We can see from the photo that fragments of ice have formed in the sea, making it difficult for both humans and animals to move on and off the coastline.

The photographer, Seaman, has seen climate change affect the earth with her own eyes. She's been visiting Antarctica and she has been able to observe a noticeable change in just the past few years.

Almond, Kyle. “Antarctica is changing. The impact could be catastrophic.” CNN, 13 August 2021, https://www.cnn.com/interactive/2021/08/weather/antarctica-climate-change- cnnphotos/. Accessed 20 October 2025.

This story is absolutely absurd. McAffee has excuse after excuse and contingency plan after contingency plan. He provides nothing about why he was in Belize to begin with. Reminds me of Alfred Inglethorp from Agatha Christie's The Mysterious affair at Styles, except Inglethorp had a very good reason to behave extremely suspicious. McAffee just sounds like hes in pure panic mode, but still has time for Vice to boost his ego? Again, its just absurd.

Although there is an option for private messaging for users to have private communication with other users, it will still be stored in the cloud server. However, in today's era of widespread and advanced Internet access, private message also infringes upon users' privacy to a certain extent.

This article reports the situation that Facebook stores users' passwords in plain text instead of encrypted password, meaning stuffs with enough access can directly see the passwords of all the users. Even though they said no one leaked or illegally used the passwords, I still have doubts about this since we don't know what they actually do. When using social media, we give up some of our privacy, so I think if there are some things that we really don't want others to know, we should try to not talk about them on social media.

I find it really concerning that Facebook decided not to notify users after such a massive data breach. It feels like they care more about protecting their reputation than protecting the people who use their platform. Even if the leaked information was already public, users still deserve to know when their data is being used or exposed in unsafe ways. I think this shows how weak data privacy laws are, especially when companies can make their own choices about whether to inform people.

This article explains how Facebook was storing a list of millions of Instagram passwords. They advertised it as tens of thousands, hoping to make the issue seem less intense. However, the number was truly in the millions. They stored the passwords in plain text, even though they were supposed to be encrypted. Records show that 20,000 Facebook employees had access to these passwords. Even though the situation seemed dire, Facebook didn't urge users to change their passwords and barely called attention to the incident. This shows how as users we must take privacy precautions into our own hands. The company will usually not be looking out for our privacy, so we must do it ourselves.

the data transfer protocol used on the World Wide Web (in lower-case letters followed by a colon, constituting the beginning of the web address of a file to be transmitted using this protocol).

This has concerning implications for companies that want to bust unions. Additionally, the fact that this is a possibility only divides management and employees further and creates adversity.

the Silk Road GIS, resonates with this caveat. GIS is not a neutered cartographic tool; it's one for framing. The interpretive logics in every parameter slope, trade hub density, terrain require the contexts to come prior to tool application. My workflow treats GIS as a reasoning medium, not software.

This happens so often without us even realizing it. Missing emails is so easy. Also, understanding what someone means over text often requires some sort of interpretation that can be taken in the completely wrong direction if the message does not say word for word what it is asking.

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I think that the discussions of race and class are inseparable and intersectional. You can't talk about one without the other. We learned las week that race is socially constructed, and that it was created and continues to be upheld for the economic interests of the people on top to continue to justify the oppression and exploitation of others. Institutionalized racism reinforces the economic conditions of certain racial and ethnic identities as well.

weakens credibility - violates ethical standards on inclusive speaking and proper sourcing

They get money from selling the information of their users to other companies. They will also be able to use more targeted ads if they use all the information they have about a user, and if the user buys something, they make more money from that purchase.

It’s interesting how something as small as changing one word or phrase can completely shift how people interpret a question. This made me think about how often survey results in the news might be influenced by the way questions are asked, not just by people’s actual opinions. I think this shows that writing survey questions is more of a science than I realized, it takes a lot of testing and awareness to get it right. Overall, this part of the reading made me appreciate how much work goes into making surveys fair, balanced, and truly representative of what people think.

Agreed. Another thought I had is that people frequently find it more difficult to challenge a statement than to agree with it, so sometimes it's also important to factor in that people can be less inclined to challenge a faulty/inaccurate assumption just because they might have a hard time articulating their disagreement or because they've had less experience exercising critical thinking where they're encouraged to challenge an assumption/the status quo.

I totally agree with this sentence because for some surveys even as a responder, I feel like the question is somehow swaying me in a certain direction to an answer. For example, when surveys are coming from school, but are not anonymous, I feel guided to say something good or only given certain choices of answer to choose from when I have other things I wish to answer as. But overall I think the idea is that it's really important to focus on creating a place where everyone feels safe and comfortable to truly express themselves.

I agree that double barreled questions shouldn't be asked. I think it can be confusing because the participant will wonder which concept to talk about if there are multiple asked in the question. I think when creating questions, this is something I have to closely pay attention to because I may not realise I am doing it. I wonder, if I am thinking a question I ask might be asking about two things, should I ask the question with one concept, and then just make the second concept a part of that question as a follow up, or make two separate questions for each concept?

ohhh

A spillover is when a virus or pathogen that usually lives in animals crosses over and infects humans. It happens when people come into close contact with animals that carry the virus or with things contaminated by them. Most spillovers don’t cause large outbreaks, but each one gives the virus a chance to adapt and spread.

Privacy would be the most important and personal type of information for each person in the world. So, how do we protect our privacy to avoid unexpected things happening? Privacy is about control, which means once peopel control themselves to avoid share their personal privacy information in the website, they would be safe.

I've rethought what privacy actually means online. I've always assumed my personal information was private and secure, but this reflects the trust we've unwittingly placed in these platforms. Once information is uploaded online, is it truly private? Even if we delete something, a copy might still remain on the server. So, I'm now unsure if deletion is even necessary.

This example surprised me. Usually when I think of the idea of privacy, I think of it as something that needs to be respected at all costs across social media, especially by the company running the site. Each user's information and habits are their own and should not be easily viewable by the company. However, this example of death threats and harassment is something that most definitely has happened before and will happen again. In this instance, I would 100% want the company to be able to access my private messages. In this case, a disruption of privacy would be ethical, because it is in the intention of creating safety and protection. Instances like these should be the exceptions to the general rule of privacy.

if upstream repo changes the URL, need this

I feel like the API calls are the most important for the largest websites that contain a bunch of information. Such as some of the recipe websites, the API calls from them had already generated all of the categories for users who call API calls to use. During my personal project, I usually use API calls from a website.

Washington still mentions the Patriots after the revolution where nothing really changed right then and there except British inclusion really made me think is there more to what he is trying to say in this farewell message. I think he is still saying America isn't as untied as the thought it would be and should maintain working on it as the years go by to make it better. I'm glad Washington is speaking his mind through this message and what should happen as America continues to grow.

I simply agree to these annotations in this section because what Madison is directly doing is supporting religious causes of the church.

It is interesting to see that Scholarly Publishing is very profitable.

Most classes I have taken the textbook is right at my fingertips on the computer. It makes life a lot easier than toting around heavy books that I don't know what to do with when class ends.

This is a curious claim that I cannot substantiate. After looking around, I see the same claim in Wikipedia's article for Copyright renewal in the United States, but the cited source (Fishman, Stephen; 2010. The Public Domain: How to Find & Use Copyright-Free Writings, Music, Art & More) doesn't appear to provide a robust citation. (On page 287 in Chapter 15, Fishman writes, "The Copyright Office estimates that only about 15% of pre-1964 published works were ever renewed", unaccompanied by a footnote.) One also notices that 1961 and 1964 are not the same year.

I stumble across a similar claim ("a 1961 report from the U.S. Copyright Office estimates that 85% of the books never had the copyrights renewed") on lcgsco.org, which disappointingly turns out to be the website for "Larimer County Genealogical Society", with no link to the report in question.

The Copyright Office does make available its historical archive of annual reports at https://www.copyright.gov/history/annual_reports.html. Could its annual report be the one referred to? Searching for the string "renewal" in the 1961 annual report turns up two noteworthy occurrences (out of a reported nine):

1. on page 2, a claim related to renewals mentioning a "15 percent" figure

2. on page 16, a description of "Studies 29–31 [… including …] 31. Renewal of Copyright"

The full sentence on page 2 where the "15 percent" figure appears is actually that "The year's increase in registrations was nearly 3 percent, this was counting a 15 percent decrease in renewal registrations, the result of the corresponding decrease in original regisrations 28 years previously." This is, troublingly, not the same thing as fewer than 15% of copyright registrations until 1961 being renewed. (It is not even the same as only 15% of registrations up for renewal in 1961 being renewed.) It is a 15% decrease in renewals relative to the prior year, i.e., number of renewals in 1961 compared to the number of renewals in 1960. If this is the report that the is meant to be the source for those claims of 85% non-renewal, it then it fails verification.

I have also come across a reference for renewal figures in a 2008 article in D-Lib Magazine (Peter B. Hirtle, "Copyright Renewal, Copyright Restoration, and the Difficulty of Determining Copyright Status"). Footnote 4 there cites the same Study 31 (attributed to a Barbara Ringer). Interestingly, it is not cited as a way to substantiate the 15% claim, but instead that "only 7% of registered copyrighted books" were renewed. It's not clear from context whether that claim is meant to be about the full range of potential renewals up to 1961, or merely the subset of works up for renewal in 1961.

At the time of this comment, I have not yet looked into Study 31 itself. I expect it to contain answers.

eLife Assessment

This study provides valuable insights into the influence of sex on bile acid metabolism and the risk of hepatocellular carcinoma (HCC). The data to support that there are inter-relationships between sex, bile acids, and HCC in mice are convincing, although this is a largely descriptive study. Future studies are needed to understand the interaction of sex hormones, bile acids, and chronic liver diseases and cancer at a mechanistic level. Also, there is not enough evidence to determine the clinical significance of the findings given the differences in bile acid composition between mice and men.

Reviewer #1 (Public review):

Liver cancer shows a high incidence in males than females with incompletely understood causes. This study utilized a mouse model that lacks the bile acid feedback mechanisms (FXR/SHP DKO mice) to study how dysregulation of bile acid homeostasis and a high circulating bile acid may underlie the gender-dependent prevalence and prognosis of HCC. By transcriptomics analysis comparing male and female mice, unique sets of gene signatures were identified and correlated with HCC outcomes in human patients. The study showed that ovariectomy procedure increased HCC incidence in female FXR/SHP DKO mice that were otherwise resistant to age-dependent HCC development, and that removing bile acids by blocking intestine bile acid absorption reduced HCC progression in FXR/SHP DKO mice. Based on these findings, the authors suggest that gender-dependent bile acid metabolism may play a role in the male-dominant HCC incidence, and that reducing bile acid level and signaling may be beneficial in HCC treatment. This study include many strengths: 1. Chronic liver diseases often proceed the development of liver and bile duct cancer. Advanced chronic liver diseases are often associated with dysregulation of bile acid homeostasis and cholestasis. This study takes advantage of a unique FXR/SHP DKO model that develop high organ bile acid exposure and spontaneous age-dependent HCC development in males but not females to identify unique HCC-associated gene signatures. The study showed that the unique gene signature in female DKO mice that had lower HCC incidence also correlated with lower grade HCC and better survival in human HCC patients. 2. The study also suggests that differentially regulated bile acid signaling or gender-dependent response to altered bile acids may contribute to gender-dependent susceptibility to HCC development and/or progression. 3. The sex-dependent differences in bile acid-mediated pathology clearly exist but are still not fully understood at the mechanistic level. Female mice have been shown to be more sensitive to bile acid toxicity in a few cholestasis models, while this study showed a male dominance of bile acid promotion of HCC. This study used ovariectomy to demonstrate that female hormones are possible underlying factors. Future studies are needed to understand the interaction of sex hormones, bile acids, and chronic liver diseases and cancer.

I've come across lots of claims online (e.g. https://lcgsco.org/the-majority-of-books-published-before-1964-are-free-of-copyrights/ and the current revision of the Wikipedia article on copyright renewal in the United States) that "A US Copyright Office study in 1961 found that fewer than 15% of registered copyrights had been renewed". I haven't been able to substantiate this claim, however.

Could this passage be the source? It clearly doesn't line up with the claim.

The Los Rios Community College District seems to want the best education for their students. Investing in your students education invests in your future as a college.

Who are the privileged few? Why is there a lock on what we can learn?

It is alarming how much more profitable academic publishing is than retail. Education should be available to everyone. Many people hold back on getting an education or continuing an education because of cost.

Academic information should be readily available to anyone that wishes to use it. What would the world be without access to academic information?

eLife Assessment

This is an important study of critical period plasticity, focused on temperature manipulations, and how different parts of the Drosophila larval motor circuit adapt or maladapt. The work convincingly demonstrates that components of the motor network respond in distinct ways to the heat shock, and the combination of functional, structural, and electrophysiological approaches makes the study of significant interest. The work points to central interneurons as primary drivers of maladaptive changes, while motoneurons and neuromuscular junctions show compensatory or homeostatic adjustments. The study is methodologically rigorous, contributing significant insights into critical period biology using a tractable invertebrate model.

Reviewer #1 (Public review):

Summary:

The authors examine the impact of heat stress during an embryonic CP in Drosophila, focusing on the larval locomotor network. They show that elevated temperature increases neuronal activity and, when applied during the CP, results in long-term instability of the network, which manifests in prolonged seizure recovery times. At the neuromuscular junction, substantial structural changes occur, including terminal overgrowth and altered receptor composition, yet synaptic transmission remains preserved due to homeostatic regulation. Motoneurons display reduced excitability but receive increased synaptic input from premotor interneurons. These findings suggest that maladaptive instability originates within the central circuitry rather than at the neuromuscular junction, where changes seem to be homeostatically compensated. The study concludes that different network components exhibit distinct and hierarchical responses to CP perturbations, with premotor interneurons setting the tone for downstream adjustments in motoneurons.

Strengths:

The work takes advantage of the unique accessibility of the Drosophila system. A major strength of the study is the integration of structural, physiological, and behavioral analyses, which allows the authors to draw a comprehensive picture of how CP perturbations shape the locomotor network. The choice of an ecologically relevant stimulus (heat stress) is particularly convincing, as it links experimental manipulations more closely to natural environmental conditions. The experiments are carefully designed, and the results are robust and consistent with previous findings in the field, while also extending them in new directions.

Weaknesses:

The study leaves some uncertainty regarding the experimental design and interpretation. The change from short to prolonged heat shock manipulations raises the possibility that the effects observed may not be confined to the critical period alone - this could be experimentally addressed or simply rephrased in the text. In addition, the maladaptive (seizure recovery) and adaptive/homeostatic phenotypes are not always clearly distinguished or highlighted, which makes it harder to appreciate how the different levels of the network plasticity fit together into a single mechanistic framework.

Reviewer #2 (Public review):

Summary:

This manuscript presents a thoughtful and well-executed study of critical period plasticity in the Drosophila larval motor circuit. The authors examined how transient heat, 32 {degree sign}C, during the embryonic stage, altered network properties, showing that premotor interneurons A27h increase excitatory drive onto motoneurons, which respond with a reduction in excitability. At the NMJ, synaptic terminals expand and GluRIIA distribution shifts, yet synaptic transmission remains largely unaffected. Despite these local compensations, the treated larvae display slower crawling and prolonged recovery from seizures, indicating that the network is functionally compromised.

Strengths:

(1) One of the major strengths of this study is the elegant dissection of a defined circuit, tracking changes from premotor interneurons through motoneurons to the NMJ. The multimodal approach provides a comprehensive view of how connected elements respond to CP perturbations.

(2) An interesting finding is that NMJ morphology changes dramatically without corresponding deficits in synaptic transmission, challenging the common assumption that larger boutons necessarily indicate stronger synapses.

(3) Another intriguing result is that even with two layers of homeostatic compensation, locomotor behavior is still impaired, highlighting the limits of compensation and underscoring the critical role of CP timing.

(4) Beyond these scientific insights, the study benefits from a well-defined, tractable system and simple experimental manipulations, which together make the results highly interpretable and reproducible.

Weaknesses:

There are a few areas where the manuscript could be strengthened.

(1) Although A27h premotor neurons are well characterized, the claim that they are the causal driver of downstream changes would be strengthened by additional experiments or a clearer discussion of the temporal hierarchy.

(2) While 32 {degree sign}C heat stress is presented as ecologically relevant, it produces maladaptive behavioral outcomes, raising questions about the ecological and mechanistic interpretation of the model. In particular, most experiments, with the exception of Figure 1, used prolonged (24h) heat treatments, which could introduce developmental effects beyond the CP itself. Comparing shorter and longer heat exposures would help clarify the specificity of the CP response.

(3) While there are schematics for experimental procedures, a circuit diagram tracing information flow and indicating where structural and functional changes occur would help readers better understand the findings.

(4) Finally, the main paradox of the study, that robust homeostatic compensations occur yet behavior remains impaired, could be explored in more depth in the Discussion.

Reviewer #3 (Public review):

Summary:

During development, neural circuits undergo brief windows of heightened neuronal plasticity (e.g., critical periods) that are thought to set the lifelong functional properties of underlying circuits. These authors, in addition to others within the Drosophila community, previously characterized a critical period in late fly embryonic development, during which alterations to neuronal activity impact late-stage larval crawling behavior. In the current study, the authors use an ethologically-relevant activation paradigm (increased temperature) to boost motor activity during embryogenesis, followed by a series of electrophysiology and imaging-based experiments to explore how 3 distinct levels of the circuit remodel in response to increases in embryonic motor activity. Specifically, they find that each level of the circuit responds differently, with increased excitatory drive from excitatory pre-motor neurons, reduced excitability in motor neurons, and no physiological changes at the NMJ despite dramatic morphological differences. Together, these data suggest that early life experience in the motor neuron drives compensatory changes at each level of the circuit to stabilize overall network output.

Strengths:

The study was well-written, and the data presented were clear and an important contribution to the field.

Weaknesses:

The sample sizes and what they referred to throughout the distinct studies were unclear. In the legends, the authors should clearly state for each experiment N=X, and if N refers to an NMJ, for example, instead of an individual animal, they should state N=X NMJs per N=X animals. This will help readers better understand the statistical impact of the study.

I still find this an astute recognition as indeed I think our position towards the university has become more negative, while both also address different audiences. The article is an appeal to universities, this booklet is an attempt at collectivising within/without the university

This is great

It seems things have gotten so much worse so quickly

This seems a bit outdated now, given the trajectory APCs went. I wonder whether the article's authors would still feel like this about APCs now.

I wonder to what extent this has been adopted in LIS education since the article was published?

Is the underlying issue connected to how we value scholarly work?

Was information a public good before?

Is it only the organisation of the 'apparatuses that govern society's presentation'. And does organisation mean capitalism?

monthly composites based on instantaneous [fv] and [uv]?

not just by latitude, also by longitude

eLife Assessment

This study provides important evidence that negative affect is associated with slower cognitive processing in daily life, with findings replicated across three independent samples and supported by rigorous statistical analyses. The strength of evidence is convincing, though reliance on a proxy measure of processing speed limits the completeness of the conclusions.

Reviewer #1 (Public review):

Summary:

A study researching the relationship between affective shifts and cognitive performance in a daily life setting.

Strengths:

The evidence provided is compelling: the findings are conceptually replicated in three samples of adequate size and statistical rigor in analyzing the data, with methods beyond the current state of the art in applied research. For example, using two-step multilevel vector autoregressive models that were adopted to allow the inclusion of covariates, and contemporaneous effects corrected for temporal relations and background covariates. In addition, the authors use beautiful visualizations to convey the different samples used (Figure 1) and intuitive and rich figures to convey their obtained results.

In summary, the authors were able to convincingly show that higher negative affect is linked to slower cognitive processing speed, with results supporting their conclusions.

Weaknesses:

I have one major concern. Although a check for careless responding has been conducted on the basis of long reaction times, I wonder whether, beyond long response times, any other sanity checks with respect to, e.g., careless responding were done? For example, a lack of variability of EMA items over subsequent occasions, e.g., say 15, is often seen as an indicator of careless responding, especially when using VAS items. In line 693, it is stated, "We added a small amount of random noise, ranging from -0.1 to +0.1, to each EMA time series to allow models to converge when EMA time series showed minimal variance over time", which I understand, but this lack of variability could also be caused by participants stopping to take the study seriously. For datasets 1 and 2, this might be more difficult to assess (due to the limited response values), but maybe the authors can get an indication of this in dataset 3?

Reviewer #2 (Public review):

Summary:

In this paper, Fittipaldi et al. assessed whether cognitive processing speed - as operationalized by the Digital Questionnaire Response Time (DQRT) - and affect (both positive and negative) are related in contemporaneous and temporaneous ways, both between and within-subject. At the between-person level, they found positive relationships with DQRT and negative affect, and the opposite for positive affect. This was similar at the within-subject contemporaneous level.

The authors further test Granger-causality in the dynamics, for both Affect -> DQRT and DQRT -> Affect. They find that affect and t-1 is associated with DQRT in the same manner as in the other models (positively for negative affect, and negatively for positive affect). Interestingly, DQRT -> Affect was largely non-significant for most affect items.

This study adds important information on the associations between affect and cognitive measures outside the lab, showcasing a methodological approach to translate laboratory research to new contexts.

Strengths

Overall, this study has a strong methodological approach, which is commendable. The use of three independent samples with different affective measures is a good way to showcase the validity of the findings. The multi-level modelling approach is also done thoroughly and appropriately within the context of MLVAR modelling. The findings are also well visualized, making it easy to follow along with the interconnected and potentially confusing analyses.

Weaknesses

The authors use the DQRT as a measure of cognitive processing, which isn't fully validated or substantiated as such. The authors do address this as a limitation, but I believe it warrants a much broader discussion, as the construct being assessed may not be the construct intended by the authors. This makes it difficult to ascertain whether the conclusion drawn (that affect impacts cognitive function) is valid. I would rather frame it that there are associations between affect and response times, which can indicate many different things, be it potentially careless responding or other mechanisms at play.

eddy driven jet stuff

describes the lessons to be learned from post-war Bosnia: equality is contested concept and that dif groups and reps are very aware of dangers of exclusion and discrimination, inclusion of some groups might lead to exclusion and institutions to include may turn out ot be exclusive and discriminatory, and necessity for time to adapt and be flexible. other post-conflict situtations interact with this issue of equality so to address the author argues it needs, precise constitutional mechs and protection of certain rights and that they need to be allowed to change/evolve over time

B&H has most complicated pol system because it combines mutli-d federal system with power-sharing amongst elites form three constituent peoples. its institutional framework served to end the 1992-1995 war and lay foundation for elite cooperation and fed.

Always a lot of questions about this part about how far out to search for genes - Might think to add a subquestion, how far does it make sense to look, then telling them to look at the 2 closest ones at each side

the immediate recognition of the dismemberment from the US could also be from ideological differences as Milosevic was seen as a communist leader of serbia more than his nationalism that he shared with other Yugoslavian leaders. US was able to frame Serbia and Slovene-Croat as communist vs democracy.

an assumption that would connect EU and US in the quick dismemberment of Yugoslavia is realted to how powerful/large the Yugoslavian army was. additionally, its suspected that american recognition of the independence of B&H was becuase they were known to induce open warfare in Yugoslavia. plus, Bosnia had the highest concentration of military industries, therefore supporting the separation ensured a rapid debilitation for Yugoslavia

emphasises the international communities involvement with the Yugoslavian responsible disintegration of Yugoslavia. There was a mix of open political support and ready acceptance of the dismemberment of Yugoslavia.

describes the series of proclamations of independence from Slovenia and Croatia, the recognition and acceptance of Slovenia, Croatia, and B&H into the UN, the civil war that broke out amongst the disintegration that the European Union and US legally intervened with to turn it into an international conflict, and the UN Security Council imposing sanctions on Yugoslavia.

Plug-in hybrid vehicles (PHEVs) are not as environmentally friendly as previously claimed, according to recent EU data.

• Real-world emissions from PHEVs average 135 g CO₂/km, only 19% less than conventional petrol and diesel cars which average 166 g CO₂/km.
• Official WLTP tests significantly underestimate emissions; PHEVs often run on the combustion engine, even in electric mode, increasing real fuel consumption.
• In electric-only mode, PHEVs still burn around 3 liters of petrol per 100 km, resulting in emissions of 68 g CO₂/km—over eight times higher than manufacturers’ claims.
• Hidden fuel consumption costs drivers approximately 500 euros per year more than official manufacturer data suggests.
• PHEVs are among the most expensive on the market; average price in 2025 in Germany, France and the UK is 55,700 euros, about 15,000 euros higher than average battery-only electric cars.
• Increasing electric range through larger batteries does not reduce emissions; heavier vehicles consume more fuel and energy overall.
• PHEVs with electric ranges above 75 km emit more CO₂ on average than those with ranges of 45–75 km.
• The biggest discrepancies are noted for Mercedes-Benz plug-in hybrids; in 2023, their real emissions exceeded official figures by an average of 494%, with the GLE-Class over by 611%.
• Automotive industry is lobbying to have PHEVs recognized as low-emission beyond 2035, despite new EU regulations that require the transition to zero-emission vehicles.
• Weakening EU regulations could undermine the development and adoption of truly zero-emission technologies.
• According to Transport & Environment, plug-in hybrids are “one of the biggest myths in motoring,” often emitting almost as much as combustion-engine cars and much more than test results indicate.
• EEA and T&E data casts doubt on PHEVs as effective solutions for transportation decarbonization; their environmental benefits are increasingly questioned.

I think whether violating privacy of users is good or bad depends on the purpose of doing that. Some social media companies violate users' privacy because they want to make sure the users' actions on the platform are legal. There are so many fake accounts and scams on the social media, so some companies might violate these users' privacy in order to protect other users from being victimized. But like we learned from last chapter, one of the main goal of social medias is to increase the time users spend on their platforms. And I think they also want users on their platforms to be as more as possible. So they might collect users and non-users' data and analyze these data without getting permission.

непонятно почему 1. как-будто и там и там мы передаём его столько раз, сколько всего процессов. То есть экономия не насколько сильная

не очень понятно как это должно рабоать. Сначала мы говорим что если несколько пользователей смотрят один порт, он может гарантировать доставку только до одного из них, а потом что всё взаимодействие группы строится вокруг одного порта, который могут также читать снаружи. как-будто это не очень удобный метод

Если честно, не очень понял как конкретно будет выглядеть accept message. Мы же должны как-то по его содержанию понять на какое именно сообщение мы отослали accept message. Мне сразу подумалось, что можно дополнительно ввести хеш-функцию для сообщений и вместе с sqeuence number'ом отправлять в accept message ещё и хеш сообщения, которое мы хотим заакцептить. Тогда узлы, принимающие accept message смогут понять, на какое именно сообщение пришло подтверждение от sequencer'а.

Compare this with the limit notation introduced in Chapter 5 below the definition of continuity.

eLife Assessment

This important work develops the C. elegans as a model organism for studying effort-based discounting by asking the worms to choose between patches of easy and hard to digest bacteria. The authors provide convincing evidence that the nematodes are effort discounting. They also provide solid evidence of involvement of dopamine in the food preference and that the finding is not restricted to lab-acclimated strains.

Reviewer #1 (Public review):

Summary:

Millet et al. show that C. elegans systematically prefers easy-to-eat bacteria but will switch its choice when harder-to-eat bacteria are offered at higher densities, producing indifference points that fit standard economic discounting models. Detailed kinetic analysis reveals that this bias arises from unchanged patch-entry rates but significantly elevated exit rates on effortful food, and dop-3 mutants lose the preference altogether, implicating dopamine in effort sensitivity. These findings extend effort-discounting behavior to a simple nematode, pushing the phylogenetic boundary of economic cost-benefit decision-making.

Strengths:

Extends the well-characterized concept of effort discounting into C. elegans, setting a new phylogenetic boundary and opening invertebrate genetics to economic-behavior studies.

Elegant use of cephalexin-elongated bacteria to manipulate "effort" without altering nutritional or olfactory cues, yielding clear preference reversals and reproducible indifference points.

Application of standard discounting models to predict novel indifference points is both rigorous and quantitatively satisfying, reinforcing the interpretation of worm behavior in economic terms.

The three-state patch-model cleanly separates entry and exit dynamics, showing that increased leaving rates-rather than altered re-entry-drive choice biases.

Demonstrates that _dop-3_ mutants lose normal effort discounting, firmly tying monoaminergic signaling to this behavior and paralleling vertebrate findings.

Demonstration of discounting in wild strain (solid evidence).

Weaknesses:

Only _dop-3_ shows an effect, whereas _cat-2_/_dat-1_ do not, leaving the broader role of dopamine synthesis and reuptake ambiguous.

With only five wild isolates tested, and only one clearly showing clear evidence of preference for the easy to eat bacteria, it's hard to conclude that effort discounting isn't a lab-strain artifact or how broadly it varies in natural populations.

Reviewer #2 (Public review):

Summary:

Here Millet et al. adapted a t-maze paradigm for use in C. elegans to understand whether nematodes exhibit effort discounting behaviors comparable to other species. C. elegans worms were reliably sensitive to how effortful the food was to consume, allowing for the application of standard economic models of decision-making to be applied to their behavior. The authors then demonstrated the necessity of dopamine signaling for this behavior, identifying dop-3 mutants in particular as insensitive to effort. Together, this work establishes a new model system for the study of discounting behavior in cost-benefit decision-making.

Strengths:

The question is well-motivated and the approach taken here is novel; it is uncommon for worms to undergo such behavioural procedures (although this lab has previously been integral to pushing the extent of the complexity of behaviours studied in C. elegans). The authors are careful in their approach to altering and testing the properties of the elongated bacteria. Similarly, they go to some effort to understand what exactly is driving behavioural choices in this context, both through application of simple standard models of effort discounting and a kinetic analysis of patch leaving. The comparisons to various dopamine mutants further extends the translational potential of their findings. I also appreciate the comparison to natural isolate strains as the question of whether this behaviour may be driven by some sort of strain-specific adaptation to the environment is not regularly addressed in mammalian counterparts to this work.

Weaknesses:

The authors have now addressed concerns about whether the mechanisms underlying the choice behavior here are generalizable to other organisms. Specifically, their work speaks to foraging-inspired effort discounting paradigms in rodents and humans in which the decision is whether to stay or leave a given resource, rather than to simultaneous decision-making across two options in a T-maze.

The dopamine results are interesting but still difficult to interpret. As the authors discuss, the lack of an effect in the cat-2 and dat-1 mutants is surprising given the effect in the dop-3 mutants. Understanding what exactly the role of dop-3 is here therefore requires further study.

Reviewer #3 (Public review):

Summary:

The authors establish a behavioral task to explore effort discounting in C. elegans. By using bacterial food that takes longer to consume, the authors show that for equivalent effort, as measured by pumping rate, animals obtain less food, as measured by fat deposition.

The authors formalize the task by applying a neuroeconomic decision making model that includes, value, effort, and discounting. They use this to estimate the discounting C. elegans apply based on ingestion effort by using a population level 2-choice T-maze.

They then analyze the behavioral dynamics of individual animals transitioning between on-food and off-food states. Harder to ingest bacteria led to increased food patch leaving.

Finally, they examined a set of mutants defective in different aspects of dopamine signaling, as dopamine plays a key role in discounting in vertebrates and regulates certain aspects of C. elegans foraging.

In their response to the first set of reviews, the authors take care to ensure their task is analogous to at least some of those used in mammals and make changes to the text to better clarify some of their conclusions. My view is the same--that this is an interesting paper for methodological and scientific reasons that brings an important theoretical framework to bear on C. elegans foraging behavior. While I think the mutant results are somewhat unsatisfying, this is not the principal contribution of the work.

Strengths:

The behavioral experiments and neuroeconomic analysis framework are compelling and interesting and make a significant contribution to the field. While these foraging behaviors have been extensively studied, few include clearly articulated theoretical models to be tested.

Demonstrating that C. elegans effort discounting fits model predictions and has stable indifference points is important for establishing these tasks as a model for decision making.

Weaknesses:

The dopamine experiments are harder to interpret. The authors point out the perplexing lack of an effect of dat-1 and cat-2. dop-3 leads to general indifference. I am not sure this is the expected result if the argument is a parallel functional role to discounting in vertebrates. dop-3 causes a range of locomotor phenotypes and may affect feeding (reduced fat storage), and thus there may be a general defect in the ability to perform the task rather than anything specific to discounting.

That said, some of the other DA mutants also have locomotor defects and do not differ from N2. But there is no clear result here-my concern is that global mutants in such a critical pathway exhibit such pleiotropy that it's difficult to conclude there is a clear and specific role for DA in effort discounting. This would require more targeted or cell-specific approaches. The authors state these experiments are outside the scope of the current study, and that at minimum their results implicate dopamine signaling in some form. I tend to agree but still think locomotion defects of DA mutants complicate this question.

Meanwhile, there are other pathways known to affect responses to food and patch leaving decisions-5HT, PDF, tyramine, etc. in their response the authors state they focus on dopamine because of its role in discounting behavior in mammals.

Author response:

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

Reviewer #1(Public Reviews):

Summary: 

Here, Millet et al. consider whether the nematode C. elegans 'discounts' the value of reward due to effort in a manner similar to that shown in other species, including rodents and humans. They designed a T-maze effort choice paradigm inspired by previous literature, but manipulated how effortful the food is to consume.C. elegans worms were sensitive to this novel manipulation, exhibiting effort-discountinglike behaviour that could be shaped by varying the density of food at each alternative in order to calculate an indifference point. This discounting-like behaviour was related to worms' rates of patch leaving, which differed between the low and high effort patches in isolation. The authors also found a potential relationship to dopamine signalling, and also that this discounting behaviour was not specific to lab-based strains of C. elegans . 

Strengths: 

The question is well-motivated, and the approach taken here is novel. The authors are careful in their approach to altering and testing the properties of the effortful, elongated bacteria. Similarly, they go to some effort to understand what exactly is driving behavioural choices in this context, both through the application of simple standard models of effort discounting and a kinetic analysis of patch leaving. The comparisons to various dopamine mutants further extend the translational potential of their findings. I also appreciate the comparison to natural isolate strains, as the question of whether this behaviour may be driven by some sort of strain-specific adaptation to the environment is not regularly addressed in mammalian counterparts. The manuscript is well-written, and the figures are clear and comprehensible. 

Weaknesses: 

Discounting is typically defined as the alteration of a subjective value by effort (or time, risk, etc.), which is then used to guide future decision-making. By adapting the standard t-maze task for C. elegans as a patch-leaving paradigm, the authors observe behaviour strongly consistent with discounting models, but that is likely driven by a different process, in particular by an online estimate of the type of food in the current patch, which then influences patch-leaving dynamics (Figure 3). This is fundamentally different from decision-making strategies relating to effort that have been described in the rodent and human literatures. 

We agree that in our study worms are likely making an on-line estimate of food quality in the current patch, but we wish to point out that rodents and humans also use on-line estimates in some significant effort-discounting paradigms. With respect to rodents, we call attention to effort discounting studies involving the widely used progressive ratio task (references in Discussion). In this task, animals can either lever-press for a preferred food or consume a less preferred food that is freely available nearby. However, the number of lever presses required to obtain preferred food increases as a function of the cumulative number of lever presses until the effort-cost of obtaining preferred food becomes too high and the animal switches to a freely available food. In essence, the lever and the freely available food are patches and the animal decides whether or not to leave the “lever” patch. It seems inescapable that the progressive ratio task involves an on-line assessment of the cost/benefit relationship associated with lever pressing. With respect to humans, one highly cited study (reference in Discussion) presented participants with a series of virtual apple trees. They could see how many apples are in the current tree and how much effort (squeezing a handgrip) is required to gather them. Their task was to decide whether or not to gather apples from that tree based on the perceived cost and benefit. Thus, on-line estimation is a common strategy used by animals and humans as shown in the effort discounting literature. We now make this point in the Discussion section titled A model of effort-discounting like behavior.

Similarly, the calculation of indifference points at the group instead of at the individual level also suggests a different underlying process and limits the translational potential of their findings. The authors do not discuss the implications of these differences or why they chose not to attempt a more analogous trial-based experiment.  

It is not clear to us why changing the read-out –– from the individual level to the population level –– necessarily suggests that a different biological mechanism is at work. In our view, there is one mechanism and it can be seen from different perspectives (e.g., individual vs population). Furthermore, the analogous trial-based experiment, as we understand it, would be to record behavior one worm at a time in the T-maze. This design is not practical because it entails recording a large number of single worms in the T-maze for 60 min each. 

In the case of both the dopamine and natural isolate experiments, the data are very noisy despite large (relative to other C. elegans experiments) sample sizes. In the dopamine experiment, disruption of dop1, dop-2, and cat-2 had no statistically significant effect. There do not appear to be any corrections for multiple comparisons, and the single significant comparison, for dop-3, had a small effect size. 

An ANOVA followed by a Dunnett test was used to test differences between groups in Fig. 4 and 5. The Dunnett test is a multiple comparison test comparing experimental groups to a single control group. It is used to minimize type I error while maintaining statistical power and does not require further correction for multiple comparisons. We have clarified the use of the Dunnett test in the statistical table.  The effect size for dop-3 is 0.5 (Cohen’s d), which is typically interpreted as a medium, not small, effect size.(e.g. Cohen, Psychological Bulletin, 1992, Vol. 112. No. 1,155-159). 

More detailed behavioural analyses on both these and the wild isolate strains, for example by applying their kinetic analysis, would likely give greater insight as to what is driving these inconsistent effects. 

More detailed behavioral analysis could reveal why we observe a difference in effort discounting in some strains and not others. However, it is not obvious what type of behavioral analysis would be needed to differentiate between pleiotropic effects of the mutations/natural isolates and more specific effects on effort discounting. A simple kinetic analysis in particular may not be enough to reveal relevant differences between mutants/natural isolates. For this reason, we think that such experiments may be better suited for future follow up studies.

Reviewer #2 (Public Reviews)

Summary: 

Millet et al. show that C. elegans systematically prefers easy-to-eat bacteria but will switch its choice when harder-to-eat bacteria are offered at higher densities, producing indifference points that fit standard economic discounting models. Detailed kinetic analysis reveals that this bias arises from unchanged patch-entry rates but significantly elevated exit rates on effortful food, and dop-3 mutants lose the preference altogether, implicating dopamine in effort sensitivity. These findings extend effortdiscounting behavior to a simple nematode, pushing the phylogenetic boundary of economic costbenefit decision-making. 

Strengths: 

(1) Extends the well-characterized concept of effort discounting into C. elegans , setting a new phylogenetic boundary and opening invertebrate genetics to economic-behavior studies. 

(2) Elegant use of cephalexin-elongated bacteria to manipulate "effort" without altering nutritional or olfactory cues, yielding clear preference reversals and reproducible indifference points. 

(3) Application of standard discounting models to predict novel indifference points is both rigorous and quantitatively satisfying, reinforcing the interpretation of worm behavior in economic terms. 

(4) The three-state patch-model cleanly separates entry and exit dynamics, showing that increased leaving rates-rather than altered re-entry-drive choice biases. 

(5) Investigates the role of dopamine in this behavior to try to establish shared mechanisms with vertebrates. 

(6) Demonstration of discounting in wild strain (solid evidence). 

Weaknesses: 

(1) The kinetic model omits rich trajectory details-such as turning angles or hazard functions-that could distinguish a bona fide roaming transition from other exit behaviors. 

The overarching goal of present paper was to develop a simple model for effort discounting in a small, genetically tractable organism.  Accordingly,  we focused on quantitative assays that are easy to implement and analyze. The patch-leaving assay and its associated kinetic analysis are one such assay. To keep things simple in this assay, we counted the number of  transitions between the three states shown in Fig. 3A. We chose not to analyze the data in terms of turning angles or hazard functions because the metrics we developed seemed sufficient. Finally, we note that there are new modeling data showing that the presumptive transitions into the roaming state can be explained in terms of a one-state stochastic model in which there is no discrete roaming state (Elife. 2025 Jul 30;14:RP104972. doi:

10.7554/eLife.104972.PMID: 40736321).

(2) Only dop-3 shows an effect, and the statistical validity of this result is questionable. It is not clear if the authors corrected for multiple comparisons, and the effect size is quite small and noisy, given the large number of worms tested. Other mutants do not show effects. Given these two concerns, the role of dopamine in C. elegans effort discounting was unconvincing. 

An ANOVA followed by a Dunnett test was used to test statistical significance in figures 4 and 5 (see above for a discussion of these tests). We believe this approach is rigorous, and the use of these tests is statistically valid. We note that the effect size for this comparison was medium.

(3) With only five wild isolates tested (and variable data quality), it's hard to conclude that effort discounting isn't a lab-strain artifact or how broadly it varies in natural populations. 

The fact that four of the five natural isolates tested display levels of effort discounting similar to N2 (only one natural isolate does not display effort discounting) argues against effort discounting being a laboratory adaption.  We have nevertheless weakened the claim regarding natural isolates. We now say effort discounting-like behavior may not be an adaptation to the laboratory environment.  

(4) Detailed analysis of behavior beyond preference indices would strengthen the dopamine link and the claim of effort discounting in wild strains. 

Going beyond preference in the behavioral analysis might or might not reveal new phenotypes that strengthen the link with dopamine. At present, however, we think such experiments are beyond the scope of the paper.

(5) A few mechanistic statements (e.g., tying satiety exclusively to nutrient signals) would benefit from explicit citations or brief clarifications for non-worm specialists. 

We are unable to identify a mechanistic statement tying satiety to nutrient signals in our manuscript.

Reviewer #3 (Public Reviews)

Summary: 

The authors establish a behavioral task to explore effort discounting in C. eleganss . By using bacterial food that takes longer to consume, the authors show that, for equivalent effort, as measured by pumping rate, they obtain less food, as measured by fat deposition. The authors formalize the task by applying a formal neuroeconomic decision-making model that includes value, effort, and discounting. They use this to estimate the discounting that C. elegans applies based on ingestion effort by using a population-level 2-choice T-maze. They then analyze the behavioral dynamics of individual animals transitioning between on-food and off-food states. Harder to ingest bacteria led to increased food patch leaving. Finally, they examined a set of mutants defective in different aspects of dopamine signaling, as dopamine plays a key role in discounting in vertebrates and regulates certain aspects of C. elegans foraging. 

Strengths: 

The behavioral experiments and neuroeconomic analysis framework are compelling, interesting, and make a significant contribution to the field. While these foraging behaviors have been extensively studied, few include clearly articulated theoretical models to be tested. 

Demonstrating that C. elegans effort discounting fits model predictions and has stable indifference points is important for establishing these tasks as a model for decision making. 

Weaknesses: 

The dopamine experiments are harder to interpret. The authors point out the perplexing lack of an effect of dat-1 and cat-2. dop-3 leads to general indifference. I am not sure this is the expected result if the argument is a parallel functional role to discounting in vertebrates. dop-3 causes a range of locomotor phenotypes and may affect feeding (reduced fat storage), and thus, there may be a general defect in the ability to perform the task rather than anything specific to discounting.

That said, some of the other DA mutants also have locomotor defects and do not differ from N2. But there is no clear result here - my concern is that global mutants in such a critical pathway exhibit such pleiotropy that it's difficult to conclude there is a clear and specific role for DA in effort discounting. This would require more targeted or cell-specific approaches. 

We agree with the reviewer that the results of the dopamine experiments are puzzling and getting a better understanding of the role of dopamine in effort-discounting will require more sensitive assays and different experimental approaches (e.g. cell-specific rescues). However, as mentioned by the reviewer, all the mutations tested have some pleiotropic effects, yet only dop-3 displays a defect in effort discounting. This, in our opinion, points to a specific role of dop-3 in effort-discounting in C. elegans. This point is now made in the Discussion in the section titled Role of dopamine signaling in effort discountinglike behavior.

Meanwhile, there are other pathways known to affect responses to food and patch leaving decisions: serotonin, pigment-dispersing factor, tyramine, etc. The paper would have benefited from a clarification about why these were not considered as promising candidates to test (in addition to or instead of dopamine). 

We focused on DA because of its well-established effect on effort discounting in rodents.

Testing other pathways is a goal for future research.

Reviewer #1 (Recommendations for the authors):

The current results are more a reframing of data gathered from a patch-leaving paradigm, but described in the form of economic choice modelling in which discounting is one possible explanation. One more parsimonious explanation that worms estimate in real-time some rate of reward and leave the patch at some threshold, consistent with canonical foraging models, previous experiments in C. elegans, and the authors' own data (Figure 3). Therefore, I am wary about some of the claims made in this manuscript, such as 'decision-making strategies based on effort-cost trade-offs are evolutionarily conserved'. 

These points are now addressed in the Discussion in a revised section titled A model of effortdiscounting like behavior. (i) We now call attention to the fact that our T-maze assay is a patch-leaving foraging paradigm. (ii) We now propose a revised model in which “worms make an on-line assessment of food value in the current patch which in turn alters patch-leaving dynamics, increasing the exit rates from cephalexin-treated patches as shown in Figure 3.” (iii) We now provide evidence from the rodent and human literature that the strategy of on-line assessment of reward value may be evolutionarily conserved in the case of a class of effort discounting tasks whose solution requires on-line assessments. 

If the reason the authors chose to do a patch-leaving style task rather than a traditional t-maze is because C. elegans is unable to retain the sort of information necessary to make such simultaneous decisions - e.g., if pre-training on the two options isn't possible - then this in itself suggests that mechanisms underlying these decisions in worms and mammals are unlikely to be the same. I mention this because I would like to suggest to the authors an alternative interpretation: that patch foraging is actually 'the' canonical computation that translates across species. This would, in fact, be nicely consistent with some other recent modelling work in humans, e.g., https://www.biorxiv.org/content/10.1101/2025.05.06.652482v1. 

Please see the previous response.

Reviewer #2 (Recommendations for the authors):

Can you provide a picture of the regular and CEPH bacteria? 

Done (see Figure 1––figure supplement 1).

Reviewer #3 (Recommendations for the authors):

I would recommend testing representative mutants in other pathways in the choice task. If possible, more targeted experiments with dop-3, including either cell-specific KOs or rescues, would very much strengthen this aspect of the paper. 

While valuable, these experiments are out of scope for the present study.

The message is pretty clear: start with why A value proposition.

The amount of money you can ask for something is primarily a function of perception (perceived value), and relative availability.

As such, the optimal cost for something is more of a psychological subjective function than an objective algorithmic process.

This obviously leaves aside the philosophical dimension of ethics.

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The authors do not wish to provide a response at this time.

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Referee #3

Evidence, reproducibility and clarity

Summary

The manuscript presents IGNITE (Inference of Gene Networks using Inverse kinetic Theory and Experiments), an unsupervised machine learning framework for constructing gene regulatory networks from single-cell RNA sequencing (scRNA-seq) data. IGNITE utilizes a kinetic inverse Ising model to infer gene interactions from binarized expression data and can predict genetic perturbation effects, such as those from knockout experiments. Although the application of inverse Ising models to network reconstruction is not entirely novel, IGNITE's specific implementation and its application to single-cell RNA sequencing data represent a new development. The method is tested on the transition from naive to formative states in murine pluripotent stem cells, a system the authors are highly knowledgeable about, and its performance is compared to state-of-the-art alternative methods.

Major concerns

My concern regards the generality of the method, particularly the entire pipeline presented, and the fairness of the performance comparison. These concerns can be easily addressed by the authors by better explaining their choices and their general applicability, and by toning down the conclusions about the comparison with existing inference methods.

The pre-processing steps are extensive, and their rationale is not always clear, though the results heavily depend on this analysis. Several steps appear to involve arbitrary choices optimized for specific outcomes, potentially introducing biases. The authors should better explain the rationale behind their choices to mitigate these concerns.

Specifically, part of the pipeline seems to be built to reproduce a specific expression pattern of 24 genes that some of the authors discovered in a previous paper. Although this prior knowledge could be useful and relevant in this specific system, it could limit the generality of the method. For example, the authors selected approximately 2000 genes based on prior knowledge and used a combination of t-SNE and UMAP for dimensionality reduction (although the two techniques have a similar goal). This specific combination seems to reproduce the pseudotime alignment the authors were expecting to find, but such prior information might not be available in general. Therefore, feature selection and the methods used to project data need more justification, especially if the goal is to create a general tool applicable across different biological systems.

Analogously, the clustering seems manually adjusted to match known expression patterns of 24 relevant genes, rather than being the result of an optimized clustering method. Additionally, the clusters overlap with different time points, raising concerns about potential batch effects. These issues should be addressed to strengthen the validity of the method.

The claims about the comparison with existing methods should be toned down. While the comparisons are useful and interesting, they might be biased due to the method's fine-tuning for the specific system studied. The claim that the model requires only scRNA-seq data is misleading, as strong prior biological knowledge was used to select, for example, the genes analyzed.

Significance

The manuscript is scientifically sound, clearly written, and deserves publication. The proposed method is quantitative, novel, theoretically grounded, and was tested in detail with appropriate null models and statistical methods. Moreover, IGNITE can be applied to various biological systems as the availability of scRNA-seq datasets is continuously growing. The paper will be of interest to a broad community of computational biologists and biology labs interested in gene regulation using scRNA-seq data.

The limitation, in my opinion, is the method's (particularly the pre-processing pipeline) fine-tuning for the specific biological system tested. Testing IGNITE on another biological system without pre-selected pre-processing steps or detailed biological priors would be more convincing and make the paper's conclusions much stronger. The comparison with other methods also may be slightly biased due to this fine-tuning.

My background is in statistical physics, with expertise in biological physics, specifically in mathematical modeling and data analysis in molecular biology.

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Referee #2

Evidence, reproducibility and clarity

Corridori et al introduce IGNITE, a computational framework to infer gene regulatory networks (GRNs) from scRNA-seq data leveraging the kinetic Ising model, which can be used to simulate synthetic gene expression and perform in-silico knockout experiments. Other similar frameworks exist, but none combine these three aspects together. The authors have generated a scRNA-seq of murine ESCs differentiation which they use to compare their method with others. Specifically they show that they can infer known regulatory interactions, that they can generate similar data than the original and that it can potentially predict gene expression changes in transcription factor knock-out perturbations.

Major comments:

• Many of the authors' claims are backed by qualitative results and not properly quantified. In Fig2, authors qualitatively compare intra gene correlations between genes for the original data and their prediction. Instead of just visualizing they should compute and report the Spearman correlation between the original expression and the predicted one. The Fraction of Agreement is not a good metric to compare knockout predictions since it is completely dependent on the class imbalance of signs, for example if the selected genes are 75% positive and 25% negative, a naive predictor that only outputs positive predictions will still have a high score. Instead, the authors should quantify this with Spearman correlation or RMSE and compare across methods. In FigS4a-b the authors qualitatively claim that other methods could not predict the expected cell composition, which they should quantify and report the values across methods. When comparing against the ground truth network, the fraction of correctly inferred interactions is technically the same as precision but is ignoring recall. I suggest the authors compute precision, recall and a combined F1 score to compare the evaluated methods. Authors claim that the method is scalable to a larger number of genes but no data is provided, they should show how their method compares to others when using a different number of cells and number of genes at memory usage and running time.
• The authors need to better describe which tests were performed when talking about significance, which thresholds and which corrections, if any, were employed.
• To reduce the number of dimensions of scRNA-seq data the authors use t-SNE and then from the obtained result UMAP to project the data into a lower dimensional space. This is fundamentally wrong since distances are not well preserved in t-SNE. Instead the authors should first employ PCA and then UMAP. Additionally, the authors use UMAP distances in the Slingshot pseudotime calculation. Similar to t-SNE, UMAP distances have no real meaning and should only be used for visualization purposes. Instead, the authors should provide Slingshot the obtained PCA embeddings.
• Dictys (PMID: 37537351) is a known GRN inference method that also can simulate gene expression but is missing in the benchmark, the authors should add it to the method comparison.
• The current manuscript is not reproducible since it is missing the method's code, the code to reproduce the figures and the generated scRNA-seq data.
• Authors claim that the method is scalable to a larger number of genes but no data is provided to back this claim. They should show how their method compares to others when using a different number of cells and number of genes.

Minor points:

• In the introduction, authors mention multimodal GRN inference methods but do not provide any references.
• In Table 1, CellOracle is annotated as not being able to do multiple KO which is wrong. Additionally, the authors mention that IGNITE uses no prior knowledge which is not really true since it requires pseudotime ordering. The authors should add a column to Table 1 whether methods require pseudotime.
• It is unclear what the dashed arrow of Fig1b means. Moreover, plotting gene expression values on top of UMAPs can be misleading, instead authors should plot the gene expression distributions binned by pseudotime.
• The authors report a p-value of 1.04x10-171 which is below detection limit (see PMID: 30921532). Authors should change it to an interval such as p < 2.2×10-16.
• To make CellOracle results easier to interpret and more comparable, authors should run it at the atlas level instead of at the cell type level, this way generating only one GRN. This can be achieved by assigning the same cluster label to all cells.
• Experimental values in FigS3b seem to have been repeated and do not match the previous ones for IGNITE and SCODE.
• It is unclear what the different circles mean in Fig5b.

Significance

This manuscript is an incremental and methodological work for specialized audiences. Its strengths are that the authors employ kinetic Ising model for GRN inference and that they provide a single framework capable of inferring, simulating and perturbing gene expression. The main limitations are that the claims should be better quantified and that the code and data need to be made accessible.

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Referee #1

Evidence, reproducibility and clarity

Summary

Corridori and colleagues propose IGNITE, a novel method to recover Gene Regulatory Networks (GRN) from single cell RNA-sequencing (scRNA-seq) data. Their method solves the inverse Ising problem generating a cohort of candidate GRN optimising it to minimise the difference to the input expression matrix. Authors report the IGNITE is able to predict wild type data and simulate both single and multiple gene knockouts. Authors benchmark this method on a in-house data set of differentiating pluripotent stem cells (PSC). They focus on a small set of genes known to be involved in PSC differentiation into formative cells. Authors benchmark IGNITE against state of the art tools (SCODE, MaxEnt and CELLORACLE). They evaluate IGNITE ability to predict wild type gene expression by comparing their data with experimental data and with SCODE. They conclude the tool has generative capacity comparable with SCODE. They also evaluate IGNITE ability to recover known interactions with respect to other tools without finding it to significantly outperform them.

Major comments

• Are the key conclusions convincing?

Conclusions appear convincing although model generalizability could be shown in a more thorough manner. For instance, analysing some other publicly available dataset could help demonstrate hyperparameters effects on GRN predictions and their robustness across different experiments. - Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?

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

I think the work would benefit from an additional benchmark on a different cellular system. This experiment would show how hyperparameters generalise across datasets and would provide potential users insights how to tweak them.

Also, how does the model scale with the number of genes? A benchmark on computation time and resources required to infer GRN of growing size would be valuable in the adoption of this tool.

In addition, I think the GRN comparison benchmark presented in section (3.4) would benefit from a quantitative discussion. Authors show inferred GRNs in Figure 4 and S5. For instance, measuring matrix similarity (when appropriate) would help understanding how predicted GRN compare. I understand authors attempt to do so by focusing on validated interactions and computing the fraction of correctly inferred interactions (FCI) but I think a measurement of the overall similarity (eg. Pearson correlation) would add on this.

Another comment regards the dependency between Correlation Matrices Distance (CMD) and FCI, shown in Figure 5. I understand that IGNITE GRN that maximise FCI are not the same that minimise CMD. However, it looks like GRN that maximise FCI have higher value in terms of biological information. I wonder whether optimization for one or the other metric could be left to the end user as a tunable parameter.

Authors should discuss why the expression of some genes does not follow the expected trends (Fig 1C vs Fig S1A). Out of the 24 genes they select for their analysis, at least four do not follow the expected trends: Sox2, according to literature, is a Naive gene, however, in Figure 1C its gene expression pattern is more similar to Formative late genes. Other genes with similar "unexpected" patterns are Zic3, Etv4 and Sall4.

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

I think suggested experiments are doable as long as authors get publicly available data, i.e. the in-house dataset they generated for this study is enough to show applicability. For example datasets analysed in SCODE paper (https://doi.org/10.1093/bioinformatics/btx194) could be used as second benchmark. The point of applying the tool to another dataset is to show how it generalises across different biological systems, experiments and, potentially, sequencing technologies. - Are the data and the methods presented in such a way that they can be reproduced?

The methods section is really clear. To enable reproducibility both raw scRNA-seq data, the IGNITE source code and code written to benchmark it should be released in the public domain in appropriate repositories (eg. ENA, GitHub, Binder etc). - Are the experiments adequately replicated and statistical analysis adequate?

Yes.

Minor comments

• Specific experimental issues that are easily addressable.

Related to the Sox2 expression pattern is the binarization shown in Figure 2D. How is it possible that Sox2 is always marked as active? Could the authors clarify how these outlier behaviours emerge and propose mitigation strategies, if any?

In section 5.11.2 it is unclear if xi are in log scale or not. Since the model starts from binarized, log transformed expression values, should not generated ones be in the same scale as the input? - Are prior studies referenced appropriately?

Yes, referencing is clear. - Are the text and figures clear and accurate?

Yes, figures appear to be clear, readable and well documented both in captions and main text. - Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

Section 3.3 could be improved by better describing experimental datasets. Only in the methods section it is clearly stated that experimental data for single KO experiments were retrieved from the literature.

Check typesetting:

• parenthesis missing in Eq. 1
• Leftover $ in section 3.1
• Parenthesis missing in Section 3.3
• Misplaced comma in section 5.2.1

Significance

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

The paper presents a method to infer GRN from scRNA-seq data alone. Applications include GRN prediction and their perturbations. This paper represents a technical advance in the field as it is the first application of the inverse Ising problem GRN inference. - Place the work in the context of the existing literature (provide references, where appropriate).

The paper itself presents the landscape of GRN inference tools using scRNA-seq data: SCODE, MaxEnt and CELLORACLE. More tools exist, for instance SCENIC (https://doi.org/10.1038/nmeth.4463) mainly relies on co-expression matrices. Other tools exist but require additional data types e.g. GRaNIE and GRaNPA (https://doi.org/10.15252/msb.202311627) leverage on physical interaction data (ATAC-seq, ChIP-seq). Similarly DeepFlyBrain uses deep neural networks to infer eGRN in Drosophila (https://doi.org/10.1038/s41586-021-04262-z). The value of tools like IGNITE and its competitors is that they do not require additional data types, which, in turn, helps in controlling experimental costs. - State what audience might be interested in and influenced by the reported findings.

The paper might be of interest to biologists interested in regulation of gene expression. The tool might turn out to be useful in planning experimental work by guiding the choice of perturbations to introduce in experimental systems. - Define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate.

I am a computational biologist.

I have no sufficient expertise to evaluate the mathematical details of the method.

Perhaps something to do also with the fact that human memory tends to retain information better when a high degree of surprise or emotion is associated with an event. See also the hyper-correction effect.

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eLife Assessment

This important study combines behavioural psychophysics with image-computable models to contrast a view-selective model of face recognition with a view-tolerant process. Although diagnostic orientations vary with viewpoint (horizontal for frontal, vertical for profile), human recognition remains consistently tuned to horizontal information, aligning with the view-tolerant model's predictions. The evidence for view-invariant recognition is solid, though testing more plausible model variants and considering generalisability to more naturalistic face stimuli would strengthen the conclusions.

Reviewer #1 (Public review):

Summary:

The authors describe the results of a single study designed to investigate the extent to which horizontal orientation energy plays a key role in supporting view-invariant face recognition. The authors collected behavioral data from adult observers who were asked to complete an old/new face matching task by learning broad-spectrum faces (not orientation filtered) during a familiarization phase and subsequently trying to label filtered faces as previously seen or novel at test. This data revealed a clear bias favoring the use of horizontal orientation energy across viewpoint changes in the target images. The authors then compared different ideal observer models (cross-correlations between target and probe stimuli) to examine how this profile might be reflected in the image-level appearance of their filtered images. This revealed that a model looking for the best matching face within a viewpoint differed substantially from human data, exhibiting a vertical orientation bias for extreme profiles. However, a model forced to match targets to probes at different viewing angles exhibited a consistent horizontal bias in much the same manner as human observers.

Strengths:

I think the question is an important one: The horizontal orientation bias is a great example of a low-level image property being linked to high-level recognition outcomes, and understanding the nature of that connection is important. I found the old/new task to be a straightforward task that was implemented ably and that has the benefit of being simple for participants to carry out and simple to analyze. I particularly appreciated that the authors chose to describe human data via a lower-dimensional model (their Gaussian fits to individual data) for further analysis. This was a nice way to express the nature of the tuning function, favoring horizontal orientation bias in a way that makes key parameters explicit. Broadly speaking, I also thought that the model comparison they include between the view-selective and view-tolerant models was a great next step. This analysis has the potential to reveal some good insights into how this bias emerges and ask fine-grained questions about the parameters in their model fits to the behavioral data.

Weaknesses:

I will start with what I think is the biggest difficulty I had with the paper. Much as I liked the model comparison analysis, I also don't quite know what to make of the view-tolerant model. As I understand the authors' description, the key feature of this model is that it does not get to compare the target and probe at the same yaw angle, but must instead pick a best match from candidates that are at different yaws. While it is interesting to see that this leads to a very different orientation profile, it also isn't obvious to me why such a comparison would be reflective of what the visual system is probably doing. I can see that the view-specific model is more or less assuming something like an exemplar representation of each face: You have the opportunity to compare a new image to a whole library of viewpoints, and presumably it isn't hard to start with some kind of first pass that identifies the best matching view first before trying to identify/match the individual in question. What I don't get about the view-tolerant model is that it seems almost like an anti-exemplar model: You specifically lack the best viewpoint in the library but have to make do with the other options. Again, this is sort of interesting and the very different behavior of the model is neat to discuss, but it doesn't seem easy to align with any theoretical perspective on face recognition. My thinking here is that it might be useful to consider an additional alternate model that doesn't specifically exclude the best-matching viewpoint, but perhaps condenses appearance across views into something like a prototype. I could even see an argument for something like the yaw-averages presented earlier in the manuscript as the basis for such a model, but this might be too much of a stretch. Overall, what I'd like to see is some kind of alternate model that incorporates the existence of the best-match viewpoint somehow, but without the explicit exemplar structure of the view-specific model.

Besides this larger issue, I would also like to see some more details about the nature of the cross-correlation that is the basis for this model comparison. I mostly think I get what is happening, but I think the authors could expand more on the nature of their noise model to make more explicit what is happening before these cross-correlations are taken. I infer that there is a noise-addition step to get them off the ceiling, but I felt that I had to read between the lines a bit to determine this.

Another thing that I think is worth considering and commenting on is the stimuli themselves and the extent to which this may limit the outcomes of their behavioral task. The use of the 3D laser-scanned faces has some obvious advantages, but also (I think) removes the possibility for pigmentation to contribute to recognition, removes the contribution of varying illumination and expression to appearance variability, and perhaps presents observers with more homogeneous faces than one typically has to worry about. I don't think these negate the current results, but I'd like the authors to expand on their discussion of these factors, particularly pigmentation. Naively, surface color and texture seem like they could offer diagnostic cues to identity that don't rely so critically on horizontal orientations, so removing these may mean that horizontal bias is particularly evident when face shape is the critical cue for recognition.

Reviewer #2 (Public review):

This study investigates the visual information that is used for the recognition of faces. This is an important question in vision research and is critical for social interactions more generally. The authors ask whether our ability to recognise faces, across different viewpoints, varies as a function of the orientation information available in the image. Consistent with previous findings from this group and others, they find that horizontally filtered faces were recognised better than vertically filtered faces. Next, they probe the mechanism underlying this pattern of data by designing two model observers. The first was optimised for faces at a specific viewpoint (view-selective). The second was generalised across viewpoints (view-tolerant). In contrast to the human data, the view-specific model shows that the information that is useful for identity judgements varies according to viewpoint. For example, frontal face identities are again optimally discriminated with horizontal orientation information, but profiles are optimally discriminated with more vertical orientation information. These findings show human face recognition is biased toward horizontal orientation information, even though this may be suboptimal for the recognition of profile views of the face.

One issue in the design of this study was the lowering of the signal-to-noise ratio in the view-selective observer. This decision was taken to avoid ceiling effects. However, it is not clear how this affects the similarity with the human observers.

Another issue is the decision to normalise image energy across orientations and viewpoints. I can see the logic in wanting to control for these effects, but this does reflect natural variation in image properties. So, again, I wonder what the results would look like without this step.

Despite the bias toward horizontal orientations in human observers, there were some differences in the orientation preference at each viewpoint. For example, frontal faces were biased to horizontal (90 degrees), but other viewpoints had biases that were slightly off horizontal (e.g., right profile: 80 degrees, left profile: 100 degrees). This does seem to show that differences in statistical information at different viewpoints (more horizontal information for frontal and more vertical information for profile) do influence human perception. It would be good to reflect on this nuance in the data.

If this is not the case, the perceptron algorithm will not terminate, but surprisingly it will stay bounded. See Block and Levin, "On the Boundedness of an Iterative Procedure for Solving a System of Linear Inequalities", Proc. Amer. Math. Soc., Vo. 26., No. 2, (1970), 229-245.

There exists \(M\) only dependent on the vectors \(v_1, \dots, v_m\), such that

$$ |\alpha_i| \leq |\alpha_1| + M $$

for every \(i = 1, 2, \dots\). In particular, if the vectors have rational coordinates, the algorithm will eventually cycle.

eLife Assessment

This important study uses a combination of behavioral and molecular techniques to identify neuromodulators that influence blood-feeding behavior in the disease vector, Anopheles stephensi. Through a combination of gene expression analysis and RNA knockdown, the authors identify neuropeptides RYamide and sNPF as candidate regulators for blood-feeding, demonstrate behavioral changes upon co-knockdown, and anatomically characterize their expression patterns. While the evidence for behavioral characterization and expression mapping is solid, the evidence supporting a direct causal role for these neuropeptides in promoting host-seeking remains unproven.

Reviewer #1 (Public review):

Summary:

Bansal et al. present a study on the fundamental blood and nectar feeding behaviors of the critical disease vector, Anopheles stephensi. The study encompasses not just the fundamental changes in blood feeding behaviors of the crucially understudied vector, but then uses a transcriptomic approach to identify candidate neuromodulation pathways which influence blood feeding behavior in this mosquito species. The authors then provide evidence through RNAi knockdown of candidate pathways that the neuromodulators sNPF and Rya modulate feeding either via their physiological activity in the brain alone or through joint physiological activity along the brain-gut axis (but critically not the gut alone). Overall, I found this study to be built on tractable, well-designed behavioral experiments.

Their study begins with a well-structured experiment to assess how the feeding behaviors of A. stephensi change over the course of its life history and in response to its age, mating, and oviposition status. The authors are careful and validate their experimental paradigm in the more well-studied Ae. aegypti, and are able to recapitulate the results of prior studies, which show that mating is a prerequisite for blood feeding behaviors in Ae. aegypt. Here they find A. Stephensi, like other Anopheline mosquitoes, has a more nuanced regulation of its blood and nectar feeding behaviors.

The authors then go on to show in a Y-maze olfactometer that ,to some degree, changes in blood feeding status depend on behavioral modulation to host cues, and this is not likely to be a simple change to the biting behaviors alone. I was especially struck by the swap in valence of the host cues for the blood-fed and mated individuals, which had not yet oviposited. This indicates that there is a change in behavior that is not simply desensitization to host cues while navigating in flight, but something much more exciting is happening.

The authors then use a transcriptomic approach to identify candidate genes in the blood-feeding stages of the mosquito's life cycle to identify a list of 9 candidates that have a role in regulating the host-seeking status of A. stephensi. Then, through investigations of gene knockdown of candidates, they identify the dual action of RYa and sNPF and candidate neuromodulators of host-seeking in this species. Overall, I found the experiments to be well-designed. I found the molecular approach to be sound. While I do not think the molecular approach is necessarily an all-encompassing mechanism identification (owing mostly to the fact that genetic resources are not yet available in A. stephensi as they are in other dipteran models), I think it sets up a rich line of research questions for the neurobiology of mosquito behavioral plasticity and comparative evolution of neuromodulator action.

Strengths:

I am especially impressed by the authors' attention to small details in the course of this article. As I read and evaluated this article, I continued to think about how many crucial details could potentially have been missed if this had not been the approach. The attention to detail paid off in spades and allowed the authors to carefully tease apart molecular candidates of blood-seeking stages. The authors' top-down approach to identifying RYamide and sNPF starting from first principles behavioral experiments is especially comprehensive. The results from both the behavioral and molecular target studies will have broad implications for the vectorial capacity of this species and comparative evolution of neural circuit modulation.

Weaknesses:

There are a few elements of data visualizations and methodological reporting that I found confusing on a first few read-throughs. Figure 1F, for example, was initially confusing as it made it seem as though there were multiple 2-choice assays for each of the conditions. I would recommend removing the "X" marker from the x-axis to indicate the mosquitoes did not feed from either nectar, blood, or neither in order to make it clear that there was one assay in which mosquitoes had access to both food sources, and the data quantify if they took both meals, one meal, or no meals.

I would also like to know more about how the authors achieved tissue-specific knockdown for RNAi experiments. I think this is an intriguing methodology, but I could not figure out from the methods why injections either had whole-body or abdomen-specific knockdown.

I also found some interpretations of the transcriptomic to be overly broad for what transcriptomes can actually tell us about the organism's state. For example, the authors mention, "Interestingly, we found that after a blood meal, glucose is neither spent nor stored, and that the female brain goes into a state of metabolic 'sugar rest', while actively processing proteins (Figure S2B, S3)".

This would require a physiological measurement to actually know. It certainly suggests that there are changes in carbohydrate metabolism, but there are too many alternative interpretations to make this broad claim from transcriptomic data alone.

Reviewer #2 (Public review):

Summary:

In this manuscript, Bansal et al examine and characterize feeding behaviour in Anopheles stephensi mosquitoes. While sharing some similarities to the well-studied Aedes aegypti mosquito, the authors demonstrate that mated females, but not unmated (virgin) females, exhibit suppression in their blood-feeding behaviour. Using brain transcriptomic analysis comparing sugar-fed, blood-fed, and starved mosquitoes, several candidate genes potentially responsible for influencing blood-feeding behaviour were identified, including two neuropeptides (short NPF and RYamide) that are known to modulate feeding behaviour in other mosquito species. Using molecular tools, including in situ hybridization, the authors map the distribution of cells producing these neuropeptides in the nervous system and in the gut. Further, by implementing systemic RNA interference (RNAi), the study suggests that both neuropeptides appear to promote blood-feeding (but do not impact sugar feeding), although the impact was observed only after both neuropeptide genes underwent knockdown.

Strengths and/or weaknesses:

Overall, the manuscript was well-written; however, the authors should review carefully, as some sections would benefit from restructuring to improve clarity. Some statements need to be rectified as they are factually inaccurate.

Below are specific concerns and clarifications needed in the opinion of this reviewer:

(1) What does "central brains" refer to in abstract and in other sections of the manuscript (including methods and results)? This term is ambiguous, and the authors should more clearly define what specific components of the central nervous system was/were used in their study.

(2) The abstract states that two neuropeptides, sNPF and RYamide are working together, but no evidence is summarized for the latter in this section.

(3) Figure 1<br /> Panel A: This should include mating events in the reproductive cycle to demonstrate differences in the feeding behavior of Ae. aegypti.<br /> Panel F: In treatments where insects were not provided either blood or sugar, how is it that some females and males had fed? Also, it is unclear why the y-axis label is % fed when the caption indicates this is a choice assay. Also, it is interesting that sugar-starved females did not increase sugar intake. Is there any explanation for this (was it expected)?

(4) Figure 3<br /> In the neurotranscriptome analysis of the (central) brain involving the two types of comparisons, can the authors clarify what "excluded in males" refers to? Does this imply that only genes not expressed in males were considered in the analysis? If so, what about co-expressed genes that have a specific function in female feeding behaviour?

(5) Figure 4<br /> The authors state that there is more efficient knockdown in the head of unfed females; however, this is not accurate since they only get knockdown in unfed animals, and no evidence of any knockdown in fed animals (panel D). This point should be revised in the results test as well. Relatedly, blood-feeding is decreased when both neuropeptide transcripts are targeted compared to uninjected (panel C) but not compared to dsGFP injected (panel E). Why is this the case if authors showed earlier in this figure (panel B) that dsGFP does not impact blood feeding? In addition, do the uninjected and dsGFP-injected relative mRNA expression data reflect combined RYa and sNPF levels? Why is there no variation in these data, and how do transcript levels of RYa and sNPF compare in the brain versus the abdomen (the presentation of data doesn't make this relationship clear).

(6) As an overall comment, the figure captions are far too long and include redundant text presented in the methods and results sections.

(7) Criteria used for identifying neuropeptides promoting blood-feeding: statement that reads "all neuropeptides, since these are known to regulate feeding behaviours". This is not accurate since not all neuropeptides govern feeding behaviors, while certainly a subset do play a role.

(8) In the section beginning with "Two neuropeptides - sNPF and RYa - showed about 25% and 40% reduced mRNA levels...", the authors state that there was no change in blood-feeding and later state the opposite. The wording should be clarified as it is unclear.

(9) Just before the conclusions section, the statement that "neuropeptide receptors are often ligand-promiscuous" is unjustified. Indeed, many studies have shown in heterologous systems that high concentrations of structurally related peptides, which are not physiologically relevant, might cross-react and activate a receptor belonging to a different peptide family; however, the natural ligand is often many times more potent (in most cases, orders of magnitude) than structurally related peptides. This is certainly the case for various RYamide and sNPF receptors characterized in various insect species.

(10) Methods<br /> In the dsRNA-mediated gene knockdown section, the authors could more clearly describe how much dsRNA was injected per target. At the moment, the reader must carry out calculations based on the concentrations provided and the injected volume range provided later in this section.

It is also unclear how tissue-specific knockdown was achieved by performing injection on different days/times. The authors need to explain/support, and justify how temporal differences in injection lead to changes in tissue-specific expression. Does the blood-brain barrier limit knockdown in the brain instead, while leaving expression in the peripheral organs susceptible? For example, in Figure 4, the data support that knockdown in the head/brain is only effective in unfed animals compared to uninjected animals, while there is no evidence of knockdown in the brain relative to dsGFP-injected animals. Comparatively, evidence appears to show stronger evidence of abdominal knockdown mostly for the RYa transcript (>90%) while still significantly for the sNPF transcript (>60%).

Reviewer #3 (Public review):

Summary:

This manuscript investigates the regulation of host-seeking behavior in Anopheles stephensi females across different life stages and mating states. Through transcriptomic profiling, the authors identify differential gene expression between "blood-hungry" and "blood-sated" states. Two neuropeptides, sNPF and RYamide, are highlighted as potential mediators of host-seeking behavior. RNAi knockdown of these peptides alters host-seeking activity, and their expression is anatomically mapped in the mosquito brain (sNPF and RYamide) and midgut (sNPF only).

Strengths:

(1) The study addresses an important question in mosquito biology, with relevance to vector control and disease transmission.

(2) Transcriptomic profiling is used to uncover gene expression changes linked to behavioral states.

(3) The identification of sNPF and RYamide as candidate regulators provides a clear focus for downstream mechanistic work.

(3) RNAi experiments demonstrate that these neuropeptides are necessary for normal host-seeking behavior.

(4) Anatomical localization of neuropeptide expression adds depth to the functional findings.

Weaknesses:

(1) The title implies that the neuropeptides promote host-seeking, but sufficiency is not demonstrated (for example, with peptide injection or overexpression experiments).

(2) The proposed model regarding central versus peripheral (gut) peptide action is inconsistently presented and lacks strong experimental support.

(3) Some conclusions appear premature based on the current data and would benefit from additional functional validation.

Author response:

Public Reviews:

Reviewer #1 (Public review):

Summary:

Bansal et al. present a study on the fundamental blood and nectar feeding behaviors of the critical disease vector, Anopheles stephensi. The study encompasses not just the fundamental changes in blood feeding behaviors of the crucially understudied vector, but then uses a transcriptomic approach to identify candidate neuromodulation pathways which influence blood feeding behavior in this mosquito species. The authors then provide evidence through RNAi knockdown of candidate pathways that the neuromodulators sNPF and Rya modulate feeding either via their physiological activity in the brain alone or through joint physiological activity along the brain-gut axis (but critically not the gut alone). Overall, I found this study to be built on tractable, well-designed behavioral experiments.

Their study begins with a well-structured experiment to assess how the feeding behaviors of A. stephensi change over the course of its life history and in response to its age, mating, and oviposition status. The authors are careful and validate their experimental paradigm in the more well-studied Ae. aegypti, and are able to recapitulate the results of prior studies, which show that mating is a prerequisite for blood feeding behaviors in Ae. aegypt. Here they find A. Stephensi, like other Anopheline mosquitoes, has a more nuanced regulation of its blood and nectar feeding behaviors.

The authors then go on to show in a Y-maze olfactometer that ,to some degree, changes in blood feeding status depend on behavioral modulation to host cues, and this is not likely to be a simple change to the biting behaviors alone. I was especially struck by the swap in valence of the host cues for the blood-fed and mated individuals, which had not yet oviposited. This indicates that there is a change in behavior that is not simply desensitization to host cues while navigating in flight, but something much more exciting is happening.

The authors then use a transcriptomic approach to identify candidate genes in the blood-feeding stages of the mosquito's life cycle to identify a list of 9 candidates that have a role in regulating the host-seeking status of A. stephensi. Then, through investigations of gene knockdown of candidates, they identify the dual action of RYa and sNPF and candidate neuromodulators of host-seeking in this species. Overall, I found the experiments to be well-designed. I found the molecular approach to be sound. While I do not think the molecular approach is necessarily an all-encompassing mechanism identification (owing mostly to the fact that genetic resources are not yet available in A. stephensi as they are in other dipteran models), I think it sets up a rich line of research questions for the neurobiology of mosquito behavioral plasticity and comparative evolution of neuromodulator action.

We appreciate the reviewer’s detailed summary of our work. We thank them for their positive comments and agree with them on the shortcomings of our approach.

Strengths:

I am especially impressed by the authors' attention to small details in the course of this article. As I read and evaluated this article, I continued to think about how many crucial details could potentially have been missed if this had not been the approach. The attention to detail paid off in spades and allowed the authors to carefully tease apart molecular candidates of blood-seeking stages. The authors' top-down approach to identifying RYamide and sNPF starting from first principles behavioral experiments is especially comprehensive. The results from both the behavioral and molecular target studies will have broad implications for the vectorial capacity of this species and comparative evolution of neural circuit modulation.

We really appreciate that the reviewer has recognised the attention to detail we have tried to put, thank you!

Weaknesses:

There are a few elements of data visualizations and methodological reporting that I found confusing on a first few read-throughs. Figure 1F, for example, was initially confusing as it made it seem as though there were multiple 2-choice assays for each of the conditions. I would recommend removing the "X" marker from the x-axis to indicate the mosquitoes did not feed from either nectar, blood, or neither in order to make it clear that there was one assay in which mosquitoes had access to both food sources, and the data quantify if they took both meals, one meal, or no meals.

We thank the reviewer for flagging the schematic in figure 1F. As suggested, we have removed the “X” markers from the x-axis and revised the axis label from “choice of food” to “choice made” to better reflect what food the mosquitoes chose in the assay. For clarity, we have now also plotted the same data as stacked graphs at the bottom of Fig. 1F, which clearly shows the proportion of mosquitoes fed on each particular choice. We avoid the stacked graph as the sole representation of this data, as it does not capture the variability in the data.

I would also like to know more about how the authors achieved tissue-specific knockdown for RNAi experiments. I think this is an intriguing methodology, but I could not figure out from the methods why injections either had whole-body or abdomen-specific knockdown.

The tissue-specific knockdown (abdomen only or abdomen+head) emerged from initial standardisations where we were unable to achieve knockdown in the head unless we used higher concentrations of dsRNA and did the injections in older females. We realised that this gave us the opportunity to isolate the neuronal contribution of these neuropeptides in the phenotype produced. Further optimisations revealed that injecting dsRNA into 0-10h old females produced abdomen-specific knockdowns without affecting head expression, whereas injections into 4 days old females resulted in knockdowns in both tissues. Moreover, head knockdowns in older females required higher dsRNA concentrations, with knockdown efficiency correlating with the amount injected. In contrast, abdominal knockdowns in younger females could be achieved even with lower dsRNA amounts.

We have mentioned the knockdown conditions- time of injection and the amount dsRNA injected- for tissue-specific knockdowns in methods but realise now that it does not explain this well enough. We have now edited it to state our methodology more clearly (see lines 932-948).

I also found some interpretations of the transcriptomic to be overly broad for what transcriptomes can actually tell us about the organism's state. For example, the authors mention, "Interestingly, we found that  after a blood meal, glucose is neither spent nor stored, and that the female brain goes into a state of metabolic 'sugar rest', while actively processing proteins (Figure S2B, S3)".

This would require a physiological measurement to actually know. It certainly suggests that there are changes in carbohydrate metabolism, but there are too many alternative interpretations to make this broad claim from transcriptomic data alone.

We thank the reviewer for pointing this out and agree with them. We have now edited our statement to read:

“Instead, our data suggests altered carbohydrate metabolism  after a blood meal, with the female brain potentially entering a state of metabolic 'sugar rest' while actively processing proteins (Figure S2B, S3). However, physiological measurements of carbohydrate and protein metabolism will be required to confirm whether glucose is indeed neither spent nor stored during this period.” See lines 271-277.

Reviewer #2 (Public review):

Summary:

In this manuscript, Bansal et al examine and characterize feeding behaviour in Anopheles stephensi mosquitoes. While sharing some similarities to the well-studied Aedes aegypti mosquito, the authors demonstrate that mated females, but not unmated (virgin) females, exhibit suppression in their bloodfeeding behaviour. Using brain transcriptomic analysis comparing sugar-fed, blood-fed, and starved mosquitoes, several candidate genes potentially responsible for influencing blood-feeding behaviour were identified, including two neuropeptides (short NPF and RYamide) that are known to modulate feeding behaviour in other mosquito species. Using molecular tools, including in situ hybridization, the authors map the distribution of cells producing these neuropeptides in the nervous system and in the gut. Further, by implementing systemic RNA interference (RNAi), the study suggests that both neuropeptides appear to promote blood-feeding (but do not impact sugar feeding), although the impact was observed only  after both neuropeptide genes underwent knockdown.

Strengths and/or weaknesses:

Overall, the manuscript was well-written; however, the authors should review carefully, as some sections would benefit from restructuring to improve clarity. Some statements need to be rectified as they are factually inaccurate.

Below are specific concerns and clarifications needed in the opinion of this reviewer:

(1) What does "central brains" refer to in abstract and in other sections of the manuscript (including methods and results)? This term is ambiguous, and the authors should more clearly define what specific components of the central nervous system was/were used in their study.

Central brain, or mid brain, is a commonly used term to refer to brain structures/neuropils without the optic lobes (For example: https://www.nature.com/articles/s41586-024-07686-5). In this study we have focused our analysis on the central brain circuits involved in modulating blood-feeding behaviour and have therefore excluded the optic lobes. As optic lobes account for nearly half of all the neurons in the mosquito brain (https://pmc.ncbi.nlm.nih.gov/articles/PMC8121336/), including them would have disproportionately skewed our transcriptomic data toward visual processing pathways.

We have indicated this in figure 3A and in the methods (see lines 800-801, 812). We have now also clarified it in the results section for neuro-transcriptomics to avoid confusion (see lines 236-237).

(2) The abstract states that two neuropeptides, sNPF and RYamide are working together, but no evidence is summarized for the latter in this section.

We thank the reviewer for pointing this out. We have now added a statement “This occurs in the context of the action of RYa in the brain” to end of the abstract, for a complete summary of our proposed model.

(3) Figure 1

Panel A: This should include mating events in the reproductive cycle to demonstrate differences in the feeding behavior of Ae. aegypti.

Our data suggest that mating can occur at any time between eclosion and oviposition in An. stephensi and between eclosion and blood feeding in Ae. aegypti. Adding these into (already busy) 1A, would cloud the purpose of the schematic, which is to indicate the time points used in the behavioural assays and transcriptomics.

Panel F: In treatments where insects were not provided either blood or sugar, how is it that some females and males had fed? Also, it is unclear why the y-axis label is % fed when the caption indicates this is a choice assay. Also, it is interesting that sugar-starved females did not increase sugar intake. Is there any explanation for this (was it expected)?

We apologise for the confusion. The experiment is indeed a choice assay in which sugar-starved or sugar-sated females, co-housed with males, were provided simultaneous access to both blood and sugar, and were assessed for the choice made (indicated on the x-axis): both blood and sugar, blood only, sugar only, or neither. The x-axis indicates the choice made by the mosquitoes, not the choice provided in the assay, and the y-axis indicates the percentage of males or females that made each particular choice. We have now removed the “X” markers from the x-axis and revised the axis label from “choice of food” to “choice made” to better reflect what food the mosquitoes chose to take.

In this assay, we scored females only for the presence or absence of each meal type (blood or sugar) and are therefore unable to comment on whether sugar-starved females consumed more sugar than sugarsated females. However, when sugar-starved, a higher proportion of females consumed both blood and sugar, while fewer fed on blood alone.

For clarity, we have now also plotted the same data as stacked graphs at the bottom of Fig. 1F, which clearly shows the proportion of mosquitoes fed on each particular choice. We avoid the stacked graph as the sole representation of this data as it does not capture the variability in the data.

(4) Figure 3

In the neurotranscriptome analysis of the (central) brain involving the two types of comparisons, can the authors clarify what "excluded in males" refers to? Does this imply that only genes not expressed in males were considered in the analysis? If so, what about co-expressed genes that have a specific function in female feeding behaviour?

This is indeed correct. We reasoned that since blood feeding is exclusive to females, we should focus our analysis on genes that were specifically upregulated in them. As the reviewer points out, it is very likely that genes commonly upregulated in males and females may also promote blood feeding and we will miss out on any such candidates based on our selection criteria.

(5) Figure 4

The authors state that there is more efficient knockdown in the head of unfed females; however, this is not accurate since they only get knockdown in unfed animals, and no evidence of any knockdown in fed animals (panel D). This point should be revised in the results test as well.

Perhaps we do not understand the reviewer’s point or there has been a misunderstanding. In figure 4D, we show that while there is more robust gene knockdown in unfed females, blood-fed females also showed modest but measurable knockdowns ranging from 5-40% for RYamide and 2-21% for sNPF.

Relatedly, blood-feeding is decreased when both neuropeptide transcripts are targeted compared to uninjected (panel C) but not compared to dsGFP injected (panel E). Why is this the case if authors showed earlier in this figure (panel B) that dsGFP does not impact blood feeding?

We realise this concern stems from our representation of the data. Since we had earlier determined that dsGFP-injected females fed similarly to uninjected females (fig 4B), we used these controls interchangeably in subsequent experiments. To avoid confusion, we have now only used the label ‘control’ in figure 4 (and supplementary figure S9) and specified which control was used for each experiment in the legend.

In addition to this, we wanted to clarify that fig 4C and 4E are independent experiments. 4C is the behaviour corresponding to when the neuropeptides were knocked down in both heads and abdomens.

4E is the behaviour corresponding to when the neuropeptides were knocked down in only the abdomens. We have now added a schematic in the plots to make this clearer.

In addition, do the uninjected and dsGFP-injected relative mRNA expression data reflect combined RYa and sNPF levels? Why is there no variation in these data,…

In these qPCRs, we calculated relative mRNA expression using the delta-delta Ct method (see line 975). For each neuropeptide its respective control was used. For simplicity, we combined the RYa and sNPF control data into a single representation. The value of this control is invariant because this method sets the control baseline to a value of 1.

…and how do transcript levels of RYa and sNPF compare in the brain versus the abdomen (the presentation of data doesn't make this relationship clear).

The reviewer is correct in pointing out that we have not clarified this relationship in our current presentation. While we have not performed absolute mRNA quantifications, we extracted relative mRNA levels from qPCR data of 96h old unmanipulated control females. We observed that both sNPF and RYa transcripts are expressed at much lower levels in the abdomens, as compared to those in the heads, as shown in the graphs inserted below.

Author response image 1.

(6) As an overall comment, the figure captions are far too long and include redundant text presented in the methods and results sections.

We thank the reviewer for flagging this and have now edited the legends to remove redundancy.

(7) Criteria used for identifying neuropeptides promoting blood-feeding: statement that reads "all neuropeptides, since these are known to regulate feeding behaviours". This is not accurate since not all neuropeptides govern feeding behaviors, while certainly a subset do play a role.

We agree with the reviewer that not all neuropeptides regulate feeding behaviours. Our statement refers to the screening approach we used: in our shortlist of candidates, we chose to validate all neuropeptides.

(8) In the section beginning with "Two neuropeptides - sNPF and RYa - showed about 25% and 40% reduced mRNA levels...", the authors state that there was no change in blood-feeding and later state the opposite. The wording should be clarified as it is unclear.

Thank you for pointing this out. We were referring to an unchanged proportion of the blood fed females. We have now edited the text to the following:

“Two neuropeptides - sNPF and RYa - showed about 25% and 40% reduced mRNA levels in the heads but the proportion of females that took blood meals remained unchanged”. See lines 338-340.

(9) Just before the conclusions section, the statement that "neuropeptide receptors are often ligand promiscuous" is unjustified. Indeed, many studies have shown in heterologous systems that high concentrations of structurally related peptides, which are not physiologically relevant, might cross-react and activate a receptor belonging to a different peptide family; however, the natural ligand is often many times more potent (in most cases, orders of magnitude) than structurally related peptides. This is certainly the case for various RYamide and sNPF receptors characterized in various insect species.

We agree with the reviewer and apologise for the mistake. We have now removed the statement.

(10) Methods

In the dsRNA-mediated gene knockdown section, the authors could more clearly describe how much dsRNA was injected per target. At the moment, the reader must carry out calculations based on the concentrations provided and the injected volume range provided later in this section.

We have now edited the section to reflect the amount of dsRNA injected per target. Please see lines 921-931.

It is also unclear how tissue-specific knockdown was achieved by performing injection on different days/times. The authors need to explain/support, and justify how temporal differences in injection lead to changes in tissue-specific expression. Does the blood-brain barrier limit knockdown in the brain instead, while leaving expression in the peripheral organs susceptible?

To achieve tissue-specific knockdowns of sNPF and RYa, we optimised both the time of injection as well as the dsRNA concentration to be injected. Injecting dsRNA into 0-10h females produced abdomen specific knockdowns without affecting head expression, whereas injections into 96h old females resulted in knockdowns in both tissues. Head knockdowns in older females required higher dsRNA concentrations, with knockdown efficiency correlating with the amount injected. In contrast, abdominal knockdowns in younger females could be achieved even with lower dsRNA amounts, reflecting the lower baseline expression of sNPF in abdomens compared to heads and the age-dependent increase in head expression (as confirmed by qPCR). It is possible that the blood-brain barrier also limits the dsRNA entering the brain, thereby requiring higher amounts to be injected for head knockdowns.

We have now edited this section to state our methodology more clearly (see lines 932-948).

For example, in Figure 4, the data support that knockdown in the head/brain is only effective in unfed animals compared to uninjected animals, while there is no evidence of knockdown in the brain relative to dsGFP-injected animals. Comparatively, evidence appears to show stronger evidence of abdominal knockdown mostly for the RYa transcript (>90%) while still significantly for the sNPF transcript (>60%).

As we explained earlier, this concern likely stems from our representation of the data. Since we had earlier determined that dsGFP-injected females fed similarly to uninjected females (fig 4B), we used these controls interchangeably in subsequent experiments. To avoid confusion, we have now only used the label ‘control’ in figure 4 (and supplementary figure S9) and specified which control was used for each experiment in the legend.

In addition to this, we wanted to clarify that fig 4C and 4E are independent experiments. 4C is the behaviour corresponding to when the neuropeptides were knocked down in both heads and abdomens. 4E is the behaviour corresponding to when the neuropeptides were knocked down in only the abdomen. We have now added a schematic in the plots to make this clearer.

Reviewer #3 (Public review):

Summary:

This manuscript investigates the regulation of host-seeking behavior in Anopheles stephensi females across different life stages and mating states. Through transcriptomic profiling, the authors identify differential gene expression between "blood-hungry" and "blood-sated" states. Two neuropeptides, sNPF and RYamide, are highlighted as potential mediators of host-seeking behavior. RNAi knockdown of these peptides alters host-seeking activity, and their expression is anatomically mapped in the mosquito brain (sNPF and RYamide) and midgut (sNPF only).

Strengths:

(1) The study addresses an important question in mosquito biology, with relevance to vector control and disease transmission.

(2) Transcriptomic profiling is used to uncover gene expression changes linked to behavioral states.

(3) The identification of sNPF and RYamide as candidate regulators provides a clear focus for downstream mechanistic work.

(3) RNAi experiments demonstrate that these neuropeptides are necessary for normal host-seeking behavior.

(4) Anatomical localization of neuropeptide expression adds depth to the functional findings.

Weaknesses:

(1) The title implies that the neuropeptides promote host-seeking, but sufficiency is not demonstrated (for example, with peptide injection or overexpression experiments).

Demonstrating sufficiency would require injecting sNPF peptide or its agonist. To date, no small-molecule agonists (or antagonists) that selectively mimic sNPF or RYa neuropeptides have been identified in insects. An NPY analogue, TM30335, has been reported to activate the Aedes aegypti NPY-like receptor 7 (NPYLR7; Duvall et al., 2019), which is also activated by sNPF peptides at higher doses (Liesch et al., 2013). Unfortunately, the compound is no longer available because its manufacturer, 7TM Pharma, has ceased operations. Synthesising the peptides is a possibility that we will explore in the future.

(2) The proposed model regarding central versus peripheral (gut) peptide action is inconsistently presented and lacks strong experimental support.

The best way to address this would be to conduct tissue-specific manipulations, the tools for which are not available in this species. Our approach to achieve head+abdomen and abdomen only knockdown was the closest we could get to achieving tissue specificity and allowed us to confirm that knockdown in the head was necessary for the phenotype. However, as the reviewer points out, this did not allow us to rule out any involvement of the abdomen. This point has been addressed in lines 364-371.

(3) Some conclusions appear premature based on the current data and would benefit from additional functional validation.

The most definitive way of demonstrating necessity of sNPF and RYa in blood feeding would be to generate mutant lines. While we are pursuing this line of experiments, they lie beyond the scope of a revision. In its absence, we relied on the knockdown of the genes using dsRNA. We would like to posit that despite only partial knockdown, mosquitoes do display defects in blood-feeding behaviour, without affecting sugar-feeding. We think this reflects the importance of sNPF in promoting blood feeding.

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

Overall, I found this manuscript to be well-prepared, visually the figures are great and clearly were carefully thought out and curated, and the research is impacwul. It was a wonderful read from start to finish. I have the following recommendations:

Thank you very much, we are very pleased to hear that you enjoyed reading our manuscript!

(1) For future manuscripts, it would make things significantly easier on the reviewer side to submit a format that uses line numbers.

We sincerely apologise for the oversight. We have now incorporated line numbers in the revised manuscript.

(2) There are a few statements in the text that I think may need clarification or might be outside the bounds of what was actually studied here. For example, in the introduction "However, mating is dispensable in Anophelines even under conditions of nutritional satiety". I am uncertain what is meant by this statement - please clarify.

We apologise for the lack of clarity in the statement and have now deleted it since we felt it was not necessary.

(3) Typo/Grammatical minutiae:

a) A small idiosyncrasy of using hyphens in compound words should also be fixed throughout. Typically, you don't hyphenate if the words are being used as a noun, as in the case: e.g. "Age affects blood feeding.". However, you would hyphenate if the two words are used as a compound adjective "Age affects blood-feeding behavior". This may not be an all-inclusive list, but here are some examples where hyphens need to either be removed or added. Some examples:

"Nutritional state also influences other internal state outputs on blood-feeding": blood-feeding -> blood feeding

"... the modulation of blood-feeding": blood-feeding -> blood feeding

"For example, whether virgin females take blood-meals...": blood-meals -> blood meals

".... how internal and external cues shape meal-choice"-> meal choice

"blood-meal" is often used throughout the text, but is correctly "blood meal" in the figures.

There are many more examples throughout.

We apologise for these errors and appreciate the reviewer’s keen eye. We have now fixed them throughout the manuscript.

b) Figure 1 Caption has a typo: "co-housed males were accessed for sugar-feeding" should be "co-housed males were assessed for sugar feeding"

We apologise for the typo and thank the reviewer for spotting it. We have now corrected this.

c) It would be helpful in some other figure captions to more clearly label which statement is relevant to which part of the text. For example, in Figure 4's caption.

"C,D. Blood-feeding and sugar-feeding behaviour of females when both RYa and sNPF are knocked down in the head (C). Relative mRNA expressions of RYa and sNPF in the heads of dsRYa+dssNPF - injected blood-fed and unfed females, as compared to that in uninjected females, analysed via qPCR (D)."

I found re-referencing C and D at the end of their statements makes it look as thought C precedes the "Relative mRNA expression" and on a first read through, I thought the figure captions were backwards. I'd recommend reformating here and throughout consistently to only have the figure letter precede its relevant caption information, e.g.:

"C. Blood-feeding and sugar-feeding behaviour of females when both RYa and sNPF are knocked down in the head. D. Relative mRNA expressions of RYa and sNPF in the heads of dsRYa+dssNPF - injected bloodfed and unfed females, as compared to that in uninjected females, analysed via qPCR."

We have now edited the legends as suggested.

Reviewer #2 (Recommendations for the authors):

Separately from the clarifications and limitations listed above, the authors could strengthen their study and the conclusions drawn if they could rescue the behavioural phenotype observed following knockdown of sNPF and RYamide. This could be achieved by injection of either sNPF or RYa peptide independently or combined following knockdown to validate the role of these peptides in promoting blood-feeding in An. stephensi. Additionally, the apparent (but unclear) regionalized (or tissue-specific) knockdown of sNPF and RYamide transcripts could be visualized and verified by implementing HCR in situ hyb in knockdown animals (or immunohistochemistry using antibodies specific for these two neuropeptides).

In a follow up of this work, we are generating mutants and peptides for these candidates and are planning to conduct exactly the experiments the reviewer suggests.

Reviewer #3 (Recommendations for the authors):

The loss-of-function data suggest necessity but not sufficiency. Synthetic peptide injection in non-host seeking (blood-fed mated or juvenile) mosquitoes would provide direct evidence for peptide-induced behavioral activation. The lack of these experiments weakens the central claim of the paper that these neuropeptides directly promote blood feeding.

As noted above, we plan to synthesise the peptide to test rescue in a mutant background and sufficiency.

Some of the claims about knockdown efficiency and interpretation are conflicting; the authors dismiss Hairy and Prp as candidates due to 30-35% knockdown, yet base major conclusions on sNPF and RYamide knockdowns with comparable efficiencies (25-40%). This inconsistency should be addressed, or the justification for different thresholds should be clearly stated.

We have not defined any specific knockdown efficacy thresholds in the manuscript, as these can vary considerably between genes, and in some cases, even modest reductions can be sufficient to produce detectable phenotypes. For example, knockdown efficiencies of even as low as about 25% - 40% gave us observable phenotypes for sNPF and RYa RNAi (Figure S9B-G).

No such phenotypes were observed for Hairy (30%) or Prp (35%) knockdowns. Either these genes are not involved in blood feeding, or the knockdown was not sufficient for these specific genes to induce phenotypes. We cannot distinguish between these scenarios.

The observation that knockdown animals take smaller blood meals is interesting and could reflect a downstream effect of altered host-seeking or an independent physiological change. The relationship between meal size and host-seeking behavior should be clarified.

We agree with the reviewer that the reduced meal size observed in sNPF and RYa knockdown animals could result from their inability to seek a host or due to an independent effect on blood meal intake. Unfortunately, we did not measure host-seeking in these animals. We plan to distinguish between these possibilities using mutants in future work.

Several figures are difficult to interpret due to cluttered labeling and poorly distinguishable color schemes. Simplifying these and improving contrast (especially for co-housed vs. virgin conditions) would enhance readability.

We regret that the reviewer found the figures difficult to follow. We have now revised our annotations throughout the manuscript for enhanced readability. For example, “D1^B” is now “D1^PBM” (post-bloodmeal) and “D1^O” is now “D1^PO” (post-oviposition). Wherever mated females were used, we have now appended “(m)” to the annotations and consistently depicted these females with striped abdomens in all the schematics. We believe these changes will improve clarity and readability.

The manuscript does not clearly justify the use of whole-brain RNA sequencing to identify peptides involved in metabolic or peripheral processes. Given that anticipatory feeding signals are often peripheral, the logic for brain transcriptomics should be explained.

The reviewer is correct in pointing out that feeding signals could also emerge from peripheral tissues. Signals from these tissues – in response to both changing nutritional and reproductive states – are then integrated by the central brain to modulate feeding choices. For example, in Drosophila, increased protein intake is mediated by central brain circuitry including those in the SEZ and central complex (Munch et al., 2022; Liu et al., 2017; Goldschmidt et al., 2023). In the context of mating, male-derived sex peptide further increases protein feeding by acting on a dedicated central brain circuitry (Walker et al., 2015). We, therefore focused on the central brain for our studies.

The proposed model suggests brain-derived peptides initiate feeding, while gut peptides provide feedback. However, gut-specific knockdowns had no effect, undermining this hypothesis. Conversely, the authors also suggest abdominal involvement based on RNAi results. These contradictions need to be resolved into a consistent model.

We thank the reviewer for raising this point and recognise their concern. Our reasons for invoking an involvement of the gut were two-fold:

(1) We find increased sNPF transcript expression in the entero-endocrine cells of the midgut in blood-hungry females, which returns to baseline  after a blood-meal (Fig. 4L, M).

(2) While the abdomen-only knockdowns did not affect blood feeding, every effective head knockdown that affected blood feeding also abolished abdominal transcript levels (Fig. S9C, F). (Achieving a head-only reduction proved impossible because (i) systemic dsRNA delivery inevitably reaches the abdomen and (ii) abdominal expression of both peptides is low, leaving little dynamic range for selective manipulation.) Consequently, we can only conclude the following: 1) that brain expression is required for the behaviour, 2) that we cannot exclude a contributory role for gut-derived sNPF. We have discussed this in lines 364-371.

The identification of candidate receptors is promising, but the manuscript would be significantly strengthened by testing whether receptor knockdowns phenocopy peptide knockdowns. Without this, it is difficult to conclude that the identified receptors mediate the behavioral effects.

We agree that functional validation of the receptors would strengthen the evidence for sNPF and RYa_mediated control of blood feeding in _An. stephensi. We selected these receptors based on sequence homology. A possibility remains that sNPF neuropeptides activate more than one receptor, each modulating a distinct circuit, as shown in the case of Drosophila Tachykinin (https://pmc.ncbi.nlm.nih.gov/articles/PMC10184743/). This will mean a systematic characterisation and knockdown of each of them to confirm their role. We are planning these experiments in the future.

The authors compared the percentage changes in sugar-fed and blood-fed animals under sugar-sated or sugar-starved conditions. Figure 1F should reflect what was discussed in the results.

Perhaps this concern stems from our representation of the data in figure 1F? We have now edited the xaxis and revised its label from “choice of food” to “choice made” to better reflect what food the mosquitoes chose to take.

For clarity, we have now also plotted the same data as stacked graphs at the bottom of Fig. 1F, which clearly shows the proportion of mosquitoes fed on each particular choice. We avoid the stacked graph as the sole representation of this data because it does not capture the variability in the data.

Minor issues:

(1) The authors used mosquitoes with belly stripes to indicate mated females. To be consistent, the post-oviposition females should also have belly stripes.

We thank the reviewer for pointing this out. We have now edited all the figures as suggested.

(2) In the first paragraph on the right column of the second page, the authors state, "Since females took blood-meals regardless of their prior sugar-feeding status and only sugar-feeding was selectively suppressed by prior sugar access." Just because the well-fed animals ate less than the starved animals does not mean their feeding behavior was suppressed.

Perhaps there has been a misunderstanding in the experimental setup of figure 1F, probably stemming from our data representation. The experiment is a choice assay in which sugar-starved or sugar-sated females, co-housed with males, were provided simultaneous access to both blood and sugar, and were assessed for the choice made (indicated on the x-axis): both blood and sugar, blood only, sugar only, or neither. We scored females only for the presence or absence of each meal type (blood or sugar) and did not quantify the amount consumed.

(3) The figure legend for Figure 1A and the naming convention for different experimental groups are difficult to follow. A simplified or consistently abbreviated scheme would help readers navigate the figures and text.

We regret that the reviewer found the figure difficult to follow. We have now revised our annotations throughout the manuscript for enhanced readability. For example, “D1^B” is now “D1^PBM” (post-bloodmeal) and “D1^O” is now “D1^PO” (post-oviposition).

(4) In the last paragraph of the Y-maze olfactory assay for host-seeking behaviour in An. stephensi in Methods, the authors state, "When testing blood-fed females, aged-matched sugar-fed females (bloodhungry) were included as positive controls where ever possible, with satisfactory results." The authors should explicitly describe what the criteria are for "satisfactory results".

We apologise for the lack of clarity. We have now edited the statement to read:

“When testing blood-fed females, age-matched sugar-fed females (blood-hungry) were included wherever possible as positive controls. These females consistently showed attraction to host cues, as expected.” See lines 786-790.

(5) In the first paragraph of the dsRNA-mediated gene knockdown section in Methods, dsRNA against GFP is used as a negative control for the injection itself, but not for the potential off-target effect.

We agree with the reviewer that dsGFP injections act as controls only for injection-related behavioural changes, and not for off-target effects of RNAi. We have now corrected the statement. See lines 919-920.

To control for off-target effects, we could have designed multiple dsRNAs targeting different parts of a given gene. We regret not including these controls for potential off-target effects of dsRNAs injected.

(6) References numbers 48, 89, and 90 are not complete citations.

We thank the reviewer for spotting these. We have now corrected these citations.

DOI: 10.3389/fimmu.2025.1638948

Resource: Mutant Mouse Regional Resource Center (RRID:SCR_002953)

Curator: @AleksanderDrozdz

SciCrunch record: RRID:SCR_002953

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Reply to the reviewers

We appreciated the positive, detailed and helpful feedback from all three reviewers.

Reviewer 1.

Minor comments.

1. In the introduction, on page 2, the authors seem a little confused about the Plk1 Polo-box domain - text as written: "...kinase domain linked to tandem Polo-box domains (PBD)", and cite a review paper. Actually, there is only a single Polo-box domain in these kinases, which contains both Polo-boxes and a bit of the upstream linker region. The "PBD" terminology denotes his 2-Polo-box +linker structure. Perhaps it would be better here to cite the PBD structure (Elia et al., Cell, 2002) as a primary citation here.

Response: Thank you for finding this error, the text has been updated and the new citation included within the text on line 65.

1. Similarly, the line "...during the G2/M transition following successful DNA damage repair" cites the Seki et al paper, but those findings are shown in the Macurek et al paper, not the Seki et al paper.

_Response: _Thank you for finding this error, the new citation included within the text on line 69.

1. Using the model of the ternary complex as shown in Figure 1B, deletion constructs of Bora missing regions within the disordered loops, but still retaining the residues that bind the PBD, FW pocket and Aurora A, can be modeled and tested to see if such deletions can improve the ipTM scores and binding affinity.

Response: ____AlphaFold3 modelling was attempted with shorter regions of Bora to see the effect on the ipTM scores. Unfortunately, when Bora was reduced to shorter sequences, such as 18-88 or 18-45 modelled with 68-120, the models became inconsistent and of a low quality. Models were also created including the short region of Bora surrounding Ser252 that interacts with the polo box domain as well as Bora 18-120, but this had minimal effect on the calculated iPTM scores.

1. On page 5, "S112A" within the sentence "Unexpectedly, the F56A/W58A Bora was less efficiently phosphorylated on S112A (Supplementary Figure S11, F compared to H and Supplementary Table S4)." This should be "S112".

Response: ____Thank you for spotting this, the error has been corrected.

1. In the assays shown in Figure 2D, the presence of excess F56AW58A Bora that remained unphosphorylated on S112 may complicate the interpretation of the results. Can the authors show that the S112-phosphorylated F56AW68A Bora is predominantly bound to Aurora A in such a mixture, perhaps by NMR using labelled pS112 F56AW58A Bora and unlabeled S112 F56AW58A Bora?

_Response: _15N13C labelled of Bora 18-120 F56A W58A was produced and assigned. We then phosphorylated a sample using ERK2, tracking with NMR, and when the reaction had progressed to a 50:50 mixture of pSer112 and Ser112 (based on peak intensities) the kinase activity was quenched by addition of EDTA to sequester Mg2+. This produced a solution containing both pS112 and unphosphorylated S112 Bora species with marker peaks in HSQC spectra that could be used to directly compare Aurora-binding to the two species. Aurora-A was introduced to the sample and the peak intensities were monitored. Although both species are affected, there is much greater peak loss from the pS112 related peaks than those for unphosphorylated S112. This indicates that Aurora-A still preferentially binds pS112 Bora over S112 Bora when the F56A W58A mutation is present. This data has been included in Supplementary Figure S11.

1. Please expand Figure 3A to better show the FW pocket-forming residues on Plk1.

Response: ____Figure 3 has been amended to reduce the size of the sequence alignments so that 3A could be made slightly larger.

1. It would be helpful to label the peaks in the mass spectra in Fig. S11 with the phospho-species that they correspond to.

Response: ____This information has been added to the mass spectra in Fig. S11 (now supplementary Figure S14) to make them easier to view.

1. In the last paragraph on page 7, "see we" in the sentence "As well as a decrease in intensity around pSer112 in Bora, see we an overall effect with decreased intensity across most of the Bora sequence." Should be corrected to "we see".

Response: ____Thank you for spotting this, the error has been corrected.

1. While not required, it would be helpful if binding or Bora to Aurora A after Erk2 phosphorylation could be shown using fluorescence polarization or ITC to lend additional support to the NMR data for S112 and S59 phosphorylation and for CEP192 and TPX2 competition.

Response: ____This question has been partially answered in previous work by Tavernier et al. (2021), who showed improved binding of Aurora-A to Bora after Erk phosphorylation (by SPR), and they used labelled-TPX2 for a series of competition FP assays in that and the recent parallel study (Pillan et al. 2025).

We made initial efforts to perform additional FP assays using longer sections of Bora with different phosphorylation states but without success (perhaps due to the multisite-binding nature of the Bora–Aurora interaction, and difficulties with directly expressing phosphorylated Bora). The revised manuscript now includes some additional NMR data to show improved Bora–Aurora-A interaction after phosphorylation at Ser59 (Supplementary Figure S12).

1. The Aurora A phosphorylation motif has been further defined beyond that reported by the Pinna lab in 2005. Notably, the Ser-59 sequence on Bora (F-R-W-S-I), has, in addition to dominant selection for AR in the -2 position, both favorable -1 (W) and +1 (I) positions based on peptide library measurements (Alexander et al., Science Signaling 2011), further arguing that it may be an excellent Aurora A phosphorylation site.

Response: ____Thank you for highlighting this publication and how it further reinforces the likelihood of Ser59 being an effective substrate for Aurora-A, this should have been included in the original manuscript. This citation has now been included.

1. Have the authors tried to model the Drosophila melanogaster Aurora A-Bora-Polo complex to see if the Asn substitution of Bora Ser59, and the expected loss of the interactions between Bora pSer59 and Plk1 Arg59 and Aurora A Arg205 are compensated by other features?

Response: ____A ternary complex between the Drosophila melanogaster orthologues was modelled using AlphaFold3 (Uniprot code PLK1 (Q9VVR2 72-165), Aurora-A kinase (Q9VGF9) 151-411 and PLK1 (P52304 21-280)). This model was analysed using PDBe PISA to identify potential interactions between the three proteins, focusing on residues that are not conserved between the human and Drosophila sequences. From this model a potential salt bridge was identified between Drosophila Bora Lys120 and PLK1 Glu93 that would not occur in the human ternary complex given Lys120 is replaced with an asparagine. This could be an alternative (kinase-independent) method for improved Bora-PLK1 interaction. When comparing the Bora:Aurora-A side of the predicted interface and focusing on the short region of Bora in between Aurora-A and PLK1, there were no clear differences seen in the residues predicted to bind to Aurora-A. This modelling has been included in Supplementary Figure S10 C and D.

1. Given the relevance of the recent publication from Zhu et al. to this study, the authors may want to comment on, or test, the relative importance of PKA and Aurora A as a potential kinase for Bora S59. While those authors argue that PKA phosphorylates Bora on Ser-59, one could easily imagine a model in which either PKA or Aurora A could initially phosphorylate that site followed by a propagation step after initial Aurora A activation, in which Aurora A phosphorylation of Bora Ser-59 is the dominant process.

Response: ____A brief discussion of this recent publication has been added to the discussion, highlighting the similarities between the two publications and the importance of pSer59, as well as suggesting that in cellulo this modification could be achieved via more than one pathway. We also include some additional NMR data to show improved Bora–Aurora-A interaction after phosphorylation at Ser59 (Supplementary Figure S12).

Reviewer 2.

Minor comments.

Page 5: '... a K82R PLK1 mutant was used to increase the stability of the protein' - It is not clear how this mutation confers increased stability of the protein. The authors do not show any data to support this. Isn't the PLK1 K82R an ATP-binding-deficient, kinase-inactive mutant?

Response: ____Thank you for spotting this, the text has been updated to clarify that this version of PLK1 was used as it is acting as a substrate in the in vitro assay as we didn’t want to see any PLK1 activity within this assay.

All panels showing the Alphabridge diagram - it would be helpful if pictorial definitions of the colour codes were provided with corresponding score ranges (in addition to the description in the figure legend).

Response:____The AlphaBridge images have been updated to include details about the plDDT scores each of the different colours refer to.

Fig 2B - The Fluorescence anisotropy assay curves do not reach a plateau. Though the effect of mutation on binding affinity is pretty clear, if possible, I suggest including more data points at higher concentrations and estimating apparent Kd values.

__Response:____The direct binding assay was repeated with a higher concentration of PLK1 in order to try and see a top plateau. This was successful and has been included in Figure 2B (shown in black). The measured Kd was 24 ± 3 µM. __

The cartoon representation of the structures and molecular interfaces - better to avoid shadows, as they compromise the clarity of the figures, particularly the ones where side chains are shown in stick representation.

Response:____The structural images have been remade to remove the shadows and improve the clarity of the images.

It is important to discuss how the parallel studies by Verza et al. and Pillan et al. complement this study, highlighting similarities and differences.

Response:____References to these two publications and details on the similarities and differences seen are now included in the discussion.

Reviewer 3.

Major comments

It would be helpful to measure the level of pThr210 PLK1 in some experiments and graph the data. The current presentation is Fig. 2D-E is qualitative rather than quantitative.

Response:____Graphs displaying the levels of pThr210 produced in the assay are now shown in Supplementary Figure S4.

Have the authors measured the binding affinity of the F/W mutant Bora for PLK1 using the assay in Fig. 2B? Likewise, for Fig. 7 the S59 mutant could be tested to see if it affects PLK1 binding or activation.

Response:____The direct binding assay has been repeated with the use of a FAM-Bora peptide that incorporates the F56A W58A mutation which shows reduced binding (Figure 2B, shown in blue). A version of the Bora peptide phosphorylated on Ser59 was also tested in the direct binding assay and this shows a similar affinity for PLK1 to the wild-type sequence (Figure 2B, shown in red compared to the wild-type shown in black).

It would be helpful if measurements of pThr210 PLK1 for all conditions were shown in the graph Fig. 7F.

Response:____This graph has been updated to include the levels of phosphorylation seen for PLK1 in all of the conditions tested.

Minor comments

I found Figure S1B easier to understand than Fig S1A and Fig 1A-B. Some of the supplemental data Fig. S1C-E could be moved to a revised Figure 1, dropping the current Fig. 1A-B. Can the interaction plots (Fig. S1C-D) be rotated to have the same original at the top and order of proteins (i.e. Bora > Aurora A > {plus minus} PLK1 depending on the plot).

Response:____Figure 1 and S1 have been rearranged to hopefully make them easier to understand, with all AlphaFold3 models of the full-length sequences kept in the supplementary figure and the focus in 1B just on the truncated model. The AlphaBridge plots have been rotated as suggested.

Figure 3F. Typo "Strongyl" not "Strongly".

Response:____Thank you for spotting this, this has been corrected in the updated manuscript.

Figure 3 could be supplemental material.

Response:__Thank you for your suggestion, but we have decided to keep this as a main figure.

Fig. 7E. Run a positive control reaction +ERK2 on the second gel to allow direct comparison of pThr210 across all the conditions tested.

Response:____These samples have been rerun on the same membrane and the levels of phosphorylation have been quantified and included in Figure 7F.

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Referee #3

Evidence, reproducibility and clarity

Summary.

Miles and co-workers have carried out a careful and high-quality study of the activation mechanisms of the mitotic kinase PLK1. Multiple proteins have been implicated in PLK1 activation and localisation as cell enter and pass through mitosis. Initial activation of PLK1 is promoted by a complex of Bora with another kinase Aurora A. Later in mitosis, this activated PLK1 associates with mitotic spindle and centrosome proteins regulating different aspects of mitosis and cytokinesis. In this study, Miles et al. extend previous work on this question by proposing and testing detailed models for Bora/Aurora A-mediated activation of PLK1 to elucidate the mechanism of this reaction.

Using the latest Alphafold they generate a series of models of the PLK1/Bora/Aurora A complex to home in on the key regions mediating interactions of the three proteins. This approach suggests an arrangement where the first ~120 amino acids of Bora wrap Aurora A and create an interaction surface for the N-terminal kinase domain of PLK1. This orients Thr210 in PLK1 towards Aurora A creating a situation likely favourable for phosphorylation, although has the authors discuss there are some caveats to this. A further prediction of the modelling helps explain the requirement for Bora phosphorylation to promote the interaction with Aurora A. This data is presented in Fig. 1 and Fig. S1-S3.

In the subsequent figures the details of this model are tested using biochemical assays and structural biology methods to validate key predictions. First the PLK1 interaction with Bora was shown to require the conserved F/W motif of Bora and a conserved pocket close to R106 on PLK1 (Fig. 2 and 3). In reconstituted PLK1 activation assays the F/W motif mutant Bora showed greatly attenuated pThr210 phosphorylation. This reaction also required phosphorylation of Bora at S112, presumably due to the interaction with Aurora A. An R106A mutant PLK1 showed reduced binding to Bora and reduced kinase activation. This data is clear and provides compelling support for the model.

Using NMR the authors then investigate the interaction between Bora and Aurora A, and more specifically the requirement for Bora phosphorylation at Ser112. The NMR data in Fig. 4 and Fig. 6 provide good support for the Alphafold model. A helpful comparison with known Aurora A binding proteins is also shown to highlight the way CEP192, TPX2 and TACC3 contact a series of conserved pockets on the surface of Aurora A which are common to the Bora interaction. S59 phosphorylation by Aurora A is also shown to play an important role in contacting PLK1 and is required for pThr210 phosphorylation.

In summary, the authors have made valuable progress in working out details of the PLK1 activation mechanism, that extends previous work in the field.

Major comments.

It would be helpful to measure the level of pThr210 PLK1 in some experiments and graph the data. The current presentation is Fig. 2D-E is qualitative rather than quantitative.

Have the authors measured the binding affinity of the F/W mutant Bora for PLK1 using the assay in Fig. 2B? Likewise, for Fig. 7 the S59 mutant could be tested to see if it affects PLK1 binding or activation.

It would be helpful if measurements of pThr210 PLK1 for all conditions were shown in the graph Fig. 7F.

Minor comments.

I found Figure S1B easier to understand than Fig S1A and Fig 1A-B. Some of the supplemental data Fig. S1C-E could be moved to a revised Figure 1, dropping the current Fig. 1A-B. Can the interaction plots (Fig. S1C-D) be rotated to have the same original at the top and order of proteins (i.e. Bora > Aurora A > {plus minus} PLK1 depending on the plot). Figure 3F. Typo "Strongyl" not "Strongly". Figure 3 could be supplemental material. Fig. 7E. Run a positive control reaction +ERK2 on the second gel to allow direct comparison of pThr210 across all the conditions tested.

Significance

Timely and orchestrated activation of multiple mitotic protein kinases is crucial for the alignment and segregation of chromosomes, and for the process of cell division. In this study the authors explore how activation of the mitotic kinase PLK1 is triggered by another mitotic kinase Aurora A, and the role played by a scaffold protein Bora.

Strengths: Detailed analysis of mechanism using biochemical and structural approaches.

Limitations: The study is focussed on the biochemical and structural mechanisms rather than the cellular outcomes. Some data would benefit from additional quantitative measurement.

Relevance: Cancer and cell biology due to the role of Aurora A in many cancers.

Reviewer expertise: Biochemistry, molecular and cell biology.

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Referee #2

Evidence, reproducibility and clarity

Summary:

PLK1 is one of the master regulators of cell division. The activation of PLK1 requires the activation loop phosphorylation at T210, mediated by Aurora A kinase. However, Aurora A phosphorylation of PLK1 T210 requires Bora, one of the several activators of Aurora A kinase. While the molecular requirement of Aurora A kinase and Bora for PLK1 activation is well established, the mechanistic understanding of how Bora facilitates PLK1 activation by Aurora A has remained an important open question for a long time. Exploiting the latest development in AI-driven structure prediction, three independent studies provide a structural and mechanistic basis for PLK1 activation by Aurora A and Bora. Here, Miles et al. have generated AlphaFold models, further characterised some of the interfaces using NMR, and validated the contribution of intermolecular interactions at suggested interfaces in vitro using recombinant proteins in kinase assays. Overall, this is a well-executed work providing important new insights into our understanding of the activation of the critical regulator of cell division, PLK1. However, as the authors have highlighted in the discussion section, one limitation of this modelling study is that the models still do not entirely explain how these interactions facilitate the phosphorylation of Thr210ur, as this residue is oriented far away from Aurora A's active site for the reaction to take place. Despite this limitation, I believe this is an important work that advances our understanding significantly.

Comments:

Experimental data satisfactorily support claims. Hence, most of my comments are minor in nature.

Points to consider during revision:

Page 5: '... a K82R PLK1 mutant was used to increase the stability of the protein' - It is not clear how this mutation confers increased stability of the protein. The authors do not show any data to support this. Isn't the PLK1 K82R an ATP-binding-deficient, kinase-inactive mutant?

All panels showing the Alphabridge diagram - it would be helpful if pictorial definitions of the colour codes were provided with corresponding score ranges (in addition to the description in the figure legend).

Fig 2B - The Fluorescence anisotropy assay curves do not reach a plateau. Though the effect of mutation on binding affinity is pretty clear, if possible, I suggest including more data points at higher concentrations and estimating apparent Kd values.

The cartoon representation of the structures and molecular interfaces - better to avoid shadows, as they compromise the clarity of the figures, particularly the ones where side chains are shown in stick representation.

It is important to discuss how the parallel studies by Verza et al. and Pillan et al. complement this study, highlighting similarities and differences.

Significance

As highlighted in the summary, a mechanistic understanding of how PLK1 is activated by Aurora A kinase and its activator Bora has remained a long-standing open question. As PLk1 is one of the major regulators of cell division, which exerts its function (via phosphorylating numerous substrates) during different stages of mitosis, understanding its activation mechanism is of critical interest for those working on the cell cycle in general and cell division in particular. A key limitation of this study is the lack of any cellular functional evaluation of the interaction interfaces.

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Referee #1

Evidence, reproducibility and clarity

Miles et al. used a combination of AlphaFold modeling, biochemical assays of mutant constructs and NMR spectroscopy to model the ternary complex of Aurora A, Bora and Plk1, and elucidate how Bora can act as a molecular bridge that facilitates the phosphorylation of the activation loop Thr210 within Plk1 by Aurora A. Their studies identified an interaction between residues 52-73 within Bora and the 'FW' pocket on the N-terminal lobe of Plk1, which binds Phe56 and Trp58 of Bora. Additionally, Ser59 of Bora was identified as a good Aurora A substrate using a Bora peptide array, and pSer59 was predicted to form bridging interactions with Aurora Arg205 and Plk1 Arg59. This was supported by NMR and biochemical assays. In addition, the authors validate that phosphorylation of Ser-112 on Bora enhances stabilization of the Aurora A-Bora complex Overall, the model revealed novel details of the interactions within the Aurora A-Bora-Plk1 ternary complex that are supported by the biochemical and NMR data. The work will be of significant interest to basic scientists whose work involves protein kinase signaling, cell division/mitosis, signal transduction, and cancer biology. We recommend publication of this manuscript with the following minor changes and additions.

1. In the introduction, on page 2, the authors seem a little confused about the Plk1 Polo-box domain - text as written: "...kinase domain linked to tandem Polo-box domains (PBD)", and cite a review paper. Actually, there is only a single Polo-box domain in these kinases, which contains both Polo-boxes and a bit of the upstream linker region. The "PBD" terminology denotes his 2-Polo-box +linker structure. Perhaps it would be better here to cite the PBD structure (Elia et al., Cell, 2002) as a primary citation here.
2. Similarly, the line "...during the G2/M transition following successful DNA damage repair" cites the Seki et al paper, but those findings are shown in the Macurek et al paper, not the Seki et al paper.
3. Using the model of the ternary complex as shown in Figure 1B, deletion constructs of Bora missing regions within the disordered loops, but still retaining the residues that bind the PBD, FW pocket and Aurora A, can be modeled and tested to see if such deletions can improve the ipTM scores and binding affinity.
4. On page 5, "S112A" within the sentence "Unexpectedly, the F56A/W58A Bora was less efficiently phosphorylated on S112A (Supplementary Figure S11, F compared to H and Supplementary Table S4)." This should be "S112".
5. In the assays shown in Figure 2D, the presence of excess F56AW58A Bora that remained unphosphorylated on S112 may complicate the interpretation of the results. Can the authors show that the S112-phosphorylated F56AW68A Bora is predominantly bound to Aurora A in such a mixture, perhaps by NMR using labelled pS112 F56AW58A Bora and unlabeled S112 F56AW58A Bora?
6. Please expand Figure 3A to better show the FW pocket-forming residues on Plk1.
7. It would be helpful to label the peaks in the mass spectra in Fig. S11 with the phospho-species that they correspond to.
8. In the last paragraph on page 7, "see we" in the sentence "As well as a decrease in intensity around pSer112 in Bora, see we an overall effect with decreased intensity across most of the Bora sequence." Should be corrected to "we see".
9. While not required, it would be helpful if binding or Bora to Aurora A after Erk2 phosphorylation could be shown using fluorescence polarization or ITC to lend additional support to the NMR data for S112 and S59 phosphorylation and for CEP192 and TPX2 competition.
10. The Aurora A phosphorylation motif has been further defined beyond that reported by the Pinna lab in 2005. Notably, the Ser-59 sequence on Bora (F-R-W-S-I), has, in addition to dominant selection for AR in the -2 position, both favorable -1 (W) and +1 (I) positions based on peptide library measurements (Alexander et al., Science Signaling 2011), further arguing that it may be an excellent Aurora A phosphorylation site.
11. Have the authors tried to model the Drosophila melanogaster Aurora A-Bora-Polo complex to see if the Asn substitution of Bora Ser59, and the expected loss of the interactions between Bora pSer59 and Plk1 Arg59 and Aurora A Arg205 are compensated by other features?
12. Given the relevance of the recent publication from Zhu et al. in https://doi.org/10.1038/s41467-025-63352-y to this study, the authors may want to comment on, or test, the relative importance of PKA and Aurora A as a potential kinase for Bora S59. While those authors argue that PKA phosphorylates Bora on Ser-59, one could easily imagine a model in which either PKA or Aurora A could initially phosphorylate that site followed by a propagation step after initial Aurora A activation, in which Aurora A phosphorylation of Bora Ser-59 is the dominant process.

-Dan Lim and Michael Yaffe

Significance

The work is well done and clearly presented.

This article by researchers at UW discuss the mass wave of misinformation in regards to the coronavirus. In this article, one of the researchers reveals that often, misinformation during massive events such as the Covid 19 out break are due to people's growing fear and anxiety. Because of the uncertainty, people are often seeking solutions, which therefore help exhilarate information they may find shocking or comforting. This is why its important to always fact check data before fully believing what you see online.

This article talks about how even if profiles may not share much information about themselves, their sexual orientation can still be deduced by their contact list, or "friends" list online. This that simple things like your network of who you know can reveal about yourself. It was revealed in the article that researches were also able to build bots which can collect information just like this to keep tabs on people. This goes for show that although you may think you are protected, you're online data can reveal things you may not want to share.

I found Catherine Stinson’s “The Dark Past of Algorithms That Associate Appearance and Criminality” especially compelling — it highlights how seemingly neutral data-mining efforts (for example facial recognition or risk scoring) embed deep historical biases and reinforce harmful associations. It makes me reflect: when we apply mining methods in social-media contexts, it’s not just about data quality but also which associations we’re willing to carry forward.

Reading this article had me very surprised. But also kind of not. It was about how Facebook tracks and stores data on people that aren't even users on the Facebook platform. I had no idea about Facebook tracking people even if they didn't have a Facebook account. But I totally believe it and it makes sense to me. These social media companies cross so many boundaries just to try and get a little more money. It disturbs me hearing that Facebook can track people that aren't Facebook users and I can't believe this is normalized.

I like this part. The author says we should not just follow the minimum rules. We should try to create a city that feels peaceful for everyone. It's not just about avoiding fines; it's about making the community a better place to live.

This is a very useful and specific solution. It explains a technical way to reduce noise—using special windows. It even says how much noise it can block (around 40 dB).

This statistic is very powerful. It shows that in just five years, the number of complaints in New York City more than doubled. This proves that the problem is not getting better; it is getting much worse. It is a clear trend.

This is a direct link between bar noise and health problems. It's not just about being annoyed. The noise causes real mental health issues like anxiety and sleep problems for many people. This is very strong evidence for my research.

This part is important because it explains why we can't just close all the bars. They are important for the city's culture and for tourism. This shows that the problem is not simple; we have to find a balance between nightlife and quiet for residents.

This is a important statistic from the study. It gives specific numbers for how loud bars are. 80 dBA is very loud, like a garbage disposal. This is solid data I can use to show how big the problem is.

eLife Assessment

This manuscript investigates inter-hemispheric interactions in the olfactory system of Xenopus tadpoles. Using a combination of electrophysiology, pharmacology, imaging, and uncaging, the transection of the contralateral nerve is shown to lead to larger odor responses in the unmanipulated hemisphere, and implicates dopamine signaling in this process. The study uses a rich and sophisticated array of tools to investigate olfactory coding and uncovers valuable mechanisms of signaling. However, the data is incomplete, with a few of the conclusions not being well-supported by the data; the interpretation should be adjusted with some caveats, or additional experiments should be done to support these conclusions.

Reviewer #1 (Public review):

In this study, the authors investigate LFP responses to methionine in the olfactory system of the Xenopus tadpole. They show that this response is local to the glomerular layer, arises ipsilaterally, and is blocked by pharmacological blockade of AMPA and NMDA receptors, with little modulation during blockade of GABA-A receptors. They then show that this response is translently enlarged following transection of the contralateral olfactory nerve, but not the optic lobe nerve. Measurement of ROS- a marker of inflammation- was not affected by contralateral nerve transection, and LFP expansion was not affected by pharmacological blockade of ROS production. Imaging biased towards presynaptic terminals suggests that the enlargement of the LFP has a presynaptic component. A D2 antagonist increases the LFP size and variability in intact tadpoles, while a GABA-B antagonist does not. On this basis, the authors conclude that the increase driven by contralateral nerve transection is due to DA signaling.

Overall, I found the array of techniques and approaches applied in this study to be creatively and effectively employed. However, several of the conclusions made in the Discussion are too strong, given the evidence presented. For example, the authors state that "The observed potentiation was not related to inflammatory mediators associated to inury, because it was caused by a release of the inhibition made by D2 dopamine receptor present in OSN axon terminals." This statement is too strong - the authors have shown that D2 receptors are sufficient to cause an increase in LFP, but not that they are required for the potentiation evoked by nerve transection. The right experiment here would be to get rid of the D2 receptors prior to transection and show that the potentiation is now abolished. In addition, the authors have not shown any data localizing D2 receptors to OSN axon terminals.

Similarly, the authors state, "the onset of LFP changes detected in glomeruli is determined by glutamate release from OSNs." Again, the authors have shown that blockade of AMPA/NMDA receptors decreases the LFP, and that uncaging of glutamate can evoke small negative deflections, but not that the intact signal arises from glutamate release from OSNs. The conclusions about the in vivo contribution of this contralateral pathway are also rather speculative. Acute silencing of one hemisphere would likely provide more insight into the moment-to-moment contributions of bilateral signals to those recorded in one hemisphere.

Author response:

Thank you for your time and for considering our manuscript as a Reviewed Preprint. We also would like to thank Reviewer 1 for their evaluation of our manuscript.

Here, we present a provisional response to reviewer comments and following their suggestions we will make an effort to: i) increase evidence for the role of dopamine in olfactory glomeruli and ii) delineate the circuit involved mediating the observed potentiation. Next, we briefly describe the set of experiments that are in progress or will be performed to improve our paper.

We will carry out immunostainings for tyrosine hydroxylase to certify that dopamine can be released on the genetically labelled glomerulus. There is a lack of good commercial antibodies for Xenopus (we already tried one and did not work, PA1-4679, Thermofisher scientific), but we will look for alternatives. In a previous set of experiments, we attempted to measure dopamine release in the glomerular layer by electroporating olfactory sensory neurons or olfactory bulb neurons with the dopamine sensors dLight1.1 (Addgene #111053) or dLight1.3 (Addgene # 111056). In our hands, fluorescence signals were extremely weak, barely undetectable. Similar results were obtained after electroporating the tectum or the rhombencephalon. We propose to repeat experiments using a more sensitive sensor such as GRAB_DA2m. Other approaches, such as performing single cell transcriptomics of olfactory sensory neurons might be considered to confirm the expression of D2 receptors.

We agree with the reviewer that we should obtain more lines of evidence in support for a presynaptic inhibition mediated by D2 receptors.To gain insight on the bilateral circuit mediating the observed potentiation of glomerular responses we are currently investigating the role of dorsolateral pallium neurons. In Xenopus tadpoles the lateral pallium plays an analogous role to the olfactory cortex in amniotes. Preliminary observations show that neurons located in this pallial region respond to ipsilateral stimulation of the olfactory epithelium and if damaged, a contralateral potentiation of glomerular output occurs. We aim to conclude this set of experiments and include it in the paper as we believe it clarifies the circuitry involved.

eLife Assessment

This valuable developmental study provides intriguing but incomplete evidence suggesting that, relative to adults, the enhancement of instrumental learning by Pavlovian bias is most pronounced in adolescence, while reward-induced memory enhancements are strongest in childhood. Although the authors tackle a key aspect of learning and motivation with rigorous experimental methods and sophisticated modeling techniques, there are substantial concerns about the absence of relevant analyses, the lack of accord between model-based and exploratory analyses, and the lack of an explanation for how the results cohere with inconsistent findings in the literature.

Reviewer #1 (Public review):

In this study, the authors aim to elucidate both how Pavlovian biases affect instrumental learning from childhood to adulthood, as well as how reward outcomes during learning influence incidental memory. While prior work has investigated both of these questions, findings have been mixed. The authors aim to contribute additional evidence to clarify the nature of developmental changes in these processes. Through a well-validated affective learning task and a large age-continuous sample of participants, the authors reveal that adolescents outperform children and adults when Pavlovian biases and instrumental learning are aligned, but that learning performance does not vary by age when they are misaligned. They also show that younger participants show greater memory sensitivity for images presented alongside rewards.

The manuscript has notable strengths. The task was carefully designed and modified with a clever, developmentally appropriate cover story, and the large sample size (N = 174) means their study was better powered than many comparable developmental learning studies. The addition of the memory measure adds a novel component to the design. The authors transparently report their somewhat confusing findings.

The manuscript also has weaknesses, which I describe in detail below.

It was not entirely clear to me what central question the researchers aimed to address. They note that prior studies using a very similar learning task design have reported inconsistent findings, but they do not propose a reason for why these inconsistent findings may emerge nor do they test a plausible cause of them (in contrast, for example, Raab et al. 2024 explicitly tested the idea that developmental changes in inferences about controllability may explain age-related change in Pavlovian influences on learning). While the authors test a sample of participants that is very large compared to many developmental studies of reinforcement learning, this sample is much smaller than two prior developmental studies that have used the same learning task (and which the authors cite - Betts et al., 2020; Moutoussis et al., 2018). Thus, the overall goal seems to be to add an additional ~170 subjects of data to the existing literature, which isn't problematic per se, but doesn't do much to advance our theoretical understanding of learning across development. They happen to find a pattern of results that differs from all three prior studies, and it is not clear how to interpret this.

Along those lines, the authors extend prior work by adding a memory manipulation to the task, in which trial-unique images were presented alongside reward outcomes. It was not clear to me whether the authors see the learning and memory questions as fundamentally connected or as two separate research questions that this paradigm allows them to address. The manuscript would potentially be more impactful if the authors integrated their discussion of these two ideas more. Did they have any a priori hypotheses about how Pavlovian biases may affect the encoding of incidentally presented images? Could heightened reward sensitivity explain both changes in learning and changes in memory? It was also not clear to me why the authors hypothesized that younger participants would demonstrate the greatest effects of reward on memory, when most of the introduction seems to suggest they might hypothesize an adolescent peak in both learning and memory.

As stated above, while the task methods seemed sound, some of the analytic decisions are potentially problematic and/or require greater justification for the results of the study to be interpretable.

Firstly, it is problematic not to include random participant slopes in the regression models. Not accounting for individual variation in the effects of interest may inflate Type I errors. I would suggest that the authors start with the maximal model, or follow the same model selection procedure they did to select the fixed effects to include for the random effects as well.

Secondly, the central learning finding - that adolescents demonstrate enhanced learning in Pavlovian-congruent conditions only - is interesting, but it is unclear why this is the case or how much should be made of this finding. The authors show that adolescents outperform others in the Pavlovian-congruent conditions but not the Pavlovian-incongruent conditions. However, this conclusion is made by analyzing the two conditions separately; they do not directly compare the strength of the adolescent peak across these conditions, which would be needed to draw this strong conclusion. Given that no prior study using the same learning design has found this, the authors should ensure that their evidence for it is strong before drawing firm conclusions.

It was also not clear to me whether any of the RL models that the authors fit could potentially explain this pattern. Presumably, they need an algorithmic mechanism in which the Pavlovian bias is enhanced when it is rewarded. This seems potentially feasible to implement and could help explain the condition-specific performance boosts.

I also have major concerns about the computational model-fitting results. While the authors seemingly follow a sound approach, the majority of the fitted lapse rates (Figure S10) are near 1. This suggests that for most participants, the best-fitting model is one in which choices are random. This may be why the authors do not observe age-related change in model parameters: for these subjects, the other parameter values are essentially meaningless since they contribute to the learned value estimate, which gets multiplied by a near-0 weight in the choice function. It is important that the authors clarify what is going on here. Is it the case that most of these subjects truly choose at random? It does seem from Figure 2A that there is extensive variability in performance. It might be helpful if the authors re-analyze their data, excluding participants who show no evidence of learning or of reward-seeking behavior. Alternatively, are there other biases that are not being accounted for (e.g., choice perseveration) that may contribute to the high lapse rates?

Parameter recovery also looks poor, particularly for gain & loss sensitivity, the lapse rate, and the Pavlovian bias - several parameters of interest. As noted above, this may be due to the fact that many of the simulations were conducted with lapse rates sampled from the empirical distribution. It would be helpful for the authors to a.) plot separately parameter recoverability for high and low lapse rates and b.) report the recoverability correlation for each parameter separately.

Finally, many of the analytic decisions made regarding the memory analyses were confusing and merit further justification.

(1) First, it seems as though the authors only analyze memory data from trials where participants "could gain a reward". Does this mean only half of the memory trials were included in the analyses? What about memory as a function of whether participants made a "correct" response? Or a correct x reward interaction effect?

(2) The RPE analysis overcomes this issue by including all trials, but the trial-wise RPEs are potentially not informative given the lapse rate issue described above.

(3) The authors exclude correct guesses but include incorrect guesses. Is this common practice in the memory literature? It seems like this could introduce some bias into the results, especially if there are age-related changes in meta-memory.

(4) Participants provided a continuum of confidence ratings, but the authors computed d' by discretizing memory into 'correct' or 'incorrect'. A more sensitive approach could compute memory ROC curves taking into account the full confidence data (e.g., Brady et al., 2020).

(5) The learning and memory tradeoff idea is interesting, but it was not clear to me what variables went into that regression model.

Reviewer #2 (Public review):

The authors of this study set out to investigate whether adolescents demonstrate enhanced instrumental learning compared to children and adults, particularly when their natural instincts align with the actions required in a learning task, using the Affective Go/No-Go Task. Their aim was to explore how motivational drives, such as sensitivity to rewards versus avoiding losses, and the congruence between automatic responses to cues and deliberate actions (termed Pavlovian-congruency) influence learning across development, while also examining incidental memory enhancements tied to positive outcomes. Additionally, they sought to uncover the cognitive mechanisms underlying these age-related differences through behavioral analyses and reinforcement learning models.

The study's major strengths lie in its rigorous methodological approach and comprehensive analysis. The use of mixed-effects logistic regression and beta-binomial regression models, with careful comparison of nested models to identify the best fit (e.g., a significant ΔBIC of 19), provides a robust framework for assessing age-related effects on learning accuracy. The task design, which separates action (pressing a key or holding back) from outcome type (earning money or avoiding a loss) across four door cues, effectively isolates these factors, allowing the authors to highlight adolescent-specific advantages in Pavlovian-congruent conditions (e.g., Go to Win and No-Go to Avoid Loss), supported by significant quadratic age interactions (p < .001). The inclusion of reaction time data and a behavioral metric of Pavlovian bias further strengthens the evidence, showing adolescents' faster responses and greater reliance on instinctual cues in congruent scenarios. The exploration of incidental memory, with a clear reward memory bias in younger participants (p < .001), adds a valuable dimension, suggesting a learning-memory trade-off that enriches the study's scope. However, weaknesses include minor inconsistencies, such as the reinforcement learning model's Pavlovian bias parameter not reflecting an adolescent enhancement despite behavioral evidence, and a weak correlation between learning and memory accuracy (r = -.17), which may indicate incomplete integration of these processes.

The authors largely achieved their aims, with the results providing convincing support for their conclusion that Pavlovian-congruency boosts instrumental learning in adolescence. The significant quadratic age effects on overall learning accuracy (p = .001) and in congruent conditions (e.g., p = .01 for Go to Win), alongside faster reaction times in these scenarios, convincingly demonstrate an adolescent peak in performance. While the reinforcement learning model's lack of an adolescent-specific Pavlovian bias parameter introduces a slight caveat, the behavioral and statistical evidence collectively align with the hypothesis, suggesting that adolescents leverage their natural instincts more effectively when these align with task demands. The incidental memory findings, showing younger participants' enhanced recall for reward-paired images, partially support the secondary aim, though the trade-off with learning accuracy warrants further exploration.

This work is likely to have an important impact on the field, offering valuable insights into developmental differences in learning and memory that could influence educational practices and psychological interventions tailored to adolescents. The methods, particularly the task's orthogonal design and probabilistic feedback, are useful to the community for studying motivation and cognition across ages, while the detailed regression analyses and reinforcement learning approach provide a solid foundation for future replication and extension. The data, including trial-by-trial accuracy and memory performance, are openly shareable, enhancing their utility for researchers exploring similar questions, though refining the model-parameter alignment could strengthen its broader applicability.

Author response:

We thank both reviewers for their thoughtful and constructive comments. To address this feedback, we plan to do the following:

Questions/Hypotheses: We will clarify the study’s motivation, central questions, and our hypotheses, with a particular focus on the integration across learning and memory.

Methods: To improve clarity and transparency, we will expand the Methods section and modify relevant figures to provide more explanation of the task, our decisions regarding data analysis approaches, and how they address our questions and hypotheses.

Learning Behavioral Analysis: As suggested by reviewers, we will fit and compare mixed-effects models with the maximal random effects structure for the within-subject variables and their interactions. We may simplify this structure as the data justify (i.e., if we encounter convergence problems or the random effects explain minimal variance). In the revision, we will also directly compare the adolescent peaks in performance across the conditions to support our conclusion that adolescents outperform people of other ages in the Pavlovian-congruent conditions.

Computational Modeling: We appreciate the reviewers’ close attention to the computational modeling methods, as it identified a small error in the reporting of the formulas we implemented. Specifically, the preprint’s softmax function had an error and should be printed as:

This correct parameterization can be seen in the Huys, 2018 public repository on line 48 here. As such, rather than indicating random choices, the lapse rates with estimated solutions close to one represent expected goal-directed behavior. That said, we acknowledge that parameter recovery indicated potential identifiability issues for some parameters, especially those with extreme values. We appreciate the reviewer’s suggestion to examine “learners” separately from “non-learners,” as has been done in prior work with adults (Cavanagh et al., 2013; Guitart-Masip et al., 2012). In this revision, we will investigate whether behavioral differences in learners vs. non-learners, among other potential explanations, accounts for the relatively poor parameter recovery. We will also explain more about why we selected these RL models, including how the Pavlovian policy works and why it adequately captures participants’ behavior.

Memory Behavioral Analysis: At the reviewers’ suggestion, we will expand our analysis of the learning-memory trade-off to fully explore this possible explanation. We will also explore the additional analyses that the reviewers suggested (e.g., ROC curves accounting for confidence ratings, analysis of correct vs. incorrect responses).

We are confident that these revisions will strengthen the work, and we are grateful to the reviewers for their thorough, insightful feedback. In the coming revision, we will provide a detailed point-by-point response to all comments and questions.

References

Cavanagh, J. F., Eisenberg, I., Guitart-Masip, M., Huys, Q., & Frank, M. J. (2013). Frontal Theta Overrides Pavlovian Learning Biases. The Journal of Neuroscience, 33(19), 8541–8548. https://doi.org/10.1523/JNEUROSCI.5754-12.2013

Guitart-Masip, M., Huys, Q. J. M., Fuentemilla, L., Dayan, P., Duzel, E., & Dolan, R. J. (2012). Go and no-go learning in reward and punishment: Interactions between affect and effect. NeuroImage, 62(1), 154–166. https://doi.org/10.1016/j.neuroimage.2012.04.024

Huys, Q. J. M. (2018). Bayesian Approaches to Learning and Decision-Making. In Computational Psychiatry (pp. 247–271). Elsevier. https://doi.org/10.1016/B978-0-12-809825-7.00010-9

man is too weak to even maintain the spirit of mutiny, needs to be whipped into submission

man will create other mysteries -find soothsayers, sorcery, heresy, atheism -- atheism here a miracle? miracle of rationality's triumph over mystery?

man are weak 'rebels'; can only be conquered by Miracle, Mystery and Authority

man only desires to renounce his freedom

men chiefly desire to submit to collective will, not follow their own desires

authority conquers the meek and gains their admiration

order of might makes right, despair of the meek forced to serve the mighty

Christ rejected the means that could make man happy (ie by limiting their freedom)

= The distribution of the sample proportion.

The distribution of X: is the set of the possible values that X can take, and how often they occur

No, the experiment did sampling withOUT replacement, because 50 balls were drawn simultaneously.

This type of tracking has always been something I've been curious about. I often notice that when I search something into google, or look for specific things on TikTok/Instagram, I soon will get ads, or posts about that thing I searched recommended to me. While I know that this is the apps taking my data and pumping out content related to it in order to get me more hooked to the app, I find this type of tracking invasive and weird. I also notice that I've been getting a lot of UW related content on my social media apps recently. So this makes me think that these apps track more then your searches, but things like your location, etc. as well.

Ai

I think these questions that are listed are all highly valuable questions. The reason why I think that is because I had been put in a lot of situations where I had to solve a problem in some kind of a way and many times I look over these factors. These are the most critical base of the solution process but I think are also very easy to miss and overlook them. Especially for "did anyone try to solve it in the past and fail?", I think this is really a strong question that needs to be pondered on and requires a lot of thinking/research based off other questions like "am I copying other person's solution/method?" "Can I learn out of their failures? Can I try it on my own?" and so on.

I think this makes an interesting point and also added another perspective. Usually when I do competitive analysis, I would usually come up with potential competition in my mind but never make an actual list of competition and comparison. Also the text mentioned that this will keep your research guided. This also added another perspective that you can use your comparison and competition to help you stay in your lane and I think that this also makes your solution go towards something that will solve a problem.

This idea really resonates with me because it highlights how important it is to research and analyze what already exists before creating something new. In UX design, it’s easy to jump straight into ideation, but taking the time to study competitors helps ensure that our design decisions are strategic rather than based on assumptions. By understanding what others have done, what works well and what doesn’t, we can build a stronger, more user-centered product that truly stands out.

Agreed. For the longest time I was searching for a "perfect framework" that would allow me to perform the most thorough competitive analysis. I then realized that the nature of the work was to show comparison, and that the methods should center around the stakeholders we're trying to communicate to.

Competitive analysis was something I wasn't aware of prior to this article, but after reading, I 100% agree with this statement. You can't just think about your customers when coming up with a solution design. Its also interesting that this is something that you will have to constantly think about. I wouldn't be surprised if it was the companies with good competitive analysis that are the one that stay afloat the longest.

I agree with this point. If you do a competitor analysis and find a competitor that is doing exactly what you want to do, what is the value in your new product? A good competitor analysis can ensure that you learn from others' mistakes, and address gaps that currently exist in the market. That's also why I think the question "why did they fail" is very important in understanding what previously went wrong when people tried to solve the problem.

I found the discussion of unintended versus intentional data poisoning especially striking — it reminded me of how a viral trend on a platform can distort a research survey in ways the authors likely never anticipated. One thing I’m wondering though: given that many social-media datasets are collected passively and opportunistically, how can researchers realistically detect when the data has already been poisoned by normal platform usage (rather than a malicious actor)?

eLife Assessment

This study provides a valuable contribution to understanding the functional and molecular organization of the medial nucleus accumbens shell in feeding. Using in vivo imaging, optogenetics, and genetic engineering, the authors present solid evidence for a rostro-caudal gradient in D1-SPN activity that refines earlier pharmacological models. The identification of Stard5 and Peg10 as molecular markers and the creation of a Stard5-Flp line represent meaningful advances for future circuit-specific studies. While stronger integration of molecular and functional results and additional analyses of other Stard5-expressing cell types (e.g., D2-SPNs, interneurons) would enhance completeness, the overall methodological rigor and convergence of findings make this a well-executed and informative study. This will be of interest to those interested in brain circuits, reward, emotion, and feeding behavior.

Reviewer #1 (Public review):

Summary:

This study examines how different parts of the brain's reward system regulate eating behavior. The authors focus on the medial shell of the nucleus accumbens, a region known to influence pleasure and motivation. They find that nerve cells in the front (rostral) portion of this region are inhibited during eating, and when artificially activated, they reduce food intake. In contrast, similar cells at the back (caudal) are excited during eating but do not suppress feeding. The team also identifies a molecular marker, Stard5, that selectively labels the rostral hotspot and enables new genetic tools to study it. These findings clarify how specific circuits in the brain control hedonic feeding, providing new entry points to understand and potentially treat conditions such as overeating and obesity.

Strengths:

(1) Conceptual advance: The work convincingly establishes a rostro-caudal gradient within the medNAcSh, clarifying earlier pharmacological studies with modern circuit-level and genetic approaches.

(2) Methodological rigor: The combination of fiber photometry, optogenetics, CRISPR-Cas9 genetic engineering, histology, FISH, scRNA-seq, and novel mouse genetics adds robustness, with complementary approaches converging on the central claim.

(3) Innovation: The generation of a Stard5-Flp line is a valuable resource that will enable precise interrogation of the rostral hotspot in future studies.

(4) Specificity of findings: The dissociation between appetitive and aversive conditions strengthens the interpretation that the observed gradient is restricted to feeding.

Weaknesses and points for clarification

(1) Role of D2-SPNs: Since D1 and D2 pathways often show opposing roles in feeding, testing, or discussing D2-SPN contributions would provide an important control and context. Since the claim is that Stard5 is expressed in both D1- and D2MSNs, it seems to contradict the exclusive role of D1R MSNs in authorizing food intake.

(2) Behavioral analyses:

a) In Figure 2, group differences in consumption appear uneven; additional analyses (e.g., lick counts across blocks and session totals) would strengthen interpretation.

b) The design and contribution of aversive assays to the main conclusions remain somewhat unclear and could be better justified.

c) The scope of behavior is mainly limited to consumption; testing related domains (motivation, reward valuation, and extinction) could broaden the significance.

(3) Molecular profiling:

a) Stard5 expression is present in both D1- and D2-SPNs; comparisons to bulk calcium signals and quantification of percentages across rostral and caudal cells would be helpful. The authors should establish whether these cells also express SerpinB2, an established marker of LH projecting neurons.

b) Verification of the Stard5-2A-Flp line (specificity, overlap with immunomarkers) should be documented more thoroughly.

c) The molecular analysis is restricted to a small set of genes; broader spatial transcriptomics could uncover additional candidate markers. See also above.

Reviewer #2 (Public review):

Summary:

Marinescu et al. combine in vivo imaging with circuit-specific optogenetic manipulation to characterize the anatomic heterogeneity of the medial nucleus accumbens shell in the control of food intake. They demonstrate that the inhibitory influence of dopamine D1 receptor-expressing neurons of the medial shell on food intake decreases along a rostro-caudal gradient, while both rostral and caudal subpopulations similarly control aversion. They then identify Stard5 and Peg10 as molecular markers of the rostral and caudal subregions, respectively. Through the development of a new mouse line expressing the flippase under the promoter of Stard5, they demonstrate that Stard5-positive neurons recapitulate the activity of D1-positive neurons of the rostral shell in response to food consumption and aversive stimuli.

Strengths:

This study brings important findings for the anatomical and functional characterization of the brain reward system and its implications in physiological and pathological feeding behavior. It is a well-designed study, technically sound, with clear and reliable effects. The generation of the new Stard5-Flp line will be a valuable tool for further investigations. The paper is very well written, the discussion is very interesting, addresses limitations of the findings, and proposes relevant future directions

Weaknesses:

At this stage, identification and characterization of the activity of Stard5-positive neurons is a bit disconnected from the rest of the paper, as this population encompasses both D1- and D2-positive neurons as well as interneurons. While they display a similar response pattern as D1-neurons, it remains to be determined whether their manipulation would result in comparable behavioral outcomes.

eLife Assessment

This study presents a valuable in-depth comparison of statistical methods for the analysis of ecological time series data, and shows that different analyses can generate different conclusions, emphasizing the importance of carefully choosing methods and of reporting methodological details. The evidence supporting the claims, based on simulated data for a two-species ecosystem, is solid, although testing on more complex datasets could be of further benefit. This paper should be of broad interest to researchers in ecology.

Reviewer #1 (Public review):

Summary:

The manuscript investigates methods for the analysis of time series data, in particular ecological time series. Such data can be analyzed using a myriad of approaches, with choices being made in both the statistical test performed and the generation of artificial datasets for comparison. The simulated data is for a two-species ecosystem. The main finding is that the rates of false positives and negatives strongly depend on the choices made during analysis, and that no one methodology is an optimal choice for all contexts. A few different scenarios were analyzed, including analysis with a time lag and communities with different species ratios.

Strengths:

The paper sets up a clear problem to motivate the study. The writing is easy to follow, given the dense subject matter. A broad range of approaches was compared for both statistical tests and surrogate data generation. The appendix will be helpful for readers, especially those readers hoping to implement these findings into their own work. The topic of the manuscript should be of interest to many readers, and the authors have put in extra effort to make the writing as clear as possible.

Weaknesses:<br /> The main conclusions are rather unsatisfying: "use more than one method of analysis", "be more transparent in how testing is done", and there is a "need for humility when drawing scientific conclusions". In fact, the findings are not instructions for how to analyze data, but instead highlight the extreme dependence of the interpretation of results on choices made during analysis. The conclusions reached in this study would be of interest to a specialized subset of researchers focused on the biostatistics of ecological data. Ending the article with a few specific recommendations for how to apply these conclusions to a broad range of datasets would increase the impact of the work.

Reviewer #2 (Public review):

Summary:

This manuscript tackles an important and often neglected aspect of time-series analysis in ecology - the multitude of "small" methodological choices that can alter outcomes. The findings are solid, though they may be limited in terms of generalizability, due to the simple use case tested.

Strengths:

(1) Comprehensive Methodological Benchmarking:

The study systematically evaluates 30 test variants (5 correlation statistics × 6 surrogate methods), which is commendable and provides a broad view of methodological behavior.

(2) Important Practical Recommendations:

The manuscript provides valuable real-world guidance, such as the superiority of tailored lags over fixed lags, the risks of using shuffling-based nulls, and the importance of selecting appropriate surrogate templates for directional tests.

(3) Novel Insights into System Dependence:

A key contribution is the demonstration that test results can vary dramatically with system state (e.g., initial conditions or abundance asymmetries), even when interaction parameters remain constant. This highlights a real-world issue for ecological inference.

(4) Clarification of Surrogate Template Effects:

The study uncovers a rarely discussed but critical issue: that the choice of which variable to surrogate in directional tests (e.g., convergent cross mapping) can drastically affect false-positive rates.

(5) Lag Selection Analysis:

The comparison of lag selection methods is a valuable addition, offering a clear takeaway that fixed-lag strategies can severely inflate false positives and that tailored-lag approaches are preferred.

(6) Transparency and Reproducibility Focus:

The authors advocate for full methodological transparency, encouraging researchers to report all analytical choices and test multiple methods.

Weaknesses / Areas for Improvement:

(1) Limited Model Generality:

The study relies solely on two-species systems and two types of competitive dynamics. This limits the ecological realism and generalizability of the findings. It's unclear how well the results would transfer to more complex ecosystems or interaction types (e.g., predator-prey, mutualism, or chaotic systems).

(2) Method Description Clarity:

Some method descriptions are too terse, and table references are mislabeled (e.g., Table 1 vs. Table 2 confusion). This reduces reproducibility and clarity for readers unfamiliar with the specific tests.

(3) Insufficient Discussion of Broader Applicability:

While the pairwise test setup justifies two-species models, the authors should more explicitly address whether the observed test sensitivities (e.g., effect of system state, template choice) are expected to hold in multi-species or networked settings.

(4) Lack of Practical Summary:

The paper offers great insights, but currently spreads recommendations throughout the text. A dedicated section or table summarizing "Best Practices" would increase accessibility and application by practitioners.

(5) No Real-World Validation:

The work is based entirely on simulation. Including or referencing an empirical case study would help illustrate how these methodological choices play out in actual ecological datasets.

Mijuel Johnson: Could the American Dream be different for each generation or ethnic/racial community?

Malinda Burke's experience: Fiscally conservative as in modern republican? Neo-liberalist view?

Polly Mann:Similar to Johnson: Is it different

"Homeownership and equity" What other factors limit someone from achieving that? -Student loans (how has that affected peoples financial gains?

David Hite: Allow for others to achieve it

Another mention of housing and the lack of accessibility for young people

Is it for everyone, is it for noone?

Have certain groups been excluded from the American Dream, is it attainable as a minority especially in the African American experience?

Sam Crane: Independent self-sufficiency? Could look at the ideas of neoliberalism and individual capital

Damian Conley's American Dream similar to Scott

Jack Ragheb's view: what paths have narrowed?

Roberto Lopez's American Dream

Scott Meyer's American Dream

Interesting statistic to search for

What resources do we no longer have that might have made the American Dream plausible back then, what do we have now?

The idealized belief brought from 1950s America and earlier beliefs

It is imperative to keep in mind these two entities coincide with each other. As our very country runs on democracy, this allows for politics to influence economy as people with power can be in positions that can have an impact on our economy. For example; U.S.-China trade war (2018-2020). The U.S. government, under President Donald Trump, imposed tariffs on hundreds of billions of dollars' worth of Chinese imports. The goal was to pressure China into changing their trade practices, protect American manufacturing, and reduce the trade deficit. The trades made Chinese goods more expensive in the U.S., which raised costs for American businesses and consumers. In response, China imposed retaliatory tariffs on U.S. exports like soybeans and cars, hurting American farmers and automakers. The uncertainty caused by the trade war slowed global investment and contributed to market volatility. It also pushed some companies to move production to other countries to avoid tariffs. Maybe taxing trades with other countries to keep manufacturing goods "American," wasn't the best idea for our economy.

Organizations like the BBC operated under a public service model, funded by license fees and guided by principles of impartiality, education, and cultural enrichment. This system reflected a time when broadcasting was seen as a national service, tightly regulated by the government to serve the public good. However, deregulation and the rise of neoliberal economic policies encouraged competition and privatization. By the 1990s and 2000s, with the expansion of satellite and digital broadcasting, streaming platforms like Netflix and Amazon Prime reshaped the media landscape. Production is often guided by audience demand, advertising revenue, and global market pressure rather than purely public service values.

Pay close attention to the use of "artificial sense of scarcity," as it's message is unveiling a deeper meaning. It is essentially establishing the cooperate companies controlling the price of manufactured goods to prolong consumption. Companies commercialize products to mass produce creating a trait of value and importance of the products. Emphasizing buying the product as soon as possible before they go away. When companies see how a certain product is being sold they can analyze the sales performance and determine to raise prices according to consumer uptake. Therefore, establishing scarcity on products that can otherwise be viewed as trivial. They, essentially, have control over the market and the price of goods.

TEXT- This poster encourages people to focus less on the material aspect like tinsel and lights and instead welcoming others and showing compassion. This poster through the use of "holy" and "prayers" shows Christian values, reminding others that the true spirit of Christmas is love, connection not materials. The font is bond and overall makes someone focus on the text.

IMAGE- The background is diagonal gradient lines with yellow and sometimes orange, all coming together, symbolistic to people coming together. Lastly, there is a gradient of all the colors combined with the text "less tinsel more love" in cursive. This Overall the color usage gives off peace and more significance to the text.

skimming through the texts to obtain a sense of what you are reading

make sure the source is relevant and is reliable.

Hi, I have a question about it.

Q1. pseudoinverse notebook uses JacobianWrtVariable.kQDot in the PseudoInverseController. However, JacobianWrtVariable.kV is used in the Pick notebook.

It means that qDot = v ?? So, is it okay to use either one ? - One confused thing : iiwa robot is 7 DOF robot. So, refer to the chapter 3 contents, position has 7 DOF (perhaps using quaternion), velocity has 6 DOF. How do we determine that qDot is not equal to v ? (Because I'm a beginner of the Drake, so I don't understand why qDot is equal to v in this example.)

Thanks.

eLife Assessment

This important work employed a recent, functional muscle network analysis for evaluating rehabilitation outcomes in post-stroke patients. While the research direction is relevant and suggests the need for further investigation, the strength of evidence supporting the claims is incomplete. Muscle interactions can serve as biomarkers, but improvements in function are not directly demonstrated, and the method's robustness is not benchmarked against existing approaches.

Reviewer #1 (Public review):

Summary:

This study addresses an important clinical challenge by proposing muscle network analysis as a tool to evaluate rehabilitation outcomes. The research direction is relevant, and the findings suggest further research. The strength of evidence supporting the claims is, however, limited: the improvements in function are not directly demonstrated, the robustness of the method is not benchmarked against already published approaches, and key terminology is not clearly defined, which reduces the clarity and impact of the work.

Comments:

There are several aspects of the current work that require clarification and improvement, both from a methodological and a conceptual standpoint.

First, the actual improvements associated with the rehabilitation protocol remain unclear. While the authors report certain quantitative metrics, the study lacks more direct evidence of functional gains. Typically, rehabilitation interventions are strengthened by complementary material (e.g., videos or case examples) that clearly demonstrate improvements in activities of daily living. Including such evidence would make the findings more compelling.

Second, the claim that the proposed muscle network analysis is robust is not sufficiently substantiated. The method is introduced without adequate reference to, or comparison with, the extensive literature that has proposed alternative metrics. It is also not evident whether a simpler analysis (e.g., EMG amplitude) might produce similar results. To highlight the added value of the proposed method, it would be important to benchmark it against established approaches. This would help clarify its specific advantages and potential applications. Moreover, several studies have shown very good outcomes when using AI and latent manifold analyses in patients with neural lesions. Interpreting the latent space appears even easier than interpreting muscle networks, as the manifolds provide a simple encoding-decoding representation of what the patient can still perform and what they can no longer do.

Third, the terminology used throughout the manuscript is sometimes ambiguous. A key example is the distinction made between "functional" and "redundant" synergies. The abstract states: "Notably, we identified a shift from redundancy to synergy in muscle coordination as a hallmark of effective rehabilitation-a transformation supported by a more precise quantification of treatment outcomes."

However, in motor control research, redundancy is not typically seen as maladaptive. Rather, it is a fundamental property of the CNS, allowing the same motor task to be achieved through different patterns of muscle activity (e.g., alternative motor unit recruitment strategies). This redundancy provides flexibility and robustness, particularly under fatiguing conditions, where new synergies often emerge. Several studies have emphasized this adaptive role of redundancy. Thus, if the authors intend to use "redundancy" differently, it is essential to define the term explicitly and justify its use to avoid misinterpretation.

Reviewer #2 (Public review):

Summary:

This study analyzes muscle interactions in post-stroke patients undergoing rehabilitation, using information-theoretic and network analysis tools applied to sEMG signals with task performance measurements. The authors identified patterns of muscle interaction that correlate well with therapeutic measures and could potentially be used to stratify patients and better evaluate the effectiveness of rehabilitation.

However, I found that the Methods and Materials section, as it stands, lacks sufficient detail and clarity for me to fully understand and evaluate the quality of the method. Below, I outline my main points of concern, which I hope the authors will address in a revision to improve the quality of the Methods section. I would also like to note that the methods appear to be largely based on a previous paper by the authors (O'Reilly & Delis, 2024), but I was unable to resolve my questions after consulting that work.

I understand the general procedure of the method to be: (1) defining a connectivity matrix, (2) refining that matrix using network analysis methods, and (3) applying a lower-dimensional decomposition to the refined matrix, which defines the sub-component of muscle interaction. However, there are a few steps not fully explained in the text.

(1) The muscle network is defined as the connectivity matrix A. Is each entry in A defined by the co-information? Is this quantity estimated for each time point of the sEMG signal and task variable? Given that there are only 10 repetitions of the measurement for each task, I do not fully understand how this is sufficient for estimating a quantity involving mutual information.

In the previous paper (O'Reilly & Delis, 2024), the authors initially defined the co-information (Equation 1.3) but then referred to mutual information (MI) in the subsequent text, which I found confusing. In addition, while the matrix A is symmetrical, it should not be orthogonal (the authors wrote AᵀA = I) unless some additional constraint was imposed?

(2) The authors should clarify what the following statement means: "Where a muscle interaction was determined to be net redundant/synergistic, their corresponding network edge in the other muscle network was set to zero."

(3) It should be clarified what the 'm' values are in Equation 1.1. Are these the co-information values after the sparsification and applying the Louvain algorithm to the matrix 'A'? Furthermore, since each task will yield a different co-information value, how is the information from different tasks (r) being combined here?

(4) In general, I recommend improving the clarity of the Methods section, particularly by being more precise in defining the quantities that are being calculated. For example, the adjacency matrix should be defined clearly using co-information at the beginning, and explain how it is changed/used throughout the rest of the section.

(5) In the previous paper (O'Reilly & Delis, 2024), the authors applied a tensor decomposition to the interaction matrix and extracted both the spatial and temporal factors. In the current work, the authors simply concatenated the temporal signals and only chose to extract the spatial mode instead. The authors should clarify this choice.

it is important to remember the location of where the information that you are citing and what paragraphs there in and the sentence to the period

The move unsettles global markets, revealing how fragile international production systems have become

Beijing’s timing blindsided Washington, exposing U.S. dependence on Chinese materials

Trump’s threat of extreme tariffs escalates tensions and risks a new phase of the trade war

This quote captures the article’s theme. China is adopting the U.S.’s own economic tactics, perhaps more effectively

Analysts warn China’s leverage in critical minerals could outweigh U.S. power in technology

China is mirroring U.S. export controls by using its dominance over rare earths, a direct challenge to the US tech restrictions.

add the Authers name and date it was published exact time and day if possible if t

okay. my opinion, placing myself in the position of the child here (so if i was under the complete impression and belief that robovie was sentient), my answer would be YES it deserves civil liberties. (i should also preface this by saying that i think prisoners should have the right to vote and to receive compensation for their work) but robovie is not sentient so now what. what would robovie do with the money. money doesnt mean anything to it. and how would robovie know what to vote for. i feel like if a non-sentient robot COULD vote, it would be a huge conflict of interest for us humans because whos telling that robot what to do?

HOLY SHIT????

HOLY SHIT.

Holy shit.

okay so ACCORDING TO the child, who is taking all of this info at face value, robovie has thoughts and feelings and history and is able to care about things. CAN robovie care about things? No. Because Robovie is not sentient. Robovie is following a script that was meticulously composed by humans. But i digress. the child doesnt know this.

She was tired of him talking about the operation

This line shows the women trying to ease the tension between the two.

Incredibly irresponsible.