It's going to send a lot of them bankrupt, without a second thought.

While I appreciated the mention of this blurb and other blurbs like it in framing the sources used with their original context for a degree of important consideration and nuance, I feel like this section detailing all this history and data could have been more clear on where this data was coming from specifically. While of course the information overall is a synthesis of colonial and modern study along with the direct words and teachings of indigenous peoples, I think it would have benefitted from making clear what data came from what particular source. It could have perhaps laid out what stemmed from actual indigenous sources and what is being inferred based on a possible outsider perspective, even a step further in laying out the initial colonial assumptions and the subsequent data from indigenous sources that served to refine or correct it. This is a small gripe on my part but I think the article could have done with some further degree of specificity in presenting this historical and cultural data overall.

Written by Aidan Pare

The core argument

The essay argues that polling has become less reliable at the same time that it has become more powerful, and that this combination distorts democratic politics.

Polls:

increasingly fail to accurately measure public opinion

yet increasingly determine who gets attention, legitimacy, money, debate access, and media coverage

How Trump fits in

The piece opens with Donald Trump claiming he has no pollster and doesn’t tailor his message to polls. Lepore calls this disingenuous:

Trump may not have had a traditional campaign pollster

but his rise depended heavily on polls for visibility and validation

polls got him into debates, dictated stage placement, and fueled media coverage

So Trump is described as “a creature of the Sea of Polls,” not above it

Why modern polls are broken

The article explains in detail why polling has deteriorated:

1. People don’t answer anymore

Response rates used to be 60–90%

Now they’re often in the single digits

Most Americans refuse poll calls, creating non-response bias

1. Technology & law made it worse

Fewer landlines

Cell-phone autodialing is illegal

Internet polls are self-selected and skew younger and more liberal

Mixed-method polling still doesn’t work well

1. Samples are tiny and fragile

National election polls often rely on ~1,000–2,000 people

Statistical “weighting” tries to fix bias, but the lower the response rate, the shakier the results

Why polls now matter more than ever

Despite being unreliable, polls are used to:

decide who qualifies for debates

determine media attention

shape fundraising and momentum

create “winners” and “losers” long before anyone votes

Fox News using polls to select debate participants is presented as a major example of polling replacing democratic processes.

Historical background

The essay gives a history of polling:

Early “straw polls” by newspapers

The rise of George Gallup in the 1930s

Polling claimed to represent “the will of the people” scientifically

But:

Early polls systematically excluded Black Americans, the poor, and the disenfranchised

Polling mirrored and amplified existing inequalities

What was presented as “public opinion” was often the opinion of a privileged subset

Deeper philosophical critique

Lepore raises a fundamental question:

What if measuring public opinion isn’t good for democracy at all?

Key ideas:

Polls treat public opinion as the sum of individual answers, ignoring how opinions are formed socially

Polls can create opinion rather than measure it

Constant polling shifts politics from deliberation and leadership to reacting to numbers

Bottom line

The piece isn’t just saying “polls are inaccurate.”

It’s saying:

Polls shape reality instead of describing it

They weaken representative democracy

They reward spectacle, momentum, and media attention over governance

And they increasingly substitute statistical artifacts for actual voting

This makes me think about how AI is going to effect this barrier. It seems like it is on the edge of super user friendly but also extremely computationally expensive. But as technology progresses it might not matter. I would guess that 'coding' languages are only going to become closer and closer to pure english.

Romeo is filled with hope and longing. He’s clinging to the "shadow" of love because he’s physically separated from Juliet.

I read another article from Britanica on deontology and Kant and it noted that 'Kant’s critics questioned his view that all duties can be derived from a purely formal principle and argued that, in his preoccupation with rational consistency, he neglected the concrete content of moral obligation'. The essential idea was that duties were multifaceted and that meant that judgment must be executed before taking action on any such duty. It is interesting how this form of thinking ended up being heavily critiqued and eventually rejected bby the majority for a deontological way of thinking in the 20th century.

R0:

EDITOR:

The reviewers agree that your manuscript addresses an important topic. They have also raised a number of well-justified concerns and points requiring clarification. I hope that you see these as opportunities to further improve your manuscript such that it may be accepted for publication.

Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The author wrote this manuscript quite well. However, there are some suggestions for improving it better including,

Abstract: The abstract is written well. However, the results showed about self-stigma representing at 49% so this result should be suggested in conclusion as well.

Introduction: The introduction is organised and written well. However, there are some suggestions about referencing that should be revised along with Vancouver style and the journal format, such as (6)(7)(8), should be (6-8) or (Mbuthia et al., 2020) should be a number of reference. Another point, the abbreviation of drug-resistant TB (DR-TB) should be the same with DRTB in table 2 (page 10). Moreover, in terms of objective of the study, it should be written clearly. The author stated in line 98-100 (page 3), but it seems like expected outcomes rather than its objectives.

Methodology: Ethics statement: It is a clear statement, however, the date of approval should be presented as well to ensure the data were collected after approval.

Study population: The author stated that the target population comprised people with TB who were on treatment and were 15 years and above. However, the results showed that there were some participants aged under 15 years (0-14) as well. Thus, the author should revise and make it correct.

Sampling procedures: The author stated that the data were collected in 12 regions, however there were only 11 regions stated in line 139-140.

Sample size: The author showed some details of sample size calculation that met 421 persons (line 147). However, there were only 367 participants recruited to this study which is less than the appropriate sample size calculated. So, the author needs to explain more details about the sample size. It should be 421 as the result of calculation with the appropriate formula. Moreover, if there are sources of the number used to calculate, the reference needed to be stated as well.

Eligibility criteria: In terms of inclusion and exclusion criteria, the author stated that all people with TB aged 15 years and older would be recruited to the research and all people who were below the age of 15 years were excluded. This is the main point that needs to be clarified because in the results, there are some participants aged 0-14 years as stated before. Moreover, in terms of ethics, participants aged less than 18 years cannot sign the consent form by themselves, their parents should sign the consent form. So, the author needs to revise and clarify further.

Data collection tools and procedures: There is no information about the questionnaire well. The questionnaire should be clarified the details, especially the items used to categorise into "no stigma and stigma (binary). If you use only one item, it should not be appropriate to categorise. This is an important point of this study that needs to be explained. As well as, if the questionnaire was conducted by previous researchers, it should be cited correctly. Moreover, the author stated in this part that stigma was assessed using a set of standardised questions rated on a five-point Likert scale (0 = Strongly disagree to 4 = Strongly agree), while, in page 6, the author used (1 = Strongly agree to 5 = Strongly disagree) as well as the data were categorised in to 5 groups staring from 1.00 - 5.00. Please check the details again.

Data analysis: The Cronbach's alpha value needs to be presented with the exact value instead of >=0.70 that it will present the reliability of tools better. Moreover, the author stated in line 181 and table 2 "TB type" but in the conclusion, the author used "treatment type". So, this point needs to be the same. For the binary classification, the author needs to explain more details about how to categorise into 2 groups: no stigma and stigma. In terms of inferential statistics, the binary logistic regression and multiple logistic regression were not used and shown in the results. So, the author needs to revise about this point again.

Results: The sum of percentage, the details in Table 1 & 2 showed the percentage of each variable, which is good. However, the author needs to check the sum of each variable should be 100%. The author may use two decimal points for presenting the percentage. Moreover, some sub-variables which there is no data (0) does not need to present in the table. Please find the details in the attached file.

In table 2, inferential statistics, the author stated in data analysis that binary logistic regression and multiple logistic regression would be used to analyse to identify the predictors. However, in the results, there is no any results based on these statistics. So, the author needs to revise about the statistics stated in data analysis. Moreover, about chi-square, the author needs to check the assumption of chi-square because No cell should have an expected frequency < 1, and at least 80% of cells should have expected frequencies of 5 or more. So, if it does not meet the assumption, its results might be wrong.

Aged 0-14, the author stated in the methodology that the participants need to be 15 years or over. So, please check the data again.

Some words should be changed for example in line 213 from prevented to obstructed. Moreover, about abbreviation "DSTB and DRTB", for DSTB, the author did not state before so it needs to be mentioned in previous part first before using in this part. As well as, DRTB, the author used DR-TB in line 79 so it needs to be the same, with or without -.

Discussion: The author wrote this part quite well, however, the author needs to check about the number of percentage presented in this part again. Moreover, citation should be revise and rewrite following the format.

References: In terms of references, the author should check the format of Vancouver style referencing in both in-cited and references part again. As well as, the author needs to check the format along with the journal format. For example, (xx) to [xx]. Please revise and rewrite following the formats.

Reviewer #2: Please see my report. I think the manuscript transition from a dissertation to a paper is incomplete. Please review my report for details. I raise concerns regarding the sampling, statistical analysis and the conclusions made regarding the results.

Reviewer #3: This cross-sectional study tackles an important global health problem, TB-related stigma among people with TB. This study has significant merits including 367 people living with tuberculosis sampled over one year; and captures various contexts, specifically 180 health facilities across 11counties aiming for a nationally representative survey of TB-related stigma in Kenya. Two hundred and twenty-eight patients provided information regarding TB-related stigma, of whom 24 reported experiencing TB-related stigma.

Several areas remain unclear to me and require further clarification, elaboration or consideration for reformatting.

1. The referencing style used is inconsistent. e.g. introduction section lines 60-61(Mbuthia et al. 2020), whereas other areas have a different style that is numbered. Consider reformatting for consistency.

2. Previous research on TB-related stigma measurement and its implications to TB related outcomes in the Kenyan context has not been highlighted.

3. Ethics statement section could be aligned for consistent formatting with other text sections of the manuscript.

4. The sample size calculation could be further clarified for the readers to judge its robustness. a. Is there a proportion of TB-related stigma assumed from a previous study? b. What is the rationale of a 90% response rate? – Lines 147 to 150. c. What was the actual response rate?

5. From the manuscript, the sample size calculated was 421 TB patients, but only 367 are reported and 228 TB patients provide information related to TB stigma. These patients were sampled over one year from 180 health facilities across 11 counties in Kenya. a. Further clarification on the sampling frame is needed. b. How many patients were sampled per health facility? Was there any gender consideration per health facility? c. How were the 12 regions chosen and how do they relate to the current national or programmatic divisions? d. It is indicated that one county was chosen from the 12 regions but only 11 counties included.

6. Elaborating on the tool and procedures used is needed for the readers to judge the robustness of the methodology used. This information is crucial in the methods section. Lines 164-165: “Stigma was assessed using a set of standardized questions rated on a five-point Likert scale (0 = Strongly Disagree to 4 = Strongly Agree).”

(i) What is the set of standardized questions? (ii) What tool was used? (iii) Has this tool been previously used in the literature? (iv) Has the tool been previously used in the Kenyan context? (v) Is this a validated tool? (vi) In what language/s were the questions asked? (vii) Who administered the survey? Provide relevant references.

These details are missing in the methods section; and need to be considered for inclusion in the main text and/or supplementary material based on journal guidelines.

1. What do the authors think could be the implications of handling neutral scores as missing? Lines 189-190: ‘Responses with a "Neutral" score were treated as missing in the binary variable.’ Please elaborate and describe the possible limitation.

2. Lines 192 to 194: “Variables with p-values <0.05 in bivariate analysis were entered into a multivariate logistic regression model to identify independent predictors of TB-related stigma” – Do the authors mean a multivariable logistic regression model?

3. In the results section, 10 participants are aged 0-14 years however, one of the study inclusion criteria is that participants should be aged 15 years and above. Further clarification is needed.

4. Are the age group categories shown in Table 1 meaningful? Would other summary descriptive statistics for age central tendency and dispersion be considered to provide more information about patient characteristics.

5. The term “Pagan” in Table 1 may be considered derogatory – consider an alternative word.

6. Several other participant characteristics would be important to understand TB-related stigma, including: a) the type of tuberculosis; b) the timing of treatment for the TB patient at which this survey was being performed; c) disclosure of a TB diagnosis; among others. There is existing global, regional and particularly Kenyan literature that supports the importance of these particular characteristics. Consider including these in Table 1.

7. Lines 228-230: “Out of 367 participants, 228 individuals with TB shared their experiences regarding stigma. Among them, 24 (11%) reported experiencing TB-related stigma, while 204 (89%) did not. The remaining 139 participants did not provide an opinion and were excluded from the bivariate analysis.” a. Based on this statement, it is not clear what the procedures for study participation were. The study was to assess TB-related stigma, but 139 participants did not provide an opinion. Please elaborate the study procedures for the readers to gain clarity. b. What are the characteristics of the individuals of TB patients who did not share their experiences regarding stigma? c. Were they different from those who did?

8. Clarification is needed regarding the proportions of stigma provided in different sections of the manuscript. TB-related stigma dimensions in Figure 2 report relatively high TB-related stigma levels (49% for self-stigma, 68% of community-level stigma); compared to the overall TB-related stigma reported as 11% and also shown in Table 2.

9. Consider including whether the type of TB was pulmonary or not, in Table 2. This is not clear.

10. Data analysis:

Lines 171-175: “Exploratory factor analysis (EFA) was conducted to test the internal consistency and construct validity of the stigma scale in the Kenyan context. Cronbach’s alpha was calculated to assess internal reliability, with values ≥0.7 indicating acceptable consistency. The principal components extraction method was used to identify underlying factors, with factor loadings ≥0.4 considered acceptable.”

• Although this section is included in the data analysis methods section, there is no data in the manuscript to support this. Please provide this information if it is available.

Lines 182-186: “Stigma-related responses covering domains such as guilt, fear, social avoidance, and disclosure concerns were numerically encoded (1 = Strongly Agree to 5 = Strongly Disagree). Scores were aggregated row-wise per participant to generate a mean stigma score, which was then categorized as follows: 1.00–1.49: Strongly Disagree, 1.50–2.49: Disagree, 2.50–3.49: Neutral, 3.50–4.49: Agree and 4.50–5.00: Strongly Agree.”

• Similarly, although this section is included in the data analysis methods section, there is no data in the manuscript to support this. Stigma is reported as a binary variable and not continuous. Please provide this information if it is available.

Lines 192-194: Variables with p-values <0.05 in bivariate analysis were entered into a multivariate logistic regression model to identify independent predictors of TB-related stigma. Outputs are presented in Table 1 and Table 2 of the Results section.

• Again, this section is included in the data analysis methods section, but there is no data in the manuscript to support this. No results are provided for multivariable logistic regression in Table 1 or Table 2. Please provide this information if it is available.

Was there a justification of including age group instead of age as a continuous variable instead in the data analyses models used?

Was the sample size calculated powered to determine the factors associated with TB-related stigma?

1. Results, Discussion and Conclusion. The main confusion for me is around denominators and the respective proportions related to TB stigma that have been presented. Clarification on this is needed.

2. Study limitations need to be acknowledged.

Ask yourself what you already know, but do not overwhelm yourself and stress for the things that you do not know. Eventually it will all make sense.

Think about how you can relate to the text or what it means to you. Do not just read because you have to but because you want to learn and benefit from it.

Sometimes it is difficult to understand text or readings but I always help myself by doing my own research even when I didn't understand a sentence or a word.

It's very sad to see the force of culture Europeans put on the Native Americans. I knew the way Europeans treated the Native Americans were cruel and selfish, but I didn't know that even matriarchy changed because of European influence.

This is something so important to know and understand. I know I want to do something creative in the future, and I'm really not sure what exact job opportunities I will end up having. But knowing how to manage media more deeply will open doors to many different creative job outlets.

It will always amaze me that human sacrifice was apart of religious rituals. Where did people ever get this idea from? What made them think that sacrificing women and children would provide them a good harvest? It's not like they had the bible, a prophet, to listen to, so where did theses ideas originate?

This is an 'aha' moment for me. While I do know the importance of this, I sometimes forget and am very explicit in students following routine procedures for a variety of reasons. While I do allow for differentiation and scaffolding and a multitude of ways to engage, I seem to have forgotten the importance of hearing your students when they are giving insight on how they want to learn (to be clear, I do so in my observations of how they work, but I do not literally listen/hear their preferences).

WELCOME TO THE INVISIBLE REALM. You just proved a spiritual reality: The answer was always here, but you had to take action to reveal it.

This tool you are using is called The Tactical Overlay (Hypothesis). It is our way of communicating "beneath" the surface of the text.

THE LESSON: Jesus said, "The Kingdom of God is at hand." He didn't say it was far away. He said it was right here—superimposed over our normal reality.

The World says: "What you see is what you get."

The Kingdom says: "What is seen is temporary; what is unseen is eternal."

To be an Insider is to live Inside-Out, Back-to-Front, The Other Way Up and Invisible. To look at a situation that seems hopeless (the surface text) and activate the Kingdomlens (this overlay) to see what God is actually doing.

YOUR MISSION (SYSTEM CHECK):

Use the Overlay: Whenever you see yellow text on this site, it means there is Kingdom Intel hidden there. Click it.

Confirm Comms: Do not create a new highlight yet. Instead, click the Reply Arrow on this note and tell us:

"I'm seeing the other layer."

Welcome to the resistance.

I do not have that, but I will learn.

The “utility calculus” framing is helpful because it makes clear that ethical judgment depends on what data we choose to count and whose outcomes we include. Online, “pernicious ignorance” can look like focusing on likes/engagement while ignoring downstream harms (e.g., non-consensual images, harassment, or impacts on people we don’t personally know), which makes the calculation feel easier but morally distorted.

The idea of pernicious ignorance explains a lot about how social media decisions are made. By focusing only on visible data like engagement, we often ignore harm, privacy, or effects on marginalized groups. This makes ethical choices seem easier, but also less responsible.

The median for how you find data could be more important in uncovering what the data means. Given that there are so many external variables that can bias the data in some way, I wonder how companies that gather data insure It's as close to being unbiased as possible.

While this example is not on social media, I think that something similar is our use of plastic in our everyday lives. On the surface, it's just a bottle of water or a bag of chips, but the reality is that plastic has now permeated into our lives at a microscopic scale.

When I think about how data is used on the web, I think the concept of "utility computing" is actually useful, because it reminds us: do we really see all the data before deciding whether something is "more beneficial than harmful"? Many times we only use the information we have, but the missing data may be the most important part. I also agree with the text about "harmful ignorance", because in reality, it is really easy for people to ignore some data that makes them uncomfortable or not in line with their own position, so the results will be more like supporting the choice they want to make. This is especially true in social media and algorithmic recommendations, where we may be seeing things that are already filtered, so if we don't ask, "What's missing?" we may be biased in our utility calculations.

If he was King of English during this time, how was he back then? Did the English have similar reactions to the people of Spain? But, assuming that Queen Elizabeth I rejected his proposal, he probably has committed controversial actions.

The oppressed humans, just like any other animal, are bound to become aggressive and fight for absent necessities. In this case, they lacked the freedom of religion, suffered from heavy taxation, the government ignoring their rights to self-governance and fueros, and even had dissenters hunted down. There would be no surprise if some citizens' families also faced poverty and homelessness. Eventually, it will most likely always end in violence unless there is intervention before it gets to the point where hunger consumes all senses. Similar happened during the French, American, and Haitian Revolutions. An occurring theme unfortunately with corrupt governments that have no regard for their people.

Inferencing from the timeline being 1584 and the word "master" being used, people of African descent were looked down upon even in European countries like Spain. Whether it would be as simple as calling them by derogatory names, reducing them down to property, etc. This small sentence really shows that the United States was not the only country normalizing such cruelty. It's more disheartening to know that this was written by a priest, someone who should be showing upmost concern and care for those around him. All branches of Christianity are supposed to promote love and kindness to thy neighbor, right? But, one could also argue that this could of been how he was raised in this type of past culture and did not know any better.

Wow, I never thought of this.

Nearly forgotten civilizations and cultures like this really make me wonder how many others were there. There could be a chance that we have all missed out on some beautiful, rich diversity without us being aware of it. I do not know about how some of you feel, but it's disappointing to me on how we lack information about some of the extremely old places. On the bright side, it makes me treasure cultures related to Indigenous American and Pacific Islander tribes, Celtic descendants, etc. I hope that we as people learn from the devastation of civilization erasure, and avoid repeating history.

Communicating with others outside of your community is a very important but tricky skill. In the agriculture industry it is important we communicate clearly with individuals not involved in agriculture to avoid spreading misinformation.

I really like that we get to pick our own topics but are their any example if we're struggling to pick one or don't know whether it fits or not?

In reference to interpretation, the syllabus is comprehensive, and easily understood. I appreciate the additional information to other services, and how you have clearly expressed the expectations of the class. The fact you also value communication, and being forthright, is not only helpful, but as a first semester student it helps ease some of the concerns.

reply to harr at https://forum.zettelkasten.de/discussion/3392/folgezettel-vs-duplex-numeric-arrangement

I'll shortly have a lot more to say on this very subtle historical subject, which I've been work at off and on over the past month or so. My analysis indicates entire lack of innovation on the fronts which you're indicating. Pages 178-180 show the period standard practice of the subject alphabetic filing you say Luhmann was innovating against, but the duplex-numeric is exactly what he was using. The method he chose had been recommended and in use since at least the 1910s—especially for law offices.

Your quotes from his 1981 paper, while interesting, create a false impression stemming from post hoc, ergo propter hoc analysis. You have to remember that by the 1980s, he's been practicing this for nearly 30 years and is providing a reflection on that practice, which is also heavily impacted by his systems theory work through those decades. I strongly suspect that his mid-century perspective didn't stray far from that Remington Rand outline or those of scores of other sources.

It bears noting that of the four potential methods suggested in the chapter, the last one is the Dewey Decimal method, which many who've been in the zettelkasten space have also very naturally tried using as a scaffolding for their filing work. Others have also reasonably suggested variations like the Universal Decimal Classification system or Wikipedia's Academic Outline of Disciplines.

One will also notice that the option of doing a "Variadex Alphabetic" arrangement hasn't ever (to my knowledge) been mentioned in the online zettelkasten space. It was given the pride of place as first in the list of options, but this stems primarily from the fact that it was a variation offered by Remington Rand as a paid product with the related accessories. Every filing cabinet company and major stationery company had variations on this theme with their own custom names and products.

I love how the textbook cites all the perfectly valid and logically sound reasons as to why the gender wage gap is a myth then cites a weak lawsuit to justify that it’s actually “discrimination against women” that is the real reason. Even admitted that “such explicit discrimination” was “less frequent” but the trends of women going for lesser paying jobs, prioritizing work-life balance and taking more time off, taking time off to prioritize child raising and family, inability to successfully negotiate starting salaries— which ironically can be linked to the “stereotype” of them being less assertive than men— and other factors was unsatisfactory in explaining why this supposed gap existed? Yeah I call bs.

This section made me realize that data systems are not neutral—they are built around assumptions about who users are. The examples of name length and gender options show how people who don’t “fit” the system are forced to adjust or misrepresent themselves. Often, the issue isn’t user error, but the limits of the data design.

I think that companies should design these forms based on their audience demographics. If majority of users are from the UK, they should be on the top, same with USA, Canada, Mongolia, etc. And then the rest should be in alphabetical, this is a utilitarian approach.

This one is personal for me: as an exchange student applying for exchange I encountered this problem many times, as it could not register my Danish address, because it is written in a different way. This highlight the fact that all data and all artefacts have politics. Even if you try to accommodate everyone, you are always forced to make choices that sometimes exclude people entirely. This could be blind of deaf people, but also gender as mentioned in the next paragraph.

Gender is a hard one to create a drop down for, since gender is a social construct and can mean something different to every person. In the first example they use terms like female and male, but those are generally seen as terms to identify sex and not gender. In recent times there are now government forms who don't ask about gender whatsoever, and only ask about your biological sex (the FAFSA form does this now! My friend put male as his sex, but since it didn't match his birth certificate (F) his application was flagged and had to go under review). I've seen gender drop downs that separate transgender from man/woman, why is there a specification? Are they not "actually" the gender they say they are in the eyes of the programmers/data collectors? Food for thought.

The discussion of unanticipated secondary use connects modern data practices to historical harms such as the use of census data during the Holocaust and other genocides. This challenges the assumption that data collected for benign purposes will remain benign. It also suggests that ethical evaluation must consider future political and social changes, not just present day intentions.

The author argues that ethical uncertainty in the digital age comes from researchers’ rapidly increasing ability to observe and experiment on people without consent or awareness. How should we evaluate responsibility when harm is unintentional but foreseeable? For example, if researchers could reasonably anticipate privacy risks from large-scale data linkage, does beneficence require them to refrain from the study entirely, or only to mitigate harm after the fact?

It’s worth remembering that a simple choice as a list of country names may seem straightforward for a coder to add, but has a lot of ramifications for the website. Whether or not a country is or isn’t a country is a hot topic for debate and both the inclusion and exclusion of a country is a political stance.

This is an important thing to consider when choosing how we store data and how we want to represent it. It is unrealistic to for example have someone who is 1000 years old. Another good case is if we only want to include a specific set of data but the user enters invalid characters which may distort our dataset.

By highlighting marriage, Brown is demonstrating the dehumanizing and undignified nature of slavery.

I never realized how powerful metadata can be. It’s interesting that it’s not just about the content of the tweets, but also about information like when and how we collected them. That extra layer can really change how we understand and analyze data. It can reveal what time someone does things, trends, and behavior that we don't see behind the scenes.

I've heard the term metadata a few times in the past, but never understood what it meant. It now makes a lot of sense that it's data about data. It's helpful to know about the data we're collecting

I've always heard the term metadata but never really knew what it meant. Very interesting to see how it is categorized and the amount of information metadata contains.

This example provides a very clear explanation of what metadata is. I used to struggle with understanding or defining metadata, but this helped me realize that metadata refers to the contextual details about the main data. For instance, if a product’s ingredients are the main data, then information about when the ingredients were purchased or the composition of those ingredients would be the metadata.

On the surface, this tweet appears to be purely innocent and cute, but in fact, there is quite a bit of information that can be gleaned from this tweet. Information such as the level of engagement, the posting of the tweet, images included in the tweet, and even the tone of the tweet can be analyzed for information about the type of tweet that works best.

The idea of informational risk stood out to me because it reframes harm as something that can emerge later, even if a study seems harmless at first. The fact that “anonymized” data can be re-identified suggests that ethical responsibility doesn’t end at data collection but extends to long-term data storage and sharing decisions.

My boss is impacted because I was supposed to be there,e but instead I got sick, so now I need to allow my boss to find a replacement for me as soon as possible.

The use of real-world cases here makes it clear that ethical issues in digital research aren’t hypothetical but that they emerge from ordinary research decisions. What stood out to me is that all three examples involve studies that were innovative but controversial, which suggests that ethical risk often increases alongside methodological ambition.

I don't see why this would be surprising—or described as "obtuse". WebDAV is HTTP. Of course the headers matter.

Despite already agreeing with the article before further reading it, the article has further convinced me that hand writing notes is a better method of notation than typing. Throughout the article it makes reference to the research and researchers, strengthening their argument and as well as quoting an outside professional from a separate field strengthening the credibility of the article which further convinces me.

In most classes, when I take notes, I try to write them down on paper to retain the information better. In my experience, when typing notes I do not retain all of the information because I am more focused on typing and not the information. When I write on paper, I hold the information a lot better and can reiterate the info myself without looking at notes.

I highly agree with this idea. As a freshman I did start out with typing out class notes, and would notice that the information would not stick in my mind. However when I transitioned to pen and paper, I was forced to "consolidate" the material spoken in the lecture to keep up with the instructor. And this would make me have to understand or grasp the "consolidation" before writing. This had a clear correlation with my grades, and since then I always preferred to write with pen and paper instead of typing out class note.

It never crossed my mind that typing letters out instead of handwriting can take away from the muscle memory of it. I think kids are definitely affected if they cannot write the letters out. Also, I think it is interesting how we can subconsciously type on a screen, but it is a completely different feeling when we physically write.

Not just lookin on how the text was written but finding the meaning behind it

looking at it from a different perspective

God's creation through speaking implies the power of the word, but also for me that word creates (fiction!)

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

Learn more at Review Commons

Reply to the reviewers

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

SECTION A - Evidence, Reproducibility, and Clarity Summary The study investigates the neurodevelopmental impact of trisomy 21 on human cortical excitatory neurons derived from induced pluripotent stem cells (hiPSCs). Key findings include a modest reduction in spontaneous firing, a marked deficit in synchronized bursting, decreased neuronal connectivity, and altered ion channel expression-particularly a downregulation of voltage‐gated potassium channels and HCN1. These conclusions are supported by a combination of in vitro calcium imaging, electrophysiological recordings, viral monosynaptic tracing, RNA sequencing, and in vivo transplantation with two‐photon imaging.

Major Comments • Convincing Nature of Key Conclusions: The study's conclusions are generally well supported by a diverse set of experimental approaches. However, certain claims regarding the intrinsic properties of the excitatory network would benefit from further qualification. In particular, the assertion that reduced synchronization is solely attributable to altered ion channel expression might be considered somewhat preliminary without additional corroborative experiments.

1.1) We agree with the reviewer and now write in the abstract: 'Together, these findings demonstrate long-lasting impairments in human cortical excitatory neuron network function associated with Trisomy 21 .' And in the Introduction: 'Collectively, the observed changes in ion channel expression, neuronal connectivity, and network activity synchronization may contribute to functional differences relevant to the cognitive and intellectual features associated with Down syndrome.'

• One major limitation of the current experimental design is the reliance on predominantly excitatory neuronal cultures derived from hiPSCs. Although the authors convincingly demonstrate differences in network synchronization and connectivity between trisomic (TS21) and control neurons, the almost exclusive focus on excitatory cells limits the physiological relevance of the in vitro network. In the developing cortex, interneurons and astrocytes play crucial roles in modulating network excitability, synaptogenesis, and plasticity. Therefore, incorporating these cell types-either through co-culture systems or through directed differentiation protocols that yield a more heterogeneous neuronal population-could help to determine whether the observed deficits are intrinsic to excitatory neurons or are compounded by a lack of proper inhibitory regulation and glial support. 1.2) Thank you for this thoughtful comment. We agree that interneurons and astrocytes are crucial for network function. To clarify, astrocytes are generated in this culture system, as we previously reported in our characterisation of the timecourse of network development using this approach (Kirwan et al., Development 2025). However, our primary goal was to first isolate and define the cell-autonomous defects intrinsic to TS21 excitatory neurons, minimizing the complexity introduced by additional neuronal types. This focused approach was chosen also because engineering a stable co-culture system with reproducible excitatory/inhibitory (E/I) proportions is a significant undertaking that extends beyond the scope of this initial investigation, and has proven challenging to date for the field. By establishing this foundational phenotype, our work complements prior studies on interneuron and glial contributions. Future studies building on this work will be essential to dissect the more complex, non-cell-autonomous effects within a heterogeneous network. Importantly, since our initial submission, two highly relevant preprints have emerged-including a notable study from the Geschwind laboratory at UCLA (Vuong et al., bioRxiv, 2025; Risgaard et al., bioRxiv, 2025), as well as our own complementary study Lattke et al, under revision, that highlight widespread transcriptional changes in excitatory cells of the human fetal DS cortex, providing strong validation for our central findings. This convergence of results from multiple groups underscores the timeliness and importance of our work.

• Furthermore, the assessment of neuronal connectivity via pseudotyped rabies virus tracing, while innovative, has inherent limitations. The quantification of connectivity as a ratio of red-to-green fluorescence pixels may be influenced by differential viral infection efficiencies, variations in the expression levels of the TVA receptor, or even by the lower basal activity levels observed in TS21 cultures. Complementary approaches-such as electron microscopy for synaptic density analysis or functional connectivity measurements using multi-electrode arrays (MEAs)-could provide additional structural and functional insights that would validate the rabies tracing data. 1.3) Thank you for this constructive feedback. While we cannot formally exclude that TS21 cells might express the TVA receptor at lower levels due to generalized gene dysregulation, we infected all WT and TS21 cultures in parallel using identical virus preparations and titers to minimize technical variability. Crucially, we also addressed the potential confound of differential basal activity by performing the rabies tracing under TTX incubation (see Suppl. Fig. 7), which blocks network activity and ensures that viral spread reflects structural connectivity alone.

While complementary methods like EM or MEA could provide additional insight, they fall outside the scope of the current study. We are confident that our rigorous controls validate our use of the rabies tracing method to assess structural connectivity.

• Qualification of Claims: Some conclusions, particularly those linking specific ion channel dysregulation (e.g., HCN1 loss) directly to network deficits, might be better presented as preliminary. The authors could temper their language to indicate that while the evidence is suggestive, the mechanistic link remains to be fully established. 1.4) We have revised the text to more clearly indicate that the link between HCN1 dysregulation and network deficits is correlative and remains to be fully established. While our ex vivo recordings suggest altered Ih-like currents consistent with reduced HCN1 expression, we now present these findings as preliminary and hypothesis-generating, pending further functional validation. We write in the discussion: However, further targeted functional validation will be needed to confirm a causal link.

• Need for Additional Experiments: Additional experiments that could further consolidate the current findings include: o Inclusion of Inhibitory Neurons or Co-culture Systems: Incorporating interneurons or astrocytes would help determine whether the observed deficits are solely intrinsic to excitatory neurons. See 1.2 o Alternative Connectivity Assessments: Complementing the rabies virus tracing with electron microscopy or multi-electrode array (MEA) recordings would add structural and functional validation of the connectivity differences. See 1.3 o Extended Temporal Profiling: Monitoring network activity over a longer developmental window would clarify whether the observed deficits represent a delay or a permanent alteration in network maturation. 1.5) In vivo we were able to track the cells for up to five months post-transplantation supporting the interpretation of a permanent alteration.

• Reproducibility and Statistical Rigor: The methods and data presentation are largely clear, with adequate replication and appropriate statistical analyses. Nonetheless, a more detailed description of the experimental replicates, particularly regarding the viral tracing and in vivo transplantation studies, would enhance reproducibility. The availability of raw data and scripts for calcium imaging analysis would also further support independent verification. We thank the reviewer for these suggestions and we now provide a more detailed description of replicates. We also add the raw data.

Minor Comments • Experimental Details: Minor revisions could include clarifying the infection efficiency and expression levels of the viral constructs used in connectivity assays to rule out technical variability.

See 1.3

• Literature Context: The authors reference prior studies appropriately; however, integrating a brief discussion comparing their findings with alternative DS models (e.g., organoids or other hiPSC-derived systems) would improve contextual clarity. We thank the reviewer for this helpful suggestion. We have now added a brief discussion comparing our findings with those reported in alternative Down syndrome models, including brain organoids and other hiPSC-derived systems. This addition helps to contextualize our results within the broader field and highlights the unique strengths and limitations of our in vitro and in vivo xenograft approach. We write: 'Our findings align with and extend previous studies using alternative Down syndrome models, such as brain organoids and other hiPSC-derived systems. Organoid models have provided valuable insights into early neurodevelopmental phenotypes in DS, including altered interneuron proportions (Xu et al Cell Stem Cell 2019) but also suggest that variability across isogenic lines can overshadow subtle trisomy 21 neurodevelopmental phenotypes (Czerminski et al Front in Neurosci 2023). However, these systems often lack the structural complexity, vascularization, and long-term maturation achievable in vivo. By using a xenotransplantation model, we were able to assess the maturation and functional properties of human neurons within a physiologically relevant environment over extended time frames, offering complementary insights into DS-associated circuit dysfunction (Huo et al Stem Cell Reports 2018; Real et al., 2018).

• Presentation and Clarity: Figures are generally clear,.But the manuscript contains a minor labeling error. On page 13, the figure is erroneously labeled as "Fig6A", whereas, based on the context and corresponding data, it should be "Fig5A". I recommend that the authors correct this mistake to ensure consistency and avoid potential confusion for readers. Thank you for pointing this out. This has been corrected in the revised manuscript.

Reviewer #1 (Significance (Required)):

SECTION B - Significance • Nature and Significance of the Advance: The work offers a substantial conceptual advance by providing a mechanistic link between trisomy 21 and impaired neuronal network synchronization. Technically, the study integrates state-of-the-art imaging, electrophysiology, and transcriptomic profiling, thereby offering a multifaceted view of DS-related neural dysfunction. Clinically, the findings have the potential to inform future therapeutic strategies targeting network connectivity and ion channel function in Down syndrome.

We thank the reviewer for this very supportive comment.

• Context in the Existing Literature: The study builds on previous observations of altered network activity in DS patients and DS mouse models (e.g., altered EEG synchronization and reduced synaptic connectivity). It extends these findings to human-derived neuronal models, thus bridging a gap between clinical observations and molecular/cellular mechanisms. Relevant literature includes studies on DS neurodevelopment and the role of ion channels in synaptic maturation. • Target Audience: The reported findings will be of interest to researchers in neurodevelopmental disorders, Down syndrome, and ion channel physiology. Additionally, the study may attract the attention of those working on hiPSC-derived models of neurological diseases, as well as clinicians interested in the pathophysiology of DS. • Keywords and Field Contextualization: Keywords: Down syndrome, trisomy 21, neuronal connectivity, synchronized network activity, hiPSC-derived cortical neurons, ion channel dysregulation.

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

Summary The manuscript by Peter et al., reports on the neuronal activity and connectivity of iPSC-derived human cortical neurons from Down syndrome (DS) that is caused by caused by trisomy of the human chromosome 21 (TS21). Major points: Although the manuscript is potentially interesting, the results appear somehow preliminary and need to be corroborated by control experiments and quantifications of effects to fully sustain the conclusions. (1) The authors have not assessed the percentage of WT and TS21 cells that acquire a neuronal or glia identity in their cultures. Indeed, the origin of alterations in network activity and connectivity observed in TS21 neurons could simply derive from reduced number of neurons arising from TS21 iPSC. Alternatively, the same alteration in network activity and connectivity could derive from a multitude of other factors including deficits in neuronal development, neurite extension, or intrinsic electrophysiological properties. In the current version of the manuscript, none of these has been investigated. 2.1) We thank the reviewer for this thoughtful comment. In response, we included an in vivo characterization of cell-type proportions at the same time points where we observed network activity defects using in vivo calcium imaging (see Supplementary Fig. 6).

Previous work has identified several cellular and molecular phenotypes in human cells, postmortem tissue, and mouse models-including those mentioned by the reviewer. In this study, our focus was on investigating neural network activity, intrinsic electrophysiological properties both in vitro and in vivo, and preliminary bulk RNA sequencing. We have also independently measured cell proportions in the human fetal cortex and conducted a more extensive transcriptomic analysis of Ts21 versus control cells in a separate study (Lattke et al., under revision). We observed a reduction of RORB/FOXP1-expressing Layer 4 neurons in the human fetal cortex at midgestation, as well as increased GFAP+ cells, reduced progenitors and a non significant reduction of Cux2+ cells in late stage DS human cell transplants, along with a gene network dysregulation specifically affecting excitatory neurons (Lattke et al., under revision). Here, we provide complementary findings, demonstrating reduced excitatory neuron network connectivity in vitro and decreased neural network synchronised activity in both in vitro and in vivo models (see also 2.8). We agree with the reviewer that this could be for a number of reasons, both cell autonomous (channel expression and/or function) or non-autonomous (connectivity and/or network composition - as reflected in differences in proportions of SATB2+ neurons generated in TS21 cortical differentiations).

(2) Electrophysiological properties of TS21 and WT neurons at day 53/54 in vitro indicate an extremely immature stage of development (i.e. RMP between -36 and -27 mV with most of the cells firing a single action potential after current injection) in the utilized culture conditions: This is far from ideal for in vitro neuronal-network studies. Finally, reduced activity of HCN1 channels should be confirmed by specific recordings isolating or blocking the related current.

2.2) Thank you for this thoughtful comment. We have also conducted ex vivo electrophysiological recordings and found that the neurons exhibit relatively immature properties, consistent with the known slow developmental trajectory of human neuron cultures. In light of this and the absence of direct confirmatory evidence, we now refer to the observed reduction in HCN1 as preliminary.

Main points highlighting the preliminary character of the study. 1) In Figure 1 immunofluorescence images of the neuronal differentiation markers (Tbr1, Ctip2 and Tuj1) are showed. However, no quantification of the percentage of cells expressing these markers for WT and TS21 neurons is reported. On the other hand, simple inspection of the representative images clearly seams to indicate a difference between the two genotypes, with TS21 cultures showing lower number of cells expressing neuronal markers. This quantification should be corroborated by a similar staining for an astrocyte marker (GFAP, but not S100b since is triplicated in DS). This is an extremely important point since it is obvious that any change in the percentage of neurons (or the neuron/astrocyte ratio) in the cultures will strongly affect the resulting network activity (shown in Figure 2) and the connectivity (showed in Figure 4). Possibly, the quantification should be done at the same time points of the calcium imaging experiments.

2.3) See 2.1. We included an in vivo characterization of cell-type proportions at the same time points where we observed network activity defects using in vivo calcium imaging. (see Supplementary Fig. 6).

2) In Figure 2 the authors show some calcium imaging traces of WT and TS21 cultures at different time points. However, they again do not show any quantification of neuronal activity. A power spectra analysis is shown in Supplementary Figure 2, but only for WT cultures, while in Supplementary Figure 3 a comparison between WT and Ts21 power spectra is done, but only at the 50 day time point, while difference in synchrony are assessed at 60 days. At minimum, the author should include in main Figure 2 the quantification of the mean calcium event rate and mean event amplitude at the different time points and the power spectra analysis for both WT and TS21 cultures at the same timepoints.

2.4) We thank the reviewer for this comment. We now add the power spectra analysis in the main Figure 2 and quantification of the mean calcium burst rate and mean event amplitude in SuppFig. 4.

Of note, the synchronized neuronal activity is present in WT cultures at day 60, but totally lost at subsequent time-points (70 and 80 days). The results of this later time points are different from previous data from the same lab (Kirwan et al., 2015). How might these data be explained? It would be important to rule out any potential issues with the health of the culture that could explain the loss of neuronal activity.It would be beneficial to check cell viability at the different time points to exclude possible confounding factors ? A propidium staining or a MTT assay would strongly improve the soundness of the calcium data.

2.5) We thank the reviewer for this important observation. The difference from the findings reported in Kirwan et al., 2015 is due to the use of a different neuronal differentiation medium in the current study (BrainPhys versus N2B27). BrainPhys medium supports robust early network activity compared to N2B27 (onset before day 60 in BrainPhys, post-day 60 in N2B27), resulting in an earlier decline in synchrony at later stages (day 70-80 in BrainPhys, compared with day 90-100 in N2B27). Importantly, in our in vivo xenograft model, burst activity is sustained up to at least 5 months post-transplantation (mpt), indicating that the neurons retain the capacity for network activity over extended periods in a more physiological environment. We adapted the text accordingly.

3) In Figure 3 there is no quantification of the number and/or density of transplanted neurons for WT and TS21, but only representative images. As above, inspection of the representative images seems to show a decrease in cells labeled by the Tbr1 neuronal marker for TS21 cells. Moreover, the in vivo calcium imaging of transplanted WT and TS21 cells lacks most of the quantification normally done in calcium imaging experiments. Are the event rate and event amplitude different between WT and TS21 neurons ? The measure of neuronal synchrony by mean pixel correlation is not well explained, but it looks somehow simplistic. Neuronal synchrony can be more precisely measured by cross-correlation analysis or spike time tiling coefficients on the traces from single-neuron ROI rather than on all pixels in the field of view, as apparently was done here.

2.6) We thank the reviewer for these valuable points. We now include quantification of the number and density of transplanted neurons for both WT and Ts21 grafts in Extended Data Figure 5 (see 2.1).

Regarding the in vivo calcium imaging, we appreciate the reviewer's suggestion to include additional standard metrics. We have quantified the event rate in Real et al 2018. These analyses reveal that Ts21 neurons show a reduction in event rate.

We agree that our initial description of the synchrony analysis using mean pixel correlation was not sufficiently detailed. We have now clarified this in the Methods and Results, and we acknowledge its limitations. Importantly, we note that the reduced synchronisation is a highly consistent phenotype, observed across at least six independent donor pairs, different differentiation protocols, and both in vitro (and in two independent labs) and in vivo settings. As suggested, future studies using ROI-based approaches-such as cross-correlation or spike-time tiling coefficients-would provide a more refined characterization of synchrony at the single-neuron level (Sintes et al, in preparation). We now include this point in the discussion.

4) The results on reduced neuronal connectivity in Figure 3 look very striking. However, these results should be accompanied by control experiments to verify the number of neuronal cells and neurite extension in WT and Ts21 cultures. These two parameters could indeed strongly influence the results. As the cultures appear to grow in clusters, bright-field images and TuJ1 staining of the cultures will also greatly help to understand the degree of morphological interconnection between the clusters.

We now add Tuj1 staining in Supplementary figure 10.

5) The authors performed RNA-seq experiments on day 50 cultures. Why the authors do not show the complete differential gene expression analysis, but only a small subset of genes? A comprehensive volcano plot and the complete list of identified genes with logFC and FDR values would be helpful. If possible, comparison of the present data (particularly on KCN and HCN expression changes) with published and publicly available expression datasets of other human or human Down syndrome iPSC-derived neurons or human Down syndrome brains will greatly increase the soundness of the present findings. In addition, the gene ontology (GO) results are mentioned in the text, but are not presented. Showing the complete GO analysis for both up and downregulated genes will help the reader to better understand the RNA-seq results. Notably, the results shown in Supplementary Figure on GRIN2A and GRIN2B expression (with values of 300-700 counts versus 2000-4000 counts, respectively) clearly indicate that in both WT and TS21 cultures the NMDA developmental switch has not occurred yet at the 50 days timepoint.

We now show volcano plots in Supplementary Fig. 11.

6) The measure of hyperpolarization-activated currents shown in Figure 5 lack proper control experiments. First, the hyperpolarizing current in TS21 cells do not reach a steady-state as the controls. The two curves are therefore hard to compare. To exclude possible difference in kinetic activation, the authors should have prolonged the current injection period (1-2 seconds). Second, to ultimately prove that such currents are mediated by HCN channels in WT cells the authors should perform some control experiments with a specific HCN blocker. A good example of a suitable protocol, with also current blockers to exclude all other possible current contributions, is the one reported in Matt et al Cell. Mol. Life Sci. 68, 125-137 (2011).

2.7) We thank the reviewer for this detailed and helpful comment. We agree that to definitively identify the recorded currents as Ih, it would be necessary to isolate them pharmacologically using specific HCN channel blockers and appropriate controls, such as those described in Matt et al., Cell. Mol. Life Sci. Unfortunately, due to current constraints, we no longer have access to the animals used in this study and cannot allocate the necessary time or resources, we are unable to perform the additional experiments at this stage.

However, our goal here was to use electrophysiological recordings as an indication of altered HCN channel activity, which we then support with molecular evidence. We now emphasize this point more clearly in the revised manuscript.

7) The manuscript lacks information on the statistical analysis used. Also, the numerosity of samples is not clear. Were the dots shown in some graph technical replicates from a single neuronal induction or were all independent neuronal inductions or a mix of the two ? Please clarify.

We now clarify the numbers in the Figure legend.

8) The method section lacks important information to guarantee reproducibility. Just a few examples: • Only electrophysiology methods for slice are reported, but not for in vitro culture.

We now clarify these details in the methods.

• Details on Laminin coating is lacking. What concentration was used ? Was poly-ornithine or poly-lysine used before Laminin coating ? We now clarify these details in the methods.

• How long cells were switched to BrainPhys medium before calcium imaging ? We now clarify these details in the methods.

Minor point/typos etc.

Introduction • Page 4 line 6: in the line "Trisomy 21 in humans commonly results in a range in developmental and morphological changes in the forebrain ..." "in" could be replaced by "of". We have fixed this. • Page 5 line 2: please remove "an" before the word "another". We have fixed this. • Page 5 line 2: please replace "ecitatory" with "excitatory". We have fixed this typo.

Results • Page 10 line 25: The concept of "pixel-wise" appears for the first time in this section and could be better introduced to facilitate the understanding of the experiment. • In the "results" section, page 11 line 1 and 4, references are made to "Figure 4D" and "4F," but these figures do not appear to be present in the figure section. Upon reviewing the rest of the section, the data seem to refer to "Figure 3D" and "3E." We have fixed this. Discussion • Page 15 line 20: please replace "synchronised" with "synchronized". We have fixed this typo. • Page 16 line 11: please replace "T21" with "TS21". We have fixed this typo. Methods • Page 19 line 12: "Pens/Strep" has to be replaced by Pen/Strep. We have fixed this typo. • Page 20 line 20: "Tocris Biocience" has to be replaced by "Tocris Bioscience". We have fixed this typo. • Page 21 line 2: "Addegene" has to be replaced by "Addgene". We have fixed this typo. Figures • Figure 3: the schematic experimental design (Fig. 3A) could be enlarged to match the width of the images/graphs below. We have fixed this. • Figure 5: the reviewer suggests resizing/repositioning the graphs in Fig. 1A so that they match the width of those below. We have fixed this. • Figure S1D: In all the figures of the paper, the respective controls for the TS21 1 and TS21 2 lines are labelled as "WT1/WT2," while in these graphs, they are called "Ctrl1" and "Ctrl2." To ensure consistency throughout the paper, it is suggested to change the names in these graphs. We have fixed this. • Figure S4L: The graph is not very clear, especially regarding the significance reported at -50 pA, please modify the graphical visualization and/or add a legend in the caption. We have fixed this.

Reviewer #2 (Significance (Required)):

Nature and significance of the advance for the field. The results presented in the manuscript are potentially interesting and useful, but not completely novel (currents deregulation has already been highlighted in mouse models of Down Syndrome).

2.8) We thank the reviewer for this comment. While we agree that current deregulation has been observed in mouse models of Down syndrome, the novelty and significance of our study lie in demonstrating these alterations directly in human neurons using both in vitro and in vivo xenograft models.

This is a critical advance because the human cortex has distinct developmental and functional properties not fully recapitulated in mice. In fact, three recent studies have already highlighted significant defects mainly in excitatory neurons within the fetal human DS cortex (Vuong et al., bioRxiv, 2025; Risgaard et al., bioRxiv, 2025; Lattke et al, under revision). Our work builds directly on these observations by providing, for the first time, an electrophysiological and network-level characterization of these human-specific deficits.

Our findings thus provide translationally relevant insight that is not merely confirmatory but extends previous work by grounding it in a human cellular context.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

Referee #2

Evidence, reproducibility and clarity

Summary

The manuscript by Peter et al., reports on the neuronal activity and connectivity of iPSC-derived human cortical neurons from Down syndrome (DS) that is caused by caused by trisomy of the human chromosome 21 (TS21).

Major points:

Although the manuscript is potentially interesting, the results appear somehow preliminary and need to be corroborated by control experiments and quantifications of effects to fully sustain the conclusions.

(1) The authors have not assessed the percentage of WT and TS21 cells that acquire a neuronal or glia identity in their cultures. Indeed, the origin of alterations in network activity and connectivity observed in TS21 neurons could simply derive from reduced number of neurons arising from TS21 iPSC. Alternatively, the same alteration in network activity and connectivity could derive from a multitude of other factors including deficits in neuronal development, neurite extension, or intrinsic electrophysiological properties. In the current version of the manuscript, none of these has been investigated.

(2) Electrophysiological properties of TS21 and WT neurons at day 53/54 in vitro indicate an extremely immature stage of development (i.e. RMP between -36 and -27 mV with most of the cells firing a single action potential after current injection) in the utilized culture conditions: This is far from ideal for in vitro neuronal-network studies. Finally, reduced activity of HCN1 channels should be confirmed by specific recordings isolating or blocking the related current.

Main points highlighting the preliminary character of the study.

1) In Figure 1 immunofluorescence images of the neuronal differentiation markers (Tbr1, Ctip2 and Tuj1) are showed. However, no quantification of the percentage of cells expressing these markers for WT and TS21 neurons is reported. On the other hand, simple inspection of the representative images clearly seams to indicate a difference between the two genotypes, with TS21 cultures showing lower number of cells expressing neuronal markers. This quantification should be corroborated by a similar staining for an astrocyte marker (GFAP, but not S100b since is triplicated in DS). This is an extremely important point since it is obvious that any change in the percentage of neurons (or the neuron/astrocyte ratio) in the cultures will strongly affect the resulting network activity (shown in Figure 2) and the connectivity (showed in Figure 4). Possibly, the quantification should be done at the same time points of the calcium imaging experiments.

2) In Figure 2 the authors show some calcium imaging traces of WT and TS21 cultures at different time points. However, they again do not show any quantification of neuronal activity. A power spectra analysis is shown in Supplementary Figure 2, but only for WT cultures, while in Supplementary Figure 3 a comparison between WT and Ts21 power spectra is done, but only at the 50 day time point, while difference in synchrony are assessed at 60 days. At minimum, the author should include in main Figure 2 the quantification of the mean calcium event rate and mean event amplitude at the different time points and the power spectra analysis for both WT and TS21 cultures at the same timepoints.

Of note, the synchronized neuronal activity is present in WT cultures at day 60, but totally lost at subsequent time-points (70 and 80 days). The results of this later time points are different from previous data from the same lab (Kirwan et al., 2015). How might these data be explained? It would be important to rule out any potential issues with the health of the culture that could explain the loss of neuronal activity.It would be beneficial to check cell viability at the different time points to exclude possible confounding factors ? A propidium staining or a MTT assay would strongly improve the soundness of the calcium data.

3) In Figure 3 there is no quantification of the number and/or density of transplanted neurons for WT and TS21, but only representative images. As above, inspection of the representative images seems to show a decrease in cells labeled by the Tbr1 neuronal marker for TS21 cells. Moreover, the in vivo calcium imaging of transplanted WT and TS21 cells lacks most of the quantification normally done in calcium imaging experiments. Are the event rate and event amplitude different between WT and TS21 neurons ? The measure of neuronal synchrony by mean pixel correlation is not well explained, but it looks somehow simplistic. Neuronal synchrony can be more precisely measured by cross-correlation analysis or spike time tiling coefficients on the traces from single-neuron ROI rather than on all pixels in the field of view, as apparently was done here.

4) The results on reduced neuronal connectivity in Figure 3 look very striking. However, these results should be accompanied by control experiments to verify the number of neuronal cells and neurite extension in WT and Ts21 cultures. These two parameters could indeed strongly influence the results. As the cultures appear to grow in clusters, bright-field images and TuJ1 staining of the cultures will also greatly help to understand the degree of morphological interconnection between the clusters.

5) The authors performed RNA-seq experiments on day 50 cultures. Why the authors do not show the complete differential gene expression analysis, but only a small subset of genes? A comprehensive volcano plot and the complete list of identified genes with logFC and FDR values would be helpful. If possible, comparison of the present data (particularly on KCN and HCN expression changes) with published and publicly available expression datasets of other human or human Down syndrome iPSC-derived neurons or human Down syndrome brains will greatly increase the soundness of the present findings. In addition, the gene ontology (GO) results are mentioned in the text, but are not presented. Showing the complete GO analysis for both up and downregulated genes will help the reader to better understand the RNA-seq results. Notably, the results shown in Supplementary Figure on GRIN2A and GRIN2B expression (with values of 300-700 counts versus 2000-4000 counts, respectively) clearly indicate that in both WT and TS21 cultures the NMDA developmental switch has not occurred yet at the 50 days timepoint.

6) The measure of hyperpolarization-activated currents shown in Figure 5 lack proper control experiments. First, the hyperpolarizing current in TS21 cells do not reach a steady-state as the controls. The two curves are therefore hard to compare. To exclude possible difference in kinetic activation, the authors should have prolonged the current injection period (1-2 seconds). Second, to ultimately prove that such currents are mediated by HCN channels in WT cells the authors should perform some control experiments with a specific HCN blocker. A good example of a suitable protocol, with also current blockers to exclude all other possible current contributions, is the one reported in Matt et al Cell. Mol. Life Sci. 68, 125-137 (2011).

7) The manuscript lacks information on the statistical analysis used. Also, the numerosity of samples is not clear. Were the dots shown in some graph technical replicates from a single neuronal induction or were all independent neuronal inductions or a mix of the two ? Please clarify.

8) The method section lacks important information to guarantee reproducibility. Just a few examples: - Only electrophysiology methods for slice are reported, but not for in vitro culture. - Details on Laminin coating is lacking. What concentration was used ? Was poly-ornithine or poly-lysine used before Laminin coating ? - How long cells were switched to BrainPhys medium before calcium imaging ?

Minor point/typos etc.

Introduction

• Page 4 line 6: in the line "Trisomy 21 in humans commonly results in a range in developmental and morphological changes in the forebrain ..." "in" could be replaced by "of".
• Page 5 line 2: please remove "an" before the word "another".
• Page 5 line 2: please replace "ecitatory" with "excitatory"

Results

• Page 10 line 25: The concept of "pixel-wise" appears for the first time in this section and could be better introduced to facilitate the understanding of the experiment.
• In the "results" section, page 11 line 1 and 4, references are made to "Figure 4D" and "4F," but these figures do not appear to be present in the figure section. Upon reviewing the rest of the section, the data seem to refer to "Figure 3D" and "3E."

Discussion

• Page 15 line 20: please replace "synchronised" with "synchronized".
• Page 16 line 11: please replace "T21" with "TS21".

Methods

• Page 19 line 12: "Pens/Strep" has to be replaced by Pen/Strep.
• Page 20 line 20: "Tocris Biocience" has to be replaced by "Tocris Bioscience".
• Page 21 line 2: "Addegene" has to be replaced by "Addgene".

Figures

• Figure 3: the schematic experimental design (Fig. 3A) could be enlarged to match the width of the images/graphs below.
• Figure 5: the reviewer suggests resizing/repositioning the graphs in Fig. 1A so that they match the width of those below.
• Figure S1D: In all the figures of the paper, the respective controls for the TS21 1 and TS21 2 lines are labelled as "WT1/WT2," while in these graphs, they are called "Ctrl1" and "Ctrl2." To ensure consistency throughout the paper, it is suggested to change the names in these graphs.
• Figure S4L: The graph is not very clear, especially regarding the significance reported at -50 pA, please modify the graphical visualization and/or add a legend in the caption.

Significance

Nature and significance of the advance for the field. The results presented in the manuscript are potentially interesting and useful, but not completely novel (currents deregulation has already been highlighted in mouse models of Down Syndrome).

Work in the context of the existing literature. This work follows the line of evidence that characterizes Down Syndrome in human neurons (Huo, H.-Q. et al. Stem Cell Rep. 10, 1251-1266 (2018); Briggs, J. A. et al. Etiology. Stem Cells 31, 467-478 (2013)), both in vitro and in xenotransplanted mice, by corrborating some important findings already found in animal models (Stern, S., Segal, M. & Moses, E. EBioMedicine 2, 1048-1062 (2015); Cramer, N. P., Xu, X., F. Haydar, T. & Galdzicki, Z. Physiol. Rep. 3, e12655 (2015); Stern, S., Keren, R., Kim, Y. & Moses, E. http://biorxiv.org/lookup/doi/10.1101/467522 (2018) doi:10.1101/467522.

Audience. Scientists in the field of pre-clinical biomedical research, especially those working on neurodevelopmental disorders and iPSC-based non-animal models.

Field of expertise. In vitro electrophysiology, Neurodevelopmental disorders, Down Syndrome, ips cells.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

Referee #1

Evidence, reproducibility and clarity

Summary

The study investigates the neurodevelopmental impact of trisomy 21 on human cortical excitatory neurons derived from induced pluripotent stem cells (hiPSCs). Key findings include a modest reduction in spontaneous firing, a marked deficit in synchronized bursting, decreased neuronal connectivity, and altered ion channel expression-particularly a downregulation of voltage‐gated potassium channels and HCN1. These conclusions are supported by a combination of in vitro calcium imaging, electrophysiological recordings, viral monosynaptic tracing, RNA sequencing, and in vivo transplantation with two‐photon imaging.

Major Comments

• Convincing Nature of Key Conclusions: The study's conclusions are generally well supported by a diverse set of experimental approaches. However, certain claims regarding the intrinsic properties of the excitatory network would benefit from further qualification. In particular, the assertion that reduced synchronization is solely attributable to altered ion channel expression might be considered somewhat preliminary without additional corroborative experiments.
• One major limitation of the current experimental design is the reliance on predominantly excitatory neuronal cultures derived from hiPSCs. Although the authors convincingly demonstrate differences in network synchronization and connectivity between trisomic (TS21) and control neurons, the almost exclusive focus on excitatory cells limits the physiological relevance of the in vitro network. In the developing cortex, interneurons and astrocytes play crucial roles in modulating network excitability, synaptogenesis, and plasticity. Therefore, incorporating these cell types-either through co-culture systems or through directed differentiation protocols that yield a more heterogeneous neuronal population-could help to determine whether the observed deficits are intrinsic to excitatory neurons or are compounded by a lack of proper inhibitory regulation and glial support.
• Furthermore, the assessment of neuronal connectivity via pseudotyped rabies virus tracing, while innovative, has inherent limitations. The quantification of connectivity as a ratio of red-to-green fluorescence pixels may be influenced by differential viral infection efficiencies, variations in the expression levels of the TVA receptor, or even by the lower basal activity levels observed in TS21 cultures. Complementary approaches-such as electron microscopy for synaptic density analysis or functional connectivity measurements using multi-electrode arrays (MEAs)-could provide additional structural and functional insights that would validate the rabies tracing data.
• Qualification of Claims: Some conclusions, particularly those linking specific ion channel dysregulation (e.g., HCN1 loss) directly to network deficits, might be better presented as preliminary. The authors could temper their language to indicate that while the evidence is suggestive, the mechanistic link remains to be fully established.
• Need for Additional Experiments: Additional experiments that could further consolidate the current findings include:
  • Inclusion of Inhibitory Neurons or Co-culture Systems: Incorporating interneurons or astrocytes would help determine whether the observed deficits are solely intrinsic to excitatory neurons.
  • Alternative Connectivity Assessments: Complementing the rabies virus tracing with electron microscopy or multi-electrode array (MEA) recordings would add structural and functional validation of the connectivity differences.
  • Extended Temporal Profiling: Monitoring network activity over a longer developmental window would clarify whether the observed deficits represent a delay or a permanent alteration in network maturation.
• Reproducibility and Statistical Rigor: The methods and data presentation are largely clear, with adequate replication and appropriate statistical analyses. Nonetheless, a more detailed description of the experimental replicates, particularly regarding the viral tracing and in vivo transplantation studies, would enhance reproducibility. The availability of raw data and scripts for calcium imaging analysis would also further support independent verification.

Minor Comments

• Experimental Details:

Minor revisions could include clarifying the infection efficiency and expression levels of the viral constructs used in connectivity assays to rule out technical variability. - Literature Context:

The authors reference prior studies appropriately; however, integrating a brief discussion comparing their findings with alternative DS models (e.g., organoids or other hiPSC-derived systems) would improve contextual clarity. - Presentation and Clarity:

Figures are generally clear,.But the manuscript contains a minor labeling error. On page 13, the figure is erroneously labeled as "Fig6A", whereas, based on the context and corresponding data, it should be "Fig5A". I recommend that the authors correct this mistake to ensure consistency and avoid potential confusion for readers.

Significance

• Nature and Significance of the Advance:

The work offers a substantial conceptual advance by providing a mechanistic link between trisomy 21 and impaired neuronal network synchronization. Technically, the study integrates state-of-the-art imaging, electrophysiology, and transcriptomic profiling, thereby offering a multifaceted view of DS-related neural dysfunction. Clinically, the findings have the potential to inform future therapeutic strategies targeting network connectivity and ion channel function in Down syndrome. - Context in the Existing Literature:

The study builds on previous observations of altered network activity in DS patients and DS mouse models (e.g., altered EEG synchronization and reduced synaptic connectivity). It extends these findings to human-derived neuronal models, thus bridging a gap between clinical observations and molecular/cellular mechanisms. Relevant literature includes studies on DS neurodevelopment and the role of ion channels in synaptic maturation. - Target Audience:

The reported findings will be of interest to researchers in neurodevelopmental disorders, Down syndrome, and ion channel physiology. Additionally, the study may attract the attention of those working on hiPSC-derived models of neurological diseases, as well as clinicians interested in the pathophysiology of DS. - Keywords and Field Contextualization:

Keywords: Down syndrome, trisomy 21, neuronal connectivity, synchronized network activity, hiPSC-derived cortical neurons, ion channel dysregulation.

Reviewer #2 (Public review):

Context and significance:

Distal renal tubular acidosis (dRTA) can be caused by mutations in a Cl-/HCO3- exchanger (kAE1) encoded by the SLC4A1 gene. The precise mechanisms underlying the pathogenesis of the disease due to these mutations is unclear, but it is thought that loss of the renal intercalated cells (ICs) that express kAE1 and/or aberrant autophagy pathway function in the remaining ICs may contribute to the disease. Understanding how mutations in SLC4A1 affect cell physiology and cells within the kidney, a major goal of this study, is an important first step to unraveling the pathophysiology of this complex heritable kidney disease.

Summary:

The authors identify a number of new mutations in the SLC4A1 gene in patients with diagnosed dRTA that they use for heterologous experiments in vitro. They also use a dRTA mouse model with a different SLC4A1 mutation for experiments in mouse kidneys. Contrary to previous work that speculated dRTA was caused mainly by trafficking defects of kAE1, the authors observe that their new mutants (with the exception of Y413H) traffic and localize at least partly to the basolateral membrane of polarized heterologous mIMCD3 cells, an immortalized murine collecting duct cell line. They go on to show that the remaining mutants induce abnormalities in the expression of autophagy markers and increased numbers of autophagosomes, along with an alkalinized intracellular pH. They also reported that cells expressing the mutated kAE1 had increased mitochondrial content coupled with lower rates of ATP synthesis. The authors also observed a partial rescue of the effects of kAE1 variants through artificially acidifying the intracellular pH. Taken together, this suggests a mechanism for dRTA independent of impaired kAE1 trafficking and dependent on intracellular pH changes that future studies should explore.

Strengths:

The authors corroborate their findings in cell culture with a well characterized dRTA KI mouse and provide convincing quantification of their images from the in vitro and mouse experiments. The data largely support the claims as stated. Some of the mutants induce different strengths of effects on autophagy and the various assays than others, and it is not clear why this is from the data in the manuscript. The authors provide discussion of potential reasons for these differences that future studies could explore.

Weaknesses:

The pH effects of their mutants are only explored in vitro, and the in vitro system has a number of differences from a living mouse kidney or ex vivo kidney slice.

Author response:

The following is the authors’ response to the original reviews.

Public Reviews:

Reviewer #1 (Public review):

Summary: 

This study is an evaluation of patient variants in the kidney isoform of AE1 linked to distal renal tubular acidosis. Drawing on observations in the mouse kidney, this study extends findings to autophagy pathways in a kidney epithelial cell line. 

Strengths: 

Experimental data are convincing and nicely done.

Thank you

Weaknesses: 

Some data are lacking or not explained clearly. Mutations are not consistently evaluated throughout the study, which makes it difficult to draw meaningful conclusions.

We have revised our manuscript to clarify some earlier explanations and provided rationale for focusing on specific variants throughout the study.

Reviewer #2 (Public review):

Context and significance: 

Distal renal tubular acidosis (dRTA) can be caused by mutations in a Cl-/HCO3- exchanger (kAE1) encoded by the SLC4A1 gene. The precise mechanisms underlying the pathogenesis of the disease due to these mutations are unclear, but it is thought that loss of the renal intercalated cells (ICs) that express kAE1 and/or aberrant autophagy pathway function in the remaining ICs may contribute to the disease. Understanding how mutations in SLC4A1 affect cell physiology and cells within the kidney, a major goal of this study, is an important first step to unraveling the pathophysiology of this complex heritable kidney disease. 

Summary: 

The authors identify a number of new mutations in the SLC4A1 gene in patients with diagnosed dRTA that they use for heterologous experiments in vitro. They also use a dRTA mouse model with a different SLC4A1 mutation for experiments in mouse kidneys. Contrary to previous work that speculated dRTA was caused mainly by trafficking defects of kAE1, the authors observe that their new mutants (with the exception of Y413H, which they only use in Figure 1) traffic and localize at least partly to the basolateral membrane of polarized heterologous mIMCD3 cells, an immortalized murine collecting duct cell line. They go on to show that the remaining mutants induce abnormalities in the expression of autophagy markers and increased numbers of autophagosomes, along with an alkalinized intracellular pH. They also reported that cells expressing the mutated kAE1 had increased mitochondrial content coupled with lower rates of ATP synthesis. The authors also observed a partial rescue of the effects of kAE1 variants through artificially acidifying the intracellular pH. Taken together, this suggests a mechanism for dRTA independent of impaired kAE1 trafficking and dependent on intracellular pH changes that future studies should explore. 

Strengths: 

The authors corroborate their findings in cell culture with a well-characterized dRTA KI mouse and provide convincing quantification of their images from the in vitro and mouse experiments

Thank you  

Weaknesses: 

The data largely support the claims as stated, with some minor suggestions for improving the clarity of the work. Some of the mutants induce different strengths of effects on autophagy and the various assays than others, and it is not clear why this is from the present manuscript, given that they propose pHi and the unifying mechanism

We have modified our manuscript to discuss the various strengths of the mutants and emphasize that alteration of cytosolic pH by kAE1 variants may not be the only mechanism leading to dRTA.  

Reviewer #3 (Public review):

Summary: 

The authors have identified novel dRTA causing SLC4A1 mutations and studied the resulting kAE1 proteins to determine how they cause dRTA. Based on a previous study on mice expressing the dRTA kAE1 R607H variant, the authors hypothesize that kAE1 variants cause an increase in intracellular pH, which disrupts autophagic and degradative flux pathways. The authors clone these new kAE1 variants and study their transport function and subcellular localization in mIMCD cells. The authors show increased abundance of LC3B II in mIMCD cells expressing some of the kAE1 variants, as well as reduced autophagic flux using eGFP-RFP-LC3. These data, as well as the abundance of autophagosomes, serve as the key evidence that these kAE1 mutants disrupt autophagy. Furthermore, the authors demonstrate that decreasing the intracellular pH abrogates the expression of LC3B II in mIMCD cells expressing mutant SLC4A1. Lastly, the authors argue that mitochondrial function, and specifically ATP synthesis, is suppressed in mIMCD cells expressing dRTA variants and that mitochondria are less abundant in AICs from the kidney of R607H kAE1 mice. While the manuscript does reveal some interesting new results about novel dRTA causing kAE1 mutations, the quality of the data to support the hypothesis that these mutations cause a reduction in autophagic flux can be improved. In particular, the precise method of how the western blots and the immunofluorescence data were quantified, with included controls, would enhance the quality of the data and offer more supportive evidence of the authors' conclusions. 

Strengths: 

The authors cloned novel dRTA causing kAE1 mutants into expression vectors to study the subcellular localization and transport properties of the variants. The immunofluorescence images are generally of high quality, and the authors do well to include multiple samples for all of their western blots.

Thank you

Weaknesses: 

Inconsistent results are reported for some of the variants. For example, R295H causes intracellular alkalinization but also has no effect on intracellular pH when measured by BCECF. The authors also appear to have performed these in vitro studies on mIMCD cells that were not polarized, and therefore, the localization of kAE1 to the basolateral membrane seems unlikely, based upon images included in the manuscript. Additionally, there is no in vivo work to demonstrate that these kAE1 variants alter intracellular pH, including the R607H mouse, which is available to the authors. The western blots are of varying quality, and it is often unclear which of the bands are being quantified. For example, LAMP1 is reported at 100kDa, the authors show three bands, and it is unclear which one(s) are used to quantify protein abundance. Strikingly, the authors report a nonsensical value for their quantification of LCRB II in Figure 2, where the ratio of LCRB II to total LCRB (I + II) is greater than one. The control experiments with starvation and bafilomyocin are not supportive and significantly reduce enthusiasm for the authors' findings regarding autophagy. There are labeling errors between the manuscript and the figures, which suggest a lack of vigilance in the drafting process.

The R295H variant was identified in a dRTA patient and as such, it was important to report it. However, this is the first mutation located in the amino-terminus of the protein, which may be involved in protein-protein interactions, so other mechanisms may cause dRTA for this variant. We have therefore modified our manuscript to state that alteration of cytosolic pH may not be the only mechanism leading to dRTA. At this time, we are not able to measure cytosolic pH in vivo and hope to be able to do it in the future.

In our revised manuscript, we also show cell surface biotinylation results supporting that plasma membrane abundance of the kAE1 S525F and R589H variants is not significantly different than WT in non-polarized mIMCD3 cells (Figure 3 A&B), in line with the predominant basolateral localization of the variants in polarized cells (Figure 1C). Therefore, these two mutant proteins are not mis-trafficked in non-polarized cells.  Finally, we have clarified which bands have been used for quantification and corrected quantifications (including ratio measurements).

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

(1) R295H is recessively inherited, whereas Y413H is dominantly inherited: this is interesting and may be linked to their cellular expression and function. Is this information known for the other mutations examined in this study? 

The S25F and R589H dRTA variants have both been reported to exhibit autosomal dominant inheritance. This information is now updated in lines 146 and 158-159.

(2) R589H expression levels are evaluated in the Western blot of Figure 1, but localization and activity are not examined in Figure 2. However, R589H is included in autophagy experiments shown in later figures. Similarly, mutant R607H is the subject of several experiments further into the manuscript, but no initial analysis is provided for this variant. 

Protein abundance and localization of the R589H mutant in mIMCD3 cells have been shown in our previous publication in Supplementary Fig 5D and Supplementary Fig 2J [1]. This now indicated on lines 158-159. Our previous paper also presented a detailed study of the R607H dRTA mutant, the mouse model corresponding to the human R589H mutation. This is now indicated on lines 70, 118-119 and 180. The present study builds upon those published findings.

(3) This inconsistency is confusing, detracts from the usefulness of the study, and makes the comparative analysis of mutations incomplete. It is difficult to extrapolate from published studies in MDCK1 cells, which show different results on trafficking. 

The mIMCD3 cell line, which more closely resembles the physiology of the mouse collecting duct than MDCK cells, was selected for this study and our previous one [1]. Accordingly, the results obtained are better aligned with in vivo evidence. In contrast, differences in mutant protein expression and localization observed in other cell lines, like the MDCK cells, are likely attributable to differences in their cellular origin. 

(4) In Figure 2, could the authors explain why total LC3B is graphed for the data shown in mouse lysates, whereas the ratio of bands is analysed for cell lysates? Both sets of data show the two LC3B bands.

Total LC3B levels were significantly increased in the mutant compared to WT; however, no significant difference was observed in the lipidation ratio. For this reason, that graph is not shown in the main paper but has been included in the Supplementary Figure 1D. 

(5) In Figure 3, representative fluorescence images should be shown for all cell lines.

We have now included representative immunofluorescence images for all cell lines in Figure 3C.

(6) pH effects: Suggest that steady state pHi (Figure 3E) and rate of alkalization (Figure 1F) would be more effective together in Figure 1. The authors should show data for the effect of nigericin on cytoplasmic pH in Figure 3. If the rate of alkalinization in the mutant cells is reduced, shouldn't the intracellular steady state pH be more acidic? A cartoon depicting the transporter activity in the cell and the expected changes in pHi would be helpful. Is there a way to activate/inhibit NHE1 and rescue the effect of the mutant kAE1? It is unclear if the link between the mutant kAE1 and mitochondrial ATP production is a consequence of the intracellular pH or an indirect effect.

We opted to keep the effect of nigericin on pHi in Supplementary Fig1A given that Figure 3 already contains 11 panels. Also, in intercalated cells, the kAE1 protein physiologically exports 1 molecule of bicarbonate in exchange of 1 chloride ion import hence a reduced transport activity would result in a more alkaline intracellular pH. To clarify this point, we have included a diagram in Figure 1E as suggested. However, to calculate the rate of intracellular alkalinisation, the transporter is functioning in the opposite direction, i.e. extruding chloride and importing bicarbonate (see methods protocol for transport assay). Therefore, in this assay (Figure 1G), a defective chloride/bicarbonate activity results in a reduced rate of intracellular alkalinisation rate. This is now explained on lines 169-172.

Disruption of NHE1 function would impair sodium homeostasis and as such, potentially affect the activity of other proteins associated with acid-base balance and autophagy in collecting duct cells. Therefore, any resulting effects may not be confidently attributed specifically to the mutant kAE1. With nigericin, we aimed to alter pHi while affecting the least possible other ion concentration. Due to space considerations, Figure 1 has been reorganised to include the rate of alkalinisation and pHi (panels F and G). 

Reviewer #2 (Recommendations for the authors):

(1) The authors could improve the readability of this manuscript for a general audience by clarifying and summarizing the respective phenotype(s)/effect(s) of the different mutants in some kind of table in the main figures. It is hard to keep track of the different disease mutants alongside the KI mouse mutations, as the text frequently discusses multiple mutants at a time. 

As requested, we added two tables (Supplementary Tables 1 & 2) in Supplementary files summarizing the data obtained in this study. We hope this will help the readership to keep track of each variant’s phenotype.

(2) The subtitle of the results section of Figure 2 should be reworded to reflect that  whole kidney lysates are used for the KI mice and not the other mutants.

As requested, the title in the Results section has been modified (lines 178-179).

(3) More discussion of why the different mutants cause different strengths of phenotypes should be included.

Different variants induce different degree of functional defects as seen in Figure 1F & G. The kAE1 R295H, the only amino acid substitution in the amino-terminal cytosol causing dRTA, does not affect the transporter’s function or cells’ pHi. Therefore, this variant may cause dRTA via a different pathway than transport-defective S525F or partially inactive R589H variants that both affect pHi. Our study does not exclude that dRTA may be caused by other defects than pHi alterations, including defective proteinprotein interactions. This discussion is now included in the manuscript on lines 386-391.

Reviewer #3 (Recommendations for the authors):

In general, I found the subject matter of this manuscript interesting and of value to the scientific community. The interpretation of the data and how much it supports the conclusion that "kAE1 variants increases pHi which alters mitochondrial function and leads to reduced cellular energy levels that eventually attenuate energy-dependent autophagic pathways" is largely incomplete. There are significant concerns about the quantification of Western blot data. Additionally, including the R607H variant in the in vitro experiments would improve the interpretation and extrapolation of in vitro data to the kidney.

We apologize for the confusion with R589H and R607H variants. The R607H mutant is the murine ortholog to the human R589H dRTA variation. To clarify this, we have added this information on line 180, in addition to lines 118-119 and line 70.

Suggestions:

(1) Can an anion replacement experiment be performed in the mIMCD cells (no Cl or no HCO3) to determine that bicarbonate transport through AE1 is responsible for the reduced ATP rates in Figure 5? Inclusion of WT +dox control would be helpful to convince the reader of the effects.

Because Seahorse real-time cell metabolism ATP rates measurements require specific and patented buffers with un-specified compositions, it was not possible to modify the Cl⁻ or HCO₃⁻ content during the ATP measurement assay. All cell lines, including empty vector cells (EV) were treated with doxycycline; thus, WT + dox was already included. The empty vector cell line treated with doxycycline allowed the exclusion of specific effects of doxycycline on mitochondrial activity as a control. This is now clarified in Figure 5 legend, lines 655-656.

(2) Can the authors measure pHi in fresh kidney sections from the R607H mouse?

Unfortunately, we are not currently able to measure pHi in fresh kidney sections and although we recognize it would benefit greatly to our study, establishing a new collaboration to perform this measurement would significantly delay the publication of this work; therefore, these results will not be available for the present manuscript. 

(3) Does pH 7.0 media have any effect on autophagy, as shown in Figure 3? Why was pH 6.6 selected?

The idea was to artificially acidify pHi in mutant cell lines (that have a steady state alkaline pHi) and assess whether this acidification corrects autophagy defects. We first determined that incubation in cell culture medium at pH 6.6 with 0.033 µM nigericin (final potassium concentration: 168 mM) for 2 hours provided optimal conditions, i.e. ensuring cell viability over the 2-hour period while effectively lowering intracellular pH to 6.9, as demonstrated in Supplementary Figure 1A-C.

(4) In vitro experiments should be performed on polarized cells with kAE1 properly inserted in the basolateral membrane. Experiments on subconfluent, non-polarized cells do not support the hypothesis that transport functions of AE1 initiate the cascade of events attributed to these SLC4A1 mutations.

To address this point, we have performed cell surface biotinylations on 70-80 % confluent mIMCD3 cells expressing kAE1 WT, S525F or R589H mutants and show that cell surface abundance of the mutants is not significantly different from the WT protein. This is now shown in Figure 3 A&B. As cell surface biotinylation provides a more quantitative assessment of protein cell surface abundance, we have removed the immunofluorescence images from non-polarised cells and replaced them with representative immunoblots from a cell surface biotinylation assay.

Concerns:

(1) No information about the B1 ATPase antibody used.

Now provided in Supplementary Material, ATP6V1B1 Antibody from Bicell cat#20901.

(2) No actin band in Figure 1E (as prepared).

Actin bands are provided for each blot in Figure 1D.

(3) Figures 1E and 1F are labelled wrong in the figure versus the results section. 

Thank you for letting us know, this is now corrected.

(4) The cortical sections shown in Figure 4 for the KI/KI do not appear to have the morphology of a CCD. The authors may want to consider including glomeruli to convince the reader of the localization of the tubules. Same concern with Figure 5G and I. The WT image in 5G does not have the morphology of a CCD. Principal cells should be predominant, and ICs should be dispersed.

Both figures 4 and 5 have been updated with images showing glomeruli (light blue “G” on figure) with neighbour and dispersed IC staining.

(5) The quantification of LAMP1 in Figure 4 is unclear. How did the authors determine the boundary of AICs, and how did they calculate the volume of lysosomes? If a zstack was used, how are the authors sure that their 10um section includes the entire AIC?

The quantification of LAMP1 is detailed under “Image analysis”, then “Volocity” sections in Supplementary Material. The boundary of A-IC was manually detected in Volocity based on the presence of the H⁺-ATPase before Volocity analysis for lysosomal volume as described in the Methods.

The 10 micron sections are expected to include full AIC as well as partial AIC, but the frequency of these events should be the same between WT and variants’ sections, therefore they were all included in the analysis if cells displayed H⁺-ATPase signal. 

(6) Figure 5: There is no description of how ATP rates are calculated from the provided traces.

We used Agilent Seahorse XF ATP rate assay kit for this experiment. In this assay, the total ATP rate is the sum of ATP production rate from both glycolysis and oxidative phosphorylation. Glycolysis releases protons in a 1:1 ratio with ATP hence the glycolytic ATP rate is calculated from the glycolytic proton efflux rate (glycoPER). GlycoPER is determined by subtracting respiration linked proton efflux from total proton efflux by inhibiting complex I and III. This information is now added to Supplementary Material, in the “Metabolic Flux analysis” section.

(7) Figure labels in Figure 5 are wrong. It seems 5H (as presented) should actually be labeled 5G. In 5H (G?), why did some cells not have any TOM20 pixel intensity for S525F and R589H variants?

Confocal image acquisition in this experiment was kept under the same settings to allow comparison between samples. Therefore, some cells show dimer fluorescence than others. From the figure 5 panels, all cells showed TOM 20 pixel intensity. Figure 5H panel has been relabelled Figure 5G.

(8) In Figure 2, the summary graphs show analysis of more samples than are visible on the included western blots. What is the rationale for this? Why does S525F have 9 samples in BafA1 while R295H only has 3 (2H)? Yet, R295H has 6 samples in 2I. In 2D, S525F has at least 9 samples. Explain.

Figure 2A-C shows representative immunoblots, among several ones independently conducted. Therefore, the final number of samples is higher than showed on Figure 2. This is now indicated in Figure 2 legend, line 603. It became clear quite early in our study that the recessive kAE1 R295H variant does not behave similarly to the other variants studied, maybe because it affects the cytosolic domain, so we did not perform as many replicates for this variant as we did for the others. However, we felt it was valuable to the research community to report the characterization of this variant and decided to keep it in our study. 

(9) In general, the actin loading does not appear to be equal between samples. And some figures show the same actin blot twice (2A, C) while some show independent actin bands for LC3B and p62. Equal loading seems a fairly significant control, considering the importance of quantification in the figures.

In addition to performing protein assays, we systematically conduct immunoblot with anti-b-actin antibody to control for loading variability. When possible, two or three proteins, including actin, are detected on the same blot, when molecular weight differ enough. This sometimes results in b-actin being used as a loading control for two different proteins, as seen on Figure 2A and 2C. This is now indicated on lines 605606.

(10) In the Supplemental Figure 2, which band is being quantified for mature CTSD at 33kDa? Same for intermediate CTSD. The quantification of V-ATPase seems questionable based on the actin variance shown in the blot. Surely the ratio of the fourth sample is greater than 1.

Supplementary Figure 2 has been updated to include arrows indicating which band was selected for the quantification. After verifying the measurements of band intensities from “Image Lab” quantification software, we confirm the results, including that fourth KI/KI sample has a ratio of 0.78 (Adj Total Band Vol (Int), lanes 10). Screen shots of quantifications are attached below.

Author response image 1.

Author response image 2.

(11) Why are the experiments performed on non-confluent IMCD cells? Figure 1D shows good basolateral localization of AE1, yet the other experiments in the manuscript appear to use IMCD cells in low confluent states, without proper localization of AE1. Figure 3A shows AE1 dispersed throughout the cytoplasm. Why have the authors decided to study the effects of an anion exchanger without it being properly localized to the basolateral membrane? Shouldn't all experiments be performed in polarized IMCDs? If AE1 isnt properly in the membrane, and the cells do not have defined apico-basolateral polarity, then what role can AE1-mediated intracellular pH change have on the results of the experiments? Were the pHi experiments in 3E performed on polarized cells? Or even 1F?

To address this point, we have performed cell surface biotinylations on 70-80 % confluent mIMCD3 cells expressing kAE1 WT, S525F or R589H mutants and show that cell surface abundance of the mutants is not significantly different from the WT protein. This is now shown in Figure 3A & B. As it provides a more quantitative assessment of protein cell surface abundance, we have removed the immunofluorescence images from non-polarised cells and replaced them with a representative immunoblot from a cell surface biotinylation assay.

(12) As mentioned in the public comments, how is the ratio A/(A+B) greater than 1? With A and B > 0. In Figure 3, the data is reasonable, but in Figure 2, the data is simply impossible. What is the explanation for this phenomenon? Why was this presentation of data approved? Is it supposedly a fold of WT, like 2K and 2L? Is the reader also to believe that total LC3B is 2-fold greater in KI/KI mice, as shown in 2K? My eyes, though not densitometry equipment, cannot confirm this. The actin bands are not equal. Yet again, there are 4 lanes of KI/KI mice, but the quantification shows 5 samples.

The ratios in figure 2D, 2F, 2H and 2L have been re-calculated and corrected. As indicated above, immunoblots are representative and quantification of additional blots has been included in the graphs.

(12) Spelling error Figure 4B: cels.

Corrected

References 

(1) Mumtaz, R. et al. Intercalated Cell Depletion and Vacuolar H+-ATPase Mistargeting in an Ae1 R607H Knockin Model. Journal of the American Society of Nephrology 28, 1507–1520 (2017).

Author response:

The following is the authors’ response to the original reviews.

Public Reviews:

Reviewer #1 (Public review):

Lahtinen et al. evaluated the association between polygenic scores and mortality. This question has been intensely studied (Sakaue 2020 Nature Medicine, Jukarainen 2022 Nature Medicine, Argentieri 2025 Nature Medicine), where most studies use PRS as an instrument to attribute death to different causes. The presented study focuses on polygenic scores of non-fatal outcomes and separates the cause of death into "external" and "internal". The majority of the results are descriptive, and the data doesn't have the power to distinguish effect sizes of the interesting comparisons: (1) differences between external vs. internal (2) differences between PGI effect and measured phenotype. I have two main comments:

(1) The authors should clarify whether the p-value reported in the text will remain significant after multiple testing adjustment. Some of the large effects might be significant; for example, Figure 2C

We have now added Benjamini-Hochberg multiple-testing adjusted p-values in the text each time we present nominal p-values. Additionally, supplementary tables S5 and S6 provide multiple-adjusted p-values for all analysed PGIs.

Although this was not always the case, many comparisons remained significant after multiple testing adjustments, especially in Figure 2C that the reviewer commented on. In the revised version, we have placed more emphasis on describing these HRs that have low p-values after multiple-test adjustment. The revised text for Figure 2C in the Results section now reads:

Panel C analyses mortality in three age-specific follow-up periods. The PGIs were more predictive of death in younger age groups, although the difference between the 25–64 and 65–79 age groups was small, except for the PGI of ADHD (HR=1.14, 95% CI 1.08; 1.21 for 25–64-year-olds; HR=1.04, 95% CI 1.00; 1.08 for 65–79-year-olds; p=0.008 for difference, p=0.27 after multiple-testing adjustment). PGIs predicted death only negligibly among those aged 80+, and the largest differences between the age groups 25–64 and 80+ were for PGIs of self-rated health (HR 0.87, 95% CI 0.82; 0.93 for 25–64-year-olds, HR 1.00, 95% CI 0.94; 1.04 for 80+ year-olds, p=2*10^-4 for difference, p=0.006 after multiple-testing adjustment), ADHD (HR 1.14, 95% CI 1.08; 1.21 for 25–64-year-olds, HR 0.99, 95% CI 0.95; 1.03 for 80+ year-olds, p=7*10^-4 for difference, p=0.012 after multiple-testing adjustment) and depressive symptoms (HR 1.12, 95% CI 1.06; 1.18 for 25–64-year-olds, HR 1.00, 95% CI 0.96; 1.04 for 80+ year-olds, p=0.002 for difference, p=0.032 after multiple-testing adjustment). Additionally, the difference in HRs between these age groups achieved significance after multiple testing adjustment at the conventional 5% level for PGIs of cigarettes per day, educational attainment, and ever smoking.

We have also included the recent study by Argentieri et al. (2025) in the literature review, which was missing from our previous version. We appreciate the reference. Other references mentioned were already included in the previous version of the manuscript.

(note that the small prediction accuracy of PGI in older age groups has been extensively studied, see Jiang, Holmes, and McVean, 2021, PLoS Genetics).

We would like to thank the reviewer for suggesting the relevant reference by Jiang et al. We have now expanded on the discussion of age-specific differences in the discussion section and included this reference.

(2) The authors might check if PGI+Phenotype has improved performance over Phenotype only. This is similar to Model 2 in Table 1, but slightly different.

The reviewer raises an interesting angle to approach the analysis. We have now added an analysis assessing the information criteria and the significance of improvement between nested models in Supplementary table S8. All the tested PGI+phenotype models show improvement over the phenotype-only model that is statistically significant at all conventional levels when tested by likelihood-ratio tests between nested models . Additionally,  improvement was found when using Akaike and Bayesian (Schwarz) information criteria (albeit sometimes modest in size). We have added a passage in the results section briefly summarising this analysis:

Supplementary table S8 presents information criteria and significance tests on corresponding models. Models with PGI+phenotype (Models 2a–f) showed improvement over models with the phenotype only (Models 1a, 1c, 1e, 1g, 1i, 1k, with a p=0.0006 or lower) in terms of both Akaike information criterion (AIC) as well as Bayesian (Schwarz) information criterion (BIC) with a p=0.0006 or lower in all comparisons. The full Model 4 again showed improvement over the model with all PGIs jointly (Model 3b, with a p=0.0002 or p=0.00002, depending on continuous/categorical phenotype measurement), which had a lower AIC but not BIC.

Reviewer #2 (Public review): 

Summary:

This study provides a comprehensive evaluation of the association between polygenic indices (PGIs) for 35 lifestyle and behavioral traits and all-cause mortality, using data from Finnish population- and family-based cohorts. The analysis was stratified by sex, cause of death (natural vs. external), age at death, and participants' educational attainment. Additional analyses focused on the six most predictive PGIs, examining their independent associations after mutual adjustment and adjustment for corresponding directly measured baseline risk factors.

Strengths:

Large sample size with long-term follow-up.

Use of both population- and family-based analytical approaches to evaluate associations.

Weaknesses:

It is unclear whether the PGIs used for each trait represent the most current or optimal versions based on the latest GWAS data.

To our reading, this comment is closely related to the “recommendations for the author” number 3 by reviewer 2, and we thus address them together. 

If the Finnish data used in this study also contributed to the development of some of the PGIs, there is a risk of overestimating their associations with mortality due to overfitting or "double-dipping." Similar inflation of effect sizes has been observed in studies using the UK Biobank, which is widely used for PGI construction.

To our reading, this comment is closely related to the “recommendations for the author” 4 by reviewer 2, and we thus address them together.

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

Specific comments:

(1) Cited reference 1 also investigated the PRS association with life span; cited reference 8 explains PRS association with healthy lifespan. Can authors be clearer about what is new in the context of these references? Specifically, what are the PGIs studied here that were not analyzed in the cited analyses?

Although some previous studies on the topic do exist, our analysis arguably has novelty in touching upon several unstudied or scarcely studied themes. These include:

A set of PGIs focusing on social, psychological, and behavioural phenotypes or PGIs for typically non-fatal health conditions.

An assessment of direct genetic effects/ confounding with a within-sibship design.

An assessment of potential heterogeneous effects by several socio-demographic characteristics.

An analysis of external causes of deaths (which can be hypothesised to be particularly relevant here, given the choice of our PGIs not focusing directly on typical causes of death).

A detailed assessment of the interplay of the most predictive PGIs with their corresponding phenotypes.

We have substantially revised the Introduction section focusing on making these novel contributions more explicit.

(2) In the Methods section, it is not very clear why the authors specifically study the "within-sibship" samples. Is this for avoiding nurturing effects from parental genotypes or for controlling assortative mating? The authors should clarify the rationale behind the design.

The substance-related rationale behind this approach was briefly discussed in the Introduction section while in the Methods section, we focused more on the technical description of our analyses. However, it is certainly worthwhile to clarify to the reader why within-sibship methods have been used. The revised passage in the methods section now states:

“In addition to this population sample, we used a within-sibship analysis sample to assess the extent of direct and indirect genetic associations captured by the PGIs, as discussed in the introduction.”

(3) Residual correlations of PGIs were no more than 0.050..." As a minor comment, since PGIs is a noisy variable, the correlation would be low; however, I don't think there are better ways to evaluate Cox assumptions, and in many cases, this assumption is not correct for strong predictors.

Yes, these points are true. Overall, it is often implausible that empirical distributions exactly match distributional assumptions in statistical models. For example, it may not be realistic to expect that the mortality hazards across categories of independent variables stay exactly proportional during long mortality-follow-ups; some deviations from constant proportions are almost inevitable. However, there are reasonable grounds to argue that in case of moderate violations of the proportional hazards assumption, the estimates still remain interpretable for practical uses. They can be read as approximating average relative hazards over the study period (for discussion, see pages 42–47 in Allison P. 2014. Event history and survival analysis: Regression for longitudinal event data (second edition). Thousand Oaks: SAGE).

(4) "PGI of ADHD (HR=1.08 95%CI 1.04;1.11 among men; HR=1.01 95%CI 0.97;1.05 among women; p=0.012 for difference)." Is this difference significant after multiple testing correction?

We have presented multiple-testing adjusted p-values together with nominal ones in this and in all other instances where they are mentioned in the text. Additionally, Supplementary tables S5–S6 present multiple-adjusted p-values for each PGIs studied.

(5) "Panel D displays that most PGIs had stronger associations with external (accidents, violent, suicide, and alcohol related deaths) than natural causes of death." Similar to the comment above, are there any results that are significantly different between internal and external?

We have added the p-values of those variables that had larger differences in the revised text. Quoting from the revised article: “The HR differences between external and natural causes of death were nominally significant at the conventional 5% level for cannabis use (p=0.016), drinks per week (p=0.028), left out of social activity (p=0.029), ADHD (p=0.031), BMI (p=0.035) and height (p=0.049), but none of these differences remained significant after adjusting for 35 multiple tests. “

(6) Table 1: The effect of the phenotype is stronger than the PGI; this is expected as PGI is a weak predictor and can be considered as "noised" measurement of true genetic value (Becker 2021 Nature Human behavior). Is there a way to adjust for the impact of noise in PGI at tagging genetic value and compare if the PGI effect is different from the phenotype effect?

PGIs are certainly imperfect measures that contain a lot of noise. However, extracting new information from what is unknown is an extremely demanding exercise, and still further complicated for example, by that we do not know the exact benchmark of total genetic effect we should be aiming at. Different methods of heritability estimation, for instance, often give dramatically differing results – for reasons that are still up to scrutiny.

We are thus not familiar with a method that could achieve satisfactory answer for this challenging task.

Reviewer #2 (Recommendations for the authors):

(3) Justification and Selection of PGIs:

For several traits, such as BMI, multiple polygenic indices (PGIs) are currently available. The criteria used to select specific PGIs for this study are not clearly described. A more systematic and reproducible approach-for example, leveraging metadata from the PGS Catalog-could strengthen the justification for PGI selection and enhance the study's generalizability.

There are numerous PGIs developed in the extensive GWAS literature, but a finite set of PGIs always needs to be chosen for any analysis. The rationale behind our decision to include every PGI from the repository of Becker et al. 2021 (full reference in the manuscript, see also https://www.thessgac.org/pgi-repository) that was available for the Finnish data (including the possibility to exclude overlapping samples, see our response to the next comment for more discussion) was to provide rigorous analysis by limiting the researchers degrees of freedom in arbitrarily choosing PGIs. Although it would have been tempting to not use some PGIs that were not expected to substantially correlate with mortality, we believe that our conservative strategy increases the credibility of the reported p-values, particularly the multiple adjustment should now work as intended. 

We also mention now this rationale when discussing the chosen PGIs in the methods section: “As the independent variables of main interest, we used 35 different PGIs in the Polygenic Index repository by Becker et al., which were mainly based on GWASes using UK Biobank and 23andMe, Inc. data samples, but also other data collections. They were tailored for the Finnish data, i.e., excluding overlapping individuals between the original GWAS and our analysis and performing linkage-disequilibrium adjustment. We used every single-trait PGI defined in the repository (except for subjective well-being, for which we were unable to obtain a meta-analysis version that excluded the overlapping samples). By limiting the researchers’ freedom in selecting the measures, this conservative strategy should increase the validity of our estimates, particularly with regards to multiple-testing adjusted p-values.”

(4) Overlap Between PGI Training Data and Study Sample:

The authors should describe any overlap between the data used to develop the PGIs and the current study sample. If such overlap exists, it may lead to overestimation of effect sizes due to "double-dipping." A discussion of this issue and its potential implications is warranted, as similar concerns have been raised in studies using UK Biobank data.

This is, fortunately, not a concern of our analysis. Overlapping samples were excluded in creating the PGIs that we used. We have now described this more clearly in the revised methods section.

(1) Clarify the Methodology for Family-Based Cox Analysis:

It is unclear what specific method was used to perform Cox regression in the family-based analysis. Please provide additional methodological details. ”

We have described the method further and added an additional reference in the revision. The text now stands:

“We compared these models to the corresponding within-sibship models, using the sibship identifier as the strata variable. This method employs a sibship-specific (instead of a whole-sample-wide baseline hazard in the population models) baseline hazard, and corresponds to a fixed-effects model in some other regression frameworks (e.g., linear model with sibship-specific intercepts)”

(2) Clarify Timing of Measured Risk Factors Relative to Follow-Up:

The main text should provide more detailed information regarding the timing of data collection for directly measured risk factors. Specifically, it should be clarified whether the measurements used correspond to the first available data for each individual after the start of follow-up, or if a different criterion was applied.

BMI, self-rated health, alcohol consumption and smoking status were measured at the baseline survey of each dataset. Education was registered as the highest completed degree up to the end of 2019. Depression was a composite of survey self-report (at the time of the baseline survey), as well as depression-related medicine purchases and hospitalizations over a two-year period before the start of the individual’s follow-up.

We have added more comprehensive information on the measurement of the phenotypes of interest in Supplementary table 2, including the timing of the measurement.

significant quote to reference

historiography on welsh seaside resorts were originally sprase despite their huge presence

the focus is usually only on the docks - the industrial aspects are looked at but not the leisure aspect

This section made me realize that storing personal data on social media is not just a technical question, but also an ethical one. For example, age can be stored as a number, but platforms still need to decide how precise it should be and how it might be used or misused. It also made me question whether some data, like exact address, really needs to be stored at all given the privacy risks.

In fact, I have always been puzzled about the collection of information such as "region" and "age". Is it really "necessary" for companies to collect such information? These pieces of information do not guarantee that the account is used by a real person - fake accounts can also randomly generate combinations of these pieces of information, but it will increase the risk of user information leakage

I found the discussion about representing gender as data especially thoughtful, because it shows how technical design decisions can have real social consequences. Treating gender as a simple binary might make data easier to process, but it can erase people’s identities and experiences. I also like the idea of combining preset options with an “other” field, since it balances inclusivity with the need for usable and consistent data.

I like how this example shows that even something that seems simple like a “data field” actually involves a lot of value judgments. Every way of storing gender has tradeoffs between inclusivity, usability, and data cleanliness, and there isn’t a purely technical solution. It also made me stop and think about whether collecting certain data is even necessary in the first place.

Exercising is time-consuming, but it is essential for a healthy lifestyle ...

The pixels that only have three color components have always made me really curious, as there is only green, blue,e and red, ed but once they are in a group,oup tcane to create a whole new different color that sometimes seems impossible. Additionally, one of the most intruiging thing about these grids is that with only these three colors, they can create the color white.

I find the discussion about the ambiguity of yesterday particularly insightful because it highlights how objective data like a timestamp is actually dependent on the observer's context, if a social media platform's automated system flags behavior based on a specific day, but that day starts and ends at different times for the user and the server. This creates a data friction that can lead to unfair outcomes, which indicates that information systems aren't neutral tools, they are specific temporal assumptions, and things might change quickly and might not reflect the lived experience of global users.

This clearly explains the use and importance of metadata. Although I often hear the term in computer science classes, I hadn’t fully understood why it is so important. In this context, I’ve learned that beyond the visible content in images, sounds, or videos, there is additional information such as time, location, or device type. This metadata may not interest the viewer directly but can be valuable for platform management, data analysts, or other stakeholders.

Bathing machines were a significantly good sign - used for ladies to change and bath - it wasn't just a rough plae but a place where ladies could bathe and feel safe

idk need to waffle but brain cant lol

Highlights the leisure too - these were not tourists but residents. seaside resorts also became a place of genral recreation like the big parks in london - this is something mitskell doesn't highlight, but could be due to the resorts purpose moreso as a high-class resort - it still woulda had workers in the town tho

Unlike Mitskell's choice of case study, Croll's decision of Barry has clear differences, it alludes greater to the impact of external factors like landowners on the relationship between industrialisation and tourism, with Lord Windsor, upon his purchase of Barry Island, Croll notes, banning visitors from the Island and prohibiting the becoming industrialisation of the Island. As such, Croll's choice of case study is interesting, and broadens the (complexities) of studying Welsh seaside resorts further. Through the case study, he suggests how landowners often decided the nature of the relationship between industrialisation and leisure, with the ammenities required for each at the whim of (blah)

like mitskell, highlights the importance of the railway in the influx of tourism. Both authors draw a clear link between this industrial development and the development of tourism. This concept of the connecting power of railway is greater developed by (blah) as he notes how this then connected the industrial workers of the rhondda valleys to Barry. This further suggests a strong relationship between industry and leisure. Industrialisation had facilitated a new working (), which saw disposable income increase for many, while industrial action encouraged parliamentary acts such as the (factory act and bank holiday acts with dates) which increased the free-time that workers could use to engage in the leisure industry, resorts like swansea and Barry, as both authors note, becoming places to do it (altho swansea's clientele was a little more posh

Reviewer #1 (Public review):

Summary:

Carloni et al. comprehensively analyze which proteins bind repetitive genomic elements in Trypanosoma brucei. For this, they perform mass spectrometry on custom-designed, tagged programmable DNA-binding proteins. After extensively verifying their programmable DNA-binding proteins (using bioinformatic analysis to infer target sites, microscopy to measure localization, ChIP-seq to identify binding sites), they present, among others, two major findings: 1) 14 of the 25 known T. brucei kinetochore proteins are enriched at 177bp repeats. As T. brucei's 177bp repeat-containing intermediate-sized and mini-chromosomes lack centromere repeats but are stable over mitosis, Carloni et al. use their data to hypothesize that a 'rudimentary' kinetochore assembles at the 177bp repeats of these chromosomes to segregate them. 2) 70bp repeats are enriched with the Replication Protein A complex, which, notably, is required for homologous recombination. Homologous recombination is the pathway used for recombination-based antigenic variation of the 70bp-repeat-adjacent variant surface glycoproteins.

Strengths and Weaknesses:

The manuscript was previously reviewed through Review Commons. As noted there, the experiments are well controlled, the claims are well supported, and the methods are clearly described. The conclusions are convincing. All concerns I raised have been addressed except one (minor point #8):

"The way the authors mapped the ChIP-seq data is potentially problematic when analyzing the same repeat type in different genomic regions. Reads with multiple equally good mapping positions were assigned randomly. This is fine when analyzing repeats by type, independent of genomic position, which is what the authors do to reach their main conclusions. However, several figures (Fig. 3B, Fig. 4B, Fig. 5B, Fig. 7) show the same repeat type at specific genomic locations." Due to the random assignment, all of these regions merely show the average signal for the given repeat. I find it misleading that this average is plotted out at "specific" genomic regions.<br /> Initially, I suggested a workaround, but the authors clarified why the workaround was not feasible, and their explanation is reasonable to me. That said, the figures still show a signal at positions where they can't be sure it actually exists. If this cannot be corrected analytically, it should at least be noted in the figure legends, Results, or Discussion.

Importantly, the authors' conclusions do not hinge on this point; they are appropriately cautious, and their interpretations remain valid regardless.

Significance:

This work is of high significance for chromosome/centromere biology, parasitology, and the study of antigenic variation. For chromosome/centromere biology, the conceptual advancement of different types of kinetochores for different chromosomes is a novelty, as far as I know. It would certainly be interesting to apply this study as a technical blueprint for other organisms with mini-chromosomes or chromosomes without known centromeric repeats. I can imagine a broad range of labs studying other organisms with comparable chromosomes to take note of and build on this study. For parasitology and the study of antigenic variation, it is crucial to know how intermediate- and mini-chromosomes are stable through cell division, as these chromosomes harbor a large portion of the antigenic repertoire. Moreover, this study also found a novel link between the homologous repair pathway and variant surface glycoproteins, via the 70bp repeats. How and at which stages during the process, 70bp repeats are involved in antigenic variation is an unresolved, and very actively studied, question in the field. Of course, apart from the basic biological research audience, insights into antigenic variation always have the potential for clinical implications, as T. brucei causes sleeping sickness in humans and nagana in cattle. Due to antigenic variation, T. brucei infections can be chronic.

Comments on revised version:

All my recommendations have been addressed.

Author response:

Point-by-point description of the revisions:

Reviewer #1 (Evidence, reproducibility and clarity):

Summary

In this article, the authors used the synthetic TALE DNA binding proteins, tagged with YFP, which were designed to target five specific repeat elements in Trypanosoma brucei genome, including centromere and telomeres-associated repeats and those of a transposon element. This is in order to detect and identified, using YFP-pulldown, specific proteins that bind to these repetitive sequences in T. brucei chromatin. Validation of the approach was done using a TALE protein designed to target the telomere repeat (TelR-TALE) that detected many of the proteins that were previously implicated with telomeric functions. A TALE protein designed to target the 70 bp repeats that reside adjacent to the VSG genes (70R-TALE) detected proteins that function in DNA repair and the protein designed to target the 177 bp repeat arrays (177R-TALE) identified kinetochore proteins associated T. brucei mega base chromosomes, as well as in intermediate and mini-chromosomes, which imply that kinetochore assembly and segregation mechanisms are similar in all T. brucei chromosome.

Major comments:

Are the key conclusions convincing?

The authors reported that they have successfully used TALE-based affinity selection of proteinassociated with repetitive sequences in the T. brucei genome. They claimed that this study has provided new information regarding the relevance of the repetitive region in the genome to chromosome integrity, telomere biology, chromosomal segregation and immune evasion strategies. These conclusions are based on high-quality research, and it is, basically, merits publication, provided that some major concerns, raised below, will be addressed before acceptance for publication.

(1) The authors used TALE-YFP approach to examine the proteome associated with five different repetitive regions of the T. brucei genome and confirmed the binding of TALE-YFP with Chip-seq analyses. Ultimately, they got the list of proteins that bound to synthetic proteins, by affinity purification and LS-MS analysis and concluded that these proteins bind to different repetitive regions of the genome. There are two control proteins, one is TRF-YFP and the other KKT2-YFP, used to confirm the interactions. However, there are no experiment that confirms that the analysis gives some insight into the role of any putative or new protein in telomere biology, VSG gene regulation or chromosomal segregation. The proteins, which have already been reported by other studies, are mentioned. Although the author discovered many proteins in these repetitive regions, their role is yet unknown. It is recommended to take one or more of the new putative proteins from the repetitive elements and show whether or not they (1) bind directly to the specific repetitive sequence (e.g., by EMSA); (2) it is recommended that the authors will knockdown of one or a small sample of the new discovered proteins, which may shed light on their function at the repetitive region, as a proof of concept.

The main request from Referee 1 is for individual evaluation of protein-DNA interaction for a few candidates identified in our TALE-YFP affinity purifications, particularly using EMSA to identify binding to the DNA repeats used for the TALE selection. In our opinion, such an approach would not actually provide the validation anticipated by the reviewer. The power of TALE-YFP affinity selection is that it enriches for protein complexes that associate with the chromatin that coats the target DNA repetitive elements rather than only identifying individual proteins or components of a complex that directly bind to DNA assembled in chromatin.

The referee suggests we express recombinant proteins and perform EMSA for selected candidates, but many of the identified proteins are unlikely to directly bind to DNA – they are more likely to associate with a combination of features present in DNA and/or chromatin (e.g. specific histone variants or histone post-translational modifications). Of course, a positive result would provide some validation but only IF the tested protein can bind DNA in isolation – thus, a negative result would be uninformative.

In fact, our finding that KKT proteins are enriched using the 177R-TALE (minichromosome repeat sequence) identifies components of the trypanosome kinetochore known (KKT2) or predicted (KKT3) to directly bind DNA (Marciano et al., 2021; PMID: 34081090), and likewise the TelR-TALE identifies the TRF component that is known to directly associate with telomeric (TTAGGG)n repeats (Reis et al 2018; PMID: 29385523). This provides reassurance on the specificity of the selection, as does the lack of cross selectivity between different TALEs used (see later point 3 below). The enrichment of the respective DNA repeats quantitated in Figure 2B (originally Figure S1) also provides strong evidence for TALE selectivity.

It is very likely that most of the components enriched on the repetitive elements targeted by our TALE-YFP proteins do not bind repetitive DNA directly. The TRF telomere binding protein is an exception – but it is the only obvious DNA binding protein amongst the many proteins identified as being enriched in our TelR-TALE-YFP and TRF-YFP affinity selections.

The referee also suggests that follow up experiments using knockdown of the identified proteins found to be enriched on repetitive DNA elements would be informative. In our opinion, this manuscript presents the development of a new methodology previously not applied to trypanosomes, and referee 2 highlights the value of this methodological development which will be relevant for a large community of kinetoplastid researchers. In-depth follow-up analyses would be beyond the scope of this current study but of course will be pursued in future. To be meaningful such knockdown analyses would need to be comprehensive in terms of their phenotypic characterisation (e.g. quantitative effects on chromosome biology and cell cycle progression, rates and mechanism of recombination underlying antigenic variation, etc) – simple RNAi knockdowns would provide information on fitness but little more. This information is already publicly available from genome-wide RNAi screens (www.tritrypDB.org), with further information on protein location available from the genome-wide protein localisation resource (Tryptag.org). Hence basic information is available on all targets selected by the TALEs after RNAi knock down but in-depth follow-up functional analysis of several proteins would require specific targeted assays beyond the scope of this study.

(2) NonR-TALE-YFP does not have a binding site in the genome, but YFP protein should still be expressed by T. brucei clones with NLS. The authors have to explain why there is no signal detected in the nucleus, while a prominent signal was detected near kDNA (see Fig.2). Why is the expression of YFP in NonR-TALE almost not shown compared to other TALE clones?

The NonR-TALE-YFP immunolocalisation signal indeed is apparently located close to the kDNA and away from the nucleus. We are not sure why this is so, but the construct is sequence validated and correct. However, we note that artefactual localisation of proteins fused to a globular eGFP tag, compared to a short linear epitope V5 tag, near to the kinetoplast has been previously reported (Pyrih et al, 2023; PMID: 37669165).

The expression of NonR-TALE-YFP is shown in Supplementary Fig. S2 in comparison to other TALE proteins. Although it is evident that NonR-TALE-YFP is expressed at lower levels than other TALEs (the different TALEs have different expression levels), it is likely that in each case the TALE proteins would be in relative excess.

It is possible that the absence of a target sequence for the NonR-TALE-YFP in the nucleus affects its stability and cellular location. Understanding these differences is tangential to the aim of this study.

However, importantly, NonR-TALE-YFP is not the only control for used for specificity in our affinity purifications. Instead, the lack of cross-selection of the same proteins by different TALEs (e.g. TelR-TALE-YFP, 177R-TALE-YFP) and the lack of enrichment of any proteins of interest by the well expressed ingiR-TALE-YFP or 147R-TALE-YFP proteins each provide strong evidence for the specificity of the selection using TALEs, as does the enrichment of similar protein sets following affinity purification of the TelR-TALE-YFP and TRF-YFP proteins which both bind telomeric (TTAGGG)n repeats. Moreover, control affinity purifications to assess background were performed using cells that completely lack an expressed YFP protein which further support specificity (Figure 6).

We have added text to highlight these important points in the revised manuscript:

Page 8:

“However, the expression level of NonR-TALE-YFP was lower than other TALE-YFP proteins; this may relate to the lack of DNA binding sites for NonR-TALE-YFP in the nucleus.”

Page 8:

“NonR-TALE-YFP displayed a diffuse nuclear and cytoplasmic signal; unexpectedly the cytoplasmic signal appeared to be in the vicinity the kDNA of the kinetoplast (mitochrondria). We note that artefactual localisation of some proteins fused to an eGFP tag has previously been observed in T. brucei (Pyrih et al, 2023).”

Page 10:

Moreover, a similar set of enriched proteins was identified in TelR-TALE-YFP affinity purifications whether compared with cells expressing no YFP fusion protein (No-YFP), the NonR-TALE-YFP or the ingiR-TALE-YFP as controls (Fig. S7B, S8A; Tables S3, S4). Thus, the most enriched proteins are specific to TelR-TALE-YFP-associated chromatin rather than to the TALE-YFP synthetic protein module or other chromatin.

(3) As a proof of concept, the author showed that the TALE method determined the same interacting partners enrichment in TelR-TALE as compared to TRF-YFP. And they show the same interacting partners for other TALE proteins, whether compared with WT cells or with the NonR-TALE parasites. It may be because NonR-TALE parasites have almost no (or very little) YFP expression (see Fig. S3) as compared to other TALE clones and the TRF-YFP clone. To address this concern, there should be a control included, with proper YFP expression.

See response to point 2, but we reiterate that the ingi-TALE -YFP and 147R-TALE-YFP proteins are well expressed (western original Fig. S3 now Fig. S2) but few proteins are detected as being enriched or correspond to those enriched in TelR-TALE-YFP or TRF-YFP affinity purifications (see Fig. S9). Therefore, the ingi-TALE -YFP and 147R-TALE-YFP proteins provide good additional negative controls for specificity as requested. To further reassure the referee we have also included additional volcano plots which compare TelR-TALE-YFP, 70R-TALE-YFP or 177R-TALE-YFP to the ingiR-TALE-YFP affinity selection (new Figure S8). As with No-YFP or NonR-TALE-YFP controls, the use of ingiR-TALE-YFP as a negative control demonstrates that known telomere associated proteins are enriched in TelR-TALE-YFP affinity purification, RPA subunits enriched with 70R-TALE-YFP and Kinetochore KKT poroteins enriched with 177RTALE-YFP. These analyses demonstrate specificity in the proteins enriched following affinity purification of our different TALE-YFPs and provide support to strengthen our original findings.

We now refer to use of No-YFP, NonR-TALE-YFP, and ingiR-TALE -YFP as controls for comparison to TelR-TALE-YFP, 70R-TALE-YFP or 177R-TALE-YFP in several places:

Page10:

“Moreover, a similar set of enriched proteins was identified in TelR-TALE-YFP affinity purifications whether compared with cells expressing no YFP fusion protein (No-YFP), the NonR-TALE-YFP or the ingiR-TALE-YFP as controls (Fig. S7B, S8A; Tables S3, S4).”

Page 11:

“Thus, the nuclear ingiR-TALE-YFP provides an additional chromatin-associated negative control for affinity purifications with the TelR-TALE-YFP, 70R-TALE-YFP and 177R-TALE-YFP proteins (Fig. S8).”

“Proteins identified as being enriched with 70R-TALE-YFP (Figure 6D) were similar in comparisons with either the No-YFP, NonR-TALE-YFP or ingiR-TALE-YFP as negative controls.”

Top Page 12:

“The same kinetochore proteins were enriched regardless of whether the 177R-TALE proteomics data was compared with No-YFP, NonR-TALE or ingiR-TALE-YFP controls.”

Discussion Page 13:

“Regardless, the 147R-TALE and ingiR-TALE proteins were well expressed in T. brucei cells, but their affinity selection did not significantly enrich for any relevant proteins. Thus, 147R-TALE and ingiR-TALE provide reassurance for the overall specificity for proteins enriched TelR-TALE, 70R-TALE and 177R-TALE affinity purifications.”

(4) After the artificial expression of repetitive sequence binding five-TALE proteins, the question is if there is any competition for the TALE proteins with the corresponding endogenous proteins? Is there any effect on parasite survival or health, compared to the control after the expression of these five TALEs YFP protein? It is recommended to add parasite growth curves, for all the TALE proteins expressing cultures.

Growth curves for cells expressing TelR-TALE-YFP, 177R-TALE-YFP and ingiR-TALE-YFP are now included (New Fig S3A). No deficit in growth was evident while passaging 70R-TALE-YFP, 147R-TALE-YFP, NonR-TALE-YFP cell lines (indeed they grew slightly better than controls).

The following text has been added page 8:

“Cell lines expressing representative TALE-YFP proteins displayed no fitness deficit (Fig. S3A).”

(5) Since the experiments were performed using whole-cell extracts without prior nuclear fractionation, the authors should consider the possibility that some identified proteins may have originated from compartments other than the nucleus. Specifically, the detection of certain binding proteins might reflect sequence homology (or partial homology) between mitochondrial DNA (maxicircles and minicircles) and repetitive regions in the nuclear genome. Additionally, the lack of subcellular separation raises the concern that cytoplasmic proteins could have been co-purified due to whole cell lysis, making it challenging to discern whether the observed proteome truly represents the nuclear interactome.

In our experimental design, we confirmed bioinformatically that the repeat sequences targeted were not represented elsewhere in the nuclear or mitochondrial genome (kDNA). The absence of subcellular fractionation could result in some cytoplasmic protein selection, but this is unlikely since each TALE targets a specific DNA sequence but is otherwise identical such that cross-selection of the same contaminating protein set would be anticipated if there was significant non-specific binding. We have previously successfully affinity selected 15 chromatin modifiers and identified associated proteins without major issues concerning cytoplasmic protein contamination (Staneva et al 2021 and 2022; PMID: 34407985 and 36169304). Of course, the possibility that some proteins are contaminants will need to be borne in mind in any future follow-up analysis of proteins of interest that we identified as being enriched on specific types of repetitive element in T. brucei. Proteins that are also detected in negative control, or negative affinity selections such as No-YFP, NoR-YFP, IngiR-TALE or 147R-TALE must be disregarded.

(6) Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?

As mentioned earlier, the author claimed that this study has provided new information concerning telomere biology, chromosomal segregation mechanisms, and immune evasion strategies. But there are no experiments that provides a role for any unknown or known protein in these processes. Thus, it is suggested to select one or two proteins of choice from the list and validate their direct binding to repetitive region(s), and their role in that region of interaction.

As highlighted in response to point 1 the suggested validation and follow up experiments may well not be informative and are beyond the scope of the methodological development presented in this manuscript. Referee 2 describes the study in its current form as “a significant conceptual and technical advancement” and “This approach enhances our understanding of chromatin organization in these regions and provides a foundation for investigating the functional roles of associated proteins in parasite biology.”

The Referee’s phrase ‘validate their direct binding to repetitive region(s)’ here may also mean to test if any of the additional proteins that we identified as being enriched with a specific TALE protein actually display enrichment over the repeat regions when examined by an orthogonal method. A key unexpected finding was that kinetochore proteins including KKT2 are enriched in our affinity purifications of the 177R-TALE-YFP that targets 177bp repeats (Figure 6F). By conducting ChIP-seq for the kinetochore specific protein KKT2 using YFP-KKT2 we confirmed that KKT2 is indeed enriched on 177bp repeat DNA but not flanking DNA (Figure 7). Moreover, several known telomere-associated proteins are detected in our affinity selections of TelRTALE-YFP (Figure 6B, FigS6; see also Reis et al, 2018 Nuc. Acids Res. PMID: 29385523; Weisert et al, 2024 Sci. Reports PMID: 39681615).

Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation.

The answer for this question depends on what the authors want to present as the achievements of the present study. If the achievement of the paper was is the creation of a new tool for discovering new proteins, associated with the repeat regions, I recommend that they add a proof for direct interactions between a sample the newly discovered proteins and the relevant repeats, as a proof of concept discussed above, However, if the authors like to claim that the study achieved new functional insights for these interactions they will have to expand the study, as mentioned above, to support the proof of concept.

See our response to point 1 and the point we labelled ‘6’ above.

Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.

I think that they are realistic. If the authors decided to check the capacity of a small sample of proteins (which was unknown before as a repetitive region binding proteins) to interacts directly with the repeated sequence, it will substantially add of the study (e.g., by EMSA; estimated time: 1 months). If the authors will decide to check the also the function of one of at least one such a newly detected proteins (e.g., by KD), I estimate the will take 3-6 months.

As highlighted previously the proposed EMSA experiment may well be uninformative for protein complex components identified in our study or for isolated proteins that directly bind DNA in the context of a complex and chromatin. RNAi knockdown data and cell location data (as well as developmental expression and orthology data) is already available through tritrypDB.org and trtyptag.org

Are the data and the methods presented in such a way that they can be reproduced? Yes

Are the experiments adequately replicated, and statistical analysis adequate?

The authors did not mention replicates. There is no statistical analysis mentioned.

The figure legends indicate that all volcano plots of TALE affinity selections were derived from three biological replicates. Cutoffs used for significance: P < 0.05 (Student's t-test).

For ChiP-seq two biological replicates were analysed for each cell line expressing the specific YFP tagged protein of interest (TALE or KKT2). This is now stated in the relevant figure legends – apologies for this oversight. The resulting data are available for scrutiny at GEO: GSE295698.

Minor comments:

Specific experimental issues that are easily addressable.

The following suggestions can be incorporated:

(1) Page 18, in the material method section author mentioned four drugs: Blasticidine, Phleomycin and G418, and hygromycin. It is recommended to mention the purpose of using these selective drugs for the parasite. If clonal selection has been done, then it should also be mentioned.

We erroneously added information on several drugs used for selection in our labaoratory. In fact all TALE-YFP construct carry the Bleomycin resistance genes which we select for using Phleomycin. Also, clones were derived by limiting dilution immediately after transfection. We have amended the text accordingly:

Page 17/18:

“Cell cultures were maintained below 3 x 106 cells/ml. Pleomycin 2.5 µg/ml was used to select transformants containing the TALE construct BleoR gene.”

“Electroporated bloodstream cells were added to 30 ml HMI-9 medium and two 10-fold serial dilutions were performed in order to isolate clonal Pleomycin resistant populations from the transfection. 1 ml of transfected cells were plated per well on 24-well plates (1 plate per serial dilution) and incubated at 37°C and 5% CO2 for a minimum of 6 h before adding 1 ml media containing 2X concentration Pleomycin (5 µg/ml) per well.”

(2) In the method section the authors mentioned that there is only one site for binding of NonR-TALE in the parasite genome. But in Fig. 1C, the authors showed zero binding site. So, there is one binding site for NonR-TALE-YFP in the genome or zero?

We thank the reviewer for pointing out this discrepancy. We have checked the latest Tb427v12 genome assembly for predicted NonR-TALE binding sites and there are no exact matches. We have corrected the text accordingly.

Page 7:

“A control NonR-TALE protein was also designed which was predicted to have no target sequence in the T. brucei genome.”

Page 17:

“A control NonR-TALE predicted to have no recognised target in the T. brucei geneome was designed as follows: BLAST searches were used to identify exact matches in the TREU927 reference genome. Candidate sequences with one or more match were discarded.”

(3) The authors used two different anti-GFP antibodies, one from Roche and the other from Thermo Fisher. Why were two different antibodies used for the same protein?

We have found that only some anti-GFP antibodies are effective for affinity selection of associated proteins, whereas others are better suited for immunolocalisation. The respective suppliers’ antibodies were optimised for each application.

(4) Page 6: in the introduction, the authors give the number of total VSG genes as 2,634. Is it known how many of them are pseudogenes?

This value corresponds to the number reported by Consentino et al. 2021 (PMID: 34541528) for subtelomeric VSGs, which is similar to the value reported by Muller et al 2018 (PMID: 30333624) (2486), both in the same strain of trypanosomes as used by us. Based on the earlier analysis by Cross et al (PMID: 24992042), 80% of the identified VSGs in their study (2584) are pseudogenes. This approximates to the estimation by Consentino of 346/2634 (13%) being fully functional VSG genes at subtelomeres, or 17% when considering VSGs at all genomic locations (433/2872).

(5) I found several typos throughout the manuscript.

Thank you for raising this, we have read through the manuscipt several times and hopefully corrected all outstanding typos.

(6) Fig. 1C: Table: below TOTAL 2nd line: the number should be 1838 (rather than 1828)

Corrected- thank you.

- Are prior studies referenced appropriately? Yes

- Are the text and figures clear and accurate? Yes

- Do you have suggestions that would help the authors improve the presentation of their data and conclusions? Suggested above

Reviewer #1 (Significance):

Describe the nature and significance of the advance (e.g., conceptual, technical, clinical) for the field:

This study represents a significant conceptual and technical advancement by employing a synthetic TALE DNA-binding protein tagged with YFP to selectively identify proteins associated with five distinct repetitive regions of T. brucei chromatin. To the best of my knowledge, it is the first report to utilize TALE-YFP for affinity-based isolation of protein complexes bound to repetitive genomic sequences in T. brucei. This approach enhances our understanding of chromatin organization in these regions and provides a foundation for investigating the functional roles of associated proteins in parasite biology. Importantly, any essential or unique interacting partners identified could serve as potential targets for therapeutic intervention.

- Place the work in the context of the existing literature (provide references, where appropriate). I agree with the information that has already described in the submitted manuscript, regarding its potential addition of the data resulted and the technology established to the study of VSGs expression, kinetochore mechanism and telomere biology.

- State what audience might be interested in and influenced by the reported findings. These findings will be of particular interest to researchers studying the molecular biology of kinetoplastid parasites and other unicellular organisms, as well as scientists investigating chromatin structure and the functional roles of repetitive genomic elements in higher eukaryotes.

- (1) Define your field of expertise with a few keywords to help the authors contextualize your point of view. Protein-DNA interactions/ chromatin/ DNA replication/ Trypanosomes

- (2) Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate. None

Reviewer #2 (Evidence, reproducibility and clarity):

Summary

Carloni et al. comprehensively analyze which proteins bind repetitive genomic elements in Trypanosoma brucei. For this, they perform mass spectrometry on custom-designed, tagged programmable DNA-binding proteins. After extensively verifying their programmable DNA-binding proteins (using bioinformatic analysis to infer target sites, microscopy to measure localization, ChIP-seq to identify binding sites), they present, among others, two major findings: 1) 14 of the 25 known T. brucei kinetochore proteins are enriched at 177bp repeats. As T. brucei's 177bp repeatcontaining intermediate-sized and mini-chromosomes lack centromere repeats but are stable over mitosis, Carloni et al. use their data to hypothesize that a 'rudimentary' kinetochore assembles at the 177bp repeats of these chromosomes to segregate them. 2) 70bp repeats are enriched with the Replication Protein A complex, which, notably, is required for homologous recombination. Homologous recombination is the pathway used for recombination-based antigenic variation of the 70bp-repeat-adjacent variant surface glycoproteins.

Major Comments

None. The experiments are well-controlled, claims well-supported, and methods clearly described. Conclusions are convincing.

Thank you for these positive comments.

Minor Comments

(1) Fig. 2 - I couldn't find an uncropped version showing multiple cells. If it exists, it should be linked in the legend or main text; Otherwise, this should be added to the supplement.

The images presented represent reproducible analyses, and independently verified by two of the authors. Although wider field of view images do not provide the resolution to be informative on cell location, as requested we have provided uncropped images in new Fig. S4 for all the cell lines shown in Figure 2A.

In addition, we have included as supplementary images (Fig. S3B) additional images of TelRTALE-YFP, 177R-TALE-YFP and ingiR-TALE YFP localisation to provide additional support their observed locations presented in Figure 1. The set of cells and images presented in Figure 2A and in Fig S3B were prepared and obtained by a different authors, independently and reproducibly validating the location of the tagged protein.

(2) I think Suppl. Fig. 1 is very valuable, as it is a quantification and summary of the ChIP-seq data. I think the authors could consider making this a panel of a main figure. For the main figure, I think the plot could be trimmed down to only show the background and the relevant repeat for each TALE protein, leaving out the non-target repeats. (This relates to minor comment 6.) Also, I believe, it was not explained how background enrichment was calculated.

We are grateful for the reviewer’s positive view of original Fig. S1 and appreciate the suggestion. We have now moved these analysis to part B of main Figure 2 in the revised manuscript – now Figure 2B. We have also provided additional details in the Methods section on the approaches used to assess background enrichment.

Page 19:

“Background enrichment calculation

The genome was divided into 50 bp sliding windows, and each window was annotated based on overlapping genomic features, including CIR147, 177 bp repeats, 70 bp repeats, and telomeric (TTAGGG)n repeats. Windows that did not overlap with any of these annotated repeat elements were defined as "background" regions and used to establish the baseline ChIP-seq signal. Enrichment for each window was calculated using bamCompare, as log₂(IP/Input). To adjust for background signal amongst all samples, enrichment values for each sample were further normalized against the corresponding No-YFP ChIP-seq dataset.”

Note: While revising the manuscript we also noticed that the script had a nomalization error. We have therefore included a corrected version of these analyses as Figure 2B (old Fig. S1)

(3) Generally, I would plot enrichment on a log2 axis. This concerns several figures with ChIP-seq data.

Our ChIP-seq enrichment is calculated by bamCompare. The resulting enrichment values are indeed log2 (IP/Input). We have made this clear in the updated figures/legends.

(4) Fig. 4C - The violin plots are very hard to interpret, as the plots are very narrow compared to the line thickness, making it hard to judge the actual volume. For example, in Centromere 5, YFP-KKT2 is less enriched than 147R-TALE over most of the centromere with some peaks of much higher enrichment (as visible in panel B), however, in panel C, it is very hard to see this same information. I'm sure there is some way to present this better, either using a different type of plot or by improving the spacing of the existing plot.

We thank the reviewer for this suggestion; we have elected to provide a Split-Violin plot instead. This improves the presentation of the data for each centromere. The original violin plot in Figure 4C has been replaced with this Split-Violin plot (still Figure 4C).

(5) Fig. 6 - The panels are missing an x-axis label (although it is obvious from the plot what is displayed).

Maybe the "WT NO-YFP vs" part that is repeated in all the plot titles could be removed from the title and only be part of the x-axis label?

In fact, to save space the X axis was labelled inside each volcano plot but we neglected to indicate that values are a log2 scale indicating enrichment. This has been rectified – see Figure 6, and Fig. S7, S8 and S9.

(6) Fig. 7 - I would like to have a quantification for the examples shown here. In fact, such a quantification already exists in Suppl. Figure 1. I think the relevant plots of that quantification (YFPKKT2 over 177bp-repeats and centromere-repeats) with some control could be included in Fig. 7 as panel C. This opportunity could be used to show enrichment separated out for intermediate-sized, mini-, and megabase-chromosomes. (relates to minor comment 2 & 8)

The CIR147 sequence is found exclusively on megabase-sized chromosomes, while the 177 bp repeats are located on intermediate- and mini-sized chromosomes. Due to limitations in the current genome assembly, it is not possible to reliably classify all chromosomes into intermediate- or mini- sized categories based on their length. Therefore, original Supplementary Fig. S1 presented the YFP-KKT2 enrichment over CIR147 and 177 bp repeats as a representative comparison between megabase chromosomes and the remaining chromosomes (corrected version now presented as main Figure 2B). Additionally, to allow direct comparison of YFP-KKT2 enrichment on CIR147 and 177 bp repeats we have included a new plot in Figure 7C which shows the relative enrichment of YFP-KKT2 on these two repeat types.

We have added the following text , page 12:

“Taking into account the relative to the number of CIR147 and 177 bp repeats in the current T.brucei genome (Cosentino et al., 2021; Rabuffo et al., 2024), comparative analyses demonstrated that YFP-KKT2 is enriched on both CIR147 and 177 bp repeats (Figure 7C).”

(7) Suppl. Fig. 8 A - I believe there is a mistake here: KKT5 occurs twice in the plot, the one in the overlap region should be KKT1-4 instead, correct?

Thanks for spotting this. It has been corrected

(8) The way that the authors mapped ChIP-seq data is potentially problematic when analyzing the same repeat type in different regions of the genome. The authors assigned reads that had multiple equally good mapping positions to one of these mapping positions, randomly.

This is perfectly fine when analysing repeats by their type, independent of their position on the genome, which is what the authors did for the main conclusions of the work.

However, several figures show the same type of repeat at different positions in the genome. Here, the authors risk that enrichment in one region of the genome 'spills' over to all other regions with the same sequence. Particularly, where they show YFP-KKT2 enrichment over intermediate- and mini-chromosomes (Fig. 7) due to the spillover, one cannot be sure to have found KKT2 in both regions.

Instead, the authors could analyze only uniquely mapping reads / read-pairs where at least one mate is uniquely mapping. I realize that with this strict filtering, data will be much more sparse. Hence, I would suggest keeping the original plots and adding one more quantification where the enrichment over the whole region (e.g., all 177bp repeats on intermediate-/mini-chromosomes) is plotted using the unique reads (this could even be supplementary). This also applies to Fig. 4 B & C.

We thank the reviewer for their thoughtful comments. Repetitive sequences are indeed challenging to analyze accurately, particularly in the context of short read ChIP-seq data. In our study, we aimed to address YFP-KKT2 enrichment not only over CIR147 repeats but also on 177 bp repeats, using both ChIP-seq and proteomics using synthetic TALE proteins targeted to the different repeat types. We appreciate the referees suggestion to consider uniquely mapped reads, however, in the updated genome assembly, the 177 bp repeats are frequently immediately followed by long stretches of 70 bp repeats which can span several kilobases. The size and repetitive nature of these regions exceeds the resolution limits of ChIP-seq. It is therefore difficult to precisely quantify enrichment across all chromosomes.

Additionally, the repeat sequences are highly similar, and relying solely on uniquely mapped reads would result in the exclusion of most reads originating from these regions, significantly underestimating the relative signals. To address this, we used Bowtie2 with settings that allow multi-mapping, assigning reads randomly among equivalent mapping positions, but ensuring each read is counted only once. This approach is designed to evenly distribute signal across all repetitive regions and preserve a meaningful average.

Single molecule methods such as DiMeLo (Altemose et al. 2022; PMID: 35396487) will need to be developed for T. brucei to allow more accurate and chromosome specific mapping of kinetochore or telomere protein occupancy at repeat-unique sequence boundaries on individual chromosomes.

Reviewer #2 (Significance):

This work is of high significance for chromosome/centromere biology, parasitology, and the study of antigenic variation. For chromosome/centromere biology, the conceptual advancement of different types of kinetochores for different chromosomes is a novelty, as far as I know. It would certainly be interesting to apply this study as a technical blueprint for other organisms with minichromosomes or chromosomes without known centromeric repeats. I can imagine a broad range of labs studying other organisms with comparable chromosomes to take note of and build on this study. For parasitology and the study of antigenic variation, it is crucial to know how intermediate- and mini-chromosomes are stable through cell division, as these chromosomes harbor a large portion of the antigenic repertoire. Moreover, this study also found a novel link between the homologous repair pathway and variant surface glycoproteins, via the 70bp repeats. How and at which stages during the process, 70bp repeats are involved in antigenic variation is an unresolved, and very actively studied, question in the field. Of course, apart from the basic biological research audience, insights into antigenic variation always have the potential for clinical implications, as T. brucei causes sleeping sickness in humans and nagana in cattle. Due to antigenic variation, T. brucei infections can be chronic.

Thank you for supporting the novelty and broad interest of our manuscript

My field of expertise / Point of view:

I'm a computer scientist by training and am now a postdoctoral bioinformatician in a molecular parasitology laboratory. The laboratory is working on antigenic variation in T. brucei. The focus of my work is on analyzing sequencing data (such as ChIP-seq data) and algorithmically improving bioinformatic tools.

Reviewer #1 (Public review):

Summary:

The authors assess the role of map3k1 in adult Planaria through whole body RNAi for various periods of time. The authors' prior work has shown that neoblasts (stem cells that can regenerate the entire body) for various tissues are intermingled in the body. Neoblasts divide to produce progenitors that migrate within a "target zone" to the "differentiated target tissues" where they differentiate into a specific cell type. Here the authors show that map3k1-i animals have ectopic eyes that form along the "normal" migration path of eye progenitors, ectopic neurons and glands along the AP axis and pharynx in ectopic anterior positions. The rest of the study shows that positional information is largely unaffected by loss of map3k1. However, loss of map3k1 leads to premature differentiated of progenitors along their normal migratory route. They also show that "long-term" whole body depletion of map3k1 results in mis-specified organs and teratomas. In short, this study convincingly demonstrates that in planaria, map3k1 maintains progenitor cells in an undifferentiated state, preventing premature fate commitment until they encounter the appropriate signals, either positional cues within a designated region or contact-dependent inputs from surrounding tissues.

Strengths:

(1) The study has appropriate controls, sample sizes and statistics.

(2) The work is high-quality.

(3) The conclusions are supported by the data.

(4) Planaria is a good system to analyze the function of map3k1, which exists in mammals but not other invertebrates.

Weaknesses:

None noted.

Author response:

The following is the authors’ response to the original reviews.

Public Reviews:

Reviewer #1 (Public review):

Summary:

The authors assess the role of map3k1 in adult Planaria through whole body RNAi for various periods of time. The authors' prior work has shown that neoblasts (stem cells that can regenerate the entire body) for various tissues are intermingled in the body. Neoblasts divide to produce progenitors that migrate within a "target zone" to the "differentiated target tissues" where they differentiate into a specific cell type. Here the authors show that map3k1-i animals have ectopic eyes that form along the "normal" migration path of eye progenitors (Fig. 1), ectopic neurons and glands along the AP axis (Fig. 2) and pharynx in ectopic anterior positions (Fig. 3). The rest of the study show that positional information is largely unaffected by loss of map3k1 (Fig. 4,5). However, loss of map3k1 leads to premature differentiated of progenitors along their normal migratory route (Fig. 6). They also show that an ill-defined "long-term" whole body depletion of map3k1 results in mis-specified organs and teratomas.

Strengths:

(1) The study has appropriate controls, sample sizes and statistics.

(2) The work appears to be high-quality.

(3) The conclusions are supported by the data.

(4) Planaria is a good system to analyze the function of map3k1, which exists in mammals but not in other invertebrates.

Weaknesses:

(1) The paper is largely descriptive with no mechanistic insights. 

The mechanistic insights we aim to address are primarily at the cellular systems level – how adult progenitor cells produce pattern. Specifically, we uncovered strong evidence that regulation of differentiation is an active process occurring in migratory progenitors and that this regulation is a major component of pattern formation during the adult processes of tissue turnover and regeneration. The map3k1 phenotype provided a tool used to reveal the existence of this regulation, and to understand the patterning abnormalities prevented by this regulatory mechanism. We updated the text in several places to make clearer some of this emphasis. For example, in the Discussion: "We suggest that differentiation is restricted during migratory targeting as an essential component of pattern formation, with the map3k1 RNAi phenotype indicating the existence and purpose of this element of patterning." 

Naturally, identifying a particular molecule involved in this process is of interest for understanding molecular mechanism; this would allow for comparison to other cellular systems in other organisms and would focus future molecular inquiry. Future molecular studies into the mechanism of Map3k1 regulation and its downstream signaling will be fascinating as next steps towards understanding the process at the molecular level more deeply. We also added some discussion considering the types of upstream activation cues that could potentially be associated with Map3k1 regulation to suppress differentiation. 

(2) Given the severe phenotypes of long-term depletion of map3k1, it is important that this exact timepoint is provided in the methods, figures, figure legends and results. 

We removed the use of the term “long-term” and instead added timepoints used to all figure legends. We also added a summary of timepoints used in the methods section and included RNAi timepoint labels in figures where a phenotype progression over time is relevant to interpretation. For timecourses, we also added suitable time information to text in the results. 

(3) Figure 1C, the ectopic eyes are difficult to see, please add arrows. 

To improve visualization, we replaced the example animal in the original Figure 1C with one that has a stronger phenotype, including arrows pointing to every ectopic event. Additionally, we included magnified images of optic cup cells and photoreceptor neurons in the trunk and tail region. This is now Figure 1B.

(4) line 217 - why does the n=2/12 animals not match the values in Figure 3B, which is 11/12 and 12/12. The numbers don't add up. Please correct/explain. 

In Figure 3B in the submitted version (3/18 had cells in the tail) had more animals scored (6 animals from a replicate experiment where 1/6 showed the cells in the tail) than the total scored (2/12 had cells in the tail) in the text, which did not have the animals from the replicate added during writing. The results are the same, just different sample sizes were noted in those locations and we fixed this issue. In the updated Figure 3, the order of presentation has shifted (e.g., prior 3B is now in 3C and Figure 3_figure supplement 1). We made sure to include numbers to all figure panels. 

(5) Figure panels do not match what is written in the results section. There is no Figure 6E. Please correct.

Thank you for catching this. We have gone through figures and text after editing to make sure that text callouts are appropriately matched to the figures. 

Reviewer #2 (Public review):

Summary:

The flatworm planarian Schmidtea mediterranea is an excellent model for understanding cell fate specification during tissue regeneration and adult tissue maintenance. Planarian stem cells, known as neoblasts, are continuously deployed to support cellular turnover and repair tissues damaged or lost due to injury. This reparative process requires great precision to recognize the location, timing, and cellular fate of a defined number of neoblast progeny. Understanding the molecular mechanisms driving this process could have important implications for regenerative medicine and enhance our understanding of how form and function are maintained in long-lived organisms such as humans. Unfortunately, the molecular basis guiding cell fate and differentiation remains poorly understood.

In this manuscript, Canales et al. identified the role of the map3k1 gene in mediating the differentiation of progenitor cells at the proper target tissue. The map3k1 function in planarians appears evolutionarily conserved as it has been implicated in regulating cell proliferation, differentiation, and cell death in mammals. The results show that the downregulation of map3k1 with RNAi leads to spatial patterning defects in different tissue types, including the eye, pharynx, and the nervous system. Intriguingly, long-term map3k1-RNAi resulted in ectopic outgrowths consistent with teratomas in planarians. The findings suggest that map3k1 mediates signaling, regulating the timing and location of cellular progenitors to maintain correct patterning during adult tissue maintenance.

Strengths:

The authors provide an entry point to understanding molecular mechanisms regulating progenitor cell differentiation and patterning during adult tissue maintenance.

The diverse set of approaches and methods applied to characterize map3k1 function strengthens the case for conserved evolutionary mechanisms in a selected number of tissue types. The creativity using transplantation experiments is commendable, and the findings with the teratoma phenotype are intriguing and worth characterizing.

Thank you to the reviewer for the positive feedback

Weaknesses:

The article presents a provocative idea related to the importance of positional control for organs and cells, which is at least in part regulated by map3k1. Nonetheless, the role of map3k1 or its potential interaction with regulators of the anterior-posterior, mediolateral axes, and PCGs is somewhat superficial. The authors could elaborate or even speculate more in the discussion section and the different scenarios incorporating these axial modulators into the map3k1 model presented in Figure 8 

First, to strengthen the support for our finding that positional information is largely unaffected in map3k1 RNAi animals, we added data regarding the expression of additional relevant position control genes (PCGs) –ndl-4, ptk7, sp5, and wnt11-1 – to the PCG panel in Figure 5. The expression domain of ndl-4, an FGF receptor-like protein family member that contributes to head patterning and anterior pole maintenance, was normal in map3k1 RNAi. wnt11-1, a PCG with expression concentrated in the posterior end of the animal and with expression dependent on general Wnt activity, was also normal in map3k1 RNAi animals. ptk7, RNAi of which can result in supernumerary pharynges, also showed normal expression in map3k1 RNAi animals. Finally, sp5, a Wnt-activated gene with expression in the tail, also showed normal expression in map3k1 RNAi animals. 

Second, to further support the conclusion that cells are not suitably responding to positional information after map3k1 RNAi, which we argue normally dictates where differentiation should occur, we added examples of differentiated cell types that are ectopically positioned within an atypical PCG expression domain for that cell type (Figure 5C). This underscores that following map3k1 RNAi the PCG expression domains do not change, but the pattern of differentiated cell types relative to these domains does shift. We also added data showing that regenerating tails had a proper wntP-2 gradient, but an anterior regenerating pharynx appeared outside of this wntP-2⁺ zone and inside of an ndl-5⁺ zone (Figure 5- figure supplement 1E). We added some discussion of these new data in the Figure 5 results section. We also noted, regarding independent recent map3k1 work (Lo, 2025), some evidence exists that a minor posterior shift in ndl-5 expression can occur after map3k1 RNAi.

Next, we added a new element to the model figure (Figure 8B) depicting that PCG expression domains remain normal after map3k1 RNAi, with ectopic differentiation occurring in an incorrect positional information environment. We refer to this new panel in the discussion: "We suggest that map3k1 is not required for the spatial distribution of progenitor-extrinsic differentiation-promoting cues themselves, but for progenitors to be restricted from differentiating until these cues are received (Figure 8B)."; we then follow this statement with a summary in the Discussion of six pieces of evidence that support this model.

Finally, we added some additional text to the discussion section about candidate mechanisms by which extrinsic cues could potentially regulate Map3k1, pointing to potential future inquiry directions. We suggest that map3k1 is not involved in regulating PCG activity domains themselves, but instead acts as a brake on differentiation within migratory progenitors through active signaling. This brake is then lifted when the progenitors hit their correct PCG-based migratory target, or when they hit their target tissue. How that occurs mechanistically is unknown. One scenario is that each progenitor is tuned to respond to a particular PCG-regulated environment (such as a particular ECM or signaling environment) to generate a molecular change that inactivates Map3K1 signaling, such as by inactivating or disengaging an RTK signal. Alternatively, the migratory process in progenitors could engage the Map3K1 signal, enabling signal cessation with arrival at a target location. When Map3K1 is active it could result in a transcriptional state that prevents full expression of differentiated factors required for maturation, tissue incorporation, and cessation of migration. These considerations are now added to the discussion.

The article can be improved by addressing inconsistencies and adding details to the results, including the main figures and supplements. This represents one of the most significant weaknesses of this otherwise intriguing manuscript. Below are some examples of a few figures, but the authors are expected to pay close attention to the remaining figures in the paper.

Details associated with the number of animals per experiment, statistical methods used, and detailed descriptions of figures appear inconsistent or lacking in almost all figures. In some instances, the percentage of animals affected by the phenotype is shown without detailing the number of animals in the experiment or the number of repeats. Figures and their legends throughout the paper lack details on what is represented and sometimes are mislabeled or unrelated. 

We endeavored to ensure that these noted details are present throughout the legends and figures for all figure panels.

Specifically, the arrows in Figure 1A are different colors. Still, no reasoning is given for this, and in the exact figure, the top side (1A) shows the percentages and the number of animals below. 

The only reason for the different colored arrows was for visibility purposes. To avoid confusion, we now use white arrows for all FISH images in figure 1, and where ever else possible. We also replaced the percentages with n numbers in the bottom left corner of the live images in Figure 1A. 

Conversely, in Figures 1B, C, and D, no details on the number of animals or percentages are shown, nor an explanation of why opsin was used in Figure 1A but not 1B. 

The original Figure 1B represented a few different examples of ectopic eye/eye cell patterns in the map3k1 RNAi animals to demonstrate the variable and disorganized nature of the phenotype. To address this, we added further explanation in the legend. We also merged 1A and 1B for simplicity of interpretation. opsin was used in Figure 1A to label cell bodies of photoreceptors. anti-Arrestin was used in the example FISH images to see if these cells were interconnected via projections, which we now clarify in the legend and in the text. 

Is Figure 1B missing an image for the respective control? Figure 1C needs details regarding what the two smaller boxes underneath are. 

The control for Figure 1B was in Figure 1A; the merger of Figures 1A/B should address this. Boxes in Figure 1C were labelled with numbers corresponding to the image above them.

Figure 1C could use an AP labeling map in 10 days (e.g., AP6 has one optic cup present). Figure 1C and F counts do not match. 

We added a cartoon to 1C to show the region imaged. Note that the 36d trunk image (now Fig. 1B) has now been replaced with a full animal image and magnified boxes that show locations of example ectopic cells. That cell in 1C was categorized as in AP5. Note that additional animals were analyzed and data added to the distribution (now Fig. 1D). 

In Figure 1C, we do not know the number of animals tested, controls used, the scale bar sizes in the first two images, nor the degree of magnification used despite the pharynx region appearing magnified in the second image.  Figure 1C is also shown out of chronological order; 36 days post RNAi is shown before 10 days post RNAi. Moreover, the legends for Figures 1C and 1D are swapped.

We have endeavored to ensure sample numbers, control images, and appropriate scale bar notation in legends are present for all images. Figure 1C has now been split into two panels: Figure 1B and Figure 1C. It does not follow a chronological order in presentation for the following logic flow: we uncover and describe the phenotype; then, with knowledge of the defect, we walk back to see how early the phenotype starts after RNAi and what the pattern of ectopic cell distribution is when the phenotype starts to emerge (using the knowledge of which cells are affected from the overt phenotype described in 1A/B). 

Additionally, Figure 1F and many other figures throughout the paper lack overall statistical considerations. Furthermore, Figure 1F has three components, but only one is labeled. Labeling each of them individually and describing them in the corresponding figure legend may be more appropriate.

The main point of the graphs in 1F (now 1D) was the overt overall pattern difference with the wild-type, which never has ectopic eye cells in the midbody or tail, and that the ectopic eye cells progress throughout the entire AP axis. However, we concur that a statistical test is a reasonable thing to show here and that is now included in the legend. The 3 components (in Figure 1F, now Figure 1D) where kept together with one figure label (D) for simplicity, but were rearranged (top and bottom) with a cartoon to the side and with modified labeling for extra clarity. 

Figure 2C shows images of gene expression for two genes, but the counts are shown for only one in Figure 2D. It is challenging to follow the author's conclusions without apparent reasoning and by only displaying quantitative considerations for one case but not the other. These inconsistencies are also observed in different figures. 

In Figure 2C, FISH images of cintillo+ and dd_17258+ neurons are shown to display the specificity of this effect to some neurons and not others. Because cintillo+ cells did not expand at all (n=24/24 animals), the counts for them would all be zero values. We only counted data for dd_17258 cells because it was the neuron that expanded compared to the control animals. We have now added a note in the legend explaining this.

In Figure 2D, 24/24 animals were reported to show the phenotype, but only eight were counted (is there a reason for this?).

8 animals were used to quantitatively characterize the spread of cells along the AP axis, as it was deemed an adequate sample size to capture the change in distribution of 17258+ cells from being head restricted to being present throughout the body. Through multiple cohorts of animals in replicates, a total of 24/24 examined animals showed this expansion phenotype. Double FISH experiments were additionally carried out using dd_17258 and various PCGs; these data are now included in Figure 5C, and these animals were added to the total counts regarding quantitative analysis of the phenotype in Figure 2D. 

In Figure 2E, the expression for three genes is shown, with some displaying anterior and posterior regions while others only show the anterior picture. Is there a particular reason for this? 

The original first panel in Figure 2E showed an example of a non-expanding gland cell type, dd_9223, which is very restricted to the head in both control and map3k1 RNAi animals. Because we did not observe a phenotype for this cell type (no cells in all control and map3k1 RNAi animal tails), we only included tail images of cell types that showed an abnormal phenotype with clear expanded to the posterior (dd_8476 and dd_7131). However, we have now included tail images of dd_9223 cells and added data for dd_9223 to the graph in Figure 2E. 

Also, in Figure 2F, the counts are shown for only the posterior region of two genes out of the three displayed in Figure 2E. It is unclear why the authors do not show counts for the anterior areas considered in Figure 2E. Furthermore, the legend for Figure 2D is missing, and the legend for 2F is mislabeled as a description for Figure 2D.

We now include tail images for dd_9223 in Figure 2E to show that there are no ectopic cells in tails. We did not originally include counts of dd_9223 because there was no phenotype observed. dd_7131 and dd_8476 cell types appeared in the posterior of even control animals at a low frequency, unlike dd_9223 cells. However, we did now add counts for dd_9223 tail regions in the graph. We did not count the anterior regions of the animal because our goal was to show data for the visible phenotype (ectopic cells in the tail) not only with an example image, but also by showing the number of cells in the tail with a graph and statistical test. Legends have been updated with correct details.

Supplement Figure 1 B reports data up to 6 weeks, but no text in the manuscript or supplement mentions any experiment going up to 6 weeks. There are no statistics for data in Supplement Figure 1E. Any significance between groups is unclear.

More details about the RNAi feeding schedules have been added in the methods section. All RNAi timepoints are now specified specifically in the legends. The Figure 1F and Figure 1- figure supplement 1E (additional data: ovo⁺; smedwi-1^- cell counts) and legends now mention the statistical tests performed and annotations (not significant *ns) or p values have been added to the graphs. For simplicity, we decided to include all smedwi-1+ counts together rather than splitting them into low and high smedwi-1+ cells, because we weren't really making any claims about low and high cells. 

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

It would be good to acknowledge in the discussion the recent paper from the Petersen lab on map3k1, published in PLoS Genet 2025, especially if the results differ between the two labs.

We added reference/discussion regarding the recent PLoS Genetics Lo, 2025 map3k1 paper at several suitable points in the manuscript.

Reviewer #2 (Recommendations for the authors):

Please pay close attention to the description of experimental details and the consistency throughout the paper. It seems like the reader has to assume or come across information that is not readily available from the text or the legends in the paper. This is an interesting paper with intriguing findings. However, the version presented here appears rushed or put together on the flight.

Thank you for your thorough feedback. We have endeavored to ensure all appropriate details are present in figures and/or figure legends.

Simplifying data may frequently be convenient when creating a widely-applicable program, but it involves leaving at least one group or perspective out. Because of this, simplification of data often contains inherent bias and developers should be aware of this.

This definitely opened my perspective on data constraints. In the reflection before, I figured that the best way to store information for social media would be through pre-set categories (for things like relationship status, address, etc), but there are definitely important details that can be hard to simplify and cut out (though, I'm sure no one needs additional details on someone's relationship status). I guess that's why there are some instances where you're able to put down a permanent address and a temporary address for those who are only residing somewhere for a short-term opportunity.

I think this is a crucial part of programming. Simplification is incredibly beneficial, but it also eliminates minor details that can still be relevant. While it can simplify and allow faster more efficient data, it's not 100% accurate

I find this especially interesting, because it's true, when we see a number or percentage it seems like it must be the correct one. But it is so important to think about the data collection behind it. If we use the bot example, when processing all the users in the systems did the data processors then remove all incomplete data (if something was missing from the profile) or did they leave it in? I believe that even though data seems unbiased, there are always choices in how it's processed that effect how the outcome looks.

I think this is important both when considering data but also just considering social media as a whole. People tend to only post the positives in their life, and even in those positive posts a lot of information is being left out of the context. If someone only posts a single photo from a concert with a lyric as a caption, it does not explain what the set was or how the experience as a whole was like for that person.

People typically don’t expect to glean much useful information from bots. In my case, at least, I would typically block or ignore them. Additionally, it’s often easy to identify a bit, but in the age of AI these lines are becoming more blurred.

I appreciate this analogy; it can also resemble our current state of our own country when people often do not take accountability for their actions because they did not participate “first hand.” Online has taken this donkey protest dilemma to the extreme; often times people are extremely more outspoken on beliefs or topics because they’re behind a screen, much like controlling bots where they don’t believe they should be held accountable for what the bot had posted/said online because “it wasn’t me!”

eLife Assessment

This important study employs a closed-loop, theta-phase-specific optogenetic manipulation of medial septal parvalbumin-expressing neurons in rats and reports that disrupting theta-timescale coordination impairs performance of challenging aspects of spatial behaviors, while sparing hippocampal replay and spatial coding in hippocampal place cells. The findings are expected to advance theoretical understanding of learning and memory operations and to provide practical implications for the application of similar optogenetic approaches. The experiments were viewed as technically rigorous, but the strength of evidence provided in the current version of the manuscript was viewed as incomplete, mostly due to limited analyses and the descriptions of some of the experimental protocols.

Reviewer #2 (Public review):

Summary:

The authors of this study developed a closed-loop optogenetic stimulation system with high temporal precision in rats to examine the effect of medial septum (MS) stimulation on the disruption of hippocampal activity at both behavioral and compressed time scales. They found that this manipulation preserved hippocampus single-cell-level spatial coding but affected theta sequences and performance during a spatial alternation task. The performance deficits were observed during the more cognitively demanding component of the task and even persisted after the stimulation was turned off. However, the effects of this disruption were confined to locomotor periods and did not impact waking rest replay, even during the early phase of stimulation-on. Their conclusion is consistent with previous findings from the Pastalkova lab, where MS disruption (using different methods) affected theta sequences and task performance but spared replay (Wang et al., 2015; Wang et al., 2016). However, it differs from a recent study in which optogenetic disruption of EC inputs during running affected both theta sequences and replay (Liu et al., 2023).

Strengths:

The experiments were well designed and controlled, and the results were generally well presented.

Weaknesses:

Major concerns are primarily technical but also conceptual. To further increase the impact of this study by contrasting findings from different disruptions, it is necessary to better align the analysis and detection methods.

Major concerns:

(1) To show that MS disruption does not affect spatial tuning, the authors computed the KL divergence of tuning curves between stimulation-on and stimulation-off conditions. I have two main questions about this analysis:

(1.1) The authors seem to impose stringent inclusion criteria requiring a large number of spikes and a strong concentration of tuning curves. These criteria may have selected strongly spatially tuned cells, which are typically more stable and potentially less vulnerable to perturbations. Based on the Figure 2 caption, it seems that fewer than 10% of cells were included in the KL divergence analysis, which is lower than the usual proportion of place cells reported in the literature. What is the rationale for using such strict inclusion criteria? What happens to the cells that are not as strongly tuned but are still identified as significant place cells?

(1.2) The KL divergence was computed between stimulation-on and stimulation-off conditions within the same animal group. However, the authors also showed that MS stimulation had lasting effects on theta sequences and performance even during stimulation-off periods. Would that lasting effect also influence spatial tuning? Based on these questions, the authors should perform additional analyses that directly measure spatial tuning quality and compare results across control and experimental groups - for example, spatial information of spikes (Skaggs et al., 1996), tuning stability, field length, and decoding error during running.

(2) The authors compared their results with those from Liu et al. (2023) and proposed that the different outcomes could be explained by different sites of disruption. However, the detection and quantification methods for theta sequences and replay differ substantially between the two studies, emphasizing different aspects of the phenomenon. I am not suggesting that either method is superior, but providing additional analyses using aligned detection methods would better support the authors' interpretations and benefit the field by enabling clearer comparisons across studies. In the current analysis, the power spectrum of the decoded ahead/behind distance only indicates that there is a rhythmic pattern, without specifying the decoding features at different theta phases. Moreover, the continuous non-local representations during ripples could include stationary representations of a location or zigzag representations that do not exhibit a linear sequential trace. Given that, the authors should show averaged decoding results corrected by the animal's actual position within theta cycles and compute a quadrant ratio. For replay analysis, they could use a linear fit (as in Liu et al., 2023) and report the proportion of significant replay events.

(3) The finding that theta sequences and performance were impaired even during stimulation-off periods is particularly interesting and warrants deeper exploration. In the Discussion, the authors claim that this may arise from "the rapid plasticity engaged during early learning." However, this explanation does not fully account for the observation. Previous studies have shown that theta sequences can develop very rapidly (Feng et al., Foster lab, 2015; Zhou et al., Dragoi lab, 2025). If the authors hypothesize that rapid plasticity during early stimulation-on disrupts the theta sequence, then the plasticity window must also be short and terminate during the subsequent stimulation-off period. Otherwise, why can't animals redevelop theta sequences during stimulation-off? The authors should conduct additional analyses during the stimulation-off periods of the W-maze task. For example:

(3.1) What is the spike-theta phase relationship? Do the phases return to normal or remain altered as during stimulation-on?

(3.2) Is there a significant place-field remapping from stimulation-on to stimulation-off? (Supplementary Figure 3F includes only a small subset of cells; what if population vector correlations are computed across all cells, or Bayesian decoding of stimulation-on spikes is performed using stimulation-off tuning curves?)

(3.3) The authors should also discuss why the stimulation-off epochs were not sufficient to support learning, and if the stimulation-off place cell sequences could have supported replay.

(4) Citations and/or discussion of key studies relevant to the current work are missing: Wang et al. in Pastalkova lab 2015-2016 studies for disruption of theta sequence (but not place cell sequence) disrupting learning but not replay, Drieu et al. in Zugaro lab 2018 study on disruption of theta sequence affecting sleep replay, Farooq and Dragoi 2019 for association between a lack of theta sequence and presence of waking rest replay during postnatal development, etc. The authors should discuss what the conceptually new findings in the current study are, given the findings of the previous literature above.

(5) The assessment of theta sequence is not state-of-the-art:

(5.1) Detecting the peak of cross-correlograms between neurons (CCG) relates to behavioral timescale CCG, not the theta sequence one; for the theta sequence, the closest to zero local peak should be used instead.

(5.2) How were other methods of detecting theta sequences performing on the stimulation-on/stimulation-off data: Bayesian decoding, firing sequences?

(5.3) How was phase precession during stimulation-on/stimulation-off?

(6) It would be important to calculate additional variables in the replay part of the study to compare the quality of replay across the 2 groups:

(6.1) Proportion of significant replay events out of the detected multiunit events.

(6.2) The average extent of trajectory depicted by the significant replay events in the targeted compared to the control, stimulation-on/stimulation-off.

Reviewer #3 (Public review):

Joshi et al. present an elegant and technically rigorous study examining how the temporal structure of hippocampal spiking during locomotion contributes to spatial learning. Using a closed-loop, theta phase-specific optogenetic manipulation of medial septal parvalbumin-expressing neurons in rats, the authors demonstrate that disrupting theta-timescale coordination impairs performance on the cognitively demanding component outbound trajectory of a spatial alternation task, while sparing hippocampal replay, place coding, and the simpler inbound learning. The work aims to dissociate the role of theta-associated temporal organization during navigation from sharp-wave ripple-associated replay during subsequent rest periods, providing a mechanistic link between theta sequences and learning. The findings have important implications for models of septo-hippocampal coordination and the functional segregation between online (theta) and offline (SWR) network states. That said, there are a few conceptual and methodological issues that need to be addressed.

One concern is the overall novelty of this work; the dissociation between online temporal sequence and offline replay events following memory deficits has previously been shown by Wang et al., 2016 elife. While the authors discuss Lui et al., 2023, which demonstrates MEC activation of inhibitory neurons at gamma frequencies during locomotion disrupts theta sequences, subsequent replay and learning (line 65-66), they do not reference Wang et al., 2016 who performed a very similar study with MS pharmacological inactivation, and report large decreases in theta power, attenuated theta frequencies together with behavioural deficits but SWR replay persisted. Given strong similarities in the manipulation and findings, this study should be discussed.

Along the same lines, it should be noted that Brandon et al. (2014, Neuron) demonstrated that hippocampal place codes can still form in novel environments despite MS inactivation and loss of theta, indicating that spatial representations can emerge without intact septal drive. Referencing this study would strengthen the discussion of how temporal coordination, rather than spatial coding per se, underlies the learning deficits observed here.

The conclusion that disrupting "theta microstructure" impairs learning relies on the assumption that the observed behavioral deficits arise from altered temporal coding from within hippocampal CA1 only. However, optogenetic modulation of medial septal PV neurons influences multiple downstream regions (entorhinal cortex, retrosplenial cortex) via widespread GABAergic projections. While the authors do touch on this, their discussion should expand to include the network-level consequences of entorhinal grid-cell disruption and how this could affect temporal coding both online and offline.

The finding that replay content, rate, and duration are unchanged is critical to the paper's claim of dissociation. However, the analysis is restricted to immobility on the track. Given evidence for distinct awake vs. sleep replay, confirming that off-track rest and post-session sleep replays are similarly unaffected would confirm the conclusions of the paper. If these data are unavailable, the limitation should be acknowledged explicitly. Moreover, statistical power for detecting subtle differences in replay organization or spatial bias should be added to the supplement (n of events per animal, variability across sessions).

The exact protocol for optogenetic stimulation is a bit confusing. For the task, the first and final third (66%) of trials were disrupted and were only stimulated when away from the reward well and only when the animal was moving. What proportion of time within "stimulated" trials remained unstimulated? Why were only 66% of trials stimulated?

Reviewer #1 (Public review):

Summary:

This study examines the role of the long non-coding RNA Dreg1 in regulating Gata3 expression and ILC2 development. Using Dreg1-deficient mice, the authors show a selective loss of ILC2s but not T or NK cells, suggesting a lineage-specific requirement for Dreg1. By integrating public chromatin and TF-binding datasets, they propose a Tcf1-Dreg1-Gata3 regulatory axis. The topic is relevant for understanding epigenetic regulation of ILC differentiation.

Strengths:

(1) Clear in vivo evidence for a lineage-specific role of Dreg1.

(2) Comprehensive integration of genomic datasets.

(3) Cross-species comparison linking mouse and human regulatory regions.

Weaknesses:

(1) Mechanistic conclusions remain correlative, relying on public data.

(2) Lack of direct chromatin or transcriptional validation of Tcf1-mediated regulation.

(3) Human enhancer function is not experimentally confirmed.

(4) Insufficient methodological detail and limited mechanistic discussion.

Note d'information : La Stratégie d'Expansion du Groupe Emeis (ex-Orpea) dans le Secteur de la Psychiatrie en France

Synthèse Exécutive

Cette note d'information analyse la stratégie d'expansion du groupe privé lucratif Emeis (anciennement Orpea) dans le secteur de la psychiatrie en France.

Elle s'appuie sur une enquête journalistique qui met en lumière comment le groupe, marqué par le scandale de ses EHPAD, capitalise sur la crise profonde de la psychiatrie publique pour s'implanter sur ce marché jugé très rentable.

L'analyse révèle une situation de crise systémique dans le secteur public : un sous-financement chronique, un manque criant de personnel (seulement 600 pédopsychiatres en France), des infrastructures vétustes et une explosion de la demande de soins, notamment chez les jeunes depuis la crise du Covid (+77 % d'épisodes dépressifs chez les 18-24 ans).

Dans ce contexte, Emeis déploie une stratégie agressive pour s'imposer, illustrée par un projet de clinique de 80 lits près de Strasbourg.

Cette implantation, menée via sa filiale Clinea, s'est initialement appuyée sur une alliance "étonnante" avec un concurrent, Clinipsy.

L'enquête suggère que cette alliance aurait pu servir de "cheval de Troie" pour Emeis, lui permettant d'obtenir des autorisations administratives que le groupe, sous le nom d'Orpea, s'était vu refuser à plusieurs reprises depuis 2007.

Les principales préoccupations soulevées sont le risque d'affaiblissement de l'hôpital public par le débauchage de son personnel, une complémentarité illusoire où le privé se concentrerait sur les cas les plus rentables en laissant les plus complexes au public, et un modèle économique basé sur la rentabilité qui pourrait se faire au détriment de la qualité des soins par la réduction des effectifs.

Enfin, le document souligne l'opacité de l'Agence Régionale de Santé (ARS) Grand Est, qui a refusé de communiquer des documents essentiels sur ce projet malgré les importants financements publics engagés.

1. Le Contexte : Une Psychiatrie Publique en Crise Profonde

La psychiatrie en France est décrite comme étant "malade" et "abandonnée par les pouvoirs publics".

Ce secteur est devenu le "parent pauvre de la santé", confronté à un manque critique de moyens alors que les besoins de soins explosent.

• Explosion de la demande : La crise du Covid et les confinements ont provoqué une forte augmentation des pathologies mentales.

◦ +77 % d'épisodes dépressifs chez les 18-24 ans.    ◦ +133 % d'hospitalisations pour tentative de suicide ou automutilation.

• Manque de moyens structurel : Le secteur public souffre d'un sous-investissement chronique.

◦ Une politique ambulatoire non financée : Depuis les années 1980, une politique de fermeture de lits a été menée au profit de soins ambulatoires (hors de l'hôpital).

Cependant, les moyens financiers n'ont pas suivi pour développer ces structures alternatives comme les Centres Médico-Psychologiques (CMP).  

◦ Pénurie de personnel : La France compte environ 600 pédopsychiatres, laissant des départements entiers sans spécialiste.  

◦ Diminution des capacités : L'hôpital public a perdu près de 7 000 places de prise en charge psychiatrique à temps complet en 15 ans.

• Vétusté des infrastructures : L'état des bâtiments publics est alarmant.

À Strasbourg, le secteur de la pédopsychiatrie des Hôpitaux Universitaires est logé dans des "bâtiments complètement vétustes" et des "préfabriqués".

L'Inspection générale des affaires sociales (Igas) a signalé des risques d'incendie et demandé un déménagement en urgence, qui n'a été annoncé que 15 ans plus tard.

"On a alerté qu'on allait droit dans le mur et le mur aujourd'hui on se le prend en pleine face." - Un soignant, cité dans le documentaire de Laurence Deur.

2. L'Émergence d'un Nouvel Eldorado : Le Secteur Privé Lucratif

La défaillance du système public crée une opportunité majeure pour les groupes privés à but lucratif, qui considèrent la psychiatrie comme un "marché très rentable".

• Un secteur profitable : Selon un rapport récent du Sénat, la psychiatrie est l'un des secteurs de la santé les plus rentables, avec des marges estimées entre 5 % et 8 %.

L'investissement principal étant l'humain, la réduction du personnel est le principal levier pour augmenter les profits.

• Une croissance rapide : La part du secteur privé lucratif dans l'offre de soins psychiatriques a considérablement augmenté :

◦ 1975 : 11 % des lits.    ◦ Aujourd'hui : Plus de 30 % des lits.

• Un parallèle avec les EHPAD : La situation actuelle en psychiatrie est comparée à la privatisation du secteur des EHPAD dans les années 1980.

Face à des établissements publics vieillissants et coûteux à rénover, l'État avait ouvert la porte au privé qui promettait de "faire moins cher, plus vite".

• Le rôle des ARS : Les Agences Régionales de Santé, autrefois réticentes à ouvrir la psychiatrie au privé, sont aujourd'hui plus enclines à le faire.

Face à l'incapacité du public à répondre à la demande immense, elles autorisent l'ouverture de cliniques et d'hôpitaux de jour privés.

3. Étude de Cas : La Stratégie d'Implantation d'Emeis à Strasbourg

L'enquête se concentre sur un projet de clinique psychiatrique privée de 80 lits à Schiltigheim, près de Strasbourg, porté par le groupe Emeis (ex-Orpea), rebaptisé pour faire oublier le scandale révélé par le livre Les Fossoyeurs. Ce projet est jugé "démesuré" et "anachronique" par les acteurs locaux.

Une Alliance Stratégique Inédite

Le projet est né d'une alliance "étonnante" entre deux concurrents :

1. Clinea : La filiale sanitaire d'Emeis/Orpea.

2. Clinipsy : Un acteur plus petit, déjà connu pour une enquête du Parquet National Financier (PNF) concernant des autorisations obtenues en région Rhône-Alpes par d'anciens fonctionnaires de l'ARS locale, ensuite embauchés par des filiales du groupe.

Cette collaboration entre concurrents directs est jugée inhabituelle, comparable à "si Intermarché et Leclerc montaient un supermarché ensemble".

L'Hypothèse du "Cheval de Troie"

L'enquête soulève l'hypothèse que cette alliance aurait servi de stratégie à Emeis pour contourner des obstacles réglementaires.

• Dissimulation : Emeis se serait "dissimulé un petit peu" derrière le nom de Clinipsy, un groupe plus petit avec une "moins mauvaise image" auprès des ARS, pour obtenir plus facilement les autorisations.

• Historique des refus : Des documents montrent qu'Orpea tentait d'ouvrir une clinique psychiatrique dans la région depuis au moins 2007 et avait essuyé au moins deux refus de la part de l'agence régionale (alors ARH).

Depuis, Clinipsy s'est désengagé du projet de clinique de 80 lits pour se concentrer sur des hôpitaux de jour, des structures moins coûteuses et "extrêmement rentables", laissant le champ libre à Emeis pour le projet principal.

"La question [...] se pose de savoir si Clinipsy a été un petit peu le cheval de Troie d'Orpea dans cette affaire." - Laurence Deur, journaliste.

4. Les Risques Systémiques de la Privatisation

L'arrivée massive d'acteurs privés lucratifs comme Emeis dans la psychiatrie fait peser plusieurs risques majeurs sur l'équilibre global du système de santé mentale.

Le "Pillage" des Ressources Humaines du Public

La principale inquiétude est que les nouvelles cliniques privées, en offrant de meilleures conditions de travail ou de rémunération, ne débauchent le personnel médical et soignant déjà en sous-effectif dans le secteur public.

• Un exemple concret : Un courrier de 2022 révèle qu'une clinique privée près de Nancy a débauché cinq médecins de l'hôpital public local, fragilisant ce dernier.

• L'inquiétude de la Mairie de Strasbourg : La maire, Jeanne Barségan, craint que le projet de 80 lits n'aggrave la pénurie de psychiatres et ne "vide" l'hôpital public de ses forces.

Une Complémentarité Illusoire : Le "Triage" des Patients

L'offre privée est souvent présentée comme "complémentaire" du public. Cependant, l'analyse montre qu'elle ne remplit pas les mêmes missions.

• Évitement des cas complexes : Le privé évite généralement les missions les plus lourdes et les moins rentables, comme l'hospitalisation sous contrainte, qui nécessite plus de personnel et de temps.

• Gestion des urgences "à la carte" : Dans le projet d'Emeis, la prise en charge des urgences se ferait "de gré à gré", sans obligation contraignante. Le médecin du privé peut accepter ou refuser un patient envoyé par le public.

• La conclusion : "Tout ce qui est complexe reste dans l'hôpital public", tandis que le privé se positionne sur des missions "plus faciles à assurer".

Le Modèle Économique : Profit vs. Qualité des Soins

Emeis est une entreprise cotée en bourse qui doit générer du profit pour ses actionnaires.

• Le levier du personnel : En psychiatrie, où "l'investissement, c'est l'humain", la principale méthode pour augmenter la rentabilité est de réduire les effectifs.

• Conflits sociaux : Plusieurs conflits sociaux ont éclaté dans des cliniques psychiatriques d'Emeis (Thionville, Nord, Isère) où le personnel dénonçait un manque d'effectifs et une réorganisation du travail impactant la qualité des soins.

Une grève de trois semaines a eu lieu à Seyssins, un événement "extrêmement rare dans le privé".

"Une entreprise est là pour faire du profit alors que l'hôpital public on lui demande pas d'être profitable, on lui demande d'être à l'équilibre." - Laurence Deur, journaliste.

5. Le Rôle et l'Opacité des Autorités de Régulation

L'enquête met en cause le manque de transparence de l'Agence Régionale de Santé (ARS) Grand Est.

• Rétention d'information : La journaliste a été "baladée pendant un mois et demi" sans obtenir de réponse ni les documents demandés concernant le projet de clinique Emeis.

L'ARS a fini par envoyer un document public générique qui ne correspondait pas à la demande.

• Recours à la CADA : Il a fallu saisir la Commission d'Accès aux Documents Administratifs (CADA) pour obtenir une partie des informations.

• Enjeux financiers publics : Cette opacité est jugée problématique car le projet engage d'importants fonds publics.

Les autorisations délivrées "valent des millions d'euros" et le groupe peut prétendre à une "dotation d'amorçage" de l'État pour financer son démarrage.

Cette situation soulève des questions sur le contrôle et la régulation de l'expansion du secteur privé lucratif, financée en partie par de l'argent public, dans un domaine aussi sensible que la santé mentale.

The realization that "text" on social media encompasses more than just English letters, but also spaces, punctuation, characters from diverse languages, and emojis, was significant. Inconsistent encoding or character handling can result in garbled text, inaccurate length calculations, and adverse effects on subsequent text cleaning, keyword statistics, and sentiment analysis. Consequently, preprocessing strings is essential prior to undertaking data analysis.

I think this is an interesting data with constraints that shift along cultural axes. While the other data types like age, name, and address can vary from culture to culture (such as characters used to input), the answers will all be relatively similar. People might for example measure their age using different calendars, or by amount of winters experienced, but a full annual cycle is used pretty much worldwide. For relationship status though, there are a lot of variables even in one culture that must be negotiated. Does dating count as different than a relationship? What about new terms like situationship? What about cultures with multiple partners? There's so many value judgements about what counts as a relationship in the act of reifying it in code. It makes me think about the ways in which our cultural ideology is represented in code, more than we often think about.

An important concept is that there are not many parasitic microbes, but the ones that are parasitic have had a huge impact on the world. This is why so many people are afraid of microbes, because they think they are all bad and harmful.

This paragraph highlights that a memory is held by an individual, but is shaped and formed by a group. It is these groups that give the memory a significance and structure.

This was my experience growing up. The story of the Pilgrims and Native Americans was celebrated, but the darker history was seldom talked about.

And some people today outright refuse to celebrate Thanksgiving due to the past treatment of Native Americans. I'm not one of those people, but that's because when I think of Thanksgiving, I think of cooking a meal and spending time with my family. No one has to venerate the past if they don't want to.

This is definitely something I dread, but I need to be more comfortable with reading them so this is the perfect opportunity to learn in a comfortable setting.

This connects very well with me because I am an emotional mess. Stress and anxiety can interfere with daily life and struggles for not just me but for many.

The text talks about "grit:. Grit is defined as passion and perseverance for long term goals. It means sticking with something even when it's hard.

I like how the text says learning can be messy. It reminds me that growth isn't always comfortable, but it's worth it in the long run.

Shrinking habitat space must be more and more heavily managed and maintained the smaller it is, as it becomes less and less self-sustaining, and is cut off more and more to become (in some cases) a sort of 'inland island". Consider also the ongoing cost of defending these spaces in public policy.

despite the sea teaching harsh lessons about life to the author it's also a place of relaxation for them not only because of the childhood memories but also because it also shows with chaos there is also calmness

MCP: JSON file with agent meta data but not actual tools only instruction of how to connect(Look up table)

NANDA index: de centralized index quilt connects registries , security useful for next stages.

centralization

But what if a student doesn't budge/reflect on their interpretation and without facilitator/peer guidance comes to fully believe their incorrect interpretation?

But what is they are objectively incorrect intepretations?

The Cherokee believe that the Earth is being held up with seemingly invisible chords or strings that stretch to the heavens which I think is a very interesting way to think about it.

But he is unaware that he is in False Barn County, and that this is the one real barn

But isn't the belief that he isn't in False Barn County a false belief?

But aren't some false beliefs more important than others?

Connection: This discussion of equity resonated with the current material presented in my 5351 course. More specifically, I would like to draw ties to “The African-Centered Worldview: Toward a Paradigm for Social Work” written by Mekada J. Graham for the Journal of Black Studies. The article highlights the critical failures of social work theory in that it is foundationally ethnocentric. More specifically, social work theory is Eurocentric as its knowledge base is formed by the systems that see an overrepresentation of Black clients. Simply put, practitioners of social work have historically applied ethnocentric theory and practice to their aid of all individuals and groups.

This being said, a line can be drawn here between equity v. equality and Afrocentric ideals v. Eurocentric ideals. Equality would seem to prescribe traditional social work theory to all, providing aid and care in a manner that is similar for each individual. However, an equity approach is analogous to the Afrocentric approach, as diverse groups and varied individuals require tailored social work that does not look the same for all. This can be further proven by examining the outcomes of a universally prescribed social work theory. Graham's article states that Black individuals are overrepresented in social work, meaning that they are most commonly in stages of disparity and seeking out aid. They are also underrepresented in preventative aid, meaning that the overrepresentation and magnified need could be alleviated if an equity approach, not an equality approach, is taken systematically. The equity approach is connected to the application of an Afrocentric approach for these reasons.

Questions 1. What steps can be implemented when a social worker is attempting to understand the intersectionality of the client while maintaining mutual respect? 2. As an African American social worker that serves majority Caucasian clients, explain how cultural humility can help shape cultural competency.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

Referee #3

Evidence, reproducibility and clarity

In this work Neupane et al used large-scale robust CRISPR-based gene activation and ablation screens to identify novel regulators of α-synuclein pathology in synucleinopathies using as read-out p-αSyn129 signals by high-throughput fluorescence microscopy. The authors reveal that mitochondrial protein OXR1 promotes Ser129-phosphorylated αSyn aggregation, while ER-associated EMC4 suppresses it via enhanced autophagic clearance, highlighting new possible mechanistic pathways in disease progression of alpha-synucleinopathies.

Major comments:

1. As correctly pointed out by the authors in Introduction p-Syn is associated with aggregates, but its functional role is far to be clear and both neuroprotective or pro-aggregations effects have been proposed. Further it has been shown that, physiological neuronal activity augments Ser129-phospho αSyn, which is a trigger for protein-protein interactions, which in turn is necessary for mediating αSyn function at the synapse (https://doi.org/10.1016/j.neuron.2023.11.020). As a consequence modulation of p- p-αSyn as possible therapeutical target for PD and synucleinopathies is quite a complicate matter. The assumption, on which the whole paper is based, that increase in p-αSyn equates to αSyn aggregation and disease progression is rather weak to this reviewer, unless further validation of it is provided. Indeed while the authors performed experiments on human iPSC-derived cortical and dopaminergic neurons on p-αSyn analysis, any measurement of αSyn aggregates/oligomers, and neuronal degeneration is provided. It is recommended to provid this experiments ideally using different tecnique like αSyn-Proximity Ligation Assay for measurements of oligomers, as it has been largely validated in autoptic brains of PD, MSA and DLB patients (doi: 10.1007/s00401-025-02871-w.), as well as cell viability/apoptosis and neurites degeneration measurements upon OXR1 and EMC4 modulation in iPSC derived cortical and dopaminergic neurons.
2. The authors claims in Results page 5: "The absence of cytoplasmic pSyn129 signal in HEK293 cells lacking α-Syn overexpression demonstrates that elevated α-Syn levels are essential to drive robust and rapid aggregation. Moreover, it indicates that the 81A antibody selectively recognizes de novo aggregates rather than the recombinant seeds". The fact that ab81A recognize deNovo aggregates and not rec seeds is quite speculative, not supported by data, and might rather indicate that ab 81A does not recognize aggregates. Thus this further implays that other technology like for example Seeding amplification assays are being employed by the authors in addition to p-αSyn129 signals in validation experiments for example in genetic PD (ideally GBA1 or LRRK2) IPSC-derived dopaminergic neurons.

Minor comments:

1. The strain-specific effects especially from patients-derived fibrils of OXR1 activation and EMC4 depletion on pSyn levels is rather weak in comparison with RAB3 and PIKFYVE (fig 3F-G) and therefore the expected relevance of these results especially in vivo in patients should be better clarified and modulated in discussion
2. In discussion authors write "We observed that OXR1 activation preferentially increases α-Syn aggregates phosphorylation (EP1536Y) in neuronal somata, suggesting that mitochondrial dysfunction exacerbates α-Syn phosphorylation in later-stage aggregates." This is quite a surprising result since distal axonal endings are particularly susceptible to mitochondrial impairments for anatomical and physiologically reasons and if p-αSyn129 accumulation is driven by mithocondrial disfunction as suggested by this paper, this should be detected in neurites as well. Please clarify.
3. Authors say that they targeted mitochondrial, trafficking, and motility (MTM) genes in human cellular models. While mitochondrial and trafficking is clear in the context of Parkinson and neurodegnerative disease, less clear is the motility genes. Please expand on this.

Significance

This is a well written, comprehensive study with a well characterized, robust CRISPR-based gene activation and ablation screening pipeline to identify novel regulators of α-synuclein pathology. Methodology is rigorous and clearly described and results are well presented. The major limitation relays in the validation experiments where only one main read-out that is p-αSyn129 fluorescence signal is employed, limiting the significance and impact of the presented results. I believe that the basic science community might benefit principally of the proposed methodology of a large high-throughput screening to modulate a large set of genes, a platform that in principle might be used also for other scientific questions.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

Referee #2

Evidence, reproducibility and clarity

In the present study, Neupane et al. performed arrayed CRISPR activation and ablation screens, targeting genes related to mitochondria, trafficking and motility, to identify genes that modulate the presence of Ser 129 phosphorylated alpha-synuclein aggregates (pSyn129) upon administration of exogenous preformed alpha-synuclein fibrils. The screens have been performed in HEK cells stably overexpressing alpha-synuclein in two independent replicates, and hits have been further validated in induced pluripotent stem cell derived forebrain and dopaminergic neurons. Following functional validations, the authors conclude that enhancing the expression of OXR1 results in a modest increase in the number of pSyn129 puncta within cells, and their size, while partial loss of EMC4 expression reduces these puncta. To date some pre-print studies have used genome-wide CRISPR screening to identify modifiers of the accumulation of alpha-synuclein preformed fibrils in cells, suggesting the importance of uptake and endolysosomal trafficking for the propagation of alpha-synuclein aggregates in recipient cells. Although the topic is of interest in the field of Parkinson's disease and synucleinopathies in general, the readout of the present screen (presence of pSyn129) is not very sensitive and without investigating endogenous alpha-synuclein or cell homeostasis in neuronal models limits the stated conclusions.

Major comments:

• Please clarify whether the positive control genes RAB13 and PIKFYVE were nominated hits within the CRISPR screens. Specifically, the authors state that the positive control of the CRISPRa screen was RAB13, expected to reduce pSyn129 upon overexpression, nevertheless this gene does not appear as a hit in the CRISPRa volcano plot (although present in table S1 but not making the cutoff). In figure 2D, activation of RAB13 does not seem to impact the main readout phenotype. Moreover, in the CRISPRo screen, PIKFYVE was used, but this gene is also not presented as a hit linked to reducing pSyn129 in the CRISPRo plot. If these control genes do not come up as hits, it is difficult to support the conclusions of the screen.
• The effect size for screen hits presented in figure 2A/B is rather small. It is difficult to interpret the power of these findings in the absence of uptake efficiency controls, such as dextrans of appropriate molecular weights.
• The readout of the screen is not very sensitive, and it is unclear what it represents. Specifically, in Figure 2F, G the authors validate the hits OXR1 and EMC4, showing a small effect, albeit statistically significant. The authors should strengthen this data by adding more experiments addressing, for instance, what the pSyn spot area and spot intensity signify for the cell. Some experiments in a neuronal context are important, including SNCA KO as a negative control.
• It is unclear why the authors chose to follow up on the OXR1 and EMC4 hits. Please explain the rationale for follow-up studies.
• Generally, the notable difference in the number of pSyn129+ cells in the non-targeting across various experiments (including Fig.1G/I compared to Fig.2G/I or Fig. 3F/G or flow cytometry experiment) suggests the readout is not very sensitive.

For instance, in figure S3 it would be important to add an experiment controlling for cell number as opposed to LDH release, as the micrographs show some differences in cells number, e.g. in the ntg vs. EMC4 condition. - The data is not sufficient to suggest that OXR1 and EMC4 are strong modulators of alpha-synuclein aggregation, as the authors suggest based on figures 2 and 3 that show statistically significant difference and a rather small effect size. It is important to provide more insight into how these genes may affect endogenous alpha-synuclein and cellular homeostasis in more detail, especially in neuronal models. Further investigating the hits in this direction in additional genetic backgrounds would also increase the relevance of the findings, e.g. in SNCA triplication or GBA-PD neurons.<br /> In Fig. S8B the immunoblot analysis shows there may be an effect of EMC4 and OXR1 CRISPRa on α-synuclein levels; please quantify for both iPSC-derived cortical neurons and dopaminergic neurons. - The pattern of tyrosine hydroxylase staining in Figure 5F does not seem specific or as expected for iPSC-derived dopaminergic neurons. Furthermore, since endogenous SNCA expression is expected to be analogous to the expression of TH (with TH+ cells expressing higher SNCA), it would be important to compare pSyn129 between TH+ cells and/or relative to the TH+ area.

Minor comments:

• The authors report that RAB13 overexpression reduces pSyn129⁺ prevalence, whereas RAB13 ablation (CRISPRo screen) enhances pSyn129⁺ levels (Figures 2D-2E). Please revise as these specific figures show no effects for this gene.
• Please specify how many individual cells (approximately) were quantified in each figure legend.
• Figure 3F/G may be better as a supplemental figure since it does not add to the conclusions of the study.
• It would be good to clarify for the reader some of the genes that serve as positive controls for the screen's readout (as shown in Fig. S2D/G).
• It would be helpful to further clarify which cell type was used in each figure legend.

Significance

Important topic but their experimental design limits the significance of their findings. Hard to improve the work in a reasonable amount of time. Also many technical issues.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

Referee #1

Evidence, reproducibility and clarity

Summary:

This study by Neupane et al. investigates modulators of α-synuclein aggregation, focusing on Ser129-phosphorylated α-synuclein (pSyn129), a pathological hallmark of Parkinson's disease (PD). The authors performed high-content image-based, arrayed CRISPR activation (CRISPRa) and knockout (CRISPRo) screens targeting > 2300 genes related to mitochondrial function, intracellular trafficking, and cytoskeletal reorganization. Using α-Syn overexpressing HEK293 cells, they identified OXR1 and EMC4 as novel modulators of pSyn129 abundance. Key findings were that activation of the mitochondrial protein OXR1 increased pSyn129 by decreasing ATP levels, while ablation of the ER-associated protein EMC4 reduced pSyn129 by enhancing autophagic flux and lysosomal clearance. These findings were validated in human iPSC-derived cortical and dopaminergic neurons.

My major comments have to do with statistical methods and with significance of their findings.

Major comments:

Are the claims and the conclusions supported by the data or do they require additional experiments or analyses to support them?

The claims and conclusions are generally well-supported by the presented data. The dual CRISPRa/CRISPRo screen provides a robust initial discovery platform, and the validation in iPSC-derived neurons strengthens the findings and their translational relevance. The mechanistic insights into OXR1 (ATP levels) and EMC4 (autophagic flux, lysosomal clearance) are supported by the described experiments. The use of two antibodies (81A and EP1536Y) for pSyn129 also enhances confidence in the measurements. I had a few questions about the statistical methods. The main concern I have about methodology for the screen is whether the authors have corrected for multiple hypotheses in their discovery screen. This is not clear from the text, methods, or legends (for Figures 2A/2B/2C).

• Figure 1B suggests a very large range of activation (multiple orders of magnitude) in the initial screen. What is the relationship between level of expression change and functional effect across the screen? How upregulated/downregulated are OXR1 and EMC4 at the mRNA and protein levels?
• Supplemental Figure S2D: Why do the non-targeting controls differ from the majority of the CRISPRa genes? If I am reading the figure correctly, it seems strange that the vast majority of the CRISPRa gene targets reduces pSyn pathology relative to the non-targeting controls (which is why I am wondering whether the level of increased expression correlates with the level of functional effect).
• In Figure 2A/B/C, is the p-value adjusted in any way for multiple comparisons? If so, this should be indicated in the legend. If not, why not? (The potential for false positives in a screen is very large and requires correction for multiple comparisons.)
• Figure 3: It's interesting that different seeding materials have different effects. However, it's quite surprising that the authors find less seeding with MSA-derived material in both the CRISPRa and CRISPRo context. This contradicts the work of Peng and coauthors (PMID 29743672) who find that MSA-derived material is much more potent in seeding aggregates in a number of different cell types. Do the authors have any thoughts about why this is the case?
• Figure 7A: pSyn129 image in the non-targeting control is poor - the very bright dots look like artifact. Not clear why the authors don't corroborate with EP1536Y antibody as they do in Figure 5.
• Overall methodology: Are the pSyn inclusions soluble? This could be easily determined by performing 1% TritonX extraction, for example, and it helps us understand how "pathological" the inclusions are.
• OPTIONAL: The authors perform some interesting experiments looking at genes affected downstream by, for example, OXR1 over-expression. It would be useful to understand whether the upstream effect is dependent on downstream effect. This could be tested by performing double perturbations (e.g. OXR1 overexpression and CCL8 knockout or ALDOC upregulation).
• OPTIONAL: The link between EMC4 ablation and enhanced ER-driven autophagic flux/lysosomal clearance could be corroborated with additional experiments. E.g.: Does EMC4 normally inhibit this pathway? Or only in the context of aSyn fibril seeding?

Are the suggested experiments realistic in terms of time and resources?

The OPTIONAL experiments are generally feasible as they employ methods that the lab is already using in this paper.

Are the experiments adequately replicated and statistical analysis adequate?

See comment about multiple hypothesis testing above.

Significance

This is a well-designed, difficult-to-accomplish study that expands the landscape of pS129Syn modulators. The validation of the primary hits identified in HEK293 cells in iPSC-derived neurons gives the findings greater relevance.

Strengths:

• Novelty: Using an unbiased and high-throughput approach, the study identifies two novel regulators of α-Syn aggregation, namely OXR1 and EMC4.
• Methodological Rigor: The use of arrayed CRISPRa/CRISPRo screens with high-content imaging is powerful and difficult to accomplish. Methodologically, this is a tour de force.
• Orthogonal Validation: The use of multiple α-Syn fibril polymorphs/strains and different antibodies (81A, EP1536Y) strengthens the robustness of the findings.

Limitations:

• It's not clear to me that pSyn129 is the ultimate readout. At a minimum, we should know something about the solubility of the inclusions. Some panels (e.g. Figure 7A) are not very informative in terms of what the authors are calling pSyn129+.
• The study relies on in vitro cellular models. While iPSC-derived neurons are relevant, the complexity of the brain environment, including glial cell interactions is not fully captured. This is fine for an initial report, but it does limit the significance.
• OXR1 and EMC4 seem to be very generic modulators. It's not clear to me that their effects are specific to aSyn or to PD in any way - they might just be effects on very basic cellular functions that would be applicable to a number of stressors or proteinopathies. Maybe that is fine (we probably need to get rid of tau aggregates, too!), but I don't think the authors can claim that they have identified "organelle-specific genetic nodes of aSyn pathology" since they biased their screen towards mitochondria and they don't test any other pathological aggregates. Moreover, from a translational perspective, it's not clear to me that implicating the antioxidant pathway or lysosomal/autophagosomal pathways in the pathogenesis of PD is new, and it's not clear that the specific genes identified would make good therapeutic targets.

technology is inherently biased. it is biased towards its creator and its creator's viewpoints. FOR EXAMPLE elon musk's grok

I'll leave this as a general comment. But remember your resume is to showcase who you are and how you can bring energy and skill to a job. Your bullet points could use a bit more energy or insight. You're first year dont sweat too much but you have to start putting emphasis on bullet points like in details. Bullshit if you have to but make it believable obviously. Your resume has so much more potential.

Also as Dan said fill up as much as you can cuz that white space at the bottom is a lot.

This one idk much to put in this one but I'm sure you can come up with 1-2 more setences on this. Projects are supposed to show what you can do and showcase your skill

I like this but I feel liek you can quantify a bit more like how many MLB data sets? or how many games in a season are you analyzing or even weekly or daily.

Mention what you used for front-end to visualize, you can just say plain HTML/CSS/JS or you can add a framework.

If you automated generation of social media graphics how much time did you save? You can quantify that.

Add more bullet points to this as I know there's not only one thing you learnt and front-end web development is a very BROAD topic.

DId you work with cross-functional teams? Did you improve a process that was slow initially by someone else on your team? Point out some languages you used.

Also idk this might be me nitpicking but idk if you're allowed to say the company project name as thats usualyl private but yet again sicne its a highschool i dont thinkl they care all that much.

Also I would rename this as "Software Developer Intern" or something because it looks like an internship seeing it spanned months. or Full Stack but since you said front end I'd just keep software developer intern or Front end developer intern.

I wonder if when a child learns many languages during childhood, the brain treats the communicative systems as all a unified mechanism, as if it if was one whole language composed of several words that are synonyms and antonyms in the semantic spectrum. Under this logic, the benefit would be for adult learners who then would consider different languages as different communicative systems, therefore locating them in different regions of the brain and ultimately enhacing neuroplasticity and synapses.

WAS gap in litrature on how powerful ID was in EP -> voting influence tool helps us to see (that they are often part of coalitions but thats it)

"This article aims to address this gap by introducing a new measure of voting influence, thereby contributing to the existing literature on the impact of radical right parties."

CONCLUSION: - ID / radical right groups are OFTEN part of winning coalitions within the EP - This does NOT mean that the group is influential (I think because still of internal infighting? - Is a crucial partner of the EPP in "some cases"

So parties don't want to work w/ ID as opposed to CR (other less radical conservative party)

BUT voting share has increased much in past five years.

THIS article is going to MEASURE / EXAMINE THE VOTING INFLUENCE OF ID IN THE EP -> doing so by lookin at the "final stage of decision making in the EP" which is PLENARY VOTING

Voting influence (introduce term here): - "ability of a party group to sway the outcome of a vote" - Basically applies to PLENARY voting WITHIN the EP -. doesn't refer to ballot box.

why is this young child so anxious?

The north was always more progressive, and there was a time when the republican part provided that, but as the population become younger and catholic and immigrant, the democrats were actually the party that had the opportunity for liberalism

But isn't this not analogous to today since the views on states rights would flip which party it found a home under

But hasn't given new england the same voting power as the south

Interesting that CITIZENS of West Germany are allowed to enter -> blames government filled w/ Nazis and American "imperialism" -> again drawing link between Bonn govt and Nazism (directly, successor state, GDR only denazified state)

"Visits by peaceful citizens of West Berlin to the capital of the German Democratic Republic (the democratic Berlin) are possible upon presentation of a West Berlin identity card. Revanchist politicians and agents of West German militarism will not be allowed to set foot in the capital of the GDR (democratic Berlin)."

But then what about GDR citizens? -> Need "spevcial permission" which seems to betray a kind of anxiety ovr brain drain / undermined control.

IS possible for women to contribute to national community (i.e., by participating in the labour economy). Hitler says women would be contributing as much as, say, husbands/fathers if they worked (strenuous) jobs AND were the only caretakers of their families.

"There may indeed be cases in which justice requires that a woman should receive the same income as a man if she is engaged in typical men's work, e.g. that of a heavy or very heavy worker and if, in addition, she has to care for children in place of a husband. But then one should achieve the equality not by increasing the basic wage, but through child allowances or, even better, through an appropriate reduction in taxes. For such a woman is contributing to the maintenance of the national community in the same way as a family man.'"

SUB argument / evidence for no equal pay for equal work -> because doesn't make economic sense: i.e., wages WON'T improve people's efficiency -> not how that works, also wartime economy cannot handle it. Specifically because it would only increase purchases on the "Black Market" Says, I guess, that they CAN externally improve women's performance in facotires, but only by increasing food supplies -> no consumer goods since war, so this would mean contributing to the Black Market.

"cannot anticipate a significant improvement in performance by equalizing the pay of men and women. Money is not worth as much as it used to be because there is a dearth of consumer goods which can be bought. "

"An increase in women's wages would in practice simply mean strengthening the black market. If one wanted to achieve a general improvement in performance that could only be done by improving food supplies and the supply of the most important commodities."

Equal pay for equal work is false

Why? BECAUSE women (again, according to Hitler, of all people) are meant to work "at home" to look after their families. Hitler doesn not consider this domestic labour to be as important as a husband/father's work in supporting the family and "national community" -> explicitly states that it is more important. "because they must make more sacrifices for the national community."

Framed in context of wages being paid NOT for performance but for "social reasons" -> namely, implicitly, workers should be paid accorindg to how much they need the money for a family / how much they contribute to "national community"

Hitler thinks that wages should NOT be paid on performance -> justifies this decision by saying that young (male) workers shouldn't be paid more than old ones even though they can likely work faster and for longer. Instead, older men should be paid more because, again, they have families to support and contribute more to the "national community". Younger men work faster but do not contribute as much because they are unattched.

Hitler, again, maintains that women both do not perform well compared to men AND have less to contribute to families / national community -> "only have themselves to look after" (in a patrarchal assumption)

In my opinion, America is so expensive now that even basic rent is hard to afford compared to people’s salary. If the monthly salary was at least three times higher than the rent, maybe people could actually survive, but right now after paying rent you still have to buy food and pay gas, internet, and electricity, so many people really cannot afford it. People are just working so hard every single day just to survive, repeating the same struggle until they cannot make it anymore, and sometimes that pressure pushes them into decisions they never really wanted to make.

"How do we know what we think we know" When reading this question, I didn't know quite how to respond. But reading about all the five societal interpretation, I understand more. There are so many different ways to interpret things. We all assimilate different thoughts and perceptions. For me, I would say that personal experiences would be the reason why I know things. But reading on, ones experience might not be the same for another persons experience. In conclusion, every person in the world works differently. One might not agree on how another person on how they interpret things. All in all, we need to be respectful of all differences and different opinions.

When people are very poor and just trying to survive, some end up doing crime, but rich people with good schools and connections don’t face that same survival pressure.

This part is a really big deal for me, because as a child if your parents have good education and a stable salary, they don’t struggle with money and their kids usually get good connections, good schools, and higher knowledge. But if you grow up with no money like me, you don’t start with those advantages, and your life chances depend a lot on how hard you work and any small connections you can build.

In my opinion, many older people are actually happy because they already experienced life. They experienced joy, they saw what they wanted to see, and they watched the world and their places change over time. Some of them might feel sad because they think they did not achieve enough, but they still experienced life and they saw what they had to see.

I’m not American, I’m Filipino. I used to think a lot of Filipino families are good families, because no matter how hard life is and how poor it is, they stick together. Even if there is a lot of fighting, yelling, shouting, they still stay together. I felt so proud that my mom and dad are still married. But these days I found out the true story, that my dad is not perfect, and the story I knew in the past is getting destroyed by learning what the real story or real picture is.

As for me, I cannot say to someone that I know about them when in reality I don’t. I can judge, but I cannot say I really know, because that is a big deal. I never put my shoes in their shoes, so how can I say I know?

When I first got here in America, there were certain things I believed because of my social background. My husband had a therapist, so I joined his therapy. At first, I just listened to other people’s problems and issues, until the therapist asked me about my own feelings about my family. I had a lot of beliefs like ‘my family is great,’ but when he asked me, I felt doomed because I didn’t know what to say and I didn’t even know the definition of feelings. As we kept working, I started to see the reality. I saw the true color, the true image of my past. I realized I have a lot of trauma, but at least now I can face it. I can see it is there, instead of lying to myself that it is not there. I know it’s not perfect and I still have a lot of issues and a lot of scramble in my life, but at least I can work on it now.

Yes, of course people have their own thoughts and their own mind. They get influenced by what they see, what they hear, and the people around them, but they still have their own mindset. They still have their own feelings and judgment about what’s going on around them, so they don’t always follow the pattern.

? Article talks about how it should be regular, but then says "monthly tasks for neighbors." Are those rlly regular?

Whats the difference? Don't obey them to a tee?

For people party it was on hand but it must have also been colonial motivations

But again gives an opportunity for SELF selection of whats important

This is interesting, and I am wondering how much further would teachers have to work during outside contract hours to make this a reality. Is this a realistic thing to expect most teachers to do? Yes, it is good, but I worry about more things being added on teacher's plates without additional pay. Just additional work. Another question, if it IS additional work and no additional pay, would that STILL be worth it? If it increases career satisfaction?

Not only is art integration good for students, but it is also good for teachers. I think that is an excellent argument, however a question I might have is is it good for ALL teachers? Or just those who are more creatively inclined? I am very creatively inclined, however I wonder if arts integration would have the same affect on a person who has never had much interest in creative arts.

Reviewer #2 (Public review):

Summary:

In this work, Gupta & Murphy present several parallel efforts. On one side, they present the hardware and software they use to build a head-fixed mouse experimental setup that they use to track in "real-time" the calcium activity in one or two spots at the surface of the cortex. On the other side, they present another setup that they use to take advantage of the "real-time" version of DeepLabCut with their mice. The hardware and software that they used/develop is described at length, both in the article and in a companion GitHub repository. Next, they present experimental work that they have done with these two setups, training mice to max out a virtual cursor to obtain a reward, by taking advantage of auditory tone feedback that is provided to the mice as they modulate either (1) their local cortical calcium activity, or (2) their limb position.

Strengths:

This work illustrates the fact that thanks to readily available experimental building blocks, body movement and calcium imaging can be carried out using readily available components, including imaging the brain using an incredibly cheap consumer electronics RGB camera (RGB Raspberry Pi Camera). It is a useful source of information for researchers that may be interested in building a similar setup, given the highly detailed overview of the system. Finally, it further confirms previous findings regarding the operant conditioning of the calcium dynamics at the surface of the cortex (Clancy et al. 2020) and suggests an alternative based on deeplabcut to the motor tasks that aim to image the brain at the mesoscale during forelimb movements (Quarta et al. 2022).

Weaknesses:

This work covers 3 separate research endeavors: (1) The development of two separate setups, their corresponding software. (2) A study that is highly inspired from the Clancy et al. 2021 paper on the modulation of the local cortical activity measured through a mesoscale calcium imaging setup. (3) A study of the mesoscale dynamics of the cortex during forelimb movements learning. Sadly, the analyses of the physiological data appears incomplete, and more generally, the paper shows weaknesses regarding several points:

The behavioral setups that are presented are representative of the state of the art in the field of mesoscale imaging/head fixed behavior community, rather than a highly innovative design. Still, they definitely have value as a starting point for laboratories interested in implementing such approaches.

Throughout the paper, there are several statements that point out how important it is to carry out this work in a closed-loop setting with an auditory feedback, but sadly there is no "no feedback" control in cortical conditioning experiments, while there is a no-feedback condition in the forelimb movement study, which shows that learning of the task can be achieved in the absence of feedback.

The analysis of the closed-loop neuronal data behavior lacks controls. Increased performance can be achieved by modulating actively only one of the two ROIs, this is not really analyzed, while this finding which does not match previous reports (Clancy et al. 2020) would be important to further examine.

Author response:

The following is the authors’ response to the original reviews.

Public reviews:

Reviewer #1 (Public review):

Summary: 

The authors provide a resource to the systems neuroscience community, by offering their Python-based CLoPy platform for closed-loop feedback training. In addition to using neural feedback, as is common in these experiments, they include a capability to use real-time movement extracted from DeepLabCut as the control signal. The methods and repository are detailed for those who wish to use this resource. Furthermore, they demonstrate the efficacy of their system through a series of mesoscale calcium imaging experiments. These experiments use a large number of cortical regions for the control signal in the neural feedback setup, while the movement feedback experiments are analyzed more extensively.

Strengths:

The primary strength of the paper is the availability of their CLoPy platform. Currently, most closed-loop operant conditioning experiments are custom built by each lab and carry a relatively large startup cost to get running. This platform lowers the barrier to entry for closed-loop operant conditioning experiments, in addition to making the experiments more accessible to those with less technical expertise.

Another strength of the paper is the use of many different cortical regions as control signals for the neurofeedback experiments. Rodent operant conditioning experiments typically record from the motor cortex and maybe one other region. Here, the authors demonstrate that mice can volitionally control many different cortical regions not limited to those previously studied, recording across many regions in the same experiment. This demonstrates the relative flexibility of modulating neural dynamics, including in non-motor regions.

Finally, adapting the closed-loop platform to use real-time movement as a control signal is a nice addition. Incorporating movement kinematics into operant conditioning experiments has been a challenge due to the increased technical difficulties of extracting real-time kinematic data from video data at a latency where it can be used as a control signal for operant conditioning. In this paper they demonstrate that the mice can learn the task using their forelimb position, at a rate that is quicker than the neurofeedback experiments.

Weaknesses:

There are several weaknesses in the paper that diminish the impact of its strengths. First, the value of the CLoPy platform is not clearly articulated to the systems neuroscience community. Similarly, the resource could be better positioned within the context of the broader open-source neuroscience community. For an example of how to better frame this resource in these contexts, I recommend consulting the pyControl paper. Improving this framing will likely increase the accessibility and interest of this paper to a less technical neuroscience audience, for instance by highlighting the types of experimental questions CLoPy can enable.

We appreciate the editor’s feedback regarding the clarity of the CLoPy platform's value and its positioning within the broader neuroscience community. We agree and understand the importance of effectively communicating the utility of CLoPy to both the systems neuroscience field and the wider open-source neuroscience community.

To address this, we have revised the introduction and discussion sections of the manuscript to more clearly articulate the unique contributions of the CLoPy platform. Specifically:

(1) We have emphasized how CLoPy can address experimental questions in systems neuroscience by highlighting its ability to enable real-time closed-loop experiments, such as investigating neural dynamics during behavior or studying adaptive cortical reorganization after injury. These examples are aimed at demonstrating its practical utility to the neuroscience audience.

(2) We have positioned CLoPy within the broader open-source neuroscience ecosystem, drawing comparisons to similar resources like pyControl. We describe how CLoPy complements existing tools by focusing on real-time optical feedback and integration with genetically encoded indicators, which are becoming increasingly popular in systems neuroscience. We also emphasize its modularity and ease of adoption in experimental settings with limited resources.

(3) To make the manuscript more accessible to a less technically inclined audience, we have restructured certain sections to focus on the types of experiments CLoPy enables, rather than the technical details of the implementation.

We have consulted the pyControl paper, as suggested, and have used it as a reference point to improve the framing of our resource. We believe these changes will increase the accessibility and appeal of the paper to a broader neuroscience audience.

While the dataset contains an impressive amount of animals and cortical regions for the neurofeedback experiment, and an analysis of the movement-feedback experiments, my excitement for these experiments is tempered by the relative incompleteness of the dataset, as well as its description and analysis in the text. For instance, in the neurofeedback experiment, many of these regions only have data from a single mouse, limiting the conclusions that can be drawn. Additionally, there is a lack of reporting of the quantitative results in the text of the document, which is needed to better understand the degree of the results. Finally, the writing of the results section could use some work, as it currently reads more like a methods section.

Thank you for your thoughtful and constructive feedback on our manuscript. We appreciate the time and effort you took to review our work and provide detailed suggestions for improvement. Below, we address the key points raised in your review:

(1) Dataset Completeness: We acknowledge that some of the neurofeedback experiments include data from only a single mouse for some cortical regions while for some cortical regions, there are several animals. This was due to practical constraints during the study, and we understand the limitations this poses for drawing broad conclusions. We felt it was still important to include these data sets with smaller sample sizes as they might be useful for others pursuing this direction in the future. To address this, we have revised the text to explicitly acknowledge these limitations and clarify that the results for some regions are exploratory in nature. We believe our flexible tool will provide a means for our lab and others include more animals representing additional cortical regions in future studies. Importantly, we have included all raw and processed data as well as code for future analysis.

(2) Quantitative Results: We recognize the importance of reporting quantitative results in the text for better clarity and interpretation. In response, we have added more detailed description of the quantitative findings from both the neurofeedback and movement-feedback experiments. This will include effect sizes, statistical measures, and key numerical results to provide a clearer understanding of the degree and significance of the observed effects.

(3) Results Section Writing: We appreciate your observation that parts of the results section read more like a methods section. To improve clarity and focus, we have restructured the results section to present the findings in a more concise and interpretative manner, while moving overly detailed descriptions of experimental procedures to the methods section.

Suggestions for improved or additional experiments, data or analyses:

Not necessary for this paper, but it would be interesting to see if the CLNF group could learn without auditory feedback.

This is a great suggestion and certainly something that could be done in the future.

There are no quantitative results in the results section. I would add important results to help the reader better interpret the data. For example, in: "Our results indicated that both training paradigms were able to lead mice to obtain a significantly larger number of rewards over time," You could show a number, with an appropriate comparison or statistical test, to demonstrate that learning was observed.

Thank you for pointing this out. We have mentioned quantification values in the results now, along with being mentioned in the figure legends, and we are quoting it in following sentences. “A ΔF/F0 threshold value was calculated from a baseline session on day 0 that would have allowed 25% performance. Starting from this basal performance of around 25% on day 1, mice (CLNF No-rule-change, N=23, n=60 and CLNF Rule-change, N=17, n=60) were able to discover the task rule and perform above 80% over ten days of training (Figure 4A, RM ANOVA p=2.83e-5), and Rule-change mice even learned a change in ROIs or rule reversal (Figure 4A, RM ANOVA p=8.3e-10, Table 5 for different rule changes). There were no significant differences between male and female mice (Supplementary Figure 3A).”

For: "Performing this analysis indicated that the Raspberry Pi system could provide reliable graded feedback within ~63 {plus minus} 15 ms for CLNF experiments." The LED test shows the sending of the signal, but the actual delay for the audio generation might be longer. This is also longer than the 50 ms mentioned in the abstract.

We appreciate the reviewer’s insightful comment. The latency reported (~63ms) was measured using the LED test, which captures the time from signal detection to output triggering on the Raspberry Pi GPIO. We agree that the total delay for auditory feedback generation could include an additional latency component related to the digital-to-analog conversion and speaker response. In our setup, we employ a fast Audiostream library written in C to generate the audio signal and expect the delay contribution to be negligible compared to the GPIO latency. Though we did not do this, it can be confirmed by an oscilloscope-based pilot measurement (for additional delay calculation). We have updated the manuscript to clarify that the 63 ± 15 ms value reflects the GPIO-triggered output latency, and we have revised the abstract to accurately state the delay as “~63 ms” rather than 50 ms. This ensures consistency and avoids underestimation of the latency. We have corrected the LED latency for CLNF and CLMF experiments in the abstract as well.

It could be helpful to visualize an individual trial for each experiment type, for instance how the audio frequency changes as movement speed / calcium activity changes.

We have added Supplementary Figure 8 that contains this data where you can see the target cortical activity trace, target paw speed, rewards, along with the audio frequency generated.

The sample sizes are small (n=1) for a few groups. I am excited by the variety of regions recorded, so it could be beneficial for the authors to collect a few more animals to beef up the sample sizes.

We've acknowledged that some of the sample sizes are small. Importantly, we have included raw and processed data as well as code for future analysis. We felt it was still important to still include these data sets with smaller sample sizes as they might be useful for others pursuing this direction in the future.

I am curious as to why 60 trials sessions were used. Was it mostly for the convenience of a 30 min session, or were the animals getting satiated? If the former, would learning have occurred more rapidly with longer sessions?

This is a great observation and the answer is it was mostly due to logistical reasons. We tried to not keep animals headfixed for more than 45 minutes in each session as they become less engaged with long duration headfixed sessions. After headfixing them, it takes about 15 minutes to get the experiment going and therefore 30 - 40 minutes long recorded sessions seemed appropriate before they stop being engaged or before they get satiated in the task. We provided supplemental water after the sessions and we observed that they consumed water after the sessions so they were not fully satiated during the sessions even when they performed well in the task and got maximum rewards. We also had inter-trial rest periods of 10s that elongated the session duration. We think it would be interesting to explore the relationship between session duration(number of trials) and task learning progression over the days in a separate study.

Figure 4E is interesting, it seems like the changes in the distribution of deltaF was in both positive and negative directions, instead of just positive. I'd be curious as to the author's thoughts as to why this is the case. Relatedly, I don't see Figure 4E, and a few other subplots, mentioned in the text. As a general comment, I would address each subplot in the text.

We have split Figure 4 into two to keep the figures more readable. Previous Figure 4E-H are now Figure 5A-D in the revised manuscript. The online real-time CLNF sessions were using a moving window average to calculate ΔF/F₀  and the figures were generated by averaging the whole recorded sessions. We have added text in Methods under “Online ΔF/F₀calculation” and “Offline ΔF/F₀ calculation” sections making it clear about how we do our ΔF/F₀ normalization based on average fluorescence over the entire session. Using this method of normalization does increase the baseline so that some peaks appear to be below zero. Additionally, it is unclear what strategy animals are employing to achieve the rule specific target activity. The task did not constrain them to have a specific strategy for cortical activation - they were rewarded as long as they crossed the threshold in target ROI(s). For example, in 2-ROI experiments, to increase ROI1-ROI2 target activity, they could increase activity of ROI1 relative to ROI2 or decreased activity of ROI1 relative to ROI1 - both would have led to a reward as long as the result crossed the threshold.

We have now addressed and added reference to the figures in the text in Results under “Mice can explore and learn an arbitrary task, rule, and target conditions” and “Mice can rapidly adapt to changes in the task rule” sections - thanks for pointing this out.

For: "In general, all ROIs assessed that encompassed sensory, pre-motor, and motor areas were capable of supporting increased reward rates over time," I would provide a visual summary showing the learning curves for the different types of regions.

We have rewritten this section to emphasize that these conclusions were based on pooled data from multiple regions of interest. The sample sizes for each type of region are different and some are missing. We believe it would be incomplete and not comparable to present this as a regular analysis since the sample sizes were not balanced. We would be happy to dive deeper into this and point to the raw and processed dataset if anyone would like to explore this further by GitHub or other queries.

Relatedly, I would further explain the fast vs slow learners, and if they mapped onto certain regions.

Mice were categorized into fast or slow learners based on the slope of learning over days (reward progression over the days) as shown in Supplementary Figure 3C,D. Our initial aim was not to probe cortical regions that led to fast vs slow learning but this was a grouping we did afterwards. Based on the analysis we did, the fast learners included the sensory (V1), somatosensory (BC, HL), and motor (M1, M2) areas, while the slow learners included the motor (M1, M2), and higher order (TR, RL) cortical areas. Testing all dorsal cortical areas would be prudent to establish their role in fast or slow learning and it is an interesting future direction.

Also I would make the labels for these plots (e.g. Supp Fig3) more intuitive, versus the acronyms currently used.

We have made more expressive labels and explained the acronyms below the Supplementary Figure 3.

The CLMF animals showed a decrease in latency across learning, what about the CLNF animals? There is currently no mention in the text or figures.

We have now incorporated the CLNF task latency data into both the Results text and Figure 4C. Briefly, task latency decreased as performance improved, increased following a rule change, and then decreased again as the animals relearned the task. The previous Figure 4C has been updated to Figure 4D, and the former Figure 4D has been moved to Supplementary Figure 4E.

Reviewer #2 (Public review):

Summary:

In this work, Gupta & Murphy present several parallel efforts. On one side, they present the hardware and software they use to build a head-fixed mouse experimental setup that they use to track in "real-time" the calcium activity in one or two spots at the surface of the cortex. On the other side, the present another setup that they use to take advantage of the "real-time" version of DeepLabCut with their mice. The hardware and software that they used/develop is described at length, both in the article and in a companion GitHub repository. Next, they present experimental work that they have done with these two setups, training mice to max out a virtual cursor to obtain a reward, by taking advantage of auditory tone feedback that is provided to the mice as they modulate either (1) their local cortical calcium activity, or (2) their limb position.

Strengths:

This work illustrates the fact that thanks to readily available experimental building blocks, body movement and calcium imaging can be carried using readily available components, including imaging the brain using an incredibly cheap consumer electronics RGB camera (RGB Raspberry Pi Camera). It is a useful source of information for researchers that may be interested in building a similar setup, given the highly detailed overview of the system. Finally, it further confirms previous findings regarding the operant conditioning of the calcium dynamics at the surface of the cortex (Clancy et al. 2020) and suggests an alternative based on deeplabcut to the motor tasks that aim to image the brain at the mesoscale during forelimb movements (Quarta et al. 2022).

Weaknesses:

This work covers 3 separate research endeavors: (1) The development of two separate setups, their corresponding software. (2) A study that is highly inspired from the Clancy et al. 2020 paper on the modulation of the local cortical activity measured through a mesoscale calcium imaging setup. (3) A study of the mesoscale dynamics of the cortex during forelimb movements learning. Sadly, the analyses of the physiological data appears uncomplete, and more generally the paper tends to offer overstatements regarding several points:

In contrast to the introductory statements of the article, closed-loop physiology in rodents is a well-established research topic. Beyond auditory feedback, this includes optogenetic feedback (O'Connor et al. 2013, Abbasi et al. 2018, 2023), electrical feedback in hippocampus (Girardeau et al. 2009), and much more.

We have included and referenced these papers in our introduction section (quoted below) and rephrased the part where our previous text indicated there are fewer studies involving closed-loop physiology.

“Some related studies have demonstrated the feasibility of closed-loop feedback in rodents, including hippocampal electrical feedback to disrupt memory consolidation (Girardeau et al.2009), optogenetic perturbations of somatosensory circuits during behavior (O'Connor et al.2013), and more recent advances employing targeted optogenetic interventions to guide behavior (Abbasi et al. 2023).”

The behavioral setups that are presented are representative of the state of the art in the field of mesoscale imaging/head fixed behavior community, rather than a highly innovative design. In particular, the closed-loop latency that they achieve (>60 ms) may be perceived by the mice. This is in contrast with other available closed-loop setups.

We thank the reviewer for this thoughtful comment and fully agree that our closed-loop latency is larger than that achieved in some other contemporary setups. Our primary aim in presenting this work, however, is not to compete with the lowest possible latencies, but to provide an open-source, accessible, and flexible platform that can be readily adopted by a broad range of laboratories. By building on widely available and lower-cost components, our design lowers the barrier of entry for groups that wish to implement closed-loop imaging and behavioral experiments, while still achieving latencies well within the range that can support many biologically meaningful applications.

For example, our latency (~60 ms) remains compatible with experimental paradigms such as:

Motor learning and skill acquisition, where sensorimotor feedback on the scale of tens to hundreds of milliseconds is sufficient to modulate performance.

Operant conditioning and reward-based learning, in which reinforcement timing windows are typically broader and not critically dependent on sub-20 ms latencies.

Cortical state dependent modulation, where feedback linked to slower fluctuations in brain activity (hundreds of milliseconds to seconds) can provide valuable insight.

Studies of perception and decision-making, in which stimulus response associations often unfold on behavioral timescales longer than tens of milliseconds.

We believe that emphasizing openness, affordability, and flexibility will encourage widespread adoption and adaptation of our setup across laboratories with different research foci. In this way, our contribution complements rather than competes with ultra-low-latency closed-loop systems, providing a practical option for diverse experimental needs.

Through the paper, there are several statements that point out how important it is to carry out this work in a closed-loop setting with an auditory feedback, but sadly there is no "no feedback" control in cortical conditioning experiments, while there is a no-feedback condition in the forelimb movement study, which shows that learning of the task can be achieved in the absence of feedback.

We fully agree that such a control would provide valuable insight into the contribution of feedback to learning in the CLNF paradigm. In designing our initial experiments, we envisioned multiple potential control conditions, including No-feedback and Random-feedback. However, our first and primary objective was to establish whether mice could indeed learn to modulate cortical ROI activation through auditory feedback, and to further investigate this across multiple cortical regions. For this reason, we focused on implementing the CLNF paradigm directly, without the inclusion of these additional control groups. To broaden the applicability of the system, we subsequently adapted the platform to the CLMF experiments, where we did incorporate a No-feedback group. These results, as the reviewer notes, strengthen the evidence for the role of feedback in shaping task performance. We agree that the inclusion of a No-feedback control group in the CLNF paradigm will be crucial in future studies to further dissect the specific contribution of feedback to cortical conditioning.

The analysis of the closed-loop neuronal data behavior lacks controls. Increased performance can be achieved by modulating actively only one of the two ROIs, this is not clearly analyzed (for instance looking at the timing of the calcium signal modulation across the two ROIs. It seems that overall ROIs1 and 2 covariate, in contrast to Clancy et al. 2020. How can this be explained?

We agree that the possibility of increased performance being driven by modulation of a single ROI is an important consideration. Our study indeed began with 1-ROI closed-loop experiments. In those early experiments, while we did observe animals improving performance across days, we realized that daily variability in ongoing cortical GCaMP activity could lead to fluctuations in threshold-crossing events. The 2-ROI design was subsequently introduced to reduce this variability, as the target activity was defined as the relative activity between the two ROIs (e.g., ROI1 – ROI2). This approach offered a more stable signal by normalizing ongoing fluctuations. In our analysis of the early 2-ROI experiments, we observed that animals adopted diverging strategies to achieve threshold crossings. Specifically, some animals increased activity in ROI1 relative to ROI2, while others decreased activity in ROI2 to accomplish the same effect. Once discovered, each animal consistently adhered to its chosen strategy throughout subsequent training sessions. This was an early and intriguing observation, but as the experiments were not originally designed to systematically test this effect, we limited our presentation to the analysis of a small number of animals (shown in Figure 11). We have added details about this observation in our Results section as well, quoted below-

“In the 2-ROI experiment where the task rule required “ROI1 - ROI2” activity to cross a threshold for reward delivery, mice displayed divergent strategies. Some animals predominantly increased ROI1 activity, whereas others reduced ROI2 activity, both approaches leading to successful threshold crossing (Figure 11)”.

We hope this clarifies how the use of two ROIs helps explain the apparent covariation of the signals, and why some divergence from the observations of Clancy et al. (2020) may be expected.

Reviewer #3 (Public review):

Summary:

The study demonstrates the effectiveness of a cost-effective closed-loop feedback system for modulating brain activity and behavior in head-fixed mice. Authors have tested real-time closed-loop feedback system in head-fixed mice two types of graded feedback: 1) Closed-loop neurofeedback (CLNF), where feedback is derived from neuronal activity (calcium imaging), and 2) Closed-loop movement feedback (CLMF), where feedback is based on observed body movement. It is a python based opensource system, and authors call it CLoPy. The authors also claim to provide all software, hardware schematics, and protocols to adapt it to various experimental scenarios. This system is capable and can be adapted for a wide use case scenario.

Authors have shown that their system can control both positive (water drop) and negative reinforcement (buzzer-vibrator). This study also shows that using the close loop system mice have shown better performance, learnt arbitrary task and can adapt to change in the rule as well. By integrating real-time feedback based on cortical GCaMP imaging and behavior tracking authors have provided strong evidence that such closed-loop systems can be instrumental in exploring the dynamic interplay between brain activity and behavior.

Strengths:

Simplicity of feedback systems designed. Simplicity of implementation and potential adoption.

Weaknesses:

Long latencies, due to slow Ca2+ dynamics and slow imaging (15 FPS), may limit the application of the system.

We appreciate the reviewer’s comment and agree that latency is an important factor in our setup. The latency arises partly from the inherent slow kinetics of calcium signaling and GCaMP6s, and partly from the imaging rate of 15 FPS (every 66 ms). These limitations can be addressed in several ways: for example, using faster calcium indicators such as GCaMP8f, or adapting the system to electrophysiological signals, which would require additional processing capacity. In our implementation, image acquisition was fixed at 15 FPS to enable real-time frame processing (256 × 256 resolution) on Raspberry Pi 4B devices. With newer hardware, such as the Raspberry Pi 5, substantially higher acquisition and processing rates are feasible (although we have not yet benchmarked this extensively). More powerful platforms such as Nvidia Jetson or conventional PCs would further support much faster data acquisition and processing.

Major comments:

(1) Page 5 paragraph 1: "We tested our CLNF system on Raspberry Pi for its compactness, general-purpose input/output (GPIO) programmability, and wide community support, while the CLMF system was tested on an Nvidia Jetson GPU device." Can these programs and hardware be integrated with windows-based system and a microcontroller (Arduino/ Tency). As for the broad adaptability that's what a lot of labs would already have (please comment/discuss)?

While we tested our CLNF system on a Raspberry Pi (chosen for its compactness, GPIO programmability, and large user community) and our CLMF system on an Nvidia Jetson GPU device (to leverage real-time GPU-based inference), the underlying software is fully written in Python. This design choice makes the system broadly adaptable: it can be run on any device capable of executing Python scripts, including Windows-based PCs, Linux machines, and macOS systems. For hardware integration, we have confirmed that the framework works seamlessly with microcontrollers such as Arduino or Teensy, requiring only minor modifications to the main script to enable sending and receiving of GPIO signals through those boards. In fact, we are already using the same system in an in-house project on a Linux-based PC where an Arduino is connected to the computer to provide GPIO functionality. Furthermore, the system is not limited to Raspberry Pi or Arduino boards; it can be interfaced with any GPIO-capable devices, including those from Adafruit and other microcontroller platforms, depending on what is readily available in individual labs. Since many neuroscience and engineering laboratories already possess such hardware, we believe this design ensures broad accessibility and ease of integration across diverse experimental setups.

(2) Hardware Constraints: The reliance on Raspberry Pi and Nvidia Jetson (is expensive) for real-time processing could introduce latency issues (~63 ms for CLNF and ~67 ms for CLMF). This latency might limit precision for faster or more complex behaviors, which authors should discuss in the discussion section.

In our system, we measured latencies of approximately ~63 ms for CLNF and ~67 ms for CLMF. While such latencies indeed limit applications requiring millisecond precision, such as fast whisker movements, saccades, or fine-reaching kinematics, we emphasize that many relevant behaviors, including postural adjustments, limb movements, locomotion, and sustained cortical state changes, occur on timescales that are well within the capture range of our system. Thus, our platform is appropriate for a range of mesoscale behavioral studies that probably needs to be discussed more. It is also important to note that these latencies are not solely dictated by hardware constraints. A significant component arises from the inherent biological dynamics of the calcium indicator (GCaMP6s) and calcium signaling itself, which introduce slower temporal kinetics independent of processing delays. Newer variants, such as GCaMP8f, offer faster response times and could further reduce effective biological latency in future implementations.

With respect to hardware, we acknowledge that Raspberry Pi provides a low-cost solution but contributes to modest computational delays, while Nvidia Jetson offers faster inference at higher cost. Our choice reflects a balance between accessibility, cost-effectiveness, and performance, making the system deployable in many laboratories. Importantly, the modular and open-source design means the pipeline can readily be adapted to higher-performance GPUs or integrated with electrophysiological recordings, which provide higher temporal resolution. Finally, we agree with the reviewer that the issue of latency highlights deeper and interesting questions regarding the temporal requirements of behavior classification. Specifically, how much data (in time) is required to reliably identify a behavior, and what is the minimum feedback delay necessary to alter neural or behavioral trajectories? These are critical questions for the design of future closed-loop systems and ones that our work helps frame.

We have added a slightly modified version of our response above in the discussion section under “Experimental applications and implications”.

(3) Neurofeedback Specificity: The task focuses on mesoscale imaging and ignores finer spatiotemporal details. Sub-second events might be significant in more nuanced behaviors. Can this be discussed in the discussion section?

This is a great point  and we have added the following to the discussion section. “In the case of CLNF we have focused on regional cortical GCAMP signals that are relatively slow in kinetics. While such changes are well suited for transcranial mesoscale imaging assessment, it is possible that cellular 2-photon imaging (Yu et al. 2021) or preparations that employ cleared crystal skulls (Kim et al. 2016) could resolve more localized and higher frequency kinetic signatures.”

(4) The activity over 6s is being averaged to determine if the threshold is being crossed before the reward is delivered. This is a rather long duration of time during which the mice may be exhibiting stereotyped behaviors that may result in the changes in DFF that are being observed. It would be interesting for the authors to compare (if data is available) the behavior of the mice in trials where they successfully crossed the threshold for reward delivery and in those trials where the threshold was not breached. How is this different from spontaneous behavior and behaviors exhibited when they are performing the test with CLNF? 

We would like to emphasize that we are not directly averaging activity over 6 s to compare against the reward threshold. Instead, the preceding 6 s of activity is used solely to compute a dynamic baseline for ΔF/F₀ ( ΔF/F₀ = (F –F₀ )/F₀). Here, F₀is calculated as the mean fluorescence intensity over the prior 6 s window and is updated continuously throughout the session. This baseline is then subtracted from the instantaneous fluorescence signal to detect relative changes in activity. The reward threshold is therefore evaluated against these baseline-corrected ΔF/F₀ values at the current time point, not against an average over 6 s. This moving-window baseline correction is a standard approach in calcium imaging analyses, as it helps control for slow drifts in signal intensity, bleaching effects, or ongoing fluctuations unrelated to the behavior of interest. Thus, the 6-s window is not introducing a temporal lag in reward assignment but is instead providing a reference to detect rapid increases in cortical activity.  We have added the term dynamic baseline to the Methods to clarify.

Recommendations for the authors

Reviewer #1 (Recommendations for the authors):

Additional suggestions for improved or additional experiments, data or analyses.

For: "Looking closely at their reward rate on day 5 (day of rule change), they had a higher reward rate in the second half of the session as compared to the first half, indicating they were adapting to the rule change within one session." It would be helpful to see this data, and would be good to see within-session learning on the rule change day

Thank you for pointing this out. We had missed referencing the figure in the text, and have now added a citation to Supplementary Figure 4A, which shows the cumulative rewards for each day of training. As seen in the plot for day 5, the cumulative rewards are comparable to those on day 1, with most rewards occurring during the second half of the session.

For: "These results suggest that motor learning led to less cortical activation across multiple regions, which may reflect more efficient processing of movement-related activity," it could also be the case that the behaviour became more stereotyped over learning, which would lead to more concentrated, correlated activity. To test this, it would be good to look at the limb variability across sessions. Similarly, if it is movement-related, there should be good decoding of limb kinematics.

Indeed, we observed that behavior became more stereotyped over the course of learning, as shown in Supplementary Figure 4C, 4D. One plausible explanation for the reduction in cortical activation across multiple regions is that behavior itself became more stereotyped, a possibility we have explored in the manuscript. Specifically, forelimb movements during the trial became increasingly correlated as mice improved on the task, particularly in the groups that received auditory feedback (Rule-change and No-rule-change groups; Figure 8). As movements became more correlated, overall body movements during trials decreased and aligned more closely with the task rule (Figure 9D). This suggests that reduced cortical activity may in part reflect changes in behavior. Importantly, however, in the Rule-change group, we observed that on the day of the rule switch (day 5), when the target shifted from the left to the right forelimb, cortical activity increased bilaterally (Figure 9A–C). This finding highlights our central point: groups that received feedback (Rule-change and No-rule-change) were able to identify the task rule more effectively, and both their behavior and cortical activity became more specifically aligned with the rule compared to the No-feedback group. We agree with the reviewers that additional analyses along these lines would be valuable future directions. To facilitate this, we have included the movement data for readers who may wish to pursue further analyses, details can be found under “Data and code availability” in Methods section. However, given the limited sample sizes in our dataset and the need to keep the manuscript focused on the central message, we felt that including these additional analyses here would risk obscuring the main findings.

For: "We believe the decrease in ΔF/F0peak is unlikely to be driven by changes in movement, as movement amplitudes did not decrease significantly during these periods (Figure 7D CLMF Rule-change)." I would formally compare the two conditions. This is an important control. Also, another way to see if the change in deltaF is related to movement would be to see if you can predict movement from the deltaF.

Figure 7D in the previous version is Figure 9D in the current revision of the manuscript. We've assessed this for the examples shown based on graphing the movement data, unfortunately there is not enough of that data to do a group analysis of movement magnitude. We would suggest that this would be an excellent future direction that would take advantage of the flexible open source nature of our tool.

Recommendations for improving the writing and presentation.

In the abstract there is no mention of the rationale for the project, or the resulting significance. I would modify this to increase readership by the behavioral neuroscience community. Similarly, the introduction also doesn't highlight the value of this resource for the field. Again, I think the pyControl paper does a good job of this. For readability, I would add more subheadings earlier in the results, to separate the different technical aspects of the system.

We have revised the introduction to include the rationale for the project, its potential implications, and its relevance for translational research. We have also framed the work within the broader context of the behavioral and systems neuroscience community. We greatly appreciate this suggestion, as we believe it enhances the clarity and accessibility of the manuscript for the community.

For: "While brain activity can be controlled through feedback, other variables such as movements have been less studied, in part because their analysis in real time is more challenging." I would highlight research that has studied the control of behavior through feedback, such as the Mathis paper where mice learn to pull a joystick to a virtual box, and adapt this motion to a force perturbation.

We have added a citation to the Mathis paper and describe this as an additional form of feedback. The text is quoted below:

“Opportunities also exist in extending real time pose classification (Forys et al. 2020; Kane et al. 2020) and movement perturbation (Mathis et al. 2017) to shape aspects of an animal’s motor repertoire.”

Some of the results content would be better suited for the methods, one example: "A previous version of the CLNF system was found to have non-linear audio generation above 10 kHz, partly due to problems in the audio generation library and partly due to the consumer-grade speaker hardware we were employing. This was fixed by switching to the Audiostream (https://github.com/kivy/audiostream) library for audio generation and testing the speakers to make sure they could output the commanded frequencies"

This is now moved to the Methods section.

For: "There are reports of cortical plasticity during motor learning tasks, both at cellular and mesoscopic scales (17-19), supporting the idea that neural efficiency could improve with learning," not sure I agree with this, the studies on cortical plasticity are usually to show a neural basis for the learning observed, efficiency is separate from this.

We have modified this statement to remove the concept of efficiency "There are reports of cortical plasticity during motor learning tasks, both at cellular and mesoscopic scales (17-19).”

The paragraph that opens "Distinct task- and reward-related cortical dynamics" that describes the experiment should appear in the previous section, as the data is introduced there.

We have moved the mentioned paragraphs in the previous section where we presented the data and other experiment details. This makes the text more readable and contextual.

I would present the different ROI rules with better descriptors and visualization to improve the readability.

We have added Supplementary Figure 7, which provides visualizations of the ROIs across all task rules used in the CLNF experiments.

Minor corrections to the text and figures.

Figure 1 is a little crowded, combining the CLNF and CLMF experiments, I would turn this into a 2 panel figure, one for each, similar to how you did figure 2.

We have revised Figure 1 to include two panels, one for CLNF and one for CLMF. The colored components indicate elements specific to each setup, while the uncolored components represent elements shared between CLNF and CLMF. Relevant text in the manuscript is updated to refer to these figures.

For Figure 2, the organization of the CLMF section is not intuitive for the reader. I would reorder it so it has a similar flow as the CLNF experiment.

We have revised the figure by updating the layout of panel B (CLMF) to align with panel A (CLNF), thereby creating a more intuitive and consistent flow between the panels. We appreciate this helpful suggestion, which we believe has substantially improved the clarity of the figure. The corresponding text in the manuscript has also been updated to reflect these changes.

For Figure 3, highlight that C and E are examples. They also seem a little out of place, so they could even be removed.

We have now explicitly labeled Figures 3C and 3E as representative examples (figure legend and on figure itself). We believe including these panels provides helpful context for readers: Figure 3C illustrates how the ROIs align on the dorsal cortical brain map with segmented cortical regions, while Figure 3E shows example paw trajectories in three dimensions, allowing visualization of the movement patterns observed during the trials.

In the plots, I would add sample sizes, for instance, in CLNF learning curve in Figure 4A, how many animals are in each group? 

We have labeled Figure 4 with number of animals used in CLNF (No-rule-change, N=23; Rule-change, N=17), and CLMF (Rule-change, N=8; No-rule-change, N=4; No-feedback, N=4).

Also, Figure 7 for example, which figures are single-sessions, versus across animals? For Figure 7c, what time bin is the data taken from?

We have clarified this now and mentioned it in all the figures. Figure 7 in the previous version is Figure 9 in the current updated manuscript. Figure 9A is from individual sessions on different days from the same mouse. Figure 9B is the group average reward centered ΔF/F₀ activity in different cortical regions (Rule-change, N=8; No-rule-change, N=4; No-feedback, N=4). Figure 9C shows average ΔF/F₀ peak values obtained within -1sec to +1sec centered around the reward point (N=8).

It says "punish" in Figure 3, but there is no punishment?

Yes, the task did not involve punishment. Each trial resulted in either a success, which is followed by a reward, or a failure, which is followed by a buzzer sound. To better reflect these outcomes, we have updated Figure 3 and replaced the labels “Reward” with “Success” and “Punish” with “Failure.”

The regression on 5c doesn't look quite right, also this panel is not mentioned in the text.

The figure referred to by the reviewer as Figure 5 is now presented as Figure 6 in the revised manuscript. Regarding the reviewer’s observation about the regression line in the left panel of Figure 5C, the apparent misalignment arises because the majority of the data points are densely clustered at the center of the scatter plot, where they overlap substantially. The regression line accurately reflects this concentration of overlapping data. To improve clarity, we have updated the figure and ensured that it is now appropriately referenced in the Results section.

Reviewer #2 (Recommendations for the authors):

(1) There would be many interesting observations and links between the peripheral and cortical studies if there was a body video available during the cortical study. Is there any such data available?

We agree that a detailed analysis of behavior during the CLNF task would be necessary to explore any behavior correlates with success in the task. Unfortunately, we do not have a sufficient video of the whole body to perform such an analysis.

(2) The text (p. 24) states: [intracortical GCAMP transients measured over days became more stereotyped in kinetics and were more correlated (to each other) as the task performance increased over the sessions (Figure 7E).] But I cannot find this quantification in the figures or text?

Figure 7 in the previous version of the manuscript now appears as Figure 9. In this figure, we present cortical activity across selected regions during trials, and in Figure 9E we highlight that this activity becomes more correlated. Since we did not formally quantify variability, we have removed the previous claim that the activity became stereotyped and revised the text in the updated manuscript accordingly.

Typos:

10-serest c (page 13)

Inverted color codes in figure 4E vs F

Reviewer #3 (Recommendations for the authors):

We have mostly attempted to limit the feedback to suggestions and posed a few questions that might be interesting to explore given the dataset the authors have collected.

Comments:

In close loop systems the latency is primary concern, and authors have successfully tested the latency of the system (Delay): from detection of an event to the reaction time was less than 67ms.

We have commented on the issues and limitations caused by latency, and potential future directions to overcome these challenges in responses to some of the previous comments.

Additional major comments:

"In general, all ROIs assessed that encompassed sensory, pre-motor, and motor areas were capable of supporting increased reward rates over time (Figure 4A, Animation 1)." Fig 4A is merely showing change in task performance over time and does not have information regarding the changes observed specific to CLNF for each ROI.

We acknowledge that the sample size for individual ROI rules was not sufficient for meaningful comparisons. To address this limitation, we pooled the data across all the rules tested. The manuscript includes a detailed list of the rules along with their corresponding sample sizes for transparency.

A ΔF/F₀ threshold value was calculated from a baseline session on day 0 that would have allowed 25% performance. Starting from this basal performance of around 25% on day 1, mice (CLNF No-rule-change, n=28 and CLNF Rule-change, n=13). It is unclear what the replicates here are. Trials or mice? The corresponding Figure legend has a much smaller n value.

Thank you for pointing this out. We realized that we had not indicated the sample replicates in the figure, and the use of n instead of N for the number of animals may have been misleading. We have now corrected the notation and clarified this information in the figure to resolve the discrepancy.

What were the replicates for each ROI pairs evaluated?

Each ROI rule and number of mice and trials are listed in Table 5 and Table 6.

Our analysis revealed that certain ROI rules (see description in methods) lead to a greater increase in success rate over time than others (Supplementary Figure 3D). The Supplementary figures 3C and 3D are blurry and could use higher resolution images. 

We have increased the font size of the text that was previously difficult to read and re-exported the figure at a higher resolution (300 DPI). We believe these changes will resolve the issue.

Also, It will help the reader is a visual representation of the ROI pairs are provided, instead of the text view. One interesting question is whether there are anatomical biases to fast vs slow learning pairs (Directionality - anterior/posterior, distance between the selected ROIs etc). This could be interesting to tease apart.

We have added Supplementary Figure 7, which provides visualizations of the ROIs across all task rules used in the CLNF experiments. While a detailed investigation of the anatomical basis of fast versus slow learning cortical ROIs is beyond the scope of the present study, we agree that this represents an exciting future direction for further research.

How distant should the ROIs be to achieve increased task performance?

We appreciate this insightful question. We did not specifically test this scenario. In our study, we selected 0.3 × 0.3 mm ROIs centered on the standard AIBS mouse brain atlas (CCF). At this resolution, ROIs do not overlap, regardless of their placement in a two-ROI experiment. Furthermore, because our threshold calculations are based on baseline recordings, we expect the system would function for any combination of ROI placements. Nonetheless, exploring this systematically would be an interesting avenue for future experiments.

Figures:

I would leave out some of the methodological details such as the protocol for water restriction (Fig. 3) out of the legend. This will help with readability.

We have removed some of the methodological details, including those mentioned above, from the legend of Figure 3 in the updated manuscript.

Fig 1 and Fig 2: In my opinion, It would be easier for the reader if the current Fig. 2, which provides a high level description of CLNF and CLBF is presented as Fig. 1. The current Fig. 1, goes into a lot of methodological implementation details, and also includes a lot of programming jargon that is being introduced early in the paper that is hard to digest early on in the paper's narrative.

Thank you for the suggestion. In the new manuscript, Figure 1 and Figure 2 have been swapped.

Higher-resolution images/ plots are needed in many instances. Unsure if this is the pdf compression done by the manuscript portal that is causing this.

All figures were prepared in vector graphics format using the open-source software Inkscape. For this manuscript, we exported the images at 300 DPI, which is generally sufficient for publication-quality documents. The submission portal may apply additional processing, which could have resulted in a reduction in image quality. We will carefully review the final submission files and ensure that all figures are clear and of high quality.

The authors repeatedly show ROI specific analysis M1_L, F1_R etc. It will be helpful to provide a key, even if redundant in all figures to help the reader.

We have now included keys to all such abbreviations in all the figures.

There are also instances of editorialization and interpretation e.g., "Surprisingly, the "Rule-change" mice were able to discover the change in rule and started performing above 70% within a day of the rule change, on day 6" that would be more appropriate in the main body of the paper.

Thank you for pointing this out in the figure legend, and we have removed it now since we already discussed this in the Results.

Minor comments

(1) The description of Figure 1 is hard to follow and can be described better based on how the information is processed and executed in the system from source to processing and back. Using separated colors (instead of shaded of grey) for the neuro feedback and movement feedback would help as well. Common components could have a different color. The specification like the description of the config file should come later.

Figure 1 in the previous version is Figure 2 in the updated version. We have taken suggestions from other reviewers and made the figure easier to understand and split it into two panels with color coding Green for CLNF, Pink for CLMF specific parts while common shared parts are left without any color.

(2) Page 20 last paragraph:

Authors are neglecting that the rule change is done one day prior and the results that you see in the second half on the 6th day are not just because of the first half of the 6th day instead combined training on the 5th day (rule change) and then the first half of the 6th day. Rephrasing this observation is essential.

We have revised the text for clarity to indicate that the performance increase observed on day 6 is not necessarily attributable to training on that day. In fact, we noted and mentioned that mice began to perform the task better during the second half of the session on day 5 itself.

(3)  The method section description of the CLMF setup (Page no 39 first paragraph) is more detailed, a diagram of this setup would make it easy to follow and a better read.

We have made changes to the CLMF setup (Figure 1B) and CLMF schematic (Figure 2B) to make it easier to understand parts of the setup and flow of control.

Reviewer #1 (Public review):

Summary:

Here Bansal et al., present a study on the fundamental blood and nectar feeding behaviors of the critical disease vector, Anopheles stephensi. The study encompasses not just the fundamental changes in blood feeding behaviors of the crucially understudied vector, but then use a transcriptomic approach to identify candidate neuromodulation path ways which influence blood feeding behavior in this mosquito species. The authors then provide evidence through RNAi knockdown of candidate pathways that the neuromodulators sNPF and Rya modulate feeding either via their physiological activity in the brain alone or through joint physiological activity along the brain-gut axis (but critically not the gut alone). Overall, I found this study to be built on tractable, well-designed behavioral experiments.

Their study begins with a well-structured experiment to assess how the feeding behaviors of A. stephensi changes over the course of its life history and in response to its age, mating and oviposition status. The authors are careful and validate their experimental paradigm in the more well-studied Ae. aegypti, and are able to recapitulate the results of prior studies which show that mating is pre-requisite for blood feeding behaviors in Ae. aegypt. Here they find A. stephensi like another Anopheline mosquitoes has a more nuanced regulation of its blood and nectar feeding behaviors.

The authors then go on to show in a Y- maze olfactometer that to some degree, changes in blood feeding status depend on behavioral modulation to host-cues, and this is not likely to be a simple change to the biting behaviors alone. I was especially struck by the swap in valence of the host-cues for the blood-fed and mated individuals which had not yet oviposited. This indicates that there is a change in behavior that is not simply desensitization to host-cues while navigating in flight, but something much more exciting happening.

The authors then use a transcriptomic approach to identify candidate genes in the blood feeding stages of the mosquito's life cycle to identify a list of 9 candidates which have a role in regulating the host-seeking status of A. stephensi. Then through investigations of gene knockdown of candidates they identify the dual action of RYa and sNPF and candidate neuromodulators of host-seeking in this species. Overrall, I found the experiments to be well-designed. I found the molecular approach to be sound. While I do not think the molecular approach is necessarily an all-encompassing mechanism identification (owing mostly to the fact that genetic resources are not yet available in A. stephensi as they are in other dipteran models), I think it sets up a rich lines of research questions for the neurobiology of mosquito behavioral plasticity and comparative evolution of neuromodulator action.

Strengths:

I am especially impressed by the authors' attention to small details in the course of this article. As I read and evaluated this article I continued to think how many crucial details I may have missed if I were the scientist conducting these experiments. That attention to detail paid off in spades and allowed the authors to carefully tease apart molecular candidates of blood-seeking stages. The authors top down approach to identifying RYamide and sNPF starting from first principles behavioral experiments is especially comprehensive. The results from both the behavioral and molecular target studies will have broad implications for the vectorial capacity of this species and comparative evolution of neural circuit modulation.

I believe the authors have adequately addressed all of my concerns; however, I think an accompanying figure to match the explained methods of the tissue-specific knockdown would help readers. The methods are now explicitly written for the timing and concentrations required to achieve tissue-specific knockdown, but seeing the data as a supplement would be especially reassuring given the critical nature of tissue-specific knockdown to the final interpretations of this paper.

Reviewer #2 (Public review):

Summary:

In this manuscript, Bansal et al examine and characterize feeding behaviour in Anopheles stephensi mosquitoes. While sharing some similarities to the well-studied Aedes aegypti mosquito, the authors demonstrate that mated-females, but not unmated (virgin) females, exhibit suppression in their blood-feeding behaviour. Using brain transcriptomic analysis comparing sugar fed, blood fed and starved mosquitoes, several candidate genes potentially responsible for influencing blood-feeding behaviour were identified, including two neuropeptides (short NPF and RYamide) that are known to modulate feeding behaviour in other mosquito species. Using molecular tools including in situ hybridization, the authors map the distribution of cells producing these neuropeptides in the nervous system and in the gut. Further, by implementing systemic RNA interference (RNAi), the study suggests that both neuropeptides appear to promote blood-feeding (but do not impact sugar feeding) although the impact was observed only after both neuropeptide genes underwent knockdown.

While the authors have addressed most of the concerns of the original manuscript, a few issues remain. Particularly, the following two points:

(5) Figure 4

The authors state that there is more efficient knockdown in the head of unfed females; however, this is not accurate since they only get knockdown in unfed animals, and no evidence of any knockdown in fed animals (panel D). This point should be revised in the results test as well.

Perhaps we do not understand the reviewer's point or there has been a misunderstanding. In Figure 4D, we show that while there is more robust gene knockdown in unfed females, blood-fed females also showed modest but measurable knockdowns ranging from 5-40% for RYamide and 2-21% for sNPF.

NEW-

In both the dsRNA treatments where animals were fed, neither was significantly different from control. Therefore, there is no change, and indeed this is confirmed by the author's labelling of the figure stats in panel 4D.

In addition, do the uninjected and dsGFP-injected relative mRNA expression data reflect combined RYa and sNPF levels? Why is there no variation in these data,...

In these qPCRs, we calculated relative mRNA expression using the delta-delta Ct method (see line 975). For each neuropeptide its respective control was used. For simplicity, we combined the RYa and sNPF control data into a single representation. The value of this control is invariant because this method sets the control baseline to a value of 1.

NEW-

The authors are claiming that there is no variation between individual qPCR experiments (particularly in their controls)? Normally, one uses a known standard value (or calibrator) across multiple experiments/plates so that variation across biological replicates can be assessed. This has an impact on statistical analyses since there is no variation in the control data. Indeed, this impacts all figures/datasets in the manuscript where qPCR data is presented. All the controls have zero variation!

Reviewer #3 (Public review):

Summary:

This manuscript investigates the regulation of host-seeking behavior in Anopheles stephensi females across different life stages and mating states. Through transcriptomic profiling, the authors identify differential gene expression between "blood-hungry" and "blood-sated" states. Two neuropeptides, sNPF and RYamide, are highlighted as potential mediators of host-seeking behavior. RNAi knockdown of these peptides alters host-seeking activity, and their expression is anatomically mapped in the mosquito brain (sNPF and RYamide) and midgut (sNPF only).

Strengths:

(1) The study addresses an important question in mosquito biology, with relevance to vector control and disease transmission.

(2) Transcriptomic profiling is used to uncover gene expression changes linked to behavioral states.

(3) The identification of sNPF and RYamide as candidate regulators provides a clear focus for downstream mechanistic work.

(3) RNAi experiments demonstrate that these neuropeptides are necessary for normal host-seeking behavior.

(4) Anatomical localization of neuropeptide expression adds depth to the functional findings.

Weaknesses:

(1) The title implies that the neuropeptides promote host-seeking, but sufficiency is not demonstrated and some conclusions appear premature based on the current data. The support for this conclusion would be strengthened with functional validation using peptide injection or genetic manipulation.

(2) The identification of candidate receptors is promising, but the manuscript would be significantly strengthened by testing whether receptor knockdowns phenocopy peptide knockdowns. Without this, it is difficult to conclude that the identified receptors mediate the behavioral effects.

(3) Some important caveats, such as variation in knockdown efficiency and the possibility of off-target effects, are not adequately discussed.

Author response:

The following is the authors’ response to the original reviews.

Public Reviews:

Reviewer #1 (Public review):

Summary:

Bansal et al. present a study on the fundamental blood and nectar feeding behaviors of the critical disease vector, Anopheles stephensi. The study encompasses not just the fundamental changes in blood feeding behaviors of the crucially understudied vector, but then uses a transcriptomic approach to identify candidate neuromodulation pathways which influence blood feeding behavior in this mosquito species. The authors then provide evidence through RNAi knockdown of candidate pathways that the neuromodulators sNPF and Rya modulate feeding either via their physiological activity in the brain alone or through joint physiological activity along the brain-gut axis (but critically not the gut alone). Overall, I found this study to be built on tractable, well-designed behavioral experiments.

Their study begins with a well-structured experiment to assess how the feeding behaviors of A. stephensi change over the course of its life history and in response to its age, mating, and oviposition status. The authors are careful and validate their experimental paradigm in the more well-studied Ae. aegypti, and are able to recapitulate the results of prior studies, which show that mating is a prerequisite for blood feeding behaviors in Ae. aegypt. Here they find A. Stephensi, like other Anopheline mosquitoes, has a more nuanced regulation of its blood and nectar feeding behaviors.

The authors then go on to show in a Y-maze olfactometer that ,to some degree, changes in blood feeding status depend on behavioral modulation to host cues, and this is not likely to be a simple change to the biting behaviors alone. I was especially struck by the swap in valence of the host cues for the blood-fed and mated individuals, which had not yet oviposited. This indicates that there is a change in behavior that is not simply desensitization to host cues while navigating in flight, but something much more exciting is happening.

The authors then use a transcriptomic approach to identify candidate genes in the blood-feeding stages of the mosquito's life cycle to identify a list of 9 candidates that have a role in regulating the host-seeking status of A. stephensi. Then, through investigations of gene knockdown of candidates, they identify the dual action of RYa and sNPF and candidate neuromodulators of host-seeking in this species. Overall, I found the experiments to be well-designed. I found the molecular approach to be sound. While I do not think the molecular approach is necessarily an all-encompassing mechanism identification (owing mostly to the fact that genetic resources are not yet available in A. stephensi as they are in other dipteran models), I think it sets up a rich line of research questions for the neurobiology of mosquito behavioral plasticity and comparative evolution of neuromodulator action.

We appreciate the reviewer’s detailed summary of our work. We thank them for their positive comments and agree with them on the shortcomings of our approach.

Strengths:

I am especially impressed by the authors' attention to small details in the course of this article. As I read and evaluated this article, I continued to think about how many crucial details could potentially have been missed if this had not been the approach. The attention to detail paid off in spades and allowed the authors to carefully tease apart molecular candidates of blood-seeking stages. The authors' top-down approach to identifying RYamide and sNPF starting from first principles behavioral experiments is especially comprehensive. The results from both the behavioral and molecular target studies will have broad implications for the vectorial capacity of this species and comparative evolution of neural circuit modulation.

We really appreciate that the reviewer has recognised the attention to detail we have tried to put, thank you!

Weaknesses:

There are a few elements of data visualizations and methodological reporting that I found confusing on a first few read-throughs. Figure 1F, for example, was initially confusing as it made it seem as though there were multiple 2-choice assays for each of the conditions. I would recommend removing the "X" marker from the x-axis to indicate the mosquitoes did not feed from either nectar, blood, or neither in order to make it clear that there was one assay in which mosquitoes had access to both food sources, and the data quantify if they took both meals, one meal, or no meals.

We thank the reviewer for flagging the schematic in figure 1F. As suggested, we have removed the “X” markers from the x-axis and revised the axis label from “choice of food” to “choice made” to better reflect what food the mosquitoes chose in the assay. For clarity, we have now also plotted the same data as stacked graphs at the bottom of Fig. 1F, which clearly shows the proportion of mosquitoes fed on each particular choice. We avoid the stacked graph as the sole representation of this data, as it does not capture the variability in the data.

I would also like to know more about how the authors achieved tissue-specific knockdown for RNAi experiments. I think this is an intriguing methodology, but I could not figure out from the methods why injections either had whole-body or abdomen-specific knockdown.

The tissue-specific knockdown (abdomen only or abdomen+head) emerged from initial standardisations where we were unable to achieve knockdown in the head unless we used higher concentrations of dsRNA and did the injections in older females. We realised that this gave us the opportunity to isolate the neuronal contribution of these neuropeptides in the phenotype produced. Further optimisations revealed that injecting dsRNA into 0-10h old females produced abdomen-specific knockdowns without affecting head expression, whereas injections into 4 days old females resulted in knockdowns in both tissues. Moreover, head knockdowns in older females required higher dsRNA concentrations, with knockdown efficiency correlating with the amount injected. In contrast, abdominal knockdowns in younger females could be achieved even with lower dsRNA amounts.

We have mentioned the knockdown conditions- time of injection and the amount dsRNA injected- for tissue-specific knockdowns in methods but realise now that it does not explain this well enough. We have now edited it to state our methodology more clearly (see lines 932-948).

I also found some interpretations of the transcriptomic to be overly broad for what transcriptomes can actually tell us about the organism's state. For example, the authors mention, "Interestingly, we found that after a blood meal, glucose is neither spent nor stored, and that the female brain goes into a state of metabolic 'sugar rest', while actively processing proteins (Figure S2B, S3)".

This would require a physiological measurement to actually know. It certainly suggests that there are changes in carbohydrate metabolism, but there are too many alternative interpretations to make this broad claim from transcriptomic data alone.

We thank the reviewer for pointing this out and agree with them. We have now edited our statement to read:

“Instead, our data suggests altered carbohydrate metabolism after a blood meal, with the female brain potentially entering a state of metabolic 'sugar rest' while actively processing proteins (Figure S2B, S3). However, physiological measurements of carbohydrate and protein metabolism will be required to confirm whether glucose is indeed neither spent nor stored during this period.” See lines 271-277.

Reviewer #2 (Public review):

Summary:

In this manuscript, Bansal et al examine and characterize feeding behaviour in Anopheles stephensi mosquitoes. While sharing some similarities to the well-studied Aedes aegypti mosquito, the authors demonstrate that mated females, but not unmated (virgin) females, exhibit suppression in their bloodfeeding behaviour. Using brain transcriptomic analysis comparing sugar-fed, blood-fed, and starved mosquitoes, several candidate genes potentially responsible for influencing blood-feeding behaviour were identified, including two neuropeptides (short NPF and RYamide) that are known to modulate feeding behaviour in other mosquito species. Using molecular tools, including in situ hybridization, the authors map the distribution of cells producing these neuropeptides in the nervous system and in the gut. Further, by implementing systemic RNA interference (RNAi), the study suggests that both neuropeptides appear to promote blood-feeding (but do not impact sugar feeding), although the impact was observed only after both neuropeptide genes underwent knockdown.

Strengths and/or weaknesses:

Overall, the manuscript was well-written; however, the authors should review carefully, as some sections would benefit from restructuring to improve clarity. Some statements need to be rectified as they are factually inaccurate.

Below are specific concerns and clarifications needed in the opinion of this reviewer:

(1) What does "central brains" refer to in abstract and in other sections of the manuscript (including methods and results)? This term is ambiguous, and the authors should more clearly define what specific components of the central nervous system was/were used in their study.

Central brain, or mid brain, is a commonly used term to refer to brain structures/neuropils without the optic lobes (For example: https://www.nature.com/articles/s41586-024-07686-5). In this study we have focused our analysis on the central brain circuits involved in modulating blood-feeding behaviour and have therefore excluded the optic lobes. As optic lobes account for nearly half of all the neurons in the mosquito brain (https://pmc.ncbi.nlm.nih.gov/articles/PMC8121336/), including them would have disproportionately skewed our transcriptomic data toward visual processing pathways. 

We have indicated this in figure 3A and in the methods (see lines 800-801, 812). We have now also clarified it in the results section for neurotranscriptomics to avoid confusion (see lines 236-237).

(2) The abstract states that two neuropeptides, sNPF and RYamide are working together, but no evidence is summarized for the latter in this section.

We thank the reviewer for pointing this out. We have now added a statement “This occurs in the context of the action of RYa in the brain” to end of the abstract, for a complete summary of our proposed model. 

(3) Figure 1

Panel A: This should include mating events in the reproductive cycle to demonstrate differences in the feeding behavior of Ae. aegypti.

Our data suggest that mating can occur at any time between eclosion and oviposition in An. stephensi and between eclosion and blood feeding in Ae. aegypti. Adding these into (already busy) 1A, would cloud the purpose of the schematic, which is to indicate the time points used in the behavioural assays and transcriptomics.

Panel F: In treatments where insects were not provided either blood or sugar, how is it that some females and males had fed? Also, it is unclear why the y-axis label is % fed when the caption indicates this is a choice assay. Also, it is interesting that sugar-starved females did not increase sugar intake. Is there any explanation for this (was it expected)?

We apologise for the confusion. The experiment is indeed a choice assay in which sugar-starved or sugar-sated females, co-housed with males, were provided simultaneous access to both blood and sugar, and were assessed for the choice made (indicated on the x-axis): both blood and sugar, blood only, sugar only, or neither. The x-axis indicates the choice made by the mosquitoes, not the choice provided in the assay, and the y-axis indicates the percentage of males or females that made each particular choice. We have now removed the “X” markers from the x-axis and revised the axis label from “choice of food” to “choice made” to better reflect what food the mosquitoes chose to take.

In this assay, we scored females only for the presence or absence of each meal type (blood or sugar) and are therefore unable to comment on whether sugar-starved females consumed more sugar than sugarsated females. However, when sugar-starved, a higher proportion of females consumed both blood and sugar, while fewer fed on blood alone.

For clarity, we have now also plotted the same data as stacked graphs at the bottom of Fig. 1F, which clearly shows the proportion of mosquitoes fed on each particular choice. We avoid the stacked graph as the sole representation of this data as it does not capture the variability in the data.

(4) Figure 3

In the neurotranscriptome analysis of the (central) brain involving the two types of comparisons, can the authors clarify what "excluded in males" refers to? Does this imply that only genes not expressed in males were considered in the analysis? If so, what about co-expressed genes that have a specific function in female feeding behaviour?

This is indeed correct. We reasoned that since blood feeding is exclusive to females, we should focus our analysis on genes that were specifically upregulated in them. As the reviewer points out, it is very likely that genes commonly upregulated in males and females may also promote blood feeding and we will miss out on any such candidates based on our selection criteria. 

(5) Figure 4

The authors state that there is more efficient knockdown in the head of unfed females; however, this is not accurate since they only get knockdown in unfed animals, and no evidence of any knockdown in fed animals (panel D). This point should be revised in the results test as well.

Perhaps we do not understand the reviewer’s point or there has been a misunderstanding. In figure 4D, we show that while there is more robust gene knockdown in unfed females, blood-fed females also showed modest but measurable knockdowns ranging from 5-40% for RYamide and 2-21% for sNPF. 

Relatedly, blood-feeding is decreased when both neuropeptide transcripts are targeted compared to uninjected (panel C) but not compared to dsGFP injected (panel E). Why is this the case if authors showed earlier in this figure (panel B) that dsGFP does not impact blood feeding?

We realise this concern stems from our representation of the data. Since we had earlier determined that dsGFP-injected females fed similarly to uninjected females (fig 4B), we used these controls interchangeably in subsequent experiments. To avoid confusion, we have now only used the label ‘control’ in figure 4 (and supplementary figure S9) and specified which control was used for each experiment in the legend.

In addition to this, we wanted to clarify that fig 4C and 4E are independent experiments. 4C is the behaviour corresponding to when the neuropeptides were knocked down in both heads and abdomens. 4E is the behaviour corresponding to when the neuropeptides were knocked down in only the abdomens. We have now added a schematic in the plots to make this clearer.

In addition, do the uninjected and dsGFP-injected relative mRNA expression data reflect combined RYa and sNPF levels? Why is there no variation in these data,…

In these qPCRs, we calculated relative mRNA expression using the delta-delta Ct method (see line 975). For each neuropeptide its respective control was used. For simplicity, we combined the RYa and sNPF control data into a single representation. The value of this control is invariant because this method sets the control baseline to a value of 1.

…and how do transcript levels of RYa and sNPF compare in the brain versus the abdomen (the presentation of data doesn't make this relationship clear).

The reviewer is correct in pointing out that we have not clarified this relationship in our current presentation. While we have not performed absolute mRNA quantifications, we extracted relative mRNA levels from qPCR data of 96h old unmanipulated control females. We observed that both sNPF and RYa transcripts are expressed at much lower levels in the abdomens, as compared to those in the heads, as shown in Author response Image 1 below. 

Author response image 1.

(6) As an overall comment, the figure captions are far too long and include redundant text presented in the methods and results sections.

We thank the reviewer for flagging this and have now edited the legends to remove redundancy.  

(7) Criteria used for identifying neuropeptides promoting blood-feeding: statement that reads "all neuropeptides, since these are known to regulate feeding behaviours". This is not accurate since not all neuropeptides govern feeding behaviors, while certainly a subset do play a role.

We agree with the reviewer that not all neuropeptides regulate feeding behaviours. Our statement refers to the screening approach we used: in our shortlist of candidates, we chose to validate all neuropeptides.

(8) In the section beginning with "Two neuropeptides - sNPF and RYa - showed about 25% and 40% reduced mRNA levels...", the authors state that there was no change in blood-feeding and later state the opposite. The wording should be clarified as it is unclear.

Thank you for pointing this out. We were referring to an unchanged proportion of the blood fed females. We have now edited the text to the following: 

“Two neuropeptides - sNPF and RYa - showed about 25% and 40% reduced mRNA levels in the heads but the proportion of females that took blood meals remained unchanged”. See lines 338-340.

(9) Just before the conclusions section, the statement that "neuropeptide receptors are often ligandpromiscuous" is unjustified. Indeed, many studies have shown in heterologous systems that high concentrations of structurally related peptides, which are not physiologically relevant, might cross-react and activate a receptor belonging to a different peptide family; however, the natural ligand is often many times more potent (in most cases, orders of magnitude) than structurally related peptides. This is certainly the case for various RYamide and sNPF receptors characterized in various insect species.

We agree with the reviewer and apologise for the mistake. We have now removed the statement.

(10) Methods

In the dsRNA-mediated gene knockdown section, the authors could more clearly describe how much dsRNA was injected per target. At the moment, the reader must carry out calculations based on the concentrations provided and the injected volume range provided later in this section.

We have now edited the section to reflect the amount of dsRNA injected per target. Please see lines 921-931.

It is also unclear how tissue-specific knockdown was achieved by performing injection on different days/times. The authors need to explain/support, and justify how temporal differences in injection lead to changes in tissue-specific expression. Does the blood-brain barrier limit knockdown in the brain instead, while leaving expression in the peripheral organs susceptible?

To achieve tissue-specific knockdowns of sNPF and RYa, we optimised both the time of injection as well as the dsRNA concentration to be injected. Injecting dsRNA into 0-10h females produced abdomen-specific knockdowns without affecting head expression, whereas injections into 96h old females resulted in knockdowns in both tissues. Head knockdowns in older females required higher dsRNA concentrations, with knockdown efficiency correlating with the amount injected. In contrast, abdominal knockdowns in younger females could be achieved even with lower dsRNA amounts, reflecting the lower baseline expression of sNPF in abdomens compared to heads and the age-dependent increase in head expression (as confirmed by qPCR). It is possible that the blood-brain barrier also limits the dsRNA entering the brain, thereby requiring higher amounts to be injected for head knockdowns. 

We have now edited this section to state our methodology more clearly (see lines 932-948).

For example, in Figure 4, the data support that knockdown in the head/brain is only effective in unfed animals compared to uninjected animals, while there is no evidence of knockdown in the brain relative to dsGFP-injected animals. Comparatively, evidence appears to show stronger evidence of abdominal knockdown mostly for the RYa transcript (>90%) while still significantly for the sNPF transcript (>60%).

As we explained earlier, this concern likely stems from our representation of the data. Since we had earlier determined that dsGFP-injected females fed similarly to uninjected females (fig 4B), we used these controls interchangeably in subsequent experiments. To avoid confusion, we have now only used the label ‘control’ in figure 4 (and supplementary figure S9) and specified which control was used for each experiment in the legend.

In addition to this, we wanted to clarify that fig 4C and 4E are independent experiments. 4C is the behaviour corresponding to when the neuropeptides were knocked down in both heads and abdomens.  4E is the behaviour corresponding to when the neuropeptides were knocked down in only the abdomen. We have now added a schematic in the plots to make this clearer.

Reviewer #3 (Public review):

Summary:

This manuscript investigates the regulation of host-seeking behavior in Anopheles stephensi females across different life stages and mating states. Through transcriptomic profiling, the authors identify differential gene expression between "blood-hungry" and "blood-sated" states. Two neuropeptides, sNPF and RYamide, are highlighted as potential mediators of host-seeking behavior. RNAi knockdown of these peptides alters host-seeking activity, and their expression is anatomically mapped in the mosquito brain (sNPF and RYamide) and midgut (sNPF only).

Strengths:

(1) The study addresses an important question in mosquito biology, with relevance to vector control and disease transmission.

(2) Transcriptomic profiling is used to uncover gene expression changes linked to behavioral states.

(3) The identification of sNPF and RYamide as candidate regulators provides a clear focus for downstream mechanistic work.

(4) RNAi experiments demonstrate that these neuropeptides are necessary for normal host-seeking behavior.

(5) Anatomical localization of neuropeptide expression adds depth to the functional findings.

Weaknesses:

(1) The title implies that the neuropeptides promote host-seeking, but sufficiency is not demonstrated (for example, with peptide injection or overexpression experiments).

Demonstrating sufficiency would require injecting sNPF peptide or its agonist. To date, no small-molecule agonists (or antagonists) that selectively mimic sNPF or RYa neuropeptides have been identified in insects. An NPY analogue, TM30335, has been reported to activate the Aedes aegypti NPY-like receptor 7 (NPYLR7; Duvall et al., 2019), which is also activated by sNPF peptides at higher doses (Liesch et al., 2013). Unfortunately, the compound is no longer available because its manufacturer, 7TM Pharma, has ceased operations. Synthesising the peptides is a possibility that we will explore in the future.

(2) The proposed model regarding central versus peripheral (gut) peptide action is inconsistently presented and lacks strong experimental support.

The best way to address this would be to conduct tissue-specific manipulations, the tools for which are not available in this species. Our approach to achieve head+abdomen and abdomen only knockdown was the closest we could get to achieving tissue specificity and allowed us to confirm that knockdown in the head was necessary for the phenotype. However, as the reviewer points out, this did not allow us to rule out any involvement of the abdomen. This point has been addressed in lines 364-371.

(3) Some conclusions appear premature based on the current data and would benefit from additional functional validation.

The most definitive way of demonstrating necessity of sNPF and RYa in blood feeding would be to generate mutant lines. While we are pursuing this line of experiments, they lie beyond the scope of a revision. In its absence, we relied on the knockdown of the genes using dsRNA. We would like to posit that despite only partial knockdown, mosquitoes do display defects in blood-feeding behaviour, without affecting sugar-feeding. We think this reflects the importance of sNPF in promoting blood feeding.

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

Overall, I found this manuscript to be well-prepared, visually the figures are great and clearly were carefully thought out and curated, and the research is impactful. It was a wonderful read from start to finish. I have the following recommendations:

Thank you very much, we are very pleased to hear that you enjoyed reading our manuscript!

(1) For future manuscripts, it would make things significantly easier on the reviewer side to submit a format that uses line numbers.

We sincerely apologise for the oversight. We have now incorporated line numbers in the revised manuscript.

(2) There are a few statements in the text that I think may need clarification or might be outside the bounds of what was actually studied here. For example, in the introduction "However, mating is dispensable in Anophelines even under conditions of nutritional satiety". I am uncertain what is meant by this statement - please clarify.

We apologise for the lack of clarity in the statement and have now deleted it since we felt it was not necessary.

(3) Typo/Grammatical minutiae:

(a) A small idiosyncrasy of using hyphens in compound words should also be fixed throughout. Typically, you don't hyphenate if the words are being used as a noun, as in the case: e.g. "Age affects blood feeding.". However, you would hyphenate if the two words are used as a compound adjective "Age affects blood-feeding behavior". This may not be an all-inclusive list, but here are some examples where hyphens need to either be removed or added. Some examples:

"Nutritional state also influences other internal state outputs on blood-feeding": blood-feeding -> blood feeding

"... the modulation of blood-feeding": blood-feeding -> blood feeding

"For example, whether virgin females take blood-meals...": blood-meals -> blood meals

".... how internal and external cues shape meal-choice"-> meal choice

"blood-meal" is often used throughout the text, but is correctly "blood meal" in the figures.

There are many more examples throughout.

We apologise for these errors and appreciate the reviewer’s keen eye. We have now fixed them throughout the manuscript.  

(b) Figure 1 Caption has a typo: "co-housed males were accessed for sugar-feeding" should be "co-housed males were assessed for sugar feeding"

We apologise for the typo and thank the reviewer for spotting it. We have now corrected this.  

(c) It would be helpful in some other figure captions to more clearly label which statement is relevant to which part of the text. For example, in Figure 4's caption.

"C,D. Blood-feeding and sugar-feeding behaviour of females when both RYa and sNPF are knocked down in the head (C). Relative mRNA expressions of RYa and sNPF in the heads of dsRYa+dssNPF - injected blood-fed and unfed females, as compared to that in uninjected females, analysed via qPCR (D)."

I found re-referencing C and D at the end of their statements makes it look as thought C precedes the "Relative mRNA expression" and on a first read through, I thought the figure captions were backwards. I'd recommend reformatting here and throughout consistently to only have the figure letter precede its relevant caption information, e.g.:

"C. Blood-feeding and sugar-feeding behaviour of females when both RYa and sNPF are knocked down in the head. D. Relative mRNA expressions of RYa and sNPF in the heads of dsRYa+dssNPF - injected bloodfed and unfed females, as compared to that in uninjected females, analysed via qPCR."

We have now edited the legends as suggested.

Reviewer #2 (Recommendations for the authors):

Separately from the clarifications and limitations listed above, the authors could strengthen their study and the conclusions drawn if they could rescue the behavioural phenotype observed following knockdown of sNPF and RYamide. This could be achieved by injection of either sNPF or RYa peptide independently or combined following knockdown to validate the role of these peptides in promoting blood-feeding in An. stephensi. Additionally, the apparent (but unclear) regionalized (or tissue-specific) knockdown of sNPF and RYamide transcripts could be visualized and verified by implementing HCR in situ hyb in knockdown animals (or immunohistochemistry using antibodies specific for these two neuropeptides). 

In a follow up of this work, we are generating mutants and peptides for these candidates and are planning to conduct exactly the experiments the reviewer suggests.

Reviewer #3 (Recommendations for the authors):

The loss-of-function data suggest necessity but not sufficiency. Synthetic peptide injection in non-hostseeking (blood-fed mated or juvenile) mosquitoes would provide direct evidence for peptide-induced behavioral activation. The lack of these experiments weakens the central claim of the paper that these neuropeptides directly promote blood feeding.

As noted above, we plan to synthesise the peptide to test rescue in a mutant background and sufficiency.  

Some of the claims about knockdown efficiency and interpretation are conflicting; the authors dismiss Hairy and Prp as candidates due to 30-35% knockdown, yet base major conclusions on sNPF and RYamide knockdowns with comparable efficiencies (25-40%). This inconsistency should be addressed, or the justification for different thresholds should be clearly stated.

We have not defined any specific knockdown efficacy thresholds in the manuscript, as these can vary considerably between genes, and in some cases, even modest reductions can be sufficient to produce detectable phenotypes. For example, knockdown efficiencies of even as low as about 25% - 40% gave us observable phenotypes for sNPF and RYa RNAi (Figure S9B-G).

No such phenotypes were observed for Hairy (30%) or Prp (35%) knockdowns. Either these genes are not involved in blood feeding, or the knockdown was not sufficient for these specific genes to induce phenotypes. We cannot distinguish between these scenarios. 

The observation that knockdown animals take smaller blood meals is interesting and could reflect a downstream effect of altered host-seeking or an independent physiological change. The relationship between meal size and host-seeking behavior should be clarified.

We agree with the reviewer that the reduced meal size observed in sNPF and RYa knockdown animals could result from their inability to seek a host or due to an independent effect on blood meal intake. Unfortunately, we did not measure host-seeking in these animals. We plan to distinguish between these possibilities using mutants in future work.

Several figures are difficult to interpret due to cluttered labeling and poorly distinguishable color schemes. Simplifying these and improving contrast (especially for co-housed vs. virgin conditions) would enhance readability. 

We regret that the reviewer found the figures difficult to follow. We have now revised our annotations throughout the manuscript for enhanced readability. For example, “D1^B” is now “D1^PBM” (post-bloodmeal) and “D1^O” is now “D1^PO” (post-oviposition). Wherever mated females were used, we have now appended “(m)” to the annotations and consistently depicted these females with striped abdomens in all the schematics. We believe these changes will improve clarity and readability.

The manuscript does not clearly justify the use of whole-brain RNA sequencing to identify peptides involved in metabolic or peripheral processes. Given that anticipatory feeding signals are often peripheral, the logic for brain transcriptomics should be explained.

The reviewer is correct in pointing out that feeding signals could also emerge from peripheral tissues. Signals from these tissues – in response to both changing nutritional and reproductive states – are then integrated by the central brain to modulate feeding choices. For example, in Drosophila, increased protein intake is mediated by central brain circuitry including those in the SEZ and central complex (Munch et al., 2022; Liu et al., 2017; Goldschmidt et al., 202ti). In the context of mating, male-derived sex peptide further increases protein feeding by acting on a dedicated central brain circuitry (Walker et al., 2015). We, therefore focused on the central brain for our studies.

The proposed model suggests brain-derived peptides initiate feeding, while gut peptides provide feedback. However, gut-specific knockdowns had no effect, undermining this hypothesis. Conversely, the authors also suggest abdominal involvement based on RNAi results. These contradictions need to be resolved into a consistent model.

We thank the reviewer for raising this point and recognise their concern. Our reasons for invoking an involvement of the gut were two-fold:

(1) We find increased sNPF transcript expression in the entero-endocrine cells of the midgut in blood-hungry females, which returns to baseline after a blood-meal (Fig. 4L, M).

(2) While the abdomen-only knockdowns did not affect blood feeding, every effective head knockdown that affected blood feeding also abolished abdominal transcript levels (Fig. S9C, F). (Achieving a head-only reduction proved impossible because (i) systemic dsRNA delivery inevitably reaches the abdomen and (ii) abdominal expression of both peptides is low, leaving little dynamic range for selective manipulation.) Consequently, we can only conclude the following: 1) that brain expression is required for the behaviour, 2) that we cannot exclude a contributory role for gut-derived sNPF. We have discussed this in lines 364-371.

The identification of candidate receptors is promising, but the manuscript would be significantly strengthened by testing whether receptor knockdowns phenocopy peptide knockdowns. Without this, it is difficult to conclude that the identified receptors mediate the behavioral effects.

We agree that functional validation of the receptors would strengthen the evidence for sNPF and RYa-mediated control of blood feeding in An. stephensi. We selected these receptors based on sequence homology. A possibility remains that sNPF neuropeptides activate more than one receptor, each modulating a distinct circuit, as shown in the case of Drosophila Tachykinin (https://pmc.ncbi.nlm.nih.gov/articles/PMC10184743/). This will mean a systematic characterisation and knockdown of each of them to confirm their role. We are planning these experiments in the future.  

The authors compared the percentage changes in sugar-fed and blood-fed animals under sugar-sated or sugar-starved conditions. Figure 1F should reflect what was discussed in the results.

Perhaps this concern stems from our representation of the data in figure 1F? We have now edited the xaxis and revised its label from “choice of food” to “choice made” to better reflect what food the mosquitoes chose to take.

For clarity, we have now also plotted the same data as stacked graphs at the bottom of Fig. 1F, which clearly shows the proportion of mosquitoes fed on each particular choice. We avoid the stacked graph as the sole representation of this data because it does not capture the variability in the data.

Minor issues:

(1) The authors used mosquitoes with belly stripes to indicate mated females. To be consistent, the post-oviposition females should also have belly stripes.

We thank the reviewer for pointing this out. We have now edited all the figures as suggested.

(2) In the first paragraph on the right column of the second page, the authors state, "Since females took blood-meals regardless of their prior sugar-feeding status and only sugar-feeding was selectively suppressed by prior sugar access." Just because the well-fed animals ate less than the starved animals does not mean their feeding behavior was suppressed.

Perhaps there has been a misunderstanding in the experimental setup of figure 1F, probably stemming from our data representation. The experiment is a choice assay in which sugar-starved or sugar-sated females, co-housed with males, were provided simultaneous access to both blood and sugar, and were assessed for the choice made (indicated on the x-axis): both blood and sugar, blood only, sugar only, or neither. We scored females only for the presence or absence of each meal type (blood or sugar) and did not quantify the amount consumed.

(3) The figure legend for Figure 1A and the naming convention for different experimental groups are difficult to follow. A simplified or consistently abbreviated scheme would help readers navigate the figures and text.

We regret that the reviewer found the figure difficult to follow. We have now revised our annotations throughout the manuscript for enhanced readability. For example, “D1^B” is now “D1^PBM” (post-bloodmeal) and “D1^O” is now “D1^PO” (post-oviposition).

(4) In the last paragraph of the Y-maze olfactory assay for host-seeking behaviour in An. stephensi in Methods, the authors state, "When testing blood-fed females, aged-matched sugar-fed females (bloodhungry) were included as positive controls where ever possible, with satisfactory results." The authors should explicitly describe what the criteria are for "satisfactory results".

We apologise for the lack of clarity. We have now edited the statement to read:

“When testing blood-fed females, age-matched sugar-fed females (blood-hungry) were included wherever possible as positive controls. These females consistently showed attraction to host cues, as expected.” See lines 786-790.

(5) In the first paragraph of the dsRNA-mediated gene knockdown section in Methods, dsRNA against GFP is used as a negative control for the injection itself, but not for the potential off-target effect.

We agree with the reviewer that dsGFP injections act as controls only for injection-related behavioural changes, and not for off-target effects of RNAi. We have now corrected the statement. See lines 919-920.

To control for off-target effects, we could have designed multiple dsRNAs targeting different parts of a given gene. We regret not including these controls for potential off-target effects of dsRNAs injected. 

(6) References numbers 48, 89, and 90 are not complete citations.

We thank the reviewer for spotting these. We have now corrected these citations.

Author response:

The following is the authors’ response to the original reviews.

First, we thank the reviewers for the valuable and constructive reviews. Thanks to these, we believe the article has been considerably improved. We have organized our response to address points that are relevant to both reviewers first, after which we address the unique concerns of each individual reviewer separately. We briefly paraphrase each concern and provide comments for clarification, outlining the precise changes that we have made to the text.

Common Concerns (R1 & R2):

Can you clarify how NREM and REM sleep relate to the oneirogen hypothesis?

Within the submission draft we tried to stay agnostic as to whether mechanistically similar replay events occur during NREM or REM sleep; however, upon a more thorough literature review, we think that there is moderately greater evidence in favor of Wake-Sleep-type replay occurring during REM sleep which is related to classical psychedelic drug mechanisms of action.

First, we should clarify that replay has been observed during both REM and NREM sleep, and dreams have been documented during both sleep stages, though the characteristics of dreams differ across stages, with NREM dreams being more closely tied to recent episodic experience and REM dreams being more bizarre/hallucinatory (see Stickgold et al., 2001 for a review). Replay during sleep has been studied most thoroughly during NREM sharp-wave ripple events, in which significant cortical-hippocampal coupling has been observed (Ji & Wilson, 2007). However, it is critical to note that the quantification methods used to identify replay events in the hippocampal literature usually focus on identifying what we term ‘episodic replay,’ which involves a near-identical recapitulation of neural trajectories that were recently experienced during waking experimental recordings (Tingley & Peyrach, 2020). In contrast, our model focuses on ‘generative replay,’ where one expects only a statistically similar reproduction of neural activity, without any particular bias towards recent or experimentally controlled experience. This latter form of replay may look closer to the ‘reactivation’ observed in cortex by many studies (e.g. Nguyen et al., 2024), where correlation structures of neural activity similar to those observed during stimulus-driven experience are recapitulated. Under experimental conditions in which an animal is experiencing highly stereotyped activity repeatedly, over extended periods of time, these two forms of replay may be difficult to dissociate.

Interestingly, though NREM replay has been shown to couple hippocampal and cortical activity, a similar study in waking animals administered psychedelics found hippocampal replay without any obvious coupling to cortical activity (Domenico et al., 2021). This could be because the coupling was not strong enough to produce full trajectories in the cortex (psychedelic administration did not increase ‘alpha’ enough), and that a causal manipulation of apical/basal influence in the cortex may be necessary to observe the increased coupling. Alternatively, as Reviewer 1 noted, it may be that psychedelics induce a form of hippocampus-decoupled replay, as one would expect from the REM stage of a recently proposed complementary learning systems model (Singh et al., 2022). 

Evidence in favor of a similarity between the mechanism of action of classical psychedelics and the mechanism of action of memory consolidation/learning during REM sleep is actually quite strong. In particular, studies have shown that REM sleep increases the activity of soma-targeting parvalbumin (PV) interneurons and decreases the activity of apical dendrite-targeting somatostatin (SOM) interneurons (Niethard et al., 2021), that this shift in balance is controlled by higher-order thalamic nuclei, and that this shift in balance is critical for synaptic consolidation of both monocular deprivation effects in early visual cortex (Zhou et al., 2020) and for the consolidation of auditory fear conditioning in the dorsal prefrontal cortex (Aime et al., 2022). These last studies were not discussed in our previous text–we have added them, in addition to a more nuanced description of the evidence connecting our model to NREM and REM replay. 

Relevant modifications: Page 4, 1st paragraph; Page 11, 1st paragraph.

Can you explain how synaptic plasticity induced by psychedelics within your model relates to learning at a behavioral level?

While the Wake-Sleep algorithm is a useful model for unsupervised statistical learning, it is not a model of reward or fear-based conditioning, which likely occur via different mechanisms in the brain (e.g. dopamine-dependent reinforcement learning or serotonin-dependent emotional learning). The Wake-Sleep algorithm is a ‘normative plasticity algorithm,’ that connects synaptic plasticity to the formation of structured neural representations, but it is not the case that all synaptic plasticity induced by psychedelic administration within our model should induce beneficial learning effects. According to the Wake-Sleep algorithm, plasticity at apical synapses is enhanced during the Wake phase, and plasticity at basal synapses is enhanced during the Sleep phase; under the oneirogen hypothesis, hallucinatory conditions (increased ‘alpha’) cause an increase in plasticity at both apical and basal sites. Because neural activity is in a fundamentally aberrant state when ‘alpha’ is increased, there are no theoretical guarantees that plasticity will improve performance on any objective: psychedelic-induced plasticity within our model could perhaps better be thought of as ‘noise’ that may have a positive or negative effect depending on the context.

In particular, such ‘noise’ may be beneficial for individuals or networks whose synapses have become locked in a suboptimal local minimum. The addition of large amounts of random plasticity could allow a system to extricate itself from such local minima over subsequent learning (or with careful selection of stimuli during psychedelic experience), similar to simulated annealing optimization approaches. If our model were fully validated, this view of psychedelic-induced plasticity as ‘noise’ could have relevance for efforts to alleviate the adverse effects of PTSD, early life trauma, or sensory deprivation; it may also provide a cautionary note against repeated use of psychedelic drugs within a short time frame, as the plasticity changes induced by psychedelic administration under our model are not guaranteed to be good or useful in-and-of themselves without subsequent re-learning and compensation.

We should also note that we have deliberately avoided connecting the oneirogen hypothesis model to fear extinction experimental results that have been observed through recordings of the hippocampus or the amygdala (Bombardi & Giovanni, 2013; Jiang et al., 2009; Kelly et al., 2024; Tiwari et al., 2024). Both regions receive extensive innervation directly from serotonergic synapses originating in the dorsal raphe nucleus, which have been shown to play an important role in emotional learning (Lesch & Waider, 2012); because classical psychedelics may play a more direct role in modulating this serotonergic innervation, it is possible that fear conditioning results (in addition to the anxiolytic effects of psychedelics) cannot be attributed to a shift in balance between apical and basal synapses induced by psychedelic administration. We have provided a more detailed review of these results in the text, as well as more clarity regarding their relation to our model.

Relevant modifications: Page 9, final paragraph; Page 12, final paragraph.

Reviewer 1 Concerns:

Is it reasonable to assign a scalar parameter ‘alpha’ to the effects of classical psychedelics? And is your proposed mechanism of action unique to classical psychedelics? E.g. Could this idea also apply to kappa opioid agonists, ketamine, or the neural mechanisms of hallucination disorders?

We have clarified that within our model ‘alpha’ is a parameter that reflects the balance between apical and basal synapses in determining the activity of neurons in the network. For the sake of simplicity we used a single ‘alpha’ parameter, but realistically, each neuron would have its own ‘alpha’ parameter, and different layers or individual neurons could be affected differentially by the administration of any particular drug; therefore, our scalar ‘alpha’ value can be thought of as a mean parameter for all neurons, disregarding heterogeneity across individual neurons.

There are many different mechanisms that could theoretically affect this ‘alpha’ parameter, including: 5-HT2a receptor agonism, kappa opioid receptor binding, ketamine administration, or possibly the effects of genetic mutations underlying the pathophysiology of complex developmental hallucination disorders. We focused exclusively on 5-HT2a receptor agonism for this study because the mechanism is comparatively simple and extensively characterized, but similar mechanisms may well be responsible for the hallucinatory symptoms of a variety of drugs and disorders.

Relevant modifications: Page 4, first paragraph; Page 13, first paragraph.

Can you clarify the role of 5-HT2a receptor expression on interneurons within your model?