG14098-1-Vlcg,RRID:IMSR_KOMP:VG14098-1-Vlcg)

Curator: @ethanbadger

SciCrunch record: RRID:IMSR_KOMP:VG14098-1-Vlcg

What is this?