负相关？

why?

In this case, the death could be the death of the autonomy of people and thinking for themselves.

The classic line I give my third graders is "I am your teacher, not your teller." I can't just tell you information and expect you to learn, you have to work to understand and make meaning on your own.

Moving away from banking concept can allow for learners to develop their own purposes through exploration and creativity. They can discover elements of the ARCS model for themselves, with the teacher as support (as opposed to demander).

Typically, teachers "prefer" the simpler lessons because it's less work on them, but we also have to ask ourselves, is it better for the students? Are we working in the best interest of the students and their futures?

Developing students ability to question what they are learning and the world around them can help them transform from passive to active learners. They begin taking more ownership of what is being learned as opposed to just mindlessly consuming and accepting.

If you want to break free from the passive cycle of the banking concept, continuing to be passive yourself and not seeking opportunities to change won't make it any better! You have to make the opportunity if there is not one and work to better yourself.

The "unknowingly" piece highlights why it is so important to consistently be checking your own practice as an educator and taking opportunities to reflect and improve so that you are able to help your students discover more and don't fall into the trap of the banking concept.

This is true, not just in adult education, but in building the foundations in education of younger students. Prioritizing rigor over exploration doesn't help learners think critically, it pushes them into drill and kill routines so they get through assignments, rather than critically understand. Building that foundation early on helps learners develop the ability to challenge this when it happens as adults.

Those that continue to want to continue the cycle of oppression continue to use the banking concept, taking advantage of the power imbalance to take away the autonomy of the learner and preventing them from understanding more about the world around them. They rely on the utilization of the banking concept and keeping that as the routine, rather than breaking free and flipping the script so that students are more actively involve in exploration and their education.

Those that want to continue to squash others and oppress others will do so by forcing them to understand one thing and taking away their autonomy and creativity, which is what the banking concept sees. This will only do a disservice to the learners in the future.

Those that want people to become mindless robot drones will not want to make education more exploratory or full of curiosity, they'll be okay with learners just being able to spit out facts and information, taking it at face value as opposed to going deeper into the knowledge.

The goal as educators should be to want to make our students better human beings and allowing them the opportunity to explore and inquire helps make them better because they get to be their own person and figure things out for themselves.

These attitudes and practices listed make me so uncomfortable thinking about being a student in a classroom like this, so very obviously learners would have a lot of issues learning if it was truly like this. Education should be collaborative where all parties are learning from each other and working together to explore the world.

Education is a team effort between student (and student's family) and teacher, which can help avoid the banking concept.

There is a big push in education that pushes teachers into the mindset that all students are capable of great things, and I feel like thinking in this mindset would help reverse "dumbing down" education and falling into the banking concept.

Absolutely! The childhood memories that we have and strong memories we have from learning, typically stem from the hands-on creativity and inquiry, not drill and killing information.

I love this metaphor because (I would hope) that most teachers agree that you would not want learners to memorize and regurgitate, but instead be active learners and take ownership of their learning. This metaphor really drives home what we typically tend to see in education with Freire's narrating statements.

Especially in math, it's important that the students not just understand what the answer is but HOW to get the answer. Related to the whole "give a man a fish, he'll eat for a day, but teach a man to fish, he'll always eat" saying, active learning helps students continually understand (when it's put in place).

This reminds me of what I learned in a previous course on engagement and motivation. Learners won't be able to develop motivation if they are detached from the content and there isn't meaning to them (per Keller's ARCS model of motivation).

Freire is on the nose here. In my own personal teaching practice and experience, I've seen that when I stand and talk at the students, they tend to zone out and it becomes like I'm talking to a wall. My current administration works hard to ensure we are being engaging and getting the students talking so the students don't become lifeless and intead make meaningful connections with the content.

what the FREAK bro. Old physicists were built different. Can you imagine not being able to do this with a computer----quite literally just sitting and looking

Using AI can often lead to misinformation or misleading answers, which can have negative effects on the user.

Need to give direct instructions to the AI to create what you're looking for. lacks the creativity on its own.

What parts of the heritage are they unable to know? Is it because some people have history that isn't written about often on the internet, so AI can't learn it?

It's hard to stay up to date on ChatGPT with how much it upgrades itself with new information. Definitely feels like trying to cast spells.

Technology may or may not have a major impact on the student ability to learn but many may argue that those who use technology to do research or take notes and study get distracted easily and find forms to cheat as rather than open book and old data use and notes

Can certain foods that are recommended as breakfast have different effects the night time or have the same health benefits ?

Why do people discontinue the participation in the project ? Do the gain anything out of it or do scientist get any answers if many never complete studies

Longitudinal research is a form of research on a studying the same group of people for a long period of time and cross sectional researcher are researchers who compare different age groups

Using AI stops us from fully understanding and gaining knowledge from our work

AI will never be able to write as creatively as humans can.

AI doesn't have a moral compass like humans do, and won't understand the consquences you may face based off it's work.

AI benefits only those building it, while hindering your education.

No work by AI can be described as new. It's just a copy of other's work. I like how he said it's "at the very least" ethically suspect.

Important thing for the professor to emphasize. If you respect him by not using AI, he'll return the same favor when looking at your work.

Makes us question the real use of AI and how people might be misusing it.

The questions in the article play a really important role in, because we can identify the main idea and what strategies as answers we can improve in our life as College students.

This is a very common fact in everyone, because you feel brilliant and independent. However, you can get cocky and don't want to try challenging things because of fear to do it wrong.

This citation delivered a very important message to how be able to combat the deficit in your daily life having a good plan.

no

no

T

T

The biggest change i'm seeing is having time for my family and not being able to do a lot of things.

1) I plan on graduate in 2 to 3 years and go into culinary school 2) 5 or more 3) Math and the mental struggle 4) yes, and ik i can

Even though we may not notice it there is a flow in everyone's life. People naturally start to fall into a pattern overtime similar how shows can blend seamlessly together and get us to sit there watching for hours.

Flow wasn't a method of success for television companies and became a way for companies to express there thoughts freely using a go with the flow desire. There was not a specific pattern or organization that the programs had to follow it was more freeform.

Flow was defined in many ways and became a way for people to ridicule televisions. Some people even viewed the way that broadcasting flowed as disorganized with ads disrupting the viewers experience. Flow wasn't smooth it was seen as a way to describe random meaningless content.

Programming has many unique interworking parts that can each be interpreted and looked at individually. By bringing all these individual parts together that is when we see the flow as it is meant to be naturally switching topics and keeps the viewer interested.

Yes but instead of us being given a few options of what we can spend our time watching or looking at, we now get to decide what content we consume. Whether it be binging a show, or doom scrolling, participating in online forums we are not relegated to what's given to us, we find what we are looking for to consume.

I feel like this statement can be attributed to Soap Operas. They really did cater to the housewife who was home everyday. My grandmother used to stop all activities when her "stories" came on and if she wasn't home to catch them she learned to use her VHS recorder to tape them for when she got home.

This statement is important because it reminds us that stories are not only a way of sharing experiences, but also a way of confronting inequality. In a diverse and multicultural society, storytelling can uncover voices that are often silenced and challenge the effects of racism. By value these stories we create space for remembering, resisting injustice and fostering healing within communities.

I agree with this because stories often spark memories and emotions that stay with us. When I listen to a story certain images stand out and they connect to my own experiences. That connection is what makes storytelling so powerful its not just about hearing someone's else words, but about remembering and feeling something personal through them.

This passage made me realize how much skill goes into oral storytelling. The timing, tone and audience connection turn it into real are even though at times its often dismissed as simple. It makes me think about how we are sometimes undervalue certain forms of expression just because they don't fit traditional ides of literature.

tiny channels in the cell wall

This is interesting because the idea of "who's ideas are these" often come up with the use of LLMs

Reading this part made me think about how it connects to my own future in public health. It reminded me that giving people better healthcare isn’t enough if the environments they live in remain unsafe. For example, if a community is surrounded by air pollution, people may continue to develop breathing problems even if they have access to clinics. The WHO highlights that improving equity often means looking beyond medical care and addressing root causes like environment, housing, and income. For me, this shows that part of public health work has to include pushing for cleaner environments and fair policies, not just treating disease.

Citations:

• Gao, C., Sanchez, K. M., & Lovinsky-Desir, S. (2023). Structural and social determinants of inequitable environmental exposures in the United States. Clinics in Chest Medicine, 44(3), 451–467. https://doi.org/10.1016/j.ccm.2023.03.002

• World Health Organization. (2023). Social determinants of health. https://www.who.int/health-topics/social-determinants-of-health

One thing that really jumped out at me while reading was the point about pollution and marginalized groups. The article pointed out that groups like American Indian, African American, and Latino populations are often placed at higher risk because of systemic racism and segregation. My ‘ah-ha’ moment was realizing that health disparities are not just about healthcare access they are tied to unfair structures that shape where people live and the air they breathe. The WHO also stresses that where people live, work, and play is just as important as the care they receive, which made this point hit even harder for me.

Citations:

• Gao, C., Sanchez, K. M., & Lovinsky-Desir, S. (2023). Structural and social determinants of inequitable environmental exposures in the United States. Clinics in Chest Medicine, 44(3), 451–467. https://doi.org/10.1016/j.ccm.2023.03.002

• World Health Organization. (2023). Social determinants of health. https://www.who.int/health-topics/social-determinants-of-health

I heard that because humans over hunted some wolfs that it eventually lead to a river changing its path. Here is the situation I am talking about from google: "human hunting of wolves led to a trophic cascade where the absence of wolves in places like Yellowstone National Park allowed elk populations to boom, overgrazing riverbanks, leading to increased erosion and degraded river systems" Has there been more than one occasion somthing like this has happened and if so has this been studied extensively?

Watching television is accessible at any time of day and has become an important part of our everyday lives to the point where people plan to watch tv at certain times to get their daily fix of television.

Television can become addictive as we get used to the flow of the programs we might not even realize that something else completely is playing now. To keep people watching it is important for shows to have something to catch the attention of the viewer towards the beginning of the program.

The goal of television channels is to get people to watch the shows towards the beginning of the flow so they keep watching and get hooked.

It is unpredictable how viewers will react to the planned flow of broadcasting. The sequences are thought out so that the viewer doesn't lose interest but films sometime felt as if there was a disruption.

By bringing certain sequences together at specific points that is how you can successfully create the flow needed in a broadcast, allowing it to run smoothly.

This shows us that M. galloprovincialis was not affected by the temperatures which can lead to a conclusion that temperatures does not affect them. Also, that they can thrive better no matter if the temperatures warm up.

This definition of document neglects to mention physical documents such a objects, which brings up the question: What is a document? It also makes me wonder when physical objects became part of archival practice. On page 14, the manual states that "---objects cannot form part of the archival collections, which by nature belong to museums or collections of antiquities...". I wonder why they exclude 3D objects.

I think that this is such a creative final project, and even though I don't have anything written for this class yet I'm already brainstorming what I might do. It makes me really excited to pour my heart into all of the assignments for this course so that I can really have some good material to base my final project on.

At what point in time did these populist change their outlook and feel hopeful for their future?

The way this is considered a new ear or birth of inequality is eye opening to me. It helps me to see that this was seen as a large change whether good or bad for America.

The way in which this sentence is written gives light towards police force action and the reality of brutality. It highlights the realness of corruption at this Tim,e and the fear businessman had that this would consume their public image.

Such an expression clearly shows the priority of higher class than others. Almost as if this statement is saying survival of the fittest or everyone for themselves.

The relationship between business men and politicians reveal how status and wealth may fluctuate ones mindset as they turn more self centered and less considerate of other people and the conditions they endure purely because they aren't in that situation.

Here we go instead of just calling them: ID's hashes... or Addresses they have to use a term based on what it enables. The mere fact that this Answers has to be in the FAQ shows that they should select a better name.

In this time, China seemed to constantly want more. More people, more trade, and more land and cities.

With the population almost doubling during his reign, I wonder if it would have happened regardless of if Hongwu was Emperor or not during that time.

The practices of infanticide and foot-binding are interesting because they directly go against the virtue of gentleness that Confucian wanted.

With a generally fair way to take the tests, it probably left room for more people to want to be in positions of power.

These five virtues are interesting to me because, though they aren't from the same religion, they are somewhat similar to the Fruits of the Spirit in the Bible. Which are: love, joy, peace, forbearance, kindness, goodness, faithfulness, gentleness, and self-control.

There is no doubt that China was extremely advanced and successful due to their abundance of goods. This is still somewhat true today given that a lot of the products used worldwide are made in China.

Every work of literature/text/film creates an image and story in our heads and we need to analyze their differences and effects in catastrophe.

Most catastrophes affect the environment and we have to keep that in mind.

Understand the devices used and write essays about them

This will make it easier for myself and most likely other people to read since you can find where and what its talking about so easily.

I find this very helpful in a way because I personally already kind of read like this.

i think this is important to understand that music can create emotion and a better movie for the audeince and the plot of the characters.

i agree the non diegetic music is onyl for the audience to understand and the actors have to pretend they don't hear the music or it would ruin the film . Jaws is a perfect example of this.

these are some important points to keep in mind is music in the film is heard by the audience and the actors then it is considers diegetic music now if the jusic can only be heard by the audience then it is considered non-diegetic this is all new information to me as well i never this phenomenon had a name to it.

I agree i think music can be used in various different ways throughout a film not only in the beginning but in scary scenes or sad plots.

silence in a shot can describe a eerie feeling especially in horror movies or emotional shots that are suppose to oimpact the audience.

this makes since because movie theaters are so loud and you can hear everything that has been adding in the sound mixers.

i think sound mixing rising the tension and emotions of the audience watching the film.

this tells me that sound mixing can affect the audios level of loudness or softness. This can be used in intense scenes or emotion romance shots.

this movie is a great example of J=cut it adds the audio before showing the next clip in the movie this can be used in many different genres comedy and horror.

this is interesting to know that nature, birds, and evrononmetal sounds can be made by a foley artist or are pre recorded in places like the library which leads me to another point the liberty is a great places to record sounds because it is quiet and background noises won't interfere with the audio being recorded.

I find this type of editing unique to the production of filmmaking i onced wanted something like this in the production of hollywood movies. not only is this creative but this allows films to perfect the audio for a shot.

How do we (humans) feel about having an artificial intelligence learning to behave like us?

This makes me reflect on the idea that many people have made the mistake of believing that AI is much more complex than the human brain.

How do we imagine ourselves? The quoted section continues on the next page. Cook guides readers through his four proposed paradigms in archival history with careful footing and an optimism which betrays his age but endears his endeavor. The question of imaging ourselves in the past, present, and future is one which the archive will answer, whether we like it or not. Even the very language of "ourselves" betrays the necessity of both looking closer at the meanings of words (metadata) and looking more expansively from diverse points of view. Whether we prefer paradigms or frameworks or mindsets, the task remains the same: Tackle the question of what it means to be human in this space-time. If something is archived, then there is a certain possibility of being remembered. If not, it will most likely be forgotten.

king who survived the flood by building a boat

• I feel like this is important too as it says that we should be able to assume and perceive our own thoughts about various topics within the field of Russian Politics. I feel like this is also say that if we want to do well within the course, we have to be able to make our own learning environments and systems, and be flexible about the issue of Russian Politics.

I feel like this is heavily important because these skills, especially discussion (speaking) and writing, are vital skills needed for future careers after the college experience. Based off of this, I feel like this class will help us as students achieve these skills and help us become better employees later down the road.

I feel that this is very important skill that is vital for learning and growth. I am just unsure how this would be display itself in our work.

I very much like this because it encourages us to challenge the topic and not accept what is presented at face value. I enjoy engaging material like this fully and have had challenges in previous classes having in-depth discussion with classmates who didn't seem interested in much else beyond repeating what they read in their textbook.

https://support.apple.com/en-us/102650

design.need : solutions - open - interoperable - ubiquitous - not build behind closed doors - hosted by companies unilaterally sell off our data - turn of our service - be sure the solution will be around 10, 100, 1000 years from now

eLife Assessment

This useful manuscript reports mechanisms behind the increase in fecundity in response to sub-lethal doses of pesticides in the crop pest, the brown plant hopper. The authors hypothesize that the pesticide works by inducing the JH titer, which through the JH signaling pathway induces egg development, for which the evidence was judged to be solid.

Reviewer #1 (Public review):

Summary:

Gao et al. has demonstrated that the the pesticide emamectin benzoate (EB) treatment of brown plathopper (BPH) leads to increased egg laying in the insect, which is a common agricultural pest. The authors hypothesize that EB upregulates JH titer resulting in increased fecundity.

Strengths:

The finding that a class of pesticide increases fecundity of brown planthopper is interesting.

Comments on revisions:

All my concerns have been addressed to reasonable level of satisfaction.

Author response:

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

Reviewer #1 (Recommendations for the authors):

(1) The onus of making the revisions understandable to the reviewers lies with the authors. In its current form, how the authors have approached the review is hard to follow, in my opinion. Although the authors have taken a lot of effort in answering the questions posed by reviewers, parallel changes in the manuscript are not clearly mentioned. In many cases, the authors have acknowledged the criticism in response to the reviewer, but have not changed their narrative, particularly in the results section.

We fully acknowledge your concern regarding the narrative linking EB-induced GluCl expression to JH biosynthesis and fecundity enhancement, particularly the need to address alternative interpretations of the data. Below, we outline the specific revisions made to address your feedback and ensure the manuscript’s narrative aligns more precisely with the experimental evidence:

(1) Revised Wording in the Results Section

To avoid overinterpretation of causality, we have modified the language in key sections of the Results (e.g., Figure 5 and related text):

Original phrasing:

“These results suggest that EB activates GluCl which induces JH biosynthesis and release, which in turn stimulates reproduction in BPH (Figure 5J).”

Revised phrasing:

“We also examined whether silencing Gluclα impacts the AstA/AstAR signaling pathway in female adults. Knock-down of Gluclα in female adults was found to have no impact on the expression of AT, AstA, AstB, AstCC, AstAR, and AstBR. However, the expression of AstCCC and AstCR was significantly upregulated in dsGluclα-injected insects (Figure 5-figure supplement 2A-H). Further studies are required to delineate the direct or indirect mechanisms underlying this effect of Gluclα-knockdown.” (line 643-649). And we have removed Figure 5J in the revised manuscript.

(2) Expanded Discussion of Alternative Mechanisms

In the Discussion section, we have incorporated a dedicated paragraph to explore alternative pathways and compensatory mechanisms:

Key additions:

“This EB action on GluClα expression is likely indirect, and we do not consider EB as transcriptional regulator of GluClα. Thus, the mechanism behind EB-mediated induction of GluClα remains to be determined. It is possible that prolonged EB exposure triggers feedback mechanisms (e.g. cellular stress responses) to counteract EB-induced GluClα dysfunction, leading to transcriptional upregulation of the channel. Hence, considering that EB exposure in our experiments lasts several days, these findings might represent indirect (or secondary) effects caused by other factors downstream of GluCl signaling that affect channel expression.” (line 837-845).

(2) In the response to reviewers, the authors have mentioned line numbers in the main text where changes were made. But very frequently, those lines do not refer to the changes or mention just a subsection of changes done. As an example please see point 1 of Specific Points below. The problem is throughout the document making it very difficult to follow the revision and contributing to the point mentioned above.

Thank you for highlighting this critical oversight. We sincerely apologize for the inconsistency in referencing line numbers and incomplete descriptions of revisions, which undoubtedly hindered your ability to track changes effectively. We have eliminated all vague or incomplete line number references from the response letter. Instead, revisions are now explicitly tied to specific sections, figures, or paragraphs.

(3) The authors need to infer the performed experiments rationally without over interpretation. Currently, many of the claims that the authors are making are unsubstantiated. As a result of the first review process, the authors have acknowledged the discrepancies, but they have failed to alter their interpretations accordingly.

We fully agree that overinterpretation of data undermines scientific rigor. In response to your feedback, we have systematically revised the manuscript to align claims strictly with experimental evidence and to eliminate unsubstantiated assertions. We sincerely apologize for the earlier overinterpretations and appreciate your insistence on precision. The revised manuscript now rigorously distinguishes between observations (e.g., EB-GluCl-JH correlations) and hypotheses (e.g., GluCl’s mechanistic role). By tempering causal language and integrating competing explanations, we aimed to present a more accurate and defensible narrative.

SPECIFIC POINTS (to each question initially raised and their rebuttals)

(1a) "Actually, there are many studies showing that insects treated with insecticides can increase the expression of target genes". Please note what is asked for is that the ligand itself induces the expression of its receptor. Of course, insecticide treatment will result in the changes expression of targets. Of all the evidences furnished in rebuttal, only Peng et al. 2017 fits the above definition. Even in this case, the accepted mode of action of chlorantraniliprole is by inducing structural change in ryanodine receptor. The observed induction of ryanodine receptor chlorantraniliprole can best be described as secondary effect. All others references do not really suffice the point asked for.

We appreciate the reviewers’ suggestions for improving the manuscript. First, we have supplemented additional studies supporting the notion that " There are several studies showing that insects treated with insecticides display increases in the expression of target genes. For example, the relative expression level of the ryanodine receptor gene of the rice stem borer, Chilo suppressalis was increased 10-fold after treatment with chlorantraniliprole, an insecticide which targets the ryanodine receptor (Peng et al., 2017). In Drosophila, starvation (and low insulin) elevates the transcription level of the receptors of the neuropeptides short neuropeptide F and tachykinin (Ko et al., 2015; Root et al., 2011). In BPH, reduction in mRNA and protein expression of a nicotinic acetylcholine receptor α8 subunit is associated with resistance to imidacloprid (Zhang et al., 2015). Knockdown of the α8 gene by RNA interference decreased the sensitivity of N. lugens to imidacloprid (Zhang et al., 2015). Hence, the expression of receptor genes may be regulated by diverse factors, including insecticide exposure.” We have inserted text in lines 846-857 to elaborate on these possibilities.

Second, we would like to reiterate our position: we have merely described this phenomenon, specifically that EB treatment increases GluClα expression. “This EB action on GluClα expression is likely indirect, and we do not consider EB as transcriptional regulator of GluClα. Thus, the mechanism behind EB-mediated induction of GluClα remains to be determined. It is possible that prolonged EB exposure triggers feedback mechanisms (e.g. cellular stress responses) to counteract EB-induced GluClα dysfunction, leading to transcriptional upregulation of the channel. Hence, considering that EB exposure in our experiments lasts several days, these findings might represent indirect (or secondary) effects caused by other factors downstream of GluCl signaling that affect channel expression.” We have inserted text in lines 837-845 to elaborate on these possibilities.

Once again, we sincerely appreciate this discussion, which has provided us with a deeper understanding of this phenomenon.

b. The authors in their rebuttal accepts that they do not consider EB to a transcriptional regulator of Gluclα and the induction of Gluclα as a result of EB can best be considered as a secondary effect. But that is not reflected in the manuscript, particularly in the result section. Current state of writing implies EB up regulation of Gluclα to an important event that contributes majorly to the hypothesis. So much so that they have retained the schematic diagram (Fig. 5J) where EB -> Gluclα is drawn. Even the heading of the subsection says "EB-enhanced fecundity in BPHs is dependent on its molecular target protein, the Gluclα channel". As mentioned in the general points, it is not enough to have a good rebuttal written to the reviewer, the parent manuscript needs to reflect on the changes asked for.

Thank you for your comments. We have carefully addressed your suggestions and made corresponding revisions to the manuscript.

We fully acknowledge the reviewer's valid concern. In this revised manuscript, “However, we do not propose that EB is a direct transcriptional regulator of Gluclα, since EB and other avermectins are known to alter the channel conformation and thus their function (Wolstenholme, 2012; Wu et al., 2017). Thus, it is likely that the observed increase in Gluclα transcipt is a secondary effect downstream of EB signaling.” (Line 625-629). We agree that the original presentation in the manuscript, particularly within the Results section, did not adequately reflect this nuance and could be misinterpreted as suggesting a direct regulatory role for EB on Gluclα transcription.

Regarding Fig. 5J, we have removed the figure and all mentions of Fig. 5J and its legend in the revised manuscript.

c. "We have inserted text on lines 738 - 757 to explain these possibilities." Not a single line in the section mentioned above discussed the topic in hand. This is serious undermining of the review process or carelessness to the extreme level.

In the Results section, we have now added descriptions “Taken together, these results reveal that EB exposure is associated with an increase in JH titer and that this elevated JH signaling contributes to enhanced fecundity in BPH.” (line 375-377).

For the figures, we have removed Fig. 4N and all mentions of Fig. 4N and its legend in the revised manuscript.

Lastly, regarding the issue of locating specific lines, we deeply regret any inconvenience caused. Due to the track changes mode used during revisions, line numbers may have shifted, resulting in incorrect references. We sincerely apologize for this and have now corrected the line numbers.

(2) The section written in rebuttal should be included in the discussion as well, explaining why authors think a nymphal treatment with JH may work in increasing fecundity of the adults. Also, the authors accept that EBs effect on JH titer in Indirect. The text of the manuscript, results section and figures should be reflective of that. It is NOT ok to accept that EB impacts JH titer indirectly in a rebuttal letter while still continuing to portray EB direct effect on JH titer. In terms of diagrams, authors cannot put a -> sign until and unless the effect is direct. This is an accepted norm in biological publications.

We appreciate the reviewer’s valuable suggestions here. We have now carefully revised the manuscript to address all concerns, particularly regarding the mechanism linking nymphal EB exposure to adult fecundity and the indirect nature of EB’s effect on JH titers. Below are our point-by-point responses and corresponding manuscript changes. Revised text is clearly marked in the resubmitted manuscript.

(1) Clarifying the mechanism linking nymphal EB treatment to adult fecundity:

Reviewer concern: Explain why nymphal EB treatment increases adult fecundity despite undetectable EB residues in adults.

Response & Actions Taken:

We agree this requires explicit discussion. We now propose that nymphal EB exposure triggers developmental reprogramming (e.g., metabolic/epigenetic changes) that persist into adulthood, indirectly enhancing JH synthesis and fecundity. This is supported by two key findings:

(1) No detectable EB residues in adults after nymphal treatment (new Figure 1–figure supplement 1C).

(2) Increased adult weight and nutrient reserves (Figure 1–figure supplement 3E,F), suggesting altered resource allocation.

Added to Discussion (Lines 793–803): Notably, after exposing fourth-instar BPH nymphs to EB, no EB residues were detected in the subsequent adult stage. This finding indicates that the EB-induced increase in adult fecundity is initiated during the nymphal stage and s manifests in adulthood - a mechanism distinct from the direct fecundity enhancement of fecundity observed when EB is applied to adults. We propose that sublethal EB exposure during critical nymphal stages may reprogram metabolic or endocrine pathways, potentially via insulin/JH crosstalk. For instance, increased nutrient storage (e.g., proteins, sugars; Figure 2–figure supplement 2) could enhance insulin signaling, which in turn promotes JH biosynthesis in adults (Ling and Raikhel, 2021; Mirth et al., 2014; Sheng et al., 2011). Future studies should test whether EB alters insulin-like peptide expression or signaling during development.

(3) Emphasizing EB’s indirect effect on JH titers:Reviewer concern: The manuscript overstated EB’s direct effect on JH. Arrows in figures implied causality where only correlation exists.

Response & Actions

Taken:We fully agree. EB’s effect on JH is indirect and multifactorial (via AstA/AstAR suppression, GluCl modulation, and metabolic changes). We have:

Removed oversimplified schematics (original Figures 3N, 4N, 5J).

Revised all causal language (e.g., "EB increases JH" → "EB exposure is associated with increased circulating JH III "). (Line 739)

Clarified in Results/Discussion that EB-induced JH changes are likely secondary to neuroendocrine disruption.

Key revisions:

Results (Lines 375–377):

"Taken together, these results reveal that EB exposure is associated with an increase in JH titer and that JH signaling contributes to enhanced fecundity in BPH."

Discussion (Lines 837–845):

This EB action on GluClα expression is likely indirect, and we do not consider EB as transcriptional regulator of GluClα. Thus, the mechanism behind EB-mediated induction of GluClα remains to be determined. It is possible that prolonged EB exposure triggers feedback mechanisms (e.g. cellular stress responses) to counteract EB-induced GluClα dysfunction, leading to transcriptional upregulation of the channel. Hence, considering that EB exposure in our experiments lasts several days, these findings might represent indirect (or secondary) effects caused by other factors downstream of GluCl signaling that affect channel expression.

a. Lines 281-285 as mentioned, does not carry the relevant information.

Thank you for your careful review of our manuscript. We sincerely apologize for the confusion regarding line references in our previous response. Due to extensive revisions and tracked changes during the revision process, the line numbers shifted, resulting in incorrect citations for Lines 281–285. The correct location for the added results (EB-induced increase in mature eggs in adult ovaries) is now in lines 253-258: “We furthermore observed that EB treatment of female adults also increases the number of mature eggs in the ovary (Figure 2-figure supplement 1).”

b. Lines 351-356 as mentioned, does not carry the relevant information. Lines 281-285 as mentioned, does not carry the relevant information.

Thank you for your careful review of our manuscript. We sincerely apologize for the confusion regarding line references in our previous response. The correct location for the added results is now in lines 366-371: “We also investigated the effects of EB treatment on the JH titer of female adults. The data indicate that the JH titer was also significantly increased in the EB-treated female adults compared with controls (Figure 3-figure supplement 3A). However, again the steroid 20-hydroxyecdysone, was not significantly different between EB-treated BPH and controls (Figure 3-figure supplement 3B).”

c. Lines 378-379 as mentioned, does not carry the relevant information. Lines 387-390 as mentioned, does not carry the relevant information.

We sincerely apologize for the confusion regarding line references in our previous response.

The correct location for the added results is now in lines 393-394: We furthermore found that EB treatment in female adults increases JHAMT expression (Figure 3-figure supplement 3C).

The other correct location for the added results is now in lines 405-408: We found that Kr-h1 was significantly upregulated in the adults of EB-treated BPH at the 5M, 5L nymph and 4 to 5 DAE stages (4.7-fold to 27.2-fold) when 4th instar nymph or female adults were treated with EB (Figure 3H and Figure 3-figure supplement 3D)..

(3) The writing quality is still extremely poor. It does not meet any publication standard, let alone elife.

We fully understand your concerns and frustrations, and we sincerely apologize for the deficiencies in our writing quality, which did not meet the high standards expected by you and the journal. We fully accept your criticism regarding the writing quality and have rigorously revised the manuscript according to your suggestions.

(4) I am confused whether Figure 2B was redone or just edited. Otherwise this seems acceptable to me.

Regarding Fig. 2B, we have edited the text on the y-axis. The previous wording included the term “retention,” which may have caused misunderstanding for both the readers and yourself, leading to the perception of contradiction. We have now revised this wording to ensure accurate comprehension.

(5) The rebuttal is accepted. However, still some of the lines mentioned does not hold relevant information.

This error has been corrected.

The correct location for the added results is now in lines 255-258 and lines 279-282: “Hence, although EB does not affect the normal egg developmental stages (see description in next section), our results suggest that EB treatment promotes oogenesis and, as a result the insects both produce more eggs in the ovary and a larger number of eggs are laid.” and “However, considering that the number of eggs laid by EB treated females was larger than in control females (Figure 1 and Figure 1-figure supplement 1), our data indicates that EB treatment of BPH can both promote both oogenesis and oviposition.”

(6) Thank you for the clarification. Although now discussed extensively in discussion section, the nuances of indirect effect and minimal change in expression should also be reflected in the result section text. This is to ensure that readers have clear idea about content of the paper.

Corrected. To ensure readers gain a clear understanding of our data, we have briefly presented these discussions in the Results section. Please see line 397-402: The levels of met mRNA slightly increased in EB-treated BPH at the 5M and 5L instar nymph and 1 to 5 DAE adult stages compared to controls (1.7-fold to 2.9-fold) (Figure 3G). However, it should be mentioned that JH action does not result in an increase of Met. Thus, it is possible that other factors (indirect effects), induced by EB treatment cause the increase in the mRNA expression level of Met.

(7) As per the author's interpretation, it becomes critical to quantitate the amount of EB present at the adult stages after a 4th instar exposure to it. Only this experiment will unambiguously proof the authors claim. Also, since they have done adult insect exposure to EB, such experiments should be systematically performed for as many sections as possible. Don't just focus on few instances where reviewers have pointed out the issue.

Thank you for raising this critical point. To address this concern, we have conducted new supplementary experiments. The new experimental results demonstrate that residual levels of emamectin benzoate (EB) in adult-stage brown planthoppers (BPH) were below the instrument detection limit following treatment of 4th instar nymphs with EB. Line 172-184: “To determine whether EB administered during the fourth-instar larval stage persists as residues in the adult stage, we used HPLC-MS/MS to quantify the amount of EB present at the adult stage after exposing 4th-instar nymphs to this compound. However, we found no detectable EB residues in the adult stage following fourth-instar nymphal treatment (Figure 1-figure supplement 1C). This suggests that the mechanism underlying the increased fecundity of female adults induced by EB treatment of nymphs may differ from that caused by direct EB treatment of female adults. Combined with our previous observation that EB treatment significantly increased the body weight of adult females (Figure 1—figure supplement 3E and F), a possible explanation for this phenomenon is that EB may enhance food intake in BPH, potentially leading to elevated production of insulin-like peptides and thus increased growth. Increased insulin signaling could potentially also stimulate juvenile hormone (JH) biosynthesis during the adult stage (Badisco et al., 2013).”

(8) Thank you for the revision. Lines 725-735 as mentioned, does not carry the relevant information. However, since the authors have decided to remove this systematically from the manuscript, discussion on this may not be required.

Thank you for identifying the limited relevance of the content in Lines 725–735 of the original manuscript. As recommended, we have removed this section in the revised version to improve logical coherence and maintain focus on the core findings.

(9) Normally, dsRNA would last for some time in the insect system and would down-regulate any further induction of target genes by EB. I suggest the authors to measure the level of the target genes by qPCR in KD insects before and after EB treatment to clear the confusion and unambiguously demonstrate the results. Please Note- such quantifications should be done for all the KD+EB experiments. Additionally, citing few papers where such a rescue effect has been demonstrated in closely related insect will help in building confidence.

We appreciate the reviewer’s suggestion to clarify the interaction between RNAi-mediated gene knockdown (KD) and EB treatment. To address this, we performed additional experiments measuring Kr-h1 expression via qPCR in dsKr-h1-injected insects before and after EB exposure.

The results (now Figure 3–figure supplement 4) show that:

(1) EB did not rescue *Kr-h1* suppression at 24h post-treatment (*p* > 0.05).

(2) Partial recovery of fecundity occurred later (Figure 3M), likely due to:

a) Degradation of dsRNA over time, reducing KD efficacy (Liu et al., 2010).

b) Indirect effects of EB (e.g., hormonal/metabolic reprogramming) compensating for residual Kr-h1 suppression.

Please see line 441-453: “Next, we investigated whether EB treatment could rescue the dsRNA-mediated gene silencing effect. To address this, we selected the Kr-h1 gene and analyzed its expression levels after EB treatment. Our results showed that Kr-h1 expression was suppressed by ~70% at 72 h post-dsRNA injection. However, EB treatment did not significantly rescue Kr-h1 expression in gene knock down insects (*p* > 0.05) at 24h post-EB treatment (Figure 3-figure supplement 4). While dsRNA-mediated Kr-h1 suppression was robust initially, its efficacy may decline during prolonged experiments. This aligns with reports in BPH, where effects of RNAi gradually diminish beyond 7 days post-injection (Liu et al., 2010a). The late-phase fecundity increase might reflect partial Kr-h1 recovery due to RNAi degradation, allowing residual EB to weakly stimulate reproduction. In addition, the physiological impact of EB (e.g., neurotoxicity, hormonal modulation) could manifest via compensatory feedback loops or metabolic remodeling.”

(10) Not a very convincing argument. Besides without a scale bar, it is hard for the reviewers to judge the size of the organism. Whole body measurements of JH synthesis enzymes will remain as a quite a drawback for the paper.

In response to your suggestion, we have also included images with scale bars (see next Figure 1). The images show that the head region is difficult to separate from the brown thoracic sclerite region. Furthermore, the anatomical position of the Corpora Allata in brown planthoppers has never been reported, making dissection uncertain and highly challenging. To address this, we are now attempting to use Drosophila as a model to investigate how EB regulates JH synthesis and reproduction.

Author response image 1.<br /> This illustration provides a visual representation of the brown planthopper (BPH), a major rice pest.<br />

Figure 1. This illustration provides a visual representation of the brown planthopper (BPH), a major rice pest.).

(11) "The phenomenon reported was specific to BPH and not found in other insects. This limits the implications of the study". This argument still holds. Combined with extreme species specificity, the general effect that EB causes brings into question the molecular specificity that the authors claim about the mode of action.

We acknowledge that the specificity of the phenomenon to BPH may limit its broader implications, but we would like to emphasize that this study provides important insights into the unique biological mechanisms in BPH, a pest of significant agricultural importance. The molecular specificity we described in the manuscript is based on rigorous experimental evidence. We believe that it contributes to valuable knowledge to understand the interaction of external factors such as EB and BPH and resurgence of pests. We hope that this study will inspire further research into the mechanisms underlying similar phenomena in other insects, thereby broadening our understanding of insect biology. Since EB also has an effect on fecundity in Drosophila, albeit opposite to that in BPHs (Fig. 1 suppl. 2), it seems likely that EB actions may be of more general interest in insect reproduction.

(12) The authors have added a few lines in the discussion but it does not change the overall design of the experiments. In this scenario, they should infer the performed experiments rationally without over interpretation. Currently, many of the claims that the authors are making are unsubstantiated. As a result of the first review process, the authors have acknowledged the discrepancies, but they have failed to alter their interpretations accordingly.

We appreciate your concern regarding the experimental design and the need for rational inference without overinterpretation. In response, we would like to clarify that our discussion is based on the experimental data we have collected. We acknowledge that our study focuses on BPH and the specific effects of EB, and while we agree that broader generalizations require further research, we believe the new findings we present are valid and contribute to the understanding of this specific system.

We also acknowledge the discrepancies you mentioned and have carefully considered your suggestions. In this revised version, we believe our interpretations are reasonable and consistent with the data, and we have adjusted our discussion to better reflect the scope of our findings. We hope that these revisions address your concerns. Thank you again for your constructive feedback.

ADDITIONAL POINTS

(1) Only one experiment was performed with Abamectin. No titration for the dosage were done for this compound, or at least not provided in the manuscript. Inclusion of this result will confuse readers. While removing this result does not impact the manuscript at all. My suggestion would be to remove this result.

We acknowledge that the abamectin experiment lacks dose-titration details and that its standalone presentation could lead to confusion. However, we respectfully request to retain these results for the following reasons:

Class-Specific Mechanism Validation:

Abamectin and emamectin benzoate (EB) are both macrocyclic lactones targeting glutamate-gated chloride channels (GluCls). The observed similarity in their effects on BPH fecundity (e.g., Figure 1—figure supplement 1B) supports the hypothesis that GluCl modulation, rather than compound-specific off-target effects, drives the reproductive enhancement. This consistency strengthens the mechanistic argument central to our study.

(2) The section "The impact of EB treatment on BPH reproductive fitness" is poorly described. This needs elaboration. A line or two should be included to describe why the parameters chosen to decide reproductive fitness were selected in the first place. I see that the definition of brachypterism has undergone a change from the first version of the manuscript. Can you provide an explanation for that? Also, there is no rationale behind inclusion of statements on insulin at this stage. The authors have not investigated insulin. Including that here will confuse readers. This can be added in the discussion though.

Thank you for your suggestion. We have added an explanation regarding the primary consideration of evaluating reproductive fitness. In the interaction between sublethal doses of insecticides and pests, reproductive fitness is a key factor, as it accurately reflects the potential impact of insecticides on pest control in the field. Among the reproductive fitness parameters, factors such as female Nilaparvata lugens body weight, lifespan, and brachypterous ratio (as short-winged N. lugens exhibit higher oviposition rates than long-winged individuals) are critical determinants of reproductive success. Therefore, we comprehensively assessed the effects of EB on these parameters to elucidate the primary mechanism by which EB influences reproduction. We sincerely appreciate your constructive feedback.

(3) "EB promotes ovarian maturation in BPH" this entire section needs to be rewritten and attention should be paid to the sequence of experiments described.

Thank you for your suggestion. Based on your recommendation, we have rewritten this section (lines 267–275) and adjusted the sequence of experimental descriptions to improve the structural clarity of this part.

(4) Figure 3N is outright wrong and should be removed or revised.

In accordance with your recommendation, we have removed the figure.

(5) When you are measuring hormonal titers, it is important to mention explicitly whether you are measuring hemolymph titer or whole body.

We believe we have explicitly stated in the Methods section (line 1013) that we measured whole-body hormone titers. However, we now added this information to figure legends.

(6)  EB induces JH biosynthesis through the peptidergic AstA/AstAR signaling pathway- this section needs attention at multiple points. Please check.

We acknowledge that direct evidence for EB-AstA/AstAR interaction is limited and have framed these findings as a hypothesis for future validation.

References

Liu, S., Ding, Z., Zhang, C., Yang, B., Liu, Z., 2010. Gene knockdown by intro-thoracic injection of double-stranded RNA in the brown planthopper, Nilaparvata lugens. Insect Biochem. Mol. Biol. 40, 666-671

But not in the US? Does that mean that they do it worldwide and we didn't catch them in the US? What do people in the UK think about this? Is there a mad cow disease analogue to horses and is that a risk?

How? By who? Did this include beef dishes at McDonald's or is this a non-sequitur?

I wonder what these inspections consist of, what point in the production process they would be? How often are they? How widespread are they? How many farms?

Where did this question come from and how was it posed? Who is tala and who is writing this email?

AND WHERES THE BEEF?!

I wonder who is responsible for confirming whether what they say is true?

For - key insight - my suffering comes from identifying too strongly with my avatar. -

for - example - poverty mentality - Donald Hoffman

for - example - poverty mentality - Donald Hoffman

for Q ❓- why would a transcendent power do such a thing? - why should death and pain be such an intrinsic creation of the transcendent? - pain receptors helo give us feedback to survive - but unfortunately, they are there often when it life is coming to an end

for - adjacency - heart of Christianity - shoe love to your abusers - Donald Hoffman

for - key insight - if that person is me, hope would I treat me? - Donald Hoffman - adjacency - if that person is me, how do I treat me? - Good Deep Humanity BEing journey

for - Science/evolution/Darwin/perception/ not the truth/but only to help us succeed at reproducing

for - quote / key insight - If if your religion is love and that's it and that's then that's how you act, you don't really need to add anything more to that. - That's that's all you really need. Love your neighbor as yourself. You're done.

• adjacency - love is all you need - love yourself - love your neighbor - my yogic song lyrics - Donald Hoffman
  • Makes me think of the llyric I wrote for a Yogic song:
    • Love
      • is the force of attraction
      • of the universe with itself

for - adjacency - awareness creates - awareness destroys - change - life coexists with death each moment - Donald Hoffman - Interesting perspective - that awareness constructs this reality and destroys it (lets it go) - This emerged the association with another idea I've often thought of: - how each moment embodies both life and death - A new moment cannot arise - unless the previous moment is let go of

for - quote / key insight - die before we die - Donald Hoffman - We will each die. That's incontrovertible. - So any attachments I have to this world will cease. - There's no doubt. - The question is can I let go of the attachments now - or will they only go for my cold dead hand?

• adjacency - example - cliche - die before we die - Donald Hoffman

for - adjacency - letting go - of knowledge - of theories - Donald Hoffman - I've often felt as he does - it's a conundrum of letting go of that (knowledge) we've invested so heavily into - quote / key insight - letting go of theories of science and self - Donald Hoffman - Science is great, but don't believe any theory. <br /> - Theories are just tools. They're not the truth. - No scientific theory, my theories included, are the truth. - And so also is my theory about who I am not the truth. - So to really let go of any theory, if I can really let go of any theory of who I am, then I'll let go of any fear

for - key insight / quote - Do I identify with my fear or step back and be the observer that watches the fear response? - Donald Hoffman? - adjacency - calmness - in the face of death - fear of death - Donald Hoffman

for - key insight - adjacency - fear - near death experience - experiential knowledge vs abstract knowledge - Donald Hoffman - He articulates a very important point, that many of us, are only partially there on the journey of journey of discovery - Belief only takes you part way there, - Embodiment is the real proof - We need to have the experience to be certain

for - comparison - emotional - vs intellectual - belief in the ideas - vs embodiment of the ideas - Donald Hoffman

for - adjacency - Christian teaching - infinite intelligence - loving God - loving your neighbor - loving yourself - all the same - Donald Hoffman

for - A Answer - you know it when you let go of all concepts and you don't try. If you're trying to get there, then you don't see what you already are. - Donald Hoffman

for - A Answer - the infinite knows itself though infinite number of perspectives - Donald Hoffman

for - Q ? - What is the meaning of life - Donald Hoffman

for - quote / key insight - consciousness has created the brain as an icon to describe how it's creating this headset - Donald Hoffman

for - adjacency - subjective vs objective reality - examining our most fundamental assumptions of reality, self and other Donald Hoffman - This is a difficult one for many people who reify objective reality to understand - It requires deep analysis and insight into our fundamental assumptions of how we employ anguage, learned while we were in our child development stage - Donald Hoffman is asking us to take that journey to uproot these most fundamental assumptions of self and other, long forgotten, but thoughtlessly projected into the present moment like an automaton

for - key insight / quote - the reason to love your neighbor - Donald Hoffman - The reason to love your neighbor as yourself is because - your neighbor IS YOUR (TRUE) SELF, just with a different headset. - And the only reason we have problems is - we don't realize how incredible you are. - So you are that which is creating this VR simulation with all of its beauty, all of its complexity. - All the complexity is you and you're doing it effortlessly.

adjacency - infinite intelligence - hologram metaphor - your neighbor is your (true) self - Deep Humanity motto - Join together (instead of Join us) - face behind the mask - Reflecting on this, it occurred to me that the Deep Humanity motto of "Join together, NOT join me/us" is deeply connected to what is being discussed in this annotation. - The problem with "joining me" is that it reflects we are still stuck in the ego reification paradigm while "join together" reflects awareness that the boundless intelligence is the true face behind the mask of each different species and each different individual of each species

for - adjacency - infinite intelligence - perspectival knowing - hologram - Donald Hoffman

for - key insight / quote - the reified ego is the root cause of all the problems in the world - we reify because we don't know who we REALLY are - Donald Hoffman - All the egoic stuff that we do causes all the problems in the world because - you don't know who you are. - You're creating this whole thing. - You're not a little player. - You're the inventor of this whole thing. - You have nothing to prove and - you don't need to be better than anybody else. - They're also master creators. - They're creating entire universes that they perceive as well. - And my own take on on this is that - you and I are really the same one reality - just looking at itself through two different headsets, - two different avatars and having a conversation. - And maybe that's what is required for this one infinite intelligence to sort of know itself.

• adjacency - poverty mentality - ego - problems of the world - samsara - nirvana - hologram model - Alan Watts - God playing hide and seek - Donald Hoffman
• When we don't believe we can be this, we limit ourselves
  • That is, we suffer from self-inflicted poverty mentality
• When he says we are the one same reality,
  • he is echoing the common spiritual teaching of the holographic metaphor where
    • the one nameless is distilling itself in so many separate identities to know itself,
  • Similiar to many spiritual teacher's teachings
    • Alan Watts referred to it as God playing Hide and Seek with itself

for - adjacency - perspectival knowing - rendering - learned in child development - language usage - This is an interesting use of the word "render" to demonstrate how even shared human experiences are still uniquely seen from different perspectives - We impute objective reality, for instance of the cup, even though we are each uniquely rendering it in different ways - It is a direct result of our child development in which we learned how to employ words to label such social contexts - We establish rules for word usage at an early age, but we forget the original conditions which gave rise to them - When we remind ourselves of the original motivation, it is a bit of a shock to the system how strange this reality is

eLife assessment

This is a useful study that applies deep transfer learning to assign patient-level disease attributes to single cells of T2D and non-diabetic patients, including obese patients. This analysis identified a single cluster of T2D-associated β-cells; and two subpopulations of obese- β-cells derived from either non-diabetic or T2D donors. The findings were validated at the protein level using immunohistochemistry on islets derived from non-diabetic and T2D organ donors, contributing solid experimental evidence for the computational analyses.

Reviewer #1 (Public review):

In this manuscript, Roy et al. used the previously published deep transfer learning tool, DEGAS, to map disease associations onto single-cell RNA-seq data from bulk expression data. The authors performed independent runs of DEGAS using T2D or obesity status and identified distinct β-cell subpopulations. β-cells with high obese-DEGAS scores contained two subpopulations derived largely from either non-diabetic or T2D donors. Finally, immunostaining using human pancreas sections from healthy and T2D donors validated the heterogeneous expression and depletion of DLK1 in T2D islets.

Strengths:

(1) This meta-analysis of previously published scRNA-seq data uses a deep transfer learning tool.

(2) Identification of novel beta cell subclusters.

(3) Identified a relatively innovative role of DLK1 in T2D disease progression.

Comments on revisions:

All previous concerns have been addressed.

Reviewer #2 (Public review):

Summary:

The manuscript by Gitanjali Roy et al. applies deep transfer learning (DEGAS) to assign patient-level disease attributes (metadata) to single cells of T2D and non-diabetic patients, including obese patients. This led to the identification of a singular cluster of T2D-associated β-cells; and two subpopulations of obese- β-cells derived from either non-diabetic or T2D donors. The objective was to identify novel and established genes implicated in T2D and obesity. Their final goal is to validate their findings at the protein level using immunohistochemistry of pancreas tissue from non-diabetic and T2D organ donors.

Strengths:

This paper is well-written, and the findings are relevant for β-cell heterogeneity in T2D and obesity.

Weaknesses:

The validation they provide is not sufficiently strong: no DLK1 immunohistochemistry is shown of obese patient-derived sections. Additional presumptive relevant candidates from this transcriptomic analysis should be screened for, at the protein level.

Comments on revisions:

The authors have largely addressed my comments. No further experiments are requested.

Author response:

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

Reviewer #1 (Public Review):

In this manuscript, Roy et al. used the previously published deep transfer learning tool, DEGAS, to map disease associations onto single-cell RNA-seq data from bulk expression data. The authors performed independent runs of DEGAS using T2D or obesity status and identified distinct β-cell subpopulations. β-cells with high obese-DEGAS scores contained two subpopulations derived largely from either non-diabetic or T2D donors. Finally, immunostaining using human pancreas sections from healthy and T2D donors validated the heterogeneous expression and depletion of DLK1 in T2D islets.

Strengths:

(1) This meta-analysis of previously published scRNA-seq data using a deep transfer learning tool.

(2) Identification of novel beta cell subclusters.

(3) Identified a relatively innovative role of DLK1 in T2D disease progression.

Thank you for your comments on the strengths of our work.

Weaknesses :

“There is little overlap of the DE list of bulk RNA-seq analysis in Figure 1D and 1E overlap with the DE list of pseudo-bulk RNA-seq analysis of all cells in Figure S2C. “

Thank you for pointing this out. To clarify, we did not perform pseudo-bulk analysis on the scRNAseq data. Instead, we used the Seurat FindClusterMarkers function to identify differentially enriched genes between T2D and ND single cells. Indeed, there are many significant genes in new Fig S2D (original S2C). There is some overlap between those data and the DEGS from bulk RNAseq data in Fig 1D, including IAPP, ENTPD3, and FFAR4. However, the limited overlap supports the notion that improved approaches are necessary to identify candidate DEGs from single cell data, as simply performing a comparison of T2D to ND of all β-cells may miss important genes or include many false positives. We have now added clarification to the text to highlight this point.

The biological meaning of "beta cells had the lowest scores compared to other cell types" is not clear.

The relatively lower T2D-DEGAS scores for beta cells overall compared to all other cell types (alpha cells, acinar cells, etc) likely reflects the fact that in T2D, beta cell-specific genes can be downregulated. This affects the DEGAS model which is reflected in the scores of all cells in the scRNAseq data. By subsetting the beta cells and replotting them on their own, we can analyze the relative differences in DEGAS scores between different subsets of beta cells. We have now amended the text to clarify, as follows:

“We next mapped the T2D-association scores onto the single cells (Fig 3A). β-cells had a wide distribution of scores, possibly reflecting β-cell heterogeneity or altered β-cell gene expression after onset of T2D (Fig 3B).”

The figures and supplemental figures were not cited following the sequence, which makes the manuscript very difficult to read. Some supplemental figures, such as Figures S1C-S1D, S2B-S2E, S3A-S3B, were not cited or mentioned in the text.

We apologize for this oversight and have now amended the text to call out all figures/panels in order of first introduction.

In Figure 7, the current resolution is too low to determine the localization of DLK1.

We have confirmed that in our Adobe Illustrator file, each microscopy panel has a DPI of >600. We have also provided the highest quality TIFF file versions of our figure set. We hope the reviewer will have access to download the high-quality TIFF file for Fig 7 if possible, or the editorial staff can provide it.

As a result of addressing the critiques, we identified CDKN1C as another promising candidate enriched in the β^T2D-DEGAS and β^obese-DEGAS subpopulations of β-cells. We found that CDKN1C is heterogeneously expressed at the protein level in β-cells and that it is increased in T2D in agreement with the DEGAS predictions. We have amended the manuscript to highlight CDKN1C more prominently while still discussing DLK1. DLK1 is very interesting, but exhibits greater donor to donor variability in its alterations in T2D.

Reviewer #2 (Public Review):

Summary:

The manuscript by Gitanjali Roy et al. applies deep transfer learning (DEGAS) to assign patient-level disease attributes (metadata) to single cells of T2D and non-diabetic patients, including obese patients. This led to the identification of a singular cluster of T2D-associated β-cells; and two subpopulations of obese- β-cells derived from either non-diabetic or T2D donors. The objective was to identify novel and established genes implicated in T2D and obesity. Their final goal is to validate their findings at the protein level using immunohistochemistry of pancreas tissue from non-diabetic and T2D organ donors.

Strengths:

This paper is well-written, and the findings are relevant for β-cell heterogeneity in T2D and obesity.

Thank you for your comments on the positive aspects of our work.

Weaknesses:

The validation they provide is not sufficiently strong: no DLK1 immunohistochemistry is shown of obese patient-derived sections.

We have acquired additional FFPE pancreas samples from the Integrated Islet Distribution Program (IIDP) from lean, overweight, and obese humans with and without T2D. We have now stained for CDKN1C and DLK1 in these samples and have integrated the data into Fig 7 and Fig S5.

Because the data with CDKN1C was more striking and consistent with the DEGAS predictions, we have chosen to highlight CDKN1C in the main figure and text. The DLK1 data is still quite interesting, although there is substantial variability between T2D donors when it comes to altered staining intensity. DLK1 presents an interesting challenge, given multiple isoforms and cleavage products, and will require further investigation as the focus of a different manuscript.

Additional presumptive relevant candidates from this transcriptomic analysis should be screened for, at the protein level.

Thank you for this suggestion. We also identified CDKN1C as promising candidate enriched in the β^T2D-DEGAS and β^obese-DEGAS subpopulations of β-cells. We found that CDKN1C is heterogeneously expressed at the protein level in β-cells and that it is increased in T2D in agreement with the DEGAS predictions. We have amended the manuscript to highlight CDKN1C more prominently while still discussing DLK1. DLK1 is very interesting but exhibits greater donor to donor variability in its alterations in T2D.

Reviewer #1 (Recommendations For The Authors):

Please explain and provide the detailed information on what percentage of the DE list of bulk RNA-seq analysis in Figures 1D and 1E overlap with the DE list of pseudo-bulk RNA-seq analysis of all cells in Figure S2C.

Addressed in response to R1 Comment 1.

Please provide the definition of each cluster of UMAP of the merged human islet scRNA-seq data.

In figure panels 2A-B,D-G and 3A, the clusters are now labeled according to the marker genes described in Fig 2C.

The integrative UMAP needs to be included in the main figure.

We have now moved previous Fig S2A and S2B into the main figures as new Fig 2A-B.

All figures and supplemental figures need to be cited following sequence.

Addressed in response to R1 Comment 3.

In Figure 7, high-resolution images are needed to determine the colocalization of INS and DLK1.

Addressed in response to R1 Comment 4.

Reviewer #2 (Recommendations For The Authors):

Results: 124-128: Fig 1H_The error bars seem high, please include whether the boxplots are SEM or SD. Also, more detail on statistics is missing.

Thank you for pointing out the need for clarification here. The whiskers on the box and whiskers plots are not error bars. By default, in geom_boxplot() and stat_boxplot(), the whiskers extend to 1.5 times the interquartile range. The box itself represents 50% of the data, the bottom of the box is the first quartile, the middle horizontal line is the median, and the top line of the box is the third quartile. We have now added a clearer description of this to the figure legend and in the methods section.

The genes shown in Fig 1H were selected because they are found in the T2D Knowledge Portal, illustrating a clear link to T2D. At the T2DKP (https://t2d.hugeamp.org/research.html?pageid=mccarthy_t2d_247), PAX4 and APOE are listed as causal, SLC2A2 has strong evidence, and CYTIP has a linked SNP. This is now discussed in the results section before the Fig 1H callout. These genes are significantly differentially expressed using edgeR in panel 1D with FDR<0.05. The individual data points for each human are shown.

Figure 6: In general, the representation of the data is quite misleading. It would be nice to have an alternative way of presenting the data, especially when comparing beta-obese differentially expressed genes and pathways and T2D beta obese. Maybe an additional Venn diagram can help. Also, it would be nice to compare data from T2D beta nonobese to ND beta obese, especially given how the story is presented in the paper.

Thank you for pointing out this clarity issue. We agree that additional alternate ways to present the data would be helpful. When we performed DEGAS using BMI as the disease feature we noted two major and one minor clusters of high-scoring cells in Fig 6A .

Author response image 1.

Author response image 2.<br />

This contrasted with the score map when we ran DEGAS with T2D as the disease feature

The main difference seems to be the low scoring β^T2D-DEGAS cluster is different from the low β^obese-DEGAS cluster.

Therefore, we could not easily apply thresholding to the β^obese-DEGAS scores, so instead we subsetted them for comparison. It was also apparent from the metadata that single cells from the left-hand side of the β-cell cluster came from donors that had T2D.

To clarify these points and address the reviewer’s concerns, we have added a comparison of the DEGs identified for β^T2D-DEGAS high vs. low and T2D-β^obese-DEGAS vs ND-β^obese-DEGAS in Fig S4J, also shown below. DLK1 and CDKNC1C fall within the intersection, in addition to being two of the most enriched candidates in each DEGAS run (Fig 4C and Fig 6D).

220-222: Figure 7C_ Is one of the nondiabetic beta samples obese? If so, please clearly label it; if not, that info is missing. One would expect that the DLK1 expression in ND obese beta cells resembles the T2D beta cell and not ND non-obese beta cells. That's a big point of this entire work, and experimentally missing. Additional candidate proteins should be checked.

We have amended the entire Fig 7 to include more data for DLK1 staining as well as adding staining for CDKN1C. We also used CellProfiler to quantify the intensity distribution of DLK1 staining in β-cells and overall found that our initial conclusions were not supported when considering an increased sample size. DLK1 expression is heterogeneous both within and between donors. While we have data from T2D donors that shows DLK1 is lost, other T2D samples indicate that DLK1 is not always lost. At least in the current sample set we have analyzed, we cannot conclude that there is a clear correlation between diabetes or BMI for DLK1. Why DLK1 labels some β-cells and not others and what the role of this subpopulation is an open question.

Alternatively, we greatly appreciate the reviewer’s suggestion to validate additional candidates, as this led us to CDKN1C. In new Fig 7E-H we now show that CDKN1C is increased in T2D β-cells, in agreement with the DEGAS predictions.

This work shows that machine learning approaches are powerful for identifying potential candidates, but it also highlights the need for these predictions to be validated at the protein level in human samples.

Discussion: Based on lack of supporting IHC data, this is an overstatement:

“DLK1 expression highly overlapped with high scoring βT2D DEGAS cells (Figure 7A) and with T2D βobese-DEGAS cells (Figure 7B). DLK1 immunostaining primarily colocalized with β-cells in non-diabetic human pancreas (Figure 7C). DLK1 showed heterogeneous expression within islets and between islets within the same pancreas section, wherein some islets had DLK1/INS co-staining in most β-cells and other islets had only a few DLK1+ β-cells. In the T2D pancreas, DLK1 staining was much less intense and in fewer β-cells, yet DLK1+/INS+ cells were observed (Figure 7C). This contrasts with the relatively higher DLK1 gene expression seen in the β-cells from the βT2D-DEGAS and T2D-βobese-DEGAS subpopulations (Figure 4D & 6C) as highlighted in Figure 7A,B. which were up- or down-regulated in subpopulations of β-cells identified by DEGAS, and to validate our findings at the protein level using immunohistochemistry of pancreas tissue from non-diabetic and T2D organ donors.”

This part was at the very end of the last results subsection. This section has been largely rewritten to better describe the new figure and the language has been tempered to not overinterpret the data shown.

“Our current findings applying DEGAS to islet data have implications for β-cell heterogeneity in T2D and obesity. The abundance of T2D-related factors and functional β-cell genes in our analysis validates applying DEGAS to islet data to identify disease-associated phenotypes and increase confidence in the novel candidate.”

This part was found at the end of the Background section. We have removed the second sentence to temper the language.

eLife Assessment

This is an important study that takes a key step towards understanding developmental disorders linked to mutations in the O-GlcNAc transferase enzyme by generating a mouse model harboring the C921Y mutation. The study thoroughly examines behavioral and anatomical differences in these mice and finds behavioral hyperactivity and learning/memory deficits, as well as phenotypic differences in skull and brain formation. However, the experimental evidence is incomplete owing to discrepancy in OGT protein/RNA levels in the C921Y mutant mice in this paper and the previous paper ("Neurodevelopmental defects in a mouse model of O-GlcNAc transferase intellectual disability "). This line of research will benefit from investigation of the differences in associated glycoproteins and mechanistic insights. This study will be of interest to those studying neurodevelopment, learning and behavior, or associated brain mechanisms.

Reviewer #1 (Public review):

This study established a C921Y OGT-ID mouse model, systematically demonstrating in mammals the pathological link between O-GlcNAc metabolic imbalance and neurodevelopmental disorders (cortical malformation, microcephaly) as well as behavioral abnormalities (hyperactivity, impulsivity, learning/memory deficits). However, critical flaws in the current findings require resolution to ensure scientific rigor.

The most concerning finding appears in Figure S12. While Supplementary Figure S12 demonstrates decreased OGA expression without significant OGT level changes in C921Y mutants via Western blot/qPCR, previous reports (Florence Authier, et al., Dis Model Mech. 2023) described OGT downregulation in Western blot and an increase in qPCR in the same models. The opposite OGT expression outcomes in supposedly identical mouse models directly challenge the model's reliability. This discrepancy raises serious concerns about either the experimental execution or the interpretation of results. The authors must revalidate the data with rigorous controls or provide a molecular biology-based explanation.

A few additional comments to the author may be helpful to improve the study.

Major

(1) While this study systematically validated multi-dimensional phenotypes (including neuroanatomical abnormalities and behavioral deficits) in OGT C921Y mutant mice, there is a lack of relevant mechanisms and intervention experiments. For example, the absence of targeted intervention studies on key signaling pathways prevents verification of whether proteomics-identified molecular changes directly drive phenotypic manifestations.

(2) Although MRI detected nodular dysplasia and heterotopia in the cingulate cortex, the cellular basis remains undefined. Spatiotemporal immunofluorescence analysis using neuronal (NeuN), astrocytic (GFAP), and synaptic (Synaptophysin) markers is recommended to identify affected cell populations (e.g., radial glial migration defects or intermediate progenitor differentiation abnormalities).

(3) While proteomics revealed dysregulation in pathways including Wnt/β-catenin and mTOR signaling, two critical issues remain unresolved: a) O-GlcNAc glycoproteomic alterations remain unexamined; b) The causal relationship between pathway changes and O-GlcNAc imbalance lacks validation. It is recommended to use co-immunoprecipitation or glycosylation sequencing to confirm whether the relevant proteins undergo O-GlcNAc modification changes, identify specific modification sites, and verify their interactions with OGT.

(4) Given that OGT-ID neuropathology likely originates embryonically, we recommend serial analyses from E14.5 to P7 to examine cellular dynamics during critical corticogenesis phases.

(5) The interpretation of Figure 8A constitutes overinterpretation. Current data fail to conclusively demonstrate impairment of OGT's protein interaction network and lack direct evidence supporting the proposed mechanisms of HCF1 misprocessing or OGA loss.

Reviewer #2 (Public review):

Summary:

The authors are trying to understand why certain mutants of O-GlcNAc transferase (OGT) appear to cause developmental disorders in humans. As an important step towards that goal, the authors generated a mouse model with one of these mutations that disrupts OGT activity. They then go on to test these mice for behavioral differences, finding that the mutant mice exhibit some signs of hyperactivity and differences in learning and memory. They then examine alterations to the structure of the brain and skull, and again find changes in the mutant mice that have been associated with developmental disorders. Finally, they identify proteins that are up- or down-regulated between the two mice as potential mechanisms to explain the observations.

Strengths:

The major strength of this manuscript is the creation of this mouse model, as a key step in beginning to understand how OGT mutants cause developmental disorders. This line will prove important for not only the authors but other investigators as well, enabling the testing of various hypotheses and potentially treatments. The experiments are also rigorously performed, and the conclusions are well supported by the data.

Weaknesses:

The only weakness identified is a lack of mechanistic insight. However, this certainly may come in the future through more targeted experimentation using this mouse model.

Author response:

Reviewer #1 (Public review):

This study established a C921Y OGT-ID mouse model, systematically demonstrating in mammals the pathological link between O-GlcNAc metabolic imbalance and neurodevelopmental disorders (cortical malformation, microcephaly) as well as behavioral abnormalities (hyperactivity, impulsivity, learning/memory deficits). However, critical flaws in the current findings require resolution to ensure scientific rigor.

The most concerning finding appears in Figure S12. While Supplementary Figure S12 demonstrates decreased OGA expression without significant OGT level changes in C921Y mutants via Western blot/qPCR, previous reports (Florence Authier, et al., Dis Model Mech. 2023) described OGT downregulation in Western blot and an increase in qPCR in the same models. The opposite OGT expression outcomes in supposedly identical mouse models directly challenge the model's reliability. This discrepancy raises serious concerns about either the experimental execution or the interpretation of results. The authors must revalidate the data with rigorous controls or provide a molecular biology-based explanation.

The referee’s assessment is based on a misunderstanding – these are certainly not the same experiment repeated twice with different answers. In the previous report of the OGT-C921Y mutant mice (Florence Authier, et al., Dis Model Mech. 2023), OGT and OGA mRNA/protein expression have been assessed in total brain protein extract from 3 months old male mice. In that study we observed a significant reduction in OGT protein levels while OGT mRNA levels were significantly increased in the mutant compared to WT controls. However, in our the current study (Figure S12), OGA and OGT mRNA/protein expression have been a) restricted to the pre-frontal cortex and b) are from 4 months old male mice, which does not allow a direct comparison of the two studies. In the pre-frontal cortex, OGT protein levels are not changed while OGT mRNA levels are increased (similarly to the total brain data), albeit not significantly. The different outcomes of OGT protein levels in both total brain and prefrontal cortex could suggest regional differences in OGT protein levels/stability as OGT mRNA levels are increased in both cases. Three other brain regions (hippocampus, striatum and cerebellum) have now also been assessed for OGT mRNA/protein expression, supporting such regional differences in OGT protein levels and these data will be included in the new version of the manuscript.

A few additional comments to the author may be helpful to improve the study.

Major

(1) While this study systematically validated multi-dimensional phenotypes (including neuroanatomical abnormalities and behavioral deficits) in OGT C921Y mutant mice, there is a lack of relevant mechanisms and intervention experiments. For example, the absence of targeted intervention studies on key signaling pathways prevents verification of whether proteomics-identified molecular changes directly drive phenotypic manifestations.

We agree with the referee that these experiments would further strenghten the work. They would, however, result in a 1-5 year delay in sharing this work with the scientific and patient communities. We will continue to work along these lines and report separately in the future.

(2) Although MRI detected nodular dysplasia and heterotopia in the cingulate cortex, the cellular basis remains undefined. Spatiotemporal immunofluorescence analysis using neuronal (NeuN), astrocytic (GFAP), and synaptic (Synaptophysin) markers is recommended to identify affected cell populations (e.g., radial glial migration defects or intermediate progenitor differentiation abnormalities).

We are currently performing these experiments so that they can be included in the version of record of this manuscript.

(3) While proteomics revealed dysregulation in pathways including Wnt/β-catenin and mTOR signaling, two critical issues remain unresolved: a) O-GlcNAc glycoproteomic alterations remain unexamined; b) The causal relationship between pathway changes and O-GlcNAc imbalance lacks validation. It is recommended to use co-immunoprecipitation or glycosylation sequencing to confirm whether the relevant proteins undergo O-GlcNAc modification changes, identify specific modification sites, and verify their interactions with OGT.

We agree with the referee that these experiments would further strenghten the work and will perform further experiments to explore whether these pathways are functionally affected. However, it is important to note that the inference that these proteins must themselves be O-GlcNAc modified is incorrect – indeed, O-GlcNAcylation of unknown protein kinase X, E3 ligase/DUB, Y or transcription factor Z could indirectly affect these pathways/proteins.

(4) Given that OGT-ID neuropathology likely originates embryonically, we recommend serial analyses from E14.5 to P7 to examine cellular dynamics during critical corticogenesis phases.

We agree with the referee that these experiments would further strenghten the work. They would, however, result in a significant delay in sharing this work with the scientific and patient communities. We will continue to work along these lines and report separately in the future.

(5) The interpretation of Figure 8A constitutes overinterpretation. Current data fail to conclusively demonstrate impairment of OGT's protein interaction network and lack direct evidence supporting the proposed mechanisms of HCF1 misprocessing or OGA loss.

For clarity, we will remove panel A from Figure 8 in the version of record – this panel was only ever meant to represent a priori hypotheses for OGT-CDG mechanisms, none of which have been either excluded or confirmed.

Reviewer #2 (Public review):

Summary:

The authors are trying to understand why certain mutants of O-GlcNAc transferase (OGT) appear to cause developmental disorders in humans. As an important step towards that goal, the authors generated a mouse model with one of these mutations that disrupts OGT activity. They then go on to test these mice for behavioral differences, finding that the mutant mice exhibit some signs of hyperactivity and differences in learning and memory. They then examine alterations to the structure of the brain and skull, and again find changes in the mutant mice that have been associated with developmental disorders. Finally, they identify proteins that are up- or down-regulated between the two mice as potential mechanisms to explain the observations.

Strengths:

The major strength of this manuscript is the creation of this mouse model, as a key step in beginning to understand how OGT mutants cause developmental disorders. This line will prove important for not only the authors but other investigators as well, enabling the testing of various hypotheses and potentially treatments. The experiments are also rigorously performed, and the conclusions are well supported by the data.

Weaknesses:

The only weakness identified is a lack of mechanistic insight. However, this certainly may come in the future through more targeted experimentation using this mouse model.

We agree with the referee that these experiments would further strenghten the work. They would, however, result in a 1-5 year delay in sharing this work with the scientific and patient communities. We will continue to work along these lines and report separately in the future.

eLife Assessment

This useful study uses fiber photometry, implantable lenses, and optogenetics to show that a subset of subthalamic nucleus neurons is active during movement, and that active but not passive avoidance depends in part on STN projections to substantia nigra. The strength of the evidence for these claims is solid, whereas evidence supporting the claims that STN is involved in cautious responding or the speed of avoidance is incomplete. This paper will be of interest to basic and applied behavioural neuroscientists working on avoidance if suitably streamlined to support the strongest claims.

Reviewer #1 (Public review):

Summary:

The manuscript presents a robust set of experiments that provide new fundamental insights into the role of STN neurons during active and passive avoidance tasks. These forms of avoidance have received comparatively less attention in the literature than the more extensively studied escape or freezing responses, despite being extremely relevant to human behaviour and more strongly influenced by cognitive control.

Strengths:

Understanding the neural infrastructure supporting avoidance behaviour would be a fundamental milestone in neuroscience. The authors employ sophisticated methods, including calcium imaging and optogenetics, to delineate the functions of STN neurons during avoidance behaviours. The work is extremely thorough, and the evidence presented is compelling. Experiments are carefully constructed, well-controlled, and the statistical analyses are appropriate.

Points for Authors' Consideration:

(1) Motoric role of STN:<br /> The authors interpret their findings within the context of active avoidance, a cognitively demanding process. An alternative interpretation is that STN activation enhances global motoric tone, facilitating general movement rather than specifically encoding cautious avoidance. Experimentally, this could be evaluated by examining STN-induced motoric tone in non-avoidance contexts, such as open field tests with bilateral stimulations. Alternatively, or additionally, the authors could explicitly discuss evidence for and against the possibility that increased motoric tone may account for aspects of the observed behaviours.

(2) Temporal Dynamics in Calcium Imaging (AA2 vs. AA1):<br /> Based on previous work by this group, a delay (~1-2 sec) in neuronal response onset was anticipated in AA2 compared to AA1. Although a delay in peak response is observed, there is no clear evidence of a significant delay in response onset or changes in slope of neural activity. The authors could quantify calcium onset latencies and slopes and statistically compare these parameters across conditions.

(3) Speed Differences (AA2 vs. AA1):<br /> Given the increased latency in AA2, and based on previous work from the group, one would expect faster movements following initiation. However, such differences are not evident in the presented data. The authors might want to discuss the absence of an expected speed increase and clarify whether this absence is consistent with previous findings.

(4) Behavioural Differences Across Neuronal Classes (Figure 7):<br /> The manuscript currently does not compare responses of neuronal classes I, II, and III between AA1 and AA2 conditions separately or provide information regarding their activity during AA3.

(5) Streamlining Narrative and Figures:<br /> Given the extensive amount of material presented, the manuscript and figures would benefit from streamlining. Many data points and graphs could be moved to supplementary materials without affecting the core interpretation and simplifying the reading of the work by a non-expert audience. Similarly, the main text could be refined to more clearly emphasise the key findings, which would improve both readability and impact. At the same time, certain aspects would benefit from additional clarification. For example, it would be helpful to explain the key features of the AA1-AA3 tasks at the point of introduction, rather than referring readers to previous literature. Overall, enhancing clarity and accessibility would serve the authors well and broaden the impact of the work.

Reviewer #2 (Public review):

Summary:

Zhou, Sajid et al. present a study investigating the STN involvement in signaled movement. They use fiber photometry, implantable lenses, and optogenetics during active avoidance experiments to evaluate this. The data are useful for the scientific community, and the overall evidence for their claims is solid, but many aspects of the findings are confusing and seemingly contradictory. For example, STN activity increases with contraversive turning in the fiber photometry experiments, but optogenetic stimulation of the STN evokes ipsiversive turning. While the authors present a huge collection of data, it is somewhat difficult to extract the key information and the meaningful implications resulting from this data.

Strengths:

The study is comprehensive in using many techniques, stimulation powers, frequencies, and configurations.

Weaknesses:

Here are the specific weaknesses of the paper.

(1) Vglut2 isn't a very selective promoter for the STN. Did the authors verify every injection across brain slices to ensure the para-subthalamic nucleus, thalamus, lateral hypothalamus, and other Vglut2-positive structures were never infected?

(2) The authors say in the methods that the high vs low power laser activation for optogenetic experiments was defined by the behavioral output. This is misleading, and the high vs low power should be objectively stated and the behavioral results divided according to the power used, not according to the behavioral outcome.

(3) In the fiber photometry experiments exposing mice to the range of tones, it is impossible to separate the STN response to the tone from the STN response to the movement evoked by the tone. The authors should expose the mouse to the tones in a condition that prevents movement, such as anesthetized or restrained, to separate out the two components.

(4) The claim 'STN activation is ideally suited to drive active avoids' needs more explanation. This claim comes after the fiber photometry experiments during active avoidance tasks, so there has been no causality established yet.

(5) The statistical comparisons in Figure 7E need some justification and/or clarification. The 9 neuron types are originally categorized based on their response during avoids, then statistics are run showing that they respond differently during avoids. It is no surprise that they would have significantly different responses, since that is how they were classified in the first place. The authors must explain this further and show that this is not a case of circular reasoning.

(6) The authors show that neurons that have strong responses to orientation show reduced activity during avoidance. What are the implications of this? The author should explain why this is interesting and important.

(7) It is not clear which conditions each mouse experienced in which order. This is critical to the interpretation of Figure 9 and the reduction of passive avoids during STN stimulation. Did these mice have the CS1+STN stimulation pairing or the STN+US pairing prior to this experiment? If they did, the stimulation of the STN could be strongly associated with either punishment or with the CS1 that predicts punishment. If that is the case, stimulating the STN during CS2 could be like presenting CS1+CS2 at the same time and could be confusing.

(8) The experiments in Figure 10 are used to say that STN stimulation is not aversive, but they only show that STN stimulation cannot be used as punishment in place of a shock. This doesn't mean that it is not aversive; it just means it is not as aversive as a shock. The authors should do a simpler aversion test, such as conditioned or real-time place preference, to claim that STN stimulation is not aversive. This is particularly surprising as previous work (Serra et al., 2023) does show that STN stimulation is aversive.

(9) In the discussion, the idea that the STN encodes 'moving away' from contralateral space is pretty vague and unsupported. It is puzzling that the STN activates more strongly to contraversive turns, but when stimulated, it evokes ipsiversive turns; however, it seems a stretch to speculate that this is related to avoidance. In the last experiments of the paper, the axons from the STN to the GPe and to the midbrain are selectively stimulated. Do these evoke ipsiversive turns similarly?

(10) In the discussion, the authors claim that the STN is essential for modulating action timing in response to demands, but their data really only show this in one direction. The STN stimulation reliably increases the speed of response in all conditions (except maximum speed conditions such as escapes). It seems to be over-interpreting the data to say this is an inability to modulate the speed of the task, especially as clear learning and speed modulation do occur under STN lesion conditions, as shown in Figure 12B. The mice learn to avoid and increase their latency in AA2 vs AA1, though the overall avoids and latency are different from controls. The more parsimonious conclusion would be that STN stimulation biases movement speed (increasing it) and that this is true in many different conditions.

(11) In the discussion, the authors claim that the STN projections to the midbrain tegmentum directly affect the active avoidance behavior, while the STN projections to the SNr do not affect it. This seems counter to their results, which show STN projections to either area can alter active avoidance behavior. What is the laser power used in these terminal experiments? If it is high (3mW), the authors may be causing antidromic action potentials in the STN somas, resulting in glutamate release in many brain areas, even when terminals are only stimulated in one area. The authors could use low (0.25mW) laser power in the terminals to reduce the chance of antidromic activation and spatially restrict the optical stimulation.

(12) Was normality tested for data prior to statistical testing?

(13) Why are there no error bars on Figure 5B, black circles and orange triangles?

Reviewer #3 (Public review):

Summary:

The authors use calcium recordings from STN to measure STN activity during spontaneous movement and in a multi-stage avoidance paradigm. They also use optogenetic excitation, optogenetic inhibition, and lesion approaches to increase or decrease the activity of STN during the avoidance paradigm. The paper reports a large amount of data and makes many claims, some seem well supported to this Reviewer, others not so much.

Strengths:

Well-supported claims include data showing that during spontaneous movements, especially contraversive ones, STN calcium activity is increased using bulk photometry measurements. Single-cell measures back this claim but also show that it is only a modest minority of STN cells that respond strongly, with most showing no response during movement, and a similar number showing smaller inhibitions during movement.

Similar data during cued active avoidance procedures show that STN calcium activity sharply increases in response to auditory cues, and during cued movements to avoid a footshock. Optogenetic and lesion experiments are consistent with an important role for STN in generating cue-evoked avoidance. And a strength of these results is that multiple bi-directional approaches were used.

Weaknesses:

I found the experimental design and presentation convoluted and the results over-interpreted.

(1) I really don't understand or accept this idea that delayed movement is necessarily indicative of cautious movements. Is the distribution of responses multi-modal in a way that might support this idea, or do the authors simply take a normal distribution and assert that the slower responses represent 'caution'? Even if responses are multi-modal and clearly distinguished by 'type', why should readers think this that delayed responses imply cautious responding instead of say: habituation or sensitization to cue/shock, variability in attention, motivation, or stress; or merely uncertainty which seems plausible given what I understand of the task design where the same mice are repeatedly tested in changing conditions. This relates to a major claim (i.e., in the work's title).

(2) Related to the last, I'm struggling to understand the rationale for dividing cells into 'types' based the their physiological responses in some experiments (e.g., Figure 7).

(3) The description and discussion of orienting head movements were not well supported, but were much discussed in the avoidance datasets. The initial speed peaks to cue seem to be the supporting data upon which these claims rest, but nothing here suggests head movement or orientation responses.

(4) Similar to the last, the authors note in several places, including abstract, the importance of STN in response timing, i.e., particularly when there must be careful or precise timing, but I don't think their data or task design provides a strong basis for this claim.

(5) I think that other reports show that STN calcium activity is recruited by inescapable foot shock as well. What do these authors see? Is shock, independent of movement, contributing to sharp signals during escapes?

(6) In particular, and related to the last point, the following work is very relevant and should be cited: https://elifesciences.org/reviewed-preprints/104643#tab-content. Note that the focus of this other paper is on a subset of VGLUT2+ Tac1 neurons in paraSTN, but using VGLUT2-Cre to target STN will target both STN and paraSTN.

(7) In multiple other instances, claims that were more tangential to the main claims were made without clearly supporting data or statistics. E.g., claim that STN activation is related to translational more than rotational movement; claim that GCaMP and movement responses to auditory cues were small; claims that 'some animals' responded differently without showing individual data.

(8) In several figures, the number of subjects used was not described. This is necessary. Also necessary is some assessment of the variability across subjects. The only measure of error shown in many figures relates to trial-to-trial or event variability, which is minimal because, in many cases, it appears that hundreds of trials may have been averaged per animal, but this doesn't provide a strong view of biological variability. When bar/line plots are used to display data, I recommend showing individual animals where feasible.

(9) Can the authors consider the extent to which calcium imaging may be better suited to identify increases compared to decreases and how this may affect the results, particularly related to the GRIN data when similar numbers of cells show responses in both directions (e.g., Figure 3)?

(10) Raw example traces are not provided.

(11) The timeline of the spontaneous movement and avoidance sessions was not clear, nor was the number of events or sessions per animal nor how this was set. It is not clear if there was pre-training or habituation, if many or variable sessions were combined per animal, or what the time gaps between sessions were, or if or how any of these parameters might influence interpretation of the results.

(12) It is not clear if or how the spread of expression outside of the target STN was evaluated, and if or how many mice were excluded due to spread or fiber placements.

struggling makes the topic more understandable in the end.

AI dulls down the information to make it understandable, but it'll make it more difficult to master the topic on your own.

But if i use it as an editor, won't it get dim down the parts that make my writing human?

it would be interesting to see how people use this high level answering to try and teach themselves a new subject, without knowing anything about the topic beforehand. Would AI be able to teach that like a professor would?

this reminds me of harry harlows monkey experiment where the monkeys had a wired mother that would give them the food they needed but no comfort and then they had a cloth covered plush? that was warm and soft and gave them some comfort. the monkeys ended up prefering the cloth covered plush over the wired mother that gave them milk. I believe some of the monkeys were in emotional distress because of the lack of nuturing

Test

This show, of the two examples, resonated with me the most.

here's another comment

*

Note, that is the same as a Backdrop in Scratch for those who think in that language.

Capitalism * Migrants have fewer protections under labor law and are discouraged from joining a union * migrants have a great wage disparity because they are easily exploitative labor * Language barriers, knowledge gap of legal process, and paying for a lawyer make it hard to have equal access to the law

Race and Gender * Racial stereotype that women have the "maternal instinct" that keeps them from opportunities for other jobs (meaning people do not offer them) * There was a lack of mobility because of the socialization of women and indigenous people to do a certain kind of labor * minority groups are faced with the challenge of mobilization in a system set up against them

Push factor

Civilizing indigenous groups

These women are also finding these informal areas of learning

Perhaps a blueprint for what woukd eventually happen in america?

jello

I agree that technology is growing rapidly and is essential in our world today.

Collectability in typewriters is different for almost everyone. I like mid-century standards, some only like pre-1900 machines, some red typewriters, some toy typewriters, some less common typefaces, and still others prefer plastic 70s portables. Some treat them like Pokémon and "gotta catch them all".

Typewriters as a whole are all "collectibles"... What is your specific definition and criteria (value, rarity, popularity, etc.)?

In aggregate, knowledgeable pricing may help you determine the most collectible ranking them by most expensive. But by this ranking there aren't many of us who can buy even a single Sholes and Glidden or collect the typewriters of famous authors like Steve Soboroff.

ETC Magazine did a rarity versus desirability survey a while back of some serious collectors: https://www.antikeychop.com/mostwantedtypewriters

Interestingly, on this list you won't find many of the most collected typewriters out there as ranked by general "popularity" including machines like the Hermes 3000 or the Olympia SM3.

The Typewriter Database also has some data (albeit skewed) of the most "popular" machines ranked based on how many examples have been uploaded by collectors: https://typewriterdatabase.com/popular.0.typewriter-models

All these rankings are highly subjective though, so, again, you should figure out what's most interesting to you and create your collection from there. Figuring this out is half the fun of doing this as a hobby.

reply to u/WRSD605 at https://old.reddit.com/r/typewriters/comments/1n6nhts/remington_16/

I believe that this practice is great, because it will give for accuarate unbiased results.

for - youtube - Just have a think - new paper - new metric for measuring emissions - ERF - to - paper - Increased transparency in accounting conventions could benefit climate policy - https://hyp.is/CUcbhF2TEfCn1ieAeq73JA/iopscience.iop.org/article/10.1088/1748-9326/adb7f2 - climate crisis - carbon emissions - agriculture has the highest of all - AgroSphere Technologies - cite this paper

for - AgroSphere Technology key research paper - carbon emissions - paper claims agriculture is the highest summary - The paper cited here is very important for AgroSphere Technology because - It shows how critical a role regenerative agriculture plays in mitigating the climate crisis - The claim of the paper is that carbon emissions from Agriculture are the biggest emissions of all

The ability for students to follow our instructions and complete assignments is, clearly, one of the most important aspects of our jobs. Needing to make sure that our instructions and direction is clear and concise is super important because if its not clear they won't do well on the assignments and that is not the goal.

These registers are all very important for teachers to have and to know about how to swap between each of them as well as instances in which we would have to use each of them. For example, using a casual register could be expected to be used before class starts, maybe after a lesson is completed, etc. Formal is for when we are teaching a lesson or potentially when we are disciplining a student. Urgent is, clearly, for when there is a life or death situation happening or something of a high caliber. Fire, fire drill, physical fight, etc.

I think this is something important to think about because as students thinking about how we're going to handle our future students when things start to get off the rail is something we don't often think about at the front of our minds.

What about professional athletes? They are making quite a bit of profit from their sports. Does this mean that what they are doing is not play? I guess this goes back to the author's previously established idea that play is completely voluntary. Once it becomes a form of work, I suppose, it can no longer be called play.

Maybe to focus on

eLife Assessment

This study demonstrates the potential role of 17α-estradiol in modulating neuronal gene expression in the aged hypothalamus of male rats, identifying key pathways and neuron subtypes affected by the drug. While the findings are useful and provide a foundation for future research, the strength of supporting evidence is incomplete due to the lack of female comparison, a young male control group, unclear link to 17α-estradiol lifespan extension in rats, and insufficient analysis of glial cells and cellular stress in CRH neurons.

Reviewer #1 (Public review):

Summary:

Previous studies have shown that treatment with 17α-estradiol (a stereoisomer of the 17β-estradiol) extends lifespan in male mice but not in females. The current study by Li et al, aimed to identify cell-specific clusters and populations in the hypothalamus of aged male rats treated with 17α-estradiol (treated for 6 months). This study identifies genes and pathways affected by 17α-estradiol in the aged hypothalamus.

Strengths:

Using single-nucleus transcriptomic sequencing (snRNA-seq) on hypothalamus from aged male rats treated with 17α-estradiol they show that 17α-estradiol significantly attenuated age-related increases in cellular metabolism, stress, and decreased synaptic activity in neurons.

Moreover, sc-analysis identified GnRH as one of the key mediators of 17α-estradiol's effects on energy homeostasis. Furthermore, they show that CRH neurons exhibited a senescent phenotype, suggesting a potential side effect of the 17α-estradiol. These conclusions are supported by supervised clustering by neuropeptides, hormones, and their receptors.

Weaknesses:

However, the study has several limitations that reduce the strength of the key claims in the manuscript. In particular:

(1) The study focused only on males and did not include comparisons with females. However, previous studies have shown that 17α-estradiol extends lifespan in a sex-specific manner in mice, affecting males but not females. Without the comparison with the female data, it's difficult to assess its relevance to the lifespan.

(2) Its not known whether 17α-estradiol leads to lifespan extension in male rats similar to male mice. Therefore, it is not possible to conclude that the observed effects in the hypothalamus, are linked to the lifespan extension. The manuscript cited in the introduction does not include lifespan data on rats.

(3) The effect of 17α-estradiol on non-neuronal cells such as microglia and astrocytes is not well described (Fig.1). Previous studies demonstrated that 17α-estradiol reduces microgliosis and astrogliosis in the hypothalamus of aged male mice. Current data suggest that the proportion of oligo, and microglia were increased by the drug treatment, while the proportions of astrocytes were decreased. These data might suggest possible species differences, differences in the treatment regimen, or differences in drug efficiency. This has to be discussed.

A more detailed analysis of glial cell types within the hypothalamus in response to drug should be provided.

(4) The conclusion that CRH neurons are going into senescence is not clearly supported by the data. A more detailed analysis of the hypothalamus such as histological examination to assess cellular senescence markers in CRH neurons, is needed to support this claim.

Revised submission:

Some of the concerns were addressed in this revised version, and the authors responded and addressed study design limitations in both sexes/ages.

However, there are still some concerns that were not sufficiently addressed:<br /> While the term "senescent" was changed to "stressed," some histological/ cellular validation of this phenotype is still needed.

Some discussion on the sex-specific effects of 17α-estradiol in the hypothalamus is still required. Previous studies in mice demonstrated that 17α-estradiol reduced hypothalamic microgliosis and astrogliosis in male but not female UM-HET3 mice.

Additionally, the provided analysis on astrocytes and microglia is superficial.

Reviewer #2 (Public review):

Summary:

Li et al. investigated the potential anti-ageing role of 17α-Estradiol on the hypothalamus of aged rats. To achieve this, they employed a very sophisticated method for single-cell genomic analysis that allowed them to analyze effects on various groups of neurons and non-neuronal cells. They were able to sub-categorize neurons according to their capacity to produce specific neurotransmitters, receptors, or hormones. They found that 17α-Estradiol treatment led to an improvement in several factors related to metabolism and synaptic transmission by bringing the expression levels of many of the genes of these pathways closer or to the same levels to those of young rats, reversing the ageing effect. Interestingly, among all neuronal groups, the proportion of Oxytocin-expressing neurons seems to be the one most significantly changing after treatment with 17α-Estradiol, suggesting an important role of these neurons on mediating its anti-ageing effects. This was also supported by an increase in circulating levels of oxytocin. It was also found that gene expression of corticotropin-releasing hormone neurons was significantly impacted by 17α-Estradiol even though it was not different between aged and young rats, suggesting that these neurons could be responsible for side effects related to this treatment. This article revealed some potential targets that should be further investigated in future studies regarding the role of 17α-Estradiol treatment in aged males.

Strengths:

• The single nucleus mRNA sequencing is a very powerful method for gene expression analysis and clustering. The supervised clustering of neurons was very helpful in revealing otherwise invisible differences between neuronal groups and helped identify specific neuronal populations as targets.

• There is a variety of functions used that allowed the differential analysis of a very complex type of data. This led to a better comparison between the different groups in many levels.

• There were some physiological parameters measured such as circulating hormone levels that helped the interpretation of the effects of the changes in hypothalamic gene expression.

Weaknesses:

• One main control group is missing from the study, the young males treated with 17α-Estradiol.

• Even though the technical approach is a sophisticated one, analyzing the whole rat hypothalamus instead of specific nuclei or subregions makes the study weaker.

• Although the authors claim to have several findings, the data fail to support these claims.

• The study is about improving ageing but no physiological data from the study demonstrated such claim with the exception of the testes histology which was not properly analyzed and was not even significantly different between the groups.

• Overall, the study remains descriptive with no physiological data to demonstrate that any of the effects on hypothalamic gene expression is related to metabolic, synaptic or other function.

Comments on revisions:

The authors revised part of the manuscript to address some of the reviewers' comments. This improved the language and the text flow to a certain extent. They also added an additional analysis including glial cells. However, they failed to address the main weaknesses brought up by the reviewers and did not add any experimental demonstration of their claims on lifespan expansion induced by 17α-estradiol in rats (the cited study does not include lifespan in rats). In addition, they insisted i keeping parts in the discussion that are not directly linked to any of the papers' findings.

Author response:

The following is the authors’ response to the previous reviews

Reviewer #1 (Public Review):

Summary:

Previous studies have shown that treatment with 17α-estradiol (a stereoisomer of the 17β-estradiol) extends lifespan in male mice but not in females. The current study by Li et al, aimed to identify cell-specific clusters and populations in the hypothalamus of aged male rats treated with 17α-estradiol (treated for 6 months). This study identifies genes and pathways affected by 17α-estradiol in the aged hypothalamus.

Strengths:

Using single-nucleus transcriptomic sequencing (snRNA-seq) on the hypothalamus from aged male rats treated with 17α-estradiol they show that 17α-estradiol significantly attenuated age-related increases in cellular metabolism, stress, and decreased synaptic activity in neurons.

Thanks.

Moreover, sc-analysis identified GnRH as one of the key mediators of 17α-estradiol's effects on energy homeostasis. Furthermore, they show that CRH neurons exhibited a senescent phenotype, suggesting a potential side effect of the 17α-estradiol. These conclusions are supported by supervised clustering by neuropeptides, hormones, and their receptors.

Thanks.

Weaknesses:

However, the study has several limitations that reduce the strength of the key claims in the manuscript. In particular:

(1) The study focused only on males and did not include comparisons with females. However, previous studies have shown that 17α-estradiol extends lifespan in a sex-specific manner in mice, affecting males but not females. Without the comparison with the female data, it's difficult to assess its relevance to the lifespan.

This study was originally designed based on previous findings indicating that lifespan extension is only effective in males, leading to the exclusion of females from the analysis. The primary focus of our research was on the transcriptional changes and serum endocrine alterations induced by 17α-estradiol in aged males compared to untreated aged males. We believe that even in the absence of female subjects, the significant effects of 17α-estradiol on metabolism in the hypothalamus, synapses, and endocrine system remain evident, particularly regarding the expression levels of GnRH and testosterone. Notably, lower overall metabolism, increased synaptic activity, and elevated levels of GnRH and testosterone are strong indicators of health and well-being in males, supporting the validity of our primary conclusions. However, including female controls would enhance the depth of our findings. If female controls were incorporated, we propose redesigning the sample groups to include aged male control, aged female control, aged female treated, aged male treated, as well as young male control, young male treated, young female control, and young female treated. We regret that we cannot provide this data in the short term. Nevertheless, we believe this reviewer’s creative idea presents a valuable avenue for future research on this topic. In this study, we emphasize the role of 17α-estradiol in overall metabolism, synaptic function, GnRH, and testosterone in aged males and underscore the importance of supervised clustering of neuropeptide-secreting neurons in the hypothalamus.

(2) It is not known whether 17α-estradiol leads to lifespan extension in male rats similar to male mice. Therefore, it is not possible to conclude that the observed effects in the hypothalamus, are linked to the lifespan extension.

Thanks for the reminding. 17α-estradiol was reported to extend lifespan in male rats similar to male mice (PMID: 33289482). We have added the valuable reference to introduction in the new version.  

(3) The effect of 17α-estradiol on non-neuronal cells such as microglia and astrocytes is not well-described (Figure 1). Previous studies demonstrated that 17α-estradiol reduces microgliosis and astrogliosis in the hypothalamus of aged male mice. Current data suggest that the proportion of oligo, and microglia were increased by the drug treatment, while the proportions of astrocytes were decreased. These data might suggest possible species differences, differences in the treatment regimen, or differences in drug efficiency. This has to be discussed.

We have reviewed reports describing changes in cell numbers following 17α-estradiol treatment in the brain, using the keywords "17α-estradiol," "17alpha-estradiol," and "microglia" or "astrocyte." Only a limited amount of data was obtained. We found one article indicating that 17α-estradiol treatment in Tg (AβPP(swe)/PS1(ΔE9)) model mice resulted in a decreased microglial cell number compared to the placebo (AβPP(swe)/PS1(ΔE9) mice), but this change was not significant when compared to the non-transgenic control (PMID: 21157032). The transgenic AβPP(swe)/PS1(ΔE9) mouse model may differ from our wild-type aging rat model in this context.

Moreover, the calculation of cell numbers was based on visual observation under a microscope across several brain tissue slices. This traditional method often yields controversial results. For example, oligodendrocytes in the corpus callosum, fornix, and spinal cord have been reported to be 20-40% more numerous in males than in females based on microscopic observations (PMID: 16452667). In contrast, another study found no significant difference in the number of oligodendrocytes between sexes when using immunohistochemistry staining (PMID: 18709647). Such discrepancies arising from traditional observational methods are inevitable.

We believe the data presented in this article are reliable because the cell number and cell ratio data were derived from high-throughput cell counting of the entire hypothalamus using single-cell suspension and droplet wrapping (10x Genomics).

(4) A more detailed analysis of glial cell types within the hypothalamus in response to drugs should be provided.

We provided more enrichment analysis data of differentially expressed genes between Y, O, and O.T in microglia and astrocytes in Figure 2—figure supplement 3. In this supplemental data, we found unlike that in neurons, Micro displayed lower levels of synapse-related cellular processes in O.T. compared to O.

(5) The conclusion that CRH neurons are going into senescence is not clearly supported by the data. A more detailed analysis of the hypothalamus such as histological examination to assess cellular senescence markers in CRH neurons, is needed to support this claim.

We also noted the inappropriate claim and have changed "senescent phenotype" to "stressed phenotype" and "abnormal phenotype" in both the abstract and results sections. The stressed phenotype could be induced by heightened functional activity in the cells, potentially indicating higher cellular activity. The GnRH and CRH neurons discussed in this paper may represent such a case, as illustrated by the observed high serum GnRH, testosterone, and cortisol levels. This revision suggestion is highly valuable and constructive for our understanding of the unique physiological characteristics revealed by these data.

Reviewer #2 (Public Review):

Summary:

Li et al. investigated the potential anti-ageing role of 17α-Estradiol on the hypothalamus of aged rats. To achieve this, they employed a very sophisticated method for single-cell genomic analysis that allowed them to analyze effects on various groups of neurons and non-neuronal cells. They were able to sub-categorize neurons according to their capacity to produce specific neurotransmitters, receptors, or hormones. They found that 17α-Estradiol treatment led to an improvement in several factors related to metabolism and synaptic transmission by bringing the expression levels of many of the genes of these pathways closer or to the same levels as those of young rats, reversing the ageing effect. Interestingly, among all neuronal groups, the proportion of Oxytocin-expressing neurons seems to be the one most significantly changing after treatment with 17α-Estradiol, suggesting an important role of these neurons in mediating its anti-ageing effects. This was also supported by an increase in circulating levels of oxytocin. It was also found that gene expression of corticotropin-releasing hormone neurons was significantly impacted by 17α-Estradiol even though it was not different between aged and young rats, suggesting that these neurons could be responsible for side effects related to this treatment. This article revealed some potential targets that should be further investigated in future studies regarding the role of 17α-Estradiol treatment in aged males.

Strengths:

(1) Single-nucleus mRNA sequencing is a very powerful method for gene expression analysis and clustering. The supervised clustering of neurons was very helpful in revealing otherwise invisible differences between neuronal groups and helped identify specific neuronal populations as targets.

Thanks.

(2) There is a variety of functions used that allow the differential analysis of a very complex type of data. This led to a better comparison between the different groups on many levels.

Thanks.

(3) There were some physiological parameters measured such as circulating hormone levels that helped the interpretation of the effects of the changes in hypothalamic gene expression

Thanks.

Weaknesses

(1) One main control group is missing from the study, the young males treated with 17α-Estradiol.

Given that the treatment period lasts six months, which extends beyond the young male rats' age range, we aimed to investigate the perturbation of 17α-Estradiol on the normal aging process. Including data from young males could potentially obscure the treatment's effects in aged males due to age effects, though similar effects between young and aged animals may exist. Long-term treatment of hormone may exert more developmental effects on the young than the old. Consequently, we decided to exclude this group from our initial sample design. We apologize for this omission.

(2) Even though the technical approach is a sophisticated one, analyzing the whole rat hypothalamus instead of specific nuclei or subregions makes the study weaker.

The precise targets of 17α-Estradiol within the hypothalamus remain unresolved. Selecting a specific nucleus for study is challenging. The supervised clustering method described in this manuscript allows us to identify the more sensitive neuron subtypes influenced by 17α-Estradiol and aging across the entire hypothalamus, without the need to isolate specific nuclei in a disturbed hypothalamic environment.

(3) Although the authors claim to have several findings, the data fail to support these claims. You may mean the claim as the senescent phenotype in Crh neuron induced by 17a-estradiol.

Thanks. We have changed the "senescent phenotype" to "stressed phenotype" in the abstract and results to avoid such claim. The stressed phenotype may be induced by heightened functional activity in the cells, potentially indicating higher cellular activity.

(4) The study is about improving ageing but no physiological data from the study demonstrated such a claim with the exception of the testes histology which was not properly analyzed and was not even significantly different between the groups.

The primary objective of this study is to elucidate the effects of 17α-Estradiol on the endocrine system in the aging hypothalamus; exploring anti-aging effects is not the main focus. From the characteristics of the aging hypothalamus, we know that down-regulated GnRH and testosterone levels, along with elevated mTOR signaling, are indicators of aging in these organs from previous publications (PMID: 37886966, PMID: 37048056, PMID: 22884327). The contrasting signaling networks related to metabolism and synaptic processes significantly differentiate young and aging hypothalami, and 17α-Estradiol helps rebalance these networks, suggesting its potential anti-aging effects.

(5) Overall, the study remains descriptive with no physiological data to demonstrate that any of the effects on hypothalamic gene expression are related to metabolic, synaptic, or other functions.

The study focuses on investigating cellular responses and endocrine changes in the aging hypothalamus induced by 17α-estradiol, utilizing single-nucleus RNA sequencing (snRNA-seq) and a novel data mining methodology to analyze various neuron subtypes. It is important to note that this study does not mainly aim to explore the anti-aging effects. Consequently, we have revised the claim in the abstract from “the effects of 17α-estradiol in anti-aging in neurons” to “the effects of 17α-estradiol on aging neurons.” We observed that the lower overall metabolism and increased expression levels of cellular processes in the synapses align with findings previously reported regarding 17α-estradiol. To address the lack of physiological data and the challenges in measuring multiple endocrine factors due to their volatile nature, we employed several bidirectional Mendelian analyses of various genome-wide association study (GWAS) data related to these serum endocrine factors to identify their mutual causal effects.

Reviewing Editor Comment:

Based on the Public Reviews and Recommendations for Authors, the Reviewers strongly recommend that revisions include an experimental demonstration of the physiological effects of the treatment on ageing in rats as well as the CRH-senescence link. Additional analysis of the glia would greatly strengthen the study, as would inclusion of females and young male controls. The important point was also raised that the work linking 17a-estradiol was performed in mice, and the link with lifespan in rats is not known. Discussion of this point is recommended.

We thank the reviewers for their constructive feedback. Regarding the recommendations in the Public Reviews and Recommendations for Authors:

a)  Physiological effects & CRH-senescence link:

We acknowledge that 17α-estradiol has been reported to extend lifespan in male rats, consistent with findings in male mice (PMID: 33289482). This point has now been noted in the Introduction. We regret that further experimental validation of the treatment's physiological effects on aging in rats was beyond the scope of this study.

b) Phenotype terminology:

In response to concerns about the "senescent" characterization of CRH neurons, we have revised this terminology to "stressed phenotype" throughout the abstract and results. While we were unable to conduct additional experiments to confirm senescence markers, this revised description better reflects the heightened cellular activity observed (as evidenced by elevated serum GnRH and testosterone levels), without implying confirmed senescence.

c) Glial cell analysis:

To address questions about glial cell function during treatment, we have added new enrichment analysis data of differentially expressed genes in microglia and astrocytes from young (Y), old (O), and old treated (O.T) groups in Figure 2—figure supplement 3. This analysis reveals that microglia exhibit contrasting synaptic-related cellular processes compared to total neurons.

d) Female and young controls:

We sincerely apologize for the absence of female subjects and young male controls in the current study. The reviewers' suggestion to examine the male-specific effects of 17α-estradiol using female controls represents an excellent direction for future research, which we plan to pursue in upcoming studies.

Reviewer #2 (Recommendations For The Authors):

General comments:

(1) The manuscript is very hard to read. Proofreading and editing by software or a professional seems necessary. The words "enhanced", "extensive" etc. are not always used in the right way.

Thanks for the suggestion. We have revised the proofreading and editing. The words "enhanced" and "extensive" were also revised in most sentences.

(2) The numbers of animals and samples are not well explained. Is it 9 rats overall or per group? If there are 8 testes samples per group, should we assume that there were 4 rats per group? The pooling of the hypothalamic how was it done? Were all the hypothalamic from each group pooled together? A small table with the animals per group and the samples would help.

We appreciate your reminder regarding the initial mistake in our manuscript preparation. In the preliminary submission, we reported 9 rats based solely on sequencing data and data mining. The revised version (v1) now includes additional experimental data, with an effective total of 12 animals (4 per group). Unfortunately, we overlooked updating this information in the v1 submission. We have since added detailed information in the Materials and Methods sections: Animals, Treatment and Tissues, and snRNA-seq Data Processing, Batch Effect Correction, and Cell Subset Annotation.

(3) The Clustering is wrong. There are genes in there that do not fall into any of the 3 categories: Neurotransmitters, Receptors, Hormones.

We acknowledge the error in gene clustering and have implemented the following corrections:

(a) The description has been updated to state: 'Vast majority of these subtypes were clustered by neuropeptides, hormones, and their receptors among all neurons.'

(b) Genes not belonging to these three categories have been substantially removed.

(c) The neuropeptide category (now including several growth hormones) has been expanded to 104 genes, while their corresponding receptors (including several sex hormone receptors) now comprise 105 genes.

(4) The coloring of groups in the graphs is inconsistent. It must be more homogeneous to make it easier to identify.

We have changed the colors of groups in Fig. 1D to make the color of cell clusters consistent in Fig. 1A-D.

(5) The groups c1-c4 are not well explained. How did the authors come up with these?

We have added more descriptions of c1-c4 in materials and methods in the new version.

(6) In most cases it's not clear if the authors are talking about cell numbers that express a certain mRNA, the level of expression of a certain mRNA, or both. They need to do a better job using more precise descriptions instead of using general terms such as "signatures", "expression profiles", "affected neurons" etc. It is very hard to understand if the number of neurons is compared between the groups or the gene expression.

We have changed the "signatures" to "gene signatures" to make it more accurate in meaning. The "affected neurons" were also changed to "sensitive neurons". But sorry that we were not able to find better alternatives to the "expression profiles".

(7) Sometimes there are claims made without justification or a reference. For example, the claim about the senescence of CRH neurons due to the upregulation of mitochondrial genes and downregulation of adherence junction genes (lines 326-328) should be supported by a reference or own findings.

The "senescence" here is not appropriate. We have changed it to "stressed phenotype" or "aberrant changes" in abstract and results.

(8) Young males treated with Estradiol as a control group is necessary and it is missing.

Your suggestion is appreciated; however, the treatment duration for aged mice (O.T) was set at 6 months, while the young mice were only 4 months old. This disparity makes it challenging to align treatment timelines for the young animals. The primary aim of this study is to investigate the perturbation of 17α-estradiol on the aging process, and any distinct effects due to age effect observed in young males might complicate our understanding of its role in aged males, though similar endocrine effects may exist in the young animals. Long-term treatment of hormone may exert more developmental effects on the young than the old. Therefore, we made the decision to exclude the young samples in our initial study design. We apologize for any confusion this may have caused.

Specific Comments:

Line 28: "elevated stresses and decreased synaptic activity": Please make this clearer. Can't claim changes in synaptic activity by gene expression.

We have changed it to "the expression level of pathways involved in synapse"

Line 32: "increased Oxytocin": serum Oxytocin.

We have added the “serum”.

Line 52 - 54: Any studies from rats?

Thanks. In rats there is also reported that 17α-estradiol has similar metabolic roles as that in mice (PMID: 33289482) and we have added it to the refences. It’s very useful for this manuscript.

Line 62 - 65: It wasn't investigated thoroughly in this paper so why was it suggested in the introduction?

We have deleted this sentence as being suggested.

Line 70: "synaptic activity" Same as line 28.

We have changed it to "pathways involved in synaptic activity".

Line 79: Why were aged rats caged alone and young by two? Could that introduce hypothalamic gene expression effects?

The young males were bred together in peace. But the aged males will fight and should be kept alone.

Lines 78, 99, 109-110: It is not clear how many animals per group were used and how many samples per group were used separately and/or grouped. Please be more specific.

We have added these information to Materials and methods/Animals, treatment and tissues and Materials and methods/snRNA-seq data processing, batch effect correction, and cell subset annotation.

Line 205: "in O" please add "versus young.".

We have changed accordingly.

Line 207: replace "were" with "was"

We have alternatively changed the "proportion" to "proportions".

Line 208: replace "that" with "compared to" and after "in O.T." add "compared to?"

We have changed accordingly.

Line 223: "O.T." compared to what? Figure?

We have changed it accordingly.

Line 227: Figure?

We have added (Figure 1E) accordingly.

Line 229: "synaptic activity" Same as line 28.

We have revised it.

Line 235: "synaptic activity" and "neuropeptide secretion" Same as line 28.

We have revised it.

Line 256:" interfered" please revise.

We changed to "exerted".

Line 263: "on the contrary" please revise.

We have changed "on the contrary" to "opposite".

Line 270: "conversed" did you mean "conserved"?

We have changed "conversed" to "inversed".

Line 296-298: Please explain. Why would these be side effects?

It’s hard to explain, therefore, we deleted the words "side effects".

Line 308: "synaptic activity" Same as line 28.

We have changed it to "expression levels of synapse-related cellular processes".

Line 314: "and sex hormone secretion and signaling"Isn't this expected?

Yes, it is expected. We have added it to the sentence "and, as expected, sex hormone secretion and signaling".

Line 325-328: Why is this senescence? Reference?

We have added “potent” to it.

Line 360-361: This doesn't show elevated synaptic activity.

"elevated synaptic activity" was changed to "The elevated expression of synapse-related pathways"

Line 363-364: "Unfortunately" is not a scientific expression and show bias.

We have changed it to "Notably".

Line 376: Similar as above.

Yes, we have change it to "in contrast".

Lines 382-385: This is speculation. Please move to discussion.

Sorry for that. We think the causal effects derived from MR result is evidence. As such, we have not changed it.

Line 389: Please revise "hormone expressing".

We have changed it accordingly.

Line 401: Isn't this effect expected due to feedback inhibition of the biochemical pathway? Please comment.

The binding capability of 17alpha-estradiol to estrogen receptors and its role in transcriptional activation remain core questions surrounded by controversy. Earlier studies suggest that 17alpha-estradiol exhibits at least 200 times less activity than 17beta-estradiol (PMID: 2249627, PMID: 16024755). However, recent data indicate that 17alpha-estradiol shows comparable genomic binding and transcriptional activation through estrogen receptor α (Esr1) to that of 17beta-estradiol (PMID: 33289482). Additionally, there is evidence that 17alpha-estradiol has anti-estrogenic effects in rats (PMID: 16042770). These findings imply possible feedback inhibition via estrogen receptors. Furthermore, 17alpha-estradiol likely differs from 17beta-estradiol due to its unique metabolic consequences and its potential to slow aging in males, an effect not attributed to 17beta-estradiol. For instance, neurons are also targets of 17alpha-estradiol, with Esr1 not being the sole target (PMID: 38776045). Intriguingly, neurons expressing Ar and Esr1 ranked among the top 20 most perturbed receptor subtypes during aging (O vs Y), but were no longer ranked in this group following treatment (O.T vs Y and O.T vs O comparisons). This indicates that 17α-estradiol administration attenuated age-associated perturbation in these neuronal subtypes, which may be a consequence of potential feedback (Figure 3D). Nevertheless, the precise effective targets of 17alpha-estradiol are still unresolved.

Line 409: This conclusion cannot be made because the effect is not statistically significant. Can say "trend" etc.

Thanks for the recommendation. We have added "potential" in front of the conclusion.

Line 426: "suggesting" please revise.

sorry, it’s a verb.

Lines 426-428: This is speculation. Please move to discussion.

The elevated GnRH levels in O.T., observed through EIA analysis, suggest a deduction regarding the direct causal effects of 17alpha-estradiol on various endocrine factors related to feeding, energy homeostasis, reproduction, osmotic regulation, stress response, and neuronal plasticity through MR analysis. Thus, we have not amended our position. We apologize for any confusion.

Lines 431-432: improved compared to what?

The statement have been revised as " The most striking role of 17α-estradiol treatment revealed in this study showed that HPG axis was substantially improved in the levels of serum Gnrh and testosterone".

Line 435: " Estrogen Receptor Antagonists". Please revise.

Thanks for the recommendation. We have changed it to "estrogen receptor antagonists".

Line 438" "Secrete". Please revise

Sorry, it is "secret".

Lines 439-449: None of this has been demonstrated. Please remove these conclusions.

We appreciate the reviewer's scrutiny regarding lines 439-449. While these statements should not be interpreted as definitive conclusions from our current data, we propose they serve as clinically relevant discussion points worthy of exploration. Our findings demonstrate 17α-estradiol's role in modulating testosterone levels in aged males. This mechanistic insight warrants consideration of its therapeutic potential for age-related hypogonadism - a hypothesis we believe merits discussion given the compound's specific endocrine effects.

Lines 450-457: No females were included in this study. Why? Also, why is this discussed? It is relevant but doesn't belong in this manuscript since it was not studied here.

Testosterone levels are crucial for male health, while estradiol levels are essential for the health and fertility of females. Previous studies have demonstrated that 17α-estradiol does not contribute to lifespan extension in females. Given the effects of 17α-estradiol on males—specifically, its role in promoting testosterone and reducing estradiol levels—we believe it is important to discuss the potential sex-biased effects of 17α-estradiol, as this could inform future investigations. We have refined this section to clarify that these points represent mechanistic hypotheses derived from our male data and existing literature, not conclusions about unstudied female physiology. This framing maintains the discussion's scientific value while respecting the study's scope.

Lines 458-459: This was not demonstrated in this article. Please remove.

We have restricted the claim to "expression level of energy metabolism in hypothalamic neurons".

Line 464: "Promoted lifespan extension" Not demonstrated. Please remove.

At the end of the sentence it was revised as "which may be a contributing factor in promoting lifespan extension".

Line 466: "Showed" No.

The whole sentence was deleted in the new version.

Line 483: "the sex-based effects". Not studied here.

Since the changes in testosterone levels are significant in this dataset and this hormone has a sex-biased nature, we find it worthwhile to suggest this as a topic for future investigation. We have added "which needs further verification in the future" at the end of this sentence.

listening to this song could be deadly and others who survive it forget about it like brainwashing.

It still brings sailors to jump overboard and the want to hear the secret ends

talking more on how important the song is to them and shows how it is less doubtful

shows how the song is irresistible

This section was a description of the natives that lived there. It seems like this guy came off patronizing in some way, as if they needed saving from their "primitive" way of living.

Discussion: Servants = Taxpayers to the king. Christians = People who are civilized compared to their "primitive ways"

Discussion Question: If the eukaryotic nucleus originated from a giant virus, that infected an archael ancestor of the eukaryotes (Bell, 2020), wouldn't that mean the original cell was an archaeal cell? And how "giant" does the virus have to be to be able to replicate this now?

https://www.sciencedirect.com/science/article/pii/S0168170220310753

"How did the discovery of the new Asgard Archaea change the way researchers understood eukaryotic evolution and the three branched tree of life?" Once scientists realized the newly discovered Asgard arhcaea genomes had genes that produced eukaryotic signature proteins, everything they knew about the origin of a eukaryotic cell was questioned. According to our understanding of the three domains of the tree of life, these proteins should not have been found in the Asgard archaea.

Advancement in technology happens frequently. We started with only one Asgard genome and within short amout of time, up to 2022, (the year of this publication), there were many more. According to an article in 2024, (Leao, et al, 2024), there were 869 Asgardarchaeota genomes. With the number of these genomes continually expanding, there is bound to be more research opportunities available, and each year ahead.

https://www.nature.com/articles/s41467-024-50195-2

so why is this guy even important. he was a rapist to my people. FUCK Christopher Columbus

They're going into middle-class areas and moving out the middle-class residents.

gentrification is REAL

The last part is NOT true. They are, in fact, making it harder to live there so that the people who are making the neighborhood bad move out along with their low income.

eLife Assessment

This is a well-done study that provides compelling data from a diverse set of approaches from single cell transcriptome data and network analysis from genetically diverse mouse cells to identify novel driver genes underlying human GWAS associations. The authors present solid evidence that network analysis of scRNA-seq data from genetically diverse mouse bone-marrow derived stromal cells can be informative for identifying human BMD GWAS driver genes. Their approach should be broadly useful and applicable to other GWAS studies.

Reviewer #1 (Public review):

In this manuscript, Dillard and colleagues integrate cross-species genomic data with a systems approach to identify potential driver genes underlying human GWAS loci and establish the cell type(s) within which these genes act and potentially drive disease.

Specifically, they utilize a large single cell RNA-seq (scRNA-seq) dataset from an osteogenic cell culture model - bone marrow-derived stromal cells cultured under osteogenic conditions (BMSC-OBs) - from a genetically diverse outbred mouse population called the Diversity Outbred (DO) stock to discover network driver genes that likely underlie human bone mineral density (BMD) GWAS loci. The DO mice segregate over 40M single nucleotide variants, many of which affect gene expression levels, therefore making this an ideal population for systems genetic and co-expression analyses.

The current study builds on previous published work from the same group that used co-expression analysis to identify co-expressed "modules" of genes that were enriched for BMD GWAS associations. In this study, the authors utilized a much larger scRNA-seq dataset from 80 DO BMSC-OBs, inferred co-expression based on Bayesian networks for each identified mesenchymal cell type, focused on networks with dynamic expression trajectories that are most likely driving differentiation of BMSC-OBs, and then prioritized genes ("differentiation driver genes" or DDGs) in these osteogenic differentation networks that had known expression or splicing QTLs (eQTL/sQTLs) in any GTEx tissue that co-localized with human BMD GWAS loci. The systems analysis is impressive, the experimental methods are described in detail, and the experiments appear to be carefully done. The computational analysis of the single cell data is comprehensive and thorough, and the evidence presented in support of the identified DDGs, including Tpx2 and Fgfrl1, is for the most part convincing. Some limitations in the data resources and methods hamper enthusiasm somewhat and are discussed below.

Overall, while this study will no doubt be valuable to the BMD community, the cross-species data integration and analytical framework may be more valuable and generally applicable to the study of other diseases, especially for diseases with robust human GWAS data but for which robust human genomic data in relevant cell types is lacking.

Specific strengths of the study include the large scRNA-seq dataset on BMSC-OBs from 80 DO mice, the clustering analysis to identify specific cell types and sub-types, the comparison of cell type frequencies across the DO mice, and the CELLECT analysis to prioritize cell clusters that are enriched for BMD heritability (Figure 1). The network analysis pipeline outlined in Figure 2 is also a strength, as is the pseudotime trajectory analysis (results in Figure 3).

Potential drawbacks of the authors' approach include their focus on genes that were previously identified as having an eQTL or sQTL in any GTEx tissue. The authors rightly point out that the GTEx database does not contain data for bone tissue, but reason that eQTLs can be shared across many tissues - this assumption is valid for many cis-eQTLs, but it could also exclude many genes as potential DDGs with effects that are specific to bone/osteoblasts. Indeed, the authors show that important BMD driver genes have cell-type specific eQTLs. Another issue concerns potential model overfitting in the iterativeWGCNA analysis of mesenchymal cell type-specific co-expression, which identified an average of 76 co-expression modules per cell cluster (range 26-153). Based on the limited number of genes that are detected as expressed in a given cell due to sparse per cell read depth (400-6200 reads/cell) and drop outs, it's surprising that as many as 153 co-expression modules could be distinguished within any cell cluster. I would suspect some degree of model overfitting is responsible for these results.

Overall, though, these concerns are minor relative to the many strengths of the study design and results. Indeed, I expect the analytical framework employed by the authors here will be valuable to -- and replicated by -- researchers in other disease areas.

Comments on revisions:

Thank you for addressing my concerns. This is an impressive study and manuscript that you should be proud of.

Reviewer #2 (Public review):

Summary:

In this manuscript, Farber and colleagues have performed single cell RNAseq analysis on bone marrow derived stem cells from DO Mice. By performing network analysis, they look for driver genes that are associated with bone mineral density GWAS associations. They identify two genes as potential candidates to showcase the utility of this approach.

Strengths:

The study is very thorough and the approach is innovative and exciting. The manuscript contains some interesting data relating to how cell differentiation is occurring and the effects of genetics on this process. The section looking for genes with eQTLs that differ across the differentiation trajectory (Figure 4) was particularly exciting.

Weaknesses:

The manuscript is, in parts, hard to read due to the use of acronyms and there are some questions about data analysis that still need to be addressed.

Comments on revisions:

Dillard et al have made several improvements to their manuscript.

(1) We previously asked the authors to determine whether any cell types were enriched for BMD-related traits since the premise of the paper is that 'many genes impacting BMD do so by influencing osteogenic differentiation or ... adipogenic differentiation'. Given the potential for the cell culture method to skew the cell type distribution non-physiologically, it is important to establish which cell types in their assay are most closely associated with BMD traits. The new CELLECT analysis and Figure 1E address this point nicely. However, it would still be nice to see the correlations between these cell types and BMD traits in the mice as this would provide independent evidence to support their physiological importance more broadly.

(2) Shortening the introduction.

(3) Addressing limitations that arise from not accounting for founder genome SNPs when aligning scRNA-seq data.

(4) The main take-away of this paper is, to us, the development of a single cell approach to studying BMD-related traits. It is encouraging that the cells post-culture appear to be representative of those pre-culture (supplemental figure 3).

However, the authors seem to have neglected several comments made by both reviewers. While we share the authors' enthusiasm for the single cell analytical approach, we do not understand their reluctance to perform further statistical tests. We feel that the following comments have still not been addressed:

(1) The manuscript still contains the following:

"To provide further support that tradeSeq-identified genes are involved in differentiation, we performed a cell type-specific expression quantitative trait locus (eQTL) analysis for each mesenchymal cell type from the 80 DO mice. We identified 563 genes (eGenes) regulated by a significant cis-eQTL in specific cell types of the BMSC-OB scRNA-seq data (Supplementary Table S14). In total, 73 eGenes were also tradeSeq-identified genes in one or more cell type boundaries along their respective trajectories (Supplementary Table S9)."

The purpose of this paragraph is to convince readers that the eGenes approach aligns with the tradeSeq approach (and that their approach can therefore be trusted). It is essential that such claims are supported by statistical reasoning. Given that it would be very simple to perform permutation/enrichment analyses to address this point, and both reviewers requested similar analyses, we do not understand the author's reluctance here. Otherwise, this section should be rewritten so that it does not imply that the identification of these genes provides support for their approach.

(2) Given that a central purpose of this manuscript is to establish a systematic workflow for identifying candidate genes, the manuscript could still benefit from more explanation as to why the authors chose to highlight Tpx2 and Fgfrl1. Tpx2 does already have a role in bone physiology through the IMPC. The authors should comment on why they did not explore Kremen1, for instance, as this gene seems important for the transition to both OB1 and 2.

A final minor comment is that it would be very helpful if the authors could indicate if the DDGs in Table 1 are also eGenes for the relevant cell type. This is much more meaningful than looking through GTEx.

Author response:

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

Reviewer #1 (Public review): 

In this manuscript, Dillard and colleagues integrate cross-species genomic data with a systems approach to identify potential driver genes underlying human GWAS loci and establish the cell type(s) within which these genes act and potentially drive disease. Specifically, they utilize a large single-cell RNA-seq (scRNA-seq) dataset from an osteogenic cell culture model - bone marrow-derived stromal cells cultured under osteogenic conditions (BMSC-OBs) - from a genetically diverse outbred mouse population called the Diversity Outbred (DO) stock to discover network driver genes that likely underlie human bone mineral density (BMD) GWAS loci. The DO mice segregate over 40M single nucleotide variants, many of which affect gene expression levels, therefore making this an ideal population for systems genetic and co-expression analyses. The current study builds on previously published work from the same group that used co-expression analysis to identify co-expressed "modules" of genes that were enriched for BMD GWAS associations. In this study, the authors utilize a much larger scRNA-seq dataset from 80 DO BMSC-OBs, infer co-expression-based and Bayesian networks for each identified mesenchymal cell type, focused on networks with dynamic expression trajectories that are most likely driving differentiation of BMSC-OBs, and then prioritized genes ("differentiation driver genes" or DDGs) in these osteogenic differentiation networks that had known expression or splicing QTLs (eQTL/sQTLs) in any GTEx tissue that colocalized with human BMD GWAS loci. The systems analysis is impressive, the experimental methods are described in detail, and the experiments appear to be carefully done. The computational analysis of the single-cell data is comprehensive and thorough, and the evidence presented in support of the identified DDGs, including Tpx2 and Fgfrl1, is for the most part convincing. Some limitations in the data resources and methods hamper enthusiasm somewhat and are discussed below. Overall, while this study will no doubt be valuable to the BMD community, the cross-species data integration and analytical framework may be more valuable and generally applicable to the study of other diseases, especially for diseases with robust human GWAS data but for which robust human genomic data in relevant cell types is lacking. 

Specific strengths of the study include the large scRNA-seq dataset on BMSC-OBs from 80 DO mice, the clustering analysis to identify specific cell types and sub-types, the comparison of cell type frequencies across the DO mice, and the CELLECT analysis to prioritize cell clusters that are enriched for BMD heritability (Figure 1). The network analysis pipeline outlined in Figure 2 is also a strength, as is the pseudotime trajectory analysis (results in Figure 3). One weakness involves the focus on genes that were previously identified as having an eQTL or sQTL in any GTEx tissue. The authors rightly point out that the GTEx database does not contain data for bone tissue, but the reason that eQTLs can be shared across many tissues - this assumption is valid for many cis-eQTLs, but it could also exclude many genes as potential DDGs with effects that are specific to bone/osteoblasts. Indeed, the authors show that important BMD driver genes have cell-type-specific eQTLs. Furthermore, the mesenchymal cell type-specific co-expression analysis by iterative WGCNA identified an average of 76 co-expression modules per cell cluster (range 26-153). Based on the limited number of genes that are detected as expressed in a given cell due to sparse per-cell read depth (400-6200 reads/cell) and dropouts, it's hard to believe that as many as 153 co-expression modules could be distinguished within any cell cluster. I would suspect some degree of model overfitting here and would expect that many/most of these identified modules have very few gene members, but the methods list a minimum module size of 20 genes. How do the numbers of modules identified in this study compare to other published scRNA-seq studies that use iterative WGCNA? 

In the section "Identification of differentiation driver genes (DDGs)", the authors identified 408 significant DDGs and found that 49 (12%) were reported by the International Mouse Knockout [sic] Consortium (IMPC) as having a significant effect on whole-body BMD when knocked out in mice. Is this enrichment significant? E.g., what is the background percentage of IMPC gene knockouts that show an effect on whole-body BMD? Similarly, they found that 21 of the 408 DDGs were genes that have BMD GWAS associations that colocalize with GTEx eQTLs/sQTLs. Given that there are > 1,000 BMD GWAS associations, is this enrichment (21/408) significant? Recommend performing a hypergeometric test to provide statistical context to the reported overlaps here. 

We thank the reviewer for their constructive feedback and thoughtful questions. In regards to the iterativeWGCNA, a larger number of modules is sometimes an outcome of the analysis, as reported in the iterativeWGCNA preprint (Greenfest-Allen et al., 2017). While we did not make a comparison to other works leveraging this tool for scRNA-seq, it has been used broadly across other published studies, such as PMID: 39640571, 40075303, 33677398, 33653874. While model overfitting, as you mention, may be a cause for more modules, our Bayesian network analysis we perform after iterativeWGCNA highlights smaller aspects of coexpression modules, as opposed to focusing on the entirety of any given module.

We did not perform enrichment or statistical tests as our goal was to simply highlight attributes or unique features of these genes for additional context.

Reviewer #2 (Public review): 

Summary: 

In this manuscript, Farber and colleagues have performed single-cell RNAseq analysis on bone marrow-derived stem cells from DO Mice. By performing network analysis, they look for driver genes that are associated with bone mineral density GWAS associations. They identify two genes as potential candidates to showcase the utility of this approach. 

Strengths: 

The study is very thorough and the approach is innovative and exciting. The manuscript contains some interesting data relating to how cell differentiation is occurring and the effects of genetics on this process. The section looking for genes with eQTLs that differ across the differentiation trajectory (Figure 4) was particularly exciting. 

Weaknesses: 

The manuscript is in parts hard to read due to the use of acronyms and there are some questions about data analysis that need to be addressed. 

We thank the reviewer for their feedback and shared enthusiasm for our work. We tried to minimize the use of technical acronyms as much as we could without compromising readability. Additionally, we addressed questions regarding aspects of data analysis. 

Reviewer #1 (Recommendations for the authors):

(1) For increased transparency and to allow reproducibility, it would be necessary for the scripts used in the analysis to be shared along with the publication of the preprint. Also, where feasible, sharing the processed data in addition to the raw data would allow the community greater access to the results and be highly beneficial. 

Thank you for this suggestion. The raw data will be available via GEO accession codes listed in the data availability statement. We will make available scripts for some analyses on our Github (https://github.com/Farber-Lab/DO80_project) and processed scRNA-seq data in a Seurat object (.rds) on Zenodo (https://zenodo.org/records/15299631)

(2) Lines 55-76: I think the summary of previous work here is too long. I understand that they would like to cover what has been done previously, but this seems like overkill. 

Good suggestion. We have streamlined some of the summary of our previous work.

(3) Did the authors try to map QTL for cell-type proportion differences in their BMSC-OBs? While 80 samples certainly limit mapping power, the data shown in Figs 4C/D suggest that you might identify a large-effect modifier of LMP/OB1 proportions. 

We did try to map QTL for cell type proportion differences, but no significant associations were identified. 

(4) Methods question: Does the read alignment method used in your analysis account for SNPs/indels that segregate among the DO/CC founder strains? If not, the authors may wish to include this in their discussion of study limitations and speculate on how unmapped reads could affect expression results. 

The read alignment method we used does not account for SNPs/indels from the DO founder strains that fall in RNA transcripts captured in the scRNA-seq data. We have included this as a limitation in our discussion (line 422-424). 

(5) Much of the discussion reads as an overview of the methods, while a discussion of the results and their context to the existing BMD literature is relatively lacking in comparison.

We have added additional explanation of the results and context to the discussion (line 381-382, 396-407). 

(6) Figure 1E and lines 146-149: Adjusted p values should be reported in the figure and accompanying text instead of switching between unadjusted and adjusted p values. 

We updated Figure 1e to portray adjusted p-values, listed the adjusted p-values in legend of Figure 1e, and listed them in the main text (line 153-154).

(7) Why do the authors bring the IMPC KO gene list into the analysis so late? This seems like a highly relevant data resource (moreso than the GTEx eQTLs/sQTLs) that could have been used much earlier to help identify DDGs. 

Given that our scRNA-seq data is also from mice, we did choose to integrate information from the IMPC to highlight supplemental features of genes in networks (i.e., genes that have an experimentally-tested and significant effect on BMD in mice). However, our primary goal was to inform human GWAS and leverage our previous work in which we identified colocalizations between human BMD GWAS and eQTL/sQTL in a human GTEx tissue, which is why this information was used to guide our network analysis.

(8) Does Fgfrl1 and/or Tpx2 have a cis-eQTL in your BMSC-OB scRNA-seq dataset? 

We did not identify cis-eQTL effects for Fgfrl1 and Tpx2.

(9) Figure 4B-C: These eQTLs may be real, but based on the diplotype patterns in Figure 4C, I suspect they are artifacts of low mapping power that are driven by rare genotype classes with one or two samples having outlier expression results. For example, if you look at the results in Fig 4C for S100a1 expression, the genotype classes with the highest/lowest expression have lower sample numbers. In the case of Pkm eQTL showing a PWK-low effect, the PWK genome has many SNPs that differ from the reference genome in the 3' UTR of this gene, and I wonder if reads overlapping these SNPs are not aligning correctly (see point 4 above) and resulting (falsely) in lower expression values for samples with a PWK haplotype. 

As mentioned above, our alignment method did not consider DO founder genetic variation that is specifically located in the 3’ end of RNA transcripts in the scRNA-seq data. We have included this as a limitation in our discussion (line 422-424).

In future studies, we intend to include larger populations of mice to potentially overcome, as you mention, any artifacts that may be attributable to low statistical power, rare genotype classes, or outlier expression.

Reviewer #2 (Recommendations for the authors):

Major Points 

(1) The authors hypothesize "that many genes impacting BMD do so by influencing osteogenic differentiation or possibly bone marrow adipogenic differentiation". However, cell type itself does not correlate with any bone trait. Does this indicate that the hypothesis is not entirely correct, as genes that drive these phenotypes would not be enriched in one particular cell type? The authors have previously identified "high-priority target genes". So, are there any cell types that are enriched for these target genes? If not, this would indicate that all these genes are more ubiquitously expressed and this is probably why they would have a greater effect on the overall bone traits. Furthermore, are the 73 eGenes (so genes with eQTLs in a particular cell type that change around cell type boundaries) or the DDGs (Table 1) enriched for these high-priority target genes? 

The bone traits measured in the DO mice are complex and impacted by many factors, including the differentiation propensity and abundance of certain cell types, both within and outside of bone. Though we did not identify correlations between cell type abundance and the bone traits we measured, we tailored our investigations to focus on cellular differentiation using the scRNA-seq data. However, future studies would need to be performed to investigate any connections between cellular differentiation, cell type abundance, and bone traits.

We did not perform enrichment analyses of either the target genes identified from our other work or eGenes identified here, but instead used the target gene list to center our network analysis and the eGenes to showcase the utility of the DO mouse population.

(2) The readability of the paper could be improved by minimising the use of acronyms and there are several instances of confusing wording throughout the paper. In many cases, this can be solved by re-organising sentences and adding a bit more detail. For example, it was unclear how you arrived at Fgfrl1 or Tpx2.

One of the goals of our study was to identify genes that have (to our knowledge) little to no known connection to BMD. We chose to highlight Fgfrl1 and Tpx2 because there is minimal literature characterizing these genes in the context of bone, which we speak to in the results (line 296-297). Additionally, we prioritized these genes in our previous work and they were identified in this study by using our network analyses using the scRNA-seq data, which we mention in the results (line 276-279).

(3) Technical aspects of the assay. In Figure 1d you show that the cell populations vary considerably between different DO mice. It would be useful to give some sense of the technical variance of this assay given that the assay involves culturing the cells in an exogenous environment. This could take the form of tests between mice within the same inbred strain, or even between different legs of the same DO mice to show that results are technically very consistent. It might also be prudent to identify that this is a potential limitation of the approach as in vitro culturing has the potential to substantially change the cell populations that are present. 

We agree that in vitro culturing, in addition to the preparation of single cells for scRNA-seq, are unavoidable sources of technical variation in this study. However, the total number of cells contributed by each of the 80 DO mice after data processing does not appear to be skewed and the distribution appears normal (see added figures, now included as Supplemental Figure 3). Therefore, technical variation is at least consistent across all samples. Nevertheless, we have mentioned the potential for technical variation artifacts in our study in the discussion (line 414-416).

(4) Need for permutation testing. "We identified 563 genes regulated by a significant eQTL in specific cell types. In total, 73 genes with eQTLs were also tradeSeq-identified genes in one or more cell type boundaries". These types of statements are fine but they need to be backed up with permutation testing to show that this level of enrichment is greater than one would expect by chance. 

We did not perform enrichment tests as our only goal was to 1. determine if eQTL could be resolved in the DO mouse population using our scRNA-seq data and 2. predict in what cell type the associated eQTL and associated eGene may have an effect.

(5) The main novelty of the paper seems to be that you have used single-cell RNA seq (given that you appear to have already detailed the candidates at the end). I don't think this makes the paper less interesting, but I think you need to reframe the paper more about the approach, and not the specific results. How you landed on these candidates is also not clear. So the paper might be improved by more robustly establishing the workflow and providing guidelines for how studies like this should be conducted in the future. 

We sought to not only devise a rigorous approach to analyze our single cell data, but also showcase the utility of the approach in practice by highlighting targets for future research (i.e., Fgfrl1 and Tpx2).

Our goal was to identify novel genes and we landed on these candidate genes (Fgfrl1 and Tpx2) because they had substantial data supporting their causality and they have yet to be fully characterized in the context of bone and BMD (line 295-297).

In regards to establishing the workflow, we have included rationale for specific aspects of our approach throughout the paper. For example, Figure 2 itemizes each step of our network analysis and we explain why each step is utilized throughout various parts results (e.g., lines 168-170, 179-181, 191-193, 202-203, 257-260, 276-277).

We have added a statement advocating for large-scale scRNA-seq from genetically diverse samples and network analyses for future studies (line 436-438).

Minor Points 

(1) In the summary you use the word "trajectory". Trajectories for what? I assume the transition between cell types, but this is not clear. 

We added text to clarify the use of trajectory in the summary (line 34).

(2) This sentence: "By 60 identifying networks enriched for genes implicated in GWAS we predicted putatively causal genes 61 for hundreds of BMD associations based on their membership in enriched modules." is also not clear. Do you mean: we predicted putatively causal genes by identifying clusters of co-expressed genes that were enriched for GWAS genes?" It is not clear how you identify the causal gene in the network. Is this just based on the hub gene? 

The aforementioned sentence has since been removed to streamline the introduction, as suggested by Reviewer 1.

In regards to causal gene identification, it is not based on whether it is hub gene. We prioritized a DDG (and their associated networks) if it was a causal gene that we identified in our previous work as having eQTL/sQTL in a GTEx tissue that colocalizes with human BMD GWAS.

(3) Figure 3C. This is good but the labels are quite small. Would be good to make all the font sizes larger. 

We have enlarged Figure 3C.

(4) Line 341 in the Discussion should be "pseudotemporal". 

We have edited “temporal” to “pseduotemporal”.

Humidifiers near the detector (person) can decrease the exposure to airborne pathogens.

Does more humidity in the room mean less change of exposure to aerosols if you are located far from the source. Additionally, time spent in the room from start of aerosolization has to be taken into consideration.

This process is rather artificial, it's possible to allow shadowing variable of the context by changing the weakening rule.