I have always been skeptical about whether privacy on social media is truly “private.” In many cases, so-called private messages are still accessible to platform developers or automated systems, which means users are trusting companies to protect their privacy rather than actually controlling it themselves. While this access can be helpful in situations like reporting threats or harassment, it also raises questions about who ultimately benefits from this arrangement. If only social media companies are able to see and manage my private data, I am not sure that this kind of “privacy” genuinely serves users’ interests rather than the platforms’ own priorities.

Private messaging creates’ an expectation of privacy, but there are situations where limited access is necessary to protect users from threats or harassment. The challenge is designing systems that allow reporting and evidence sharing in harmful situations without turning routine private communication into something routinely monitored.

I was aware that direct messaging can store data, not so "private" after all

This section made me realize that privacy is not just about “hiding secrets,” but about control over our information and context. For example, we might want to talk differently with friends than with teachers or employers, but social media can mix everything together (context collapse). I also didn’t think about how “private messages” aren’t truly private since companies can still store and scan them. It feels like using social media always means giving up some privacy, even when we don’t notice it.

This is a good reminder that “private” on social media usually just means private from other users, not from the platform itself. It feels like the label creates a sense of safety that isn’t really accurate, especially when companies can still scan or access messages behind the scenes.

This is a good reminder that “private” on social media usually just means private from other users, not from the platform itself. It feels like the label creates a sense of safety that isn’t really accurate, especially when companies can still scan or access messages behind the scenes.

This section discusses the importance of privacy in everyday life. It argues that privacy is not just about covering up something bad, but also about comfort, dignity, and context. For example, someone may want to keep something private because they are embarrassed about it, or they want to avoid misunderstandings due to context collapse. However, the main idea of the text is that privacy is important for an individual because it helps them avoid the consequences of public exposure.

This is a particularly important note in my opinion. There are cases about sex trafficking victims who were found and the predator prosecuted because of social media giant having access to private messages and information. Of course it isn't something they should throw about, but when it's such a big part of our lives, it makes sense that it should help the police in investigation.

This makes me think of the Tea app data leak in which almost all users had their information leaked because the developer allegedly stored it all in a public Google Drive. Certain ethical situations should be mandatory to follow when creating a social platform, even (or especially) if a developer is inexperienced.

That’s such a good reminder that “private” messaging usually just means “not public,” not “only between two people.” It makes me want to be more careful about what I assume is truly confidential when I DM. I also think it’s wild how much of this is automated—like filtering, scanning, or flagging messages without us noticing. It raises a real question of how much privacy we’re actually trading for convenience.

This highlights the tension between privacy and accountability on social media. Messages are labeled “private,” but that privacy is conditional and mediated by the platform. While access to private messages can be essential for safety and harm prevention, it also requires strong safeguards so that surveillance and misuse don’t become the default rather than the exception.

It is interesting that using symbols, uppercase letters, and numbers does not significantly increase the difficulty of brute-force attacks, while increasing the length of a password dramatically raises the cost of cracking it. However, many social media platforms still emphasize “complex” password rules rather than encouraging longer passwords. This can create a false sense of security for users, who may believe their passwords are strong when they are not. Ironically, these complexity requirements can even make passwords harder to remember, leading users to reuse them or choose predictable patterns, which ultimately gives attackers more opportunities.

This statement shifts the focus of "protection" from the company level to the individual level, emphasizing that users still have actionable self-protection strategies. The significance of 2FA lies in the fact that even if a password is leaked, it is difficult for attackers to log in directly using only the password, thus reducing the probability of credential stuffing and account takeover. It also reminds us that security is layered – even the best platform security can be compromised by individual vulnerabilities such as phishing or weak passwords. However, this also highlights a limitation: 2FA can only reduce the risk of "account theft," but it cannot solve structural problems such as the platform itself leaking your private data.

This statement highlights the fragility of the "trust relationship" between users and the platform: we share information assuming the platform will protect it properly. It also implies that the problem is not an isolated incident, but "happens frequently," suggesting that security failures may be related to systems, processes, or business priorities. More importantly, the consequences of a single security breach often extend beyond the platform itself, affecting users' accounts on other websites and posing risks to their real lives. Readers will naturally ask: why did the platform fail—was it due to insufficient technical capabilities, management negligence, or prioritizing growth and convenience over security?

This shows how even major platforms can ignore basic security practices. How can platforms be held to stricter accountability standards when they fail to protect user data?

This has been a massive problem since the creation and widespread use of social media, and there has never been a definitive resolution to it, as hackers will always find ways to access people's personal information. Additionally, as mentioned, employees will always misuse their access and would also likely sell important personal information, especially if it comes to celebrities.

When reading this section I'm reminded of a pretty infamous case that happened not long ago. The "Tea App" was used among young girls all across North America, and it was known for being an app where young women would go online and post about men they've been with and their bad, weird, or good attributes- essentially "spilling the tea". It was marketed as a "safe space" for women, where they could post anonomously and communicate potential catfishes, offenders, or overall bad men. However in 2023 a hacker had managed to leak all of the users' information, including but not limited to- credit card information, addresses, and 13,000 government IDs. This happened because the Tea app hadn't properly encrypted or protected the data, allowing the hacker to virtually access alll the users' information.**

I find the concept of securty and privacy on social media incredibly intriguing, as users are almost always promised that just by having a username and password, your data is completely protected, or at least we are given that assumption. However, it's relatively easy to hack into anyone's account if you have the right knowledge and know where to look. Especially if you have the capabality to manage an app or website from the back end, having the ability to go through data within an application can lead to data leaks, and private information you thought no one would have can suddenly be given to the world.

This example illustrates a gap between users’ expectations of privacy and the actual practices of social media companies. Although users consent to sharing data, that consent assumes responsible stewardship, which is violated when companies fail to implement basic security measures.

I remember a story in 2014, where many celebrities' personal photos were leaked because of a simple phishing scam involving an employee. It reminded me that network protection is not the only that needs to be protected but employees need training as well.

The passage emphasizes the difference between the expectation of users regarding their privacy on social media and how these companies actually provide security for their data. It talks about how passwords need to be encrypted so that they cannot be easily read, but how some companies failed to do so, putting their users’ private information at risk, as shown in the cases of Facebook and Adobe.

Yeah, it’s kind of a weird trade—we hand over a ton of personal info because we assume the platform will protect it, but breaches still happen all the time. It makes “trust” feel more like a gamble than a guarantee. What also bugs me is that once your data is out there, you can’t really take it back, even if the company apologizes or improves security later. It definitely makes me think twice about what I share and what permissions I give apps.

This section helped me realize that security failures are often not just technical problems, but also human and organizational ones. Even when proper security practices are well known, companies still choose convenience or cost-saving over protecting users’ data. What stood out to me most was how easily individuals can become targets through things like password reuse or phishing, which makes personal security practices like two-factor authentication feel necessary rather than optional.

I have heard multiple cases/instances of this happening but never heard of any follow up about this, at least in the cases of social media. Were people's accounts then hacked? What came from this? I'm aware it's bad to generalize based on your own experiences, but I was only ever hacked once on instagram (my account started posting scam advertisements and changed my profile picture), but I just changed my password and the problem went away. Was it a similar case for different users? Did anything serious come from these cases?

What feels most concerning in these examples is that users don’t really have a way to verify whether companies are following proper security practices. We’re asked to trust platforms with highly sensitive information, but when breaches happen, the consequences mostly fall on users rather than the companies. This creates a serious imbalance in responsibility and risk.

This underscores that burnout isn't just a general workplace issue but a specific crisis within the nursing profession that requires specialized self-care strategies.

This overall secrtion stood out to me because of the amount of clarity it provided on why literature reviews are essential across all research disciplines ,not just as background but aspart of the research process.

Reviewer #1 (Public review):

Meiotic recombination at chromosome ends can be deleterious, and its initiation-the programmed formation of DSBs-has long been known to be suppressed. However, the underlying mechanisms of this suppression remained unclear. A bottleneck has been the repetitive sequences embedded within chromosome ends, which make them challenging to analyze using genomic approaches. The authors addressed this issue by developing a new computational pipeline that reliably maps ChIP-seq reads and other genomic data, enabling exploration of previously inaccessible yet biologically important regions of the genome.

In budding yeast, chromosome ends (~20 kb) show depletion of axis proteins (Red1 and Hop1) important for recruiting DSB-forming proteins. Using their newly developed pipeline, the authors reanalyzed previously published datasets and data generated in this study, revealing heretofore unseen details at chromosome ends. While axis proteins are depleted at chromosome ends, the meiotic cohesin component Rec8 is not. Y' elements play a crucial role in this suppression. The suppression does not depend on the physical chromosome ends but on cis-acting elements. Dot1 suppresses Red1 recruitment at chromosome ends but promotes it in interior regions. Sir complex renders subtelomeric chromatin inaccessible to the DSB-forming machinery.

The high-quality data and extensive analyses provide important insights into the mechanisms that suppress meiotic DSB formation at chromosome ends. To fully realise this value, several aspects of data presentation and interpretation should be clarified to ensure that the conclusions are stated with appropriate precision and that remaining future issues are clearly articulated.

(1) To assess the chromosome fusion effects on overall subtelomeric suppression, authors should guide how to look at the data presented in Figure 2b-c. Based on the authors' definition of the terminal 20 kb as the suppressed region, SK1 chrIV-R and S288c chrI-L would be affected by the chromosome fusion, if any. In addition, I find it somewhat challenging to draw clear conclusions from inspecting profiles to compare subtelomeric and internal regions. Perhaps, applying a quantitative approach - such as a bootstrap-based analysis similar to those presented earlier-would be easier to interpret.

(2) The relationship between coding density and Red1 signal needs clarification. An important conclusion from Figure 3 is that the subtelomeric depletion of Red1 primarily reflects suppression of the Rec8-dependent recruitment pathway, whereas Rec8-independent recruitment appears similar between ends and internal regions. Based on the authors' previous papers (referencess 13, 16), I thought coding (or nucleosome) density primarily influences the Rec8-independent pathway. However, the correlations presented in Figure 2d-e (also implied in Figure 3a) appear opposite to my expectation. Specifically, differences in axis protein binding between chromosome ends and internal regions (or within chromosome ends), where the Rec8-dependent pathway dominates, correlate with coding density. In contrast, no such correlation is evident in rec8Δ cells, where only the Rec8-independent pathway is active and end-specific depletion is absent. One possibility is that masking coding regions within Y' elements influences the correlation analysis. Additional analysis and a clearer explanation would be highly appreciated.

(3) The Dot1-Sir3 section staring from L266 should be clarified. I found this section particularly difficult to follow. It begins by stating that dot1∆ leads to Sir complex spreading, but then moves directly to an analysis of Red1 ChIP in sir3∆ without clearly articulating the underlying hypothesis. I wonder if this analysis is intended to explain the differences observed between dot1∆ and H3K79R mutants in the previous section. I also did not get the concluding statement - Dot1 counteracts Sir3 activity. As sir3Δ alone does not affect subtelomeric suppression, it is unclear what Dot1 counteracts. Perhaps, explicitly stating the authors' working model at the outset of this section would greatly clarify the rationale, results, and conclusions.

Reviewer #2 (Public review):

Summary:

In this manuscript, Raghavan and his colleagues sought to identify cis-acting elements and/or protein factors that limit meiotic crossover at chromosome ends. This is important for avoiding chromosome rearrangements and preventing chromosome missegregation.

By reanalyzing published ChIP datasets, the researchers identified a correlation between low levels of protein axis binding - which are known to modulate homologous recombination - and the presence of cis-acting elements such as the subtelomeric element Y' and low gene density. Genetic analyses coupled with ChIP experiments revealed that the differential binding of the Red1 protein in subtelomeric regions requires the methyltransferase Dot1. Interestingly, Red1 depletion in subtelomeric regions does not impact DSB formation. Another surprising finding is that deleting DOT1 has no effect on Red1 loading in the absence of the silencing factor Sir3. Unlike Dot1, Sir3 directly impacts DSB formation, probably by limiting promoter access to Spo11. However, this explains only a small part of the low levels of DSBs forming in subtelomeric regions.

Strengths:

(1) This work provides intriguing observations, such as the impact of Dot1 and Sir3 on Red1 loading and the uncoupling of Red1 loading and DSB induction in subtelomeric regions.

(2) The separation of axis protein deposition and DSB induction observed in the absence of Dot1 is interesting because it rules out the possibility that the binding pattern of these proteins is sufficient to explain the low level of DSB in subtelomeric regions.

(3) The demonstration that Sir3 suppresses the induction of DSBs by limiting the openness of promoters in subtelomeric regions is convincing.

Weaknesses:

(1) The impact of the cis-encoded signal is not demonstrated. Y' containing subtelomeres behave differently from X-only, but this is only correlative. No compelling manipulation has been performed to test the impact of these elements on protein axis recruitment or DSB formation.

(2) The mechanism by which Dot1 and Sir3 impact Red1 loading is missing.

(3) Sir3's impact on DSB induction is compelling, yet it only accounts for a small proportion of DSB depletion in subtelomeric regions. Thus, the main mechanisms suppressing crossover close to the ends of chromosomes remain to be deciphered.

Reviewer #1 (Public review):

Summary:

In this study, Nagao and Mochizuki examine the fate of germline chromosome ends during somatic genome differentiation in the ciliate Tetrahymena thermophila. During sexual reproduction, a new somatic genome is created from a zygotic, germline-derived genome by extensive programmed DNA elimination events. It has been known for some time that the termini of the germline chromosomes are eliminated, but the exact process and kinetics of the elimination events have not been thoroughly investigated. The authors first use germline-specific telomere probes to show that the loss of these chromosome ends occurs with similar timing as other DNA elimination events. By comparative analysis of the assembled germline and somatic genomes, the authors find that the ends of each of the germline chromosomes are composed of a few hundred kilobases of micronuclear limited sequences (MLS) that are removed starting around 14 hours after the start of conjugation, which initiates sexual development. They then develop an in situ hybridization assay to track the fate of one end of chromosome 4 while simultaneously following the adjacent macronuclear destined sequence (MDS) retained in the new somatic genome. This allows the authors to more clearly show that these adjacent chromosomal segments are initially amplified in the developing genome before the terminal MLS is eliminated. Finally, they mutate the chromosome breakage sequence (CBS) that normally separates the MLS terminus from the adjacent MDS region, to show that strains that develop with only one mutant chromosome can produce viable sexual progeny, but it appears that both the MLS and the MDS from the mutant chromosome are lost. If both chromosome copies have the CBS mutation, the cells arrest during development and do not eliminate many germline-limited sequences and fail to produce viable progeny. Overall, this study provides many new insights into the fate of germline chromosome ends during somatic genome remodeling and suggests extensive coordination of different DNA elimination events in Tetrahymena.

Strengths:

Overall, the experiments were well executed with appropriate controls. The findings are generally robust. Importantly, the study provides several novel findings. First, the authors provide a fairly comprehensive characterization of the size of the MLS at the end of each germline chromosome. I'm not sure whether this has been published elsewhere. Second, the authors develop a novel method to study the fate of chromosome termini during development and use it to conclusively track the elimination of these termini. Third, the authors show that the elimination of these termini appears to occur concurrently with most other DNA elimination events during somatic genome differentiation. And fourth, the authors show that failure to separate these eliminated sequences from the normally retained chromosome alters the fate of these adjacent MDS and the loss of the cells' ability to produce viable progeny.

Weaknesses:

It appears the authors did extensive analysis of the MLS chromosome ends, but did not provide too much information related to their composition. If this has not been published elsewhere, it would be useful to describe the proportion of unique and repetitive sequences and provide more information about the general composition of the chromosome ends. Such information would help the reader understand the nature of these MLS and how they may or may not differ from other eliminated sequences. Although the development of the novel FISH probes for large chromosome ends allowed for these novel discoveries, the signal in several images was visible, but often quite faint. I'm not sure there is anything the authors could do to improve the signal-to-noise ratio, but one needs to stare at the images carefully to understand the findings. One main weakness in the opinion of this reviewer is that the authors did very little to understand why, when a terminal MLS and the adjacent MDS fail to get separated because of failure in chromosome breakage, both segments are eliminated. The authors propose that possibly essential genes in the MDS get silenced, and the resulting lack of gene expression is the issue, but this and other possibilities were not tested. The study would provide more mechanistic insight if they had tried to assess whether the MDS on the CBS mutant chromosome becomes enriched in silencing modifications (e.g., H3K9me3). Alternatively, the authors could have examined changes in gene expression for some of the loci on the neighbouring MDS. The other main weakness is that since the authors only mutated the end of one germline chromosome, it is not clear whether the elimination of the MDS adjacent to the terminal MLS on chromosome 4 when the CBS is mutated is a general phenomenon, i.e., would happen at all chromosome ends, or is unique to the situation at Chromosome 4R. Knowing whether it is a general phenomenon or not would provide important insight into the authors' findings.

Reviewer #2 (Public review):

Summary:

Nagao and Mochizuki investigated how the germline (MIC) telomere was removed during programmed genome rearrangement in the developing somatic nucleus (MAC). Using an optimized oligo-FISH procedure, the authors demonstrated that MIC telomeres were co-eliminated with a large region of MIC-limited sequences (MLS) demarcated on the opposite side by a sub-telomeric chromosome breakage site (CBS). This conclusion was corroborated by the latest assembly of the Tetrahymena MIC genome. They further employed CRISPR-Cas9 mutagenesis to disrupt a specific sub-telomeric CBS (4R-CBS). In uniparental progeny (mutant X WT), DNA elimination of the sub-telomeric MLS was not affected, but the adjacent MAC-destined sequence (MDS) may be co-eliminated. However, in biparental progeny (mutant X mutant), global DNA elimination was arrested, revealing previously unrecognized connections between chromosome breakage and DNA elimination. It also paves the way for future studies into the underlying molecular mechanisms. The work is rigorous, well-controlled, and offers important insights into how eukaryotic genomes demarcate genic regions (retained DNA) and regions derived from transposable elements (TE; eliminated DNA) during differentiation. The identification of chromosome breakage sequences as barriers preventing the spread of silencing (and ultimately, DNA elimination) from TE-derived regions into functional somatic genes is a key conceptual contribution.

Strengths:

New method development: Oligo-FISH in Tetrahymena. This allows high-resolution visualization of critical genome rearrangement events during MIC-to-MAC differentiation. This method will be a very powerful tool in this area of study.

Integration of cytological and genomic data. The conclusion is strongly supported by both analyses.

Rigorous genetic analysis of the role played by 4R-CBS in separating the fate of sub-telomeric MLS (elimination) and MDS (retention). DNA elimination in ciliates has long been regarded as an extreme form of gene silencing. Now, chromosome breakage sequences can be viewed as an extreme form of gene insulators.

Weaknesses:

The finding of global disruption of DNA elimination in 4R-CBS mutant progeny is highly intriguing, but it's mostly presented as a hypothesis in the Discussion. The authors propose that the failure to separate MLS from MDS allows aberrant heterochromatin spreading from the former into the latter, potentially silencing genes required for DNA elimination itself. While supported by prior literature on heterochromatin feedback loops, the specific targets silenced are not identified. While results from ChIP-seq and small RNA-seq can greatly strengthen the paper, the reviewer understands that direct molecular characterization may be beyond the scope of the current work.

R0:

Reviewer #1:

Methodology: study design & datasource, heading overlap with data source and extraction. You may consider differentiating the study design+population from the data source+data extraction to improve clarity and avoid repetition.

The covariates are presented in a table. Consider adding a concise paragraph describing key variables and their categorization. Perhaps detailed coding and operational definitions should be presented in a supplementary table.

The analysis plan refers to Objective 2 and Objective 3 however, the study objectives are not stated anywhere earlier in the manuscript. They should be explicitly stated to improve coherence

Also, this contradicts “shared frailty at the individual level”. Please clarify the intended clustering structure. Did you model with the shared or Individual-level frailty?

Reviewer #2:

This manuscript addresses an important and under-researched area by examining long-term trends in attrition from HIV care and associated predictors among adolescent girls and young women (AGYW) with non-viral load suppression in Tanzania. The use of routine programmatic data is a major strength and enhances the relevance of the findings for the national program. The objectives are clear, and the results provide insights into patterns of disengagement from care in this vulnerable population. However, the manuscript would benefit from clearer operational definitions of key outcomes particularly inconsistent viral load suppression. Further discussion linking the findings to existing regional and global literature, as well as clearer description of programmatic and policy implications, would strengthen the paper. I recommend minor revisions to improve clarity and consistency.

R1:

Reviewer #1:

All comments have been addressed

Reviewer #2:

General review of the revised manuscript I have reviewed the revised manuscript and found that the authors have addressed all the comments; however, a few minor edits are still required before publication. Please see the table below.

Section: Introduction <br /> Comment: Correct spelling UANIDS <br /> Line number: 58

Section: Methods <br /> Comment: It is essential that the term inconsistent viral load suppression needs to be clearly defined in the manuscript. Note that two viral load results ≥1000 copies/ml at least six months after ART initiation is the standard definition for non-viral suppression or ART virological failure.<br /> Ideally, inconsistent viral load suppression would have been a situation whereby PLHIV achieves an undetectable viral load at least 6 months after ART initiation, but subsequently experience detectable viral load result/s ≥1000 copies/ml. To avoid confusion, refer to this sentence in conclusion: Notably, individuals with an initial unsuppressed viral load were more likely to disengage from care.

Section: Results <br /> Comment: Table 1: First line and second line not defined. Not every reader knows what Tanzanian ART regimens. Line number: 170-171

Section: Discussion Comment: A citation is not inserted <br /> Line number: 253

Section: Discussion Comment: Correct the word form to read from Line number: 254

Be formal and respectful when giving feedback to others.

Always do the instructor questions first because that's what's most likely to be graded.

Reviewer #1 (Public review):

Summary:

A hallmark of cortical development is the temporal progression of lineage programs in radial glia progenitors (RGs) that orderly generate a large set of glutamatergic projection neuron types, which are deployed to the cortex in a largely inside-out sequence. This process is thought to contribute to the formation of proper cortical circuitry, but the underlying cellular and molecular mechanisms remain poorly understood. To a large extent, this is due to technical limitations that can fate map RGs and their progeny with cell type resolution, and manipulate gene expression with proper cell and temporal resolution. Building on the TEMPO technique that Tsumin Lee group developed, here Azur et al show that the RNA binding protein Imp1 functions as a dosage- and stage-dependent post-transcriptional mechanism that orchestrates developmental stage transitions in radial glial progenitors, and controls neuronal fate decisions and spatial organization of neuronal and glial cell progeny. Their results suggest that while transcriptional regulators define available cellular states and gate major transitions, post-transcriptional mechanisms like Imp1 provide an additional layer of control by modulating stage-specific transcript stability. Imp1 thus acts as a temporal coordinator whose dosage and timing determine whether developmental transitions are temporarily delayed or blocked. These findings establish a new framework for understanding how post-transcriptional mechanisms integrate with transcriptional and epigenetic regulatory layers to control cortical temporal patterning.

Strengths:

The authors apply a novel genetic fate mapping and gene manipulation technology (TEMPO) with cellular resolution. This reveals a dosage- and stage-dependent post-transcriptional mechanism that orchestrates developmental stage transitions in radial glial progenitors, and controls neuronal fate decisions and spatial organization of neuronal and glial cell/astrocyte progeny.

Weaknesses:

The endogenous developmental expression pattern of Imp1 and TEMPO-mediated overexpression are not well described or characterized with cellular resolution (whether only in radial glial cells or also in post-mitotic neurons). Thus, the interpretations of the overexpression phenotypes are not always clear.

R0:

Reviewer #1:

The article is relevant and timely. Please use COREQ guidelines/other community guidelines for qualitative research listed on the EQUATOR network to improve the rigour and flow of the article. Additional suggestions for your consideration are listed below. 1. The rationale for the article as well as research question needs to be made more explicit. Additionally, the novelty of the article is relatively unclear. 2. The use of a framework devised for infectious diseases needs to be examined- why was this framework chosen? 3. Line 52-54: It may be useful to examine the cause of death in context of age; additionally, the later use of terms like young-old-middle aged are ambiguous later in the article, please provide an operational definition. 4. Line 54-57: The reason for prioritising lived experience is unclear. The logical flow establishing the rationale for this inquiry needs strengthening. 5. The linkages of NCDs with urbanisation need more citation and can be explored better. The authors may consider reassessing the introduction section which seems to appear definitive without providing a research gap. 6. Why is this research needed? What makes it relevant for global health? This needs to be elucidated in the text. 7. The use of the word "drug peddler" should be in quotes at least at first use, to ensure that it is seen in its local context. 8. The narrative findings are rich and well presented- the global health impact of these findings/future paths based on these findings need to be be made explicit.

Reviewer #2:

This manuscript is well-written and engaging, and I would like to commend the authors for presenting such rich and dense information.

Here are my comments, which I believe will enhance the content of this manuscript.

1. Page 2, line 27 (abstract section): The term "oppression" appears quite strong, and I do not find any evidence supporting it in the results section. Could the authors clarify what they mean by "oppression"? Additionally, the sentence “as gender norms and experiences of masculinities and femininities reflected the division of roles and access to resources by men and women, which in turn shaped their ability to seek early and better healthcare interventions” seems to contradict the notion of oppression if participants are able to seek early and improved healthcare interventions.

2. Page 6, line 133: typo: a dot is in the middle of the sentence. Consider removing.

3. Page 7 on selection of study participants: How did researchers identify participants based on diabetes and hypertension criteria, given that these medical conditions require a confirmed diagnosis from health professionals? Additionally, were any participants identified using a snowball sampling technique?

4. It is mentioned that this study was conducted as part of the broad ARISE project. Can the authors clarify whether the study participants were enrolled into the main project and if so, to what extent this initial involvement of the main study had impacted the data collection?

5. An important section on data collection is missing. I would like authors to include this in order to explain what specific data were collected at each round, why was it necessary to split data collection over different timepoints, where and in which language were data collected, how long lasted interviews on average, and who collected the data, any bias that may result from the way the study participants perceived the data collection team during fieldwork?

6. The data analysis section requires further clarification. It would be beneficial if the authors could elaborate on their data coding strategy. It appears that a deductive approach was employed, yet they did not explain how the coding frame was initially developed before its application to the data, nor did they specify who conducted these procedures. Additionally, information regarding the software used to facilitate the data analysis is missing.

7. The use of relevant qualitative data reporting guideline is missing. This is important to include as it will help ensure that ensure that the methods and findings are clearly and transparently communicated in the manuscript.

8. In relation to adapting the framework for Infectious Diseases of Poverty Research, it would be beneficial if the authors could clarify the specific adaptations made to the framework and how it was applied during data analysis.

9. They mentioned that participants who faced distress during the interviews were allowed to grieve and were consoled. How many participants developed such condition during interviews at which round of data collection, and to what extent did this impact on data collected?

10. This study seeks to explore the lived experiences of individuals affected by NCDs in informal settlements. However, the findings presented in the results section, particularly the initial part titled "lived experience of NCD," fall short of adequately conveying the participants' current experiences with these health conditions. Firstly, the authors include excerpts from three informants but fail to demonstrate how these accounts are representative of all study participants. Secondly, the discussion of informants' lives prior to developing their current health conditions renders the information less pertinent to the study's objectives. It would be beneficial if the authors could focus on participants current lives to discuss the intersectionality of NCDs with social, economic, and gender factors within the participants' living environments, and how these elements contribute to shaping the management of their health conditions. This way of presenting the findings restricts our understanding, as the same observation is reiterated throughout the discussion section.

11. In the context of chronic disease, it can be assumed that participants with diabetes, hypertension, or comorbidities might encounter similar yet distinct challenges. It would be beneficial for the authors to discuss the findings across these cases, highlighting both similarities and differences, and to establish a hierarchy within the data.

12. The use of terms like "people," "women," or "men" in the results section can be misleading, as they might suggest that the findings apply to the general population. Instead, it is advisable to use terms such as "informants," "study participants," or "men" or "women in this study" to ensure that the information reported is limited to those individuals who participated in this data collection.

Reviewer #3 (Public review):

Summary:

In this study, the authors injected a contrast agent into patients and followed the induced signal change with MRI. Doing so, they observed cerebrospinal fluid (CSF) drainage whose magnitude and dynamics varied by anatomical location and scaled with a range of cognitive and socio-demographic metrics, including sleep scores and sex.

Strengths:

I would first like to stress that I am not a specialist in the topic of that paper; so my comments should be taken with a grain of salt, and feedback from the other reviewers should also be carefully considered.

I found the text concise and the figures straightforward to understand. Although they are manually defined, the authors compared drainage across different anatomical locations, which is a positive feature. Albeit purely correlative, the attempt to connect these otherwise 'peripheral' measures to cognitive variables is quite interesting. I also particularly liked the last paragraph of the discussion, which listed the main limitations of the study.

Weaknesses:

In the paragraph starting at line 446, the authors interpret poor sleep quality as being a cause and a consequence of impaired CSF clearance, but their approach is purely correlational. In other words, a third variable could be driving both of these parameters (correct?), thereby explaining their correlation. Later, they also proposed that therapeutically altering CSF clearance could improve cognitive symptoms, but, again, if there's a hidden cause of the correlation, that does not seem like a valid possibility. I believe there were other instances of this sort of inferential problem in the Discussion. It seems essential, particularly in clinical research, to precisely identify what the available evidence supports (correlation) and what is speculation (causation).

Assuming I did not miss it, the approach for testing and reporting correlations is not specified. In particular, the authors report correlation with CSF drainage and a variety of other metrics. But how many tests did the authors perform? They solely mention that they used the Benjamini-Hochberg method to correct for multiple comparisons. How were the decisions to test for this or that effect determined? Or did they test all the metrics they had? Also, that particular correction method is limited when statistics are negatively correlated. It would be helpful to validate findings with another approach.

I assume many of the metrics the authors use are also correlated with one another. Is it possible that a single principal component is driving the different correlations they see? Performing dimensionality reduction across available metrics and relating the resulting principal components to CSF drainage would help clarify the forces at play here.

In their interpretations, the authors claim that the CSF drainage they observe occurs through the bone marrow of the skull. How confident can we be in that claim? Is it that there are no other likely possibilities? It might be an unnecessary question, but given there seems to be no causal intervention (which is fine), and no consideration of alternatives, I am wondering whether this is because other possibilities are improbable or whether they were not adequately considered.

R0:

Reviewer #1: Title: Probabilistic Forecasting of Monthly Dengue Cases Using Epidemiological and Climate Signals: A BiLSTM–Naive Bayes Model Versus Mechanistic and Count-Model Baselines. Manuscript Number: PGPH-D-25-03170

This manuscript presents a rigorous comparative study of probabilistic forecasting models for monthly dengue incidence in Freetown, Sierra Leone, covering the period 2015–2025. It evaluates four major model classes—NB-GLM, INGARCH-NB, Renewal-NB, and BiLSTM-NB—under a leakage-safe rolling-origin evaluation. The article demonstrates strong methodological maturity, careful control of data leakage, and thorough probabilistic evaluation using proper scoring rules, interval coverage, sharpness metrics, PIT diagnostics, and Diebold–Mariano tests. The manuscript is generally well-written, technically sound, and addresses an important operational public health problem. It positions itself as one of the few works offering aligned comparisons of mechanistic, statistical, and deep-learning models under realistic constraints for West African dengue surveillance. This article presents a methodologically rigorous comparison of four probabilistic forecasting approaches—NB-GLM, INGARCH-NB, Renewal-NB, and BiLSTM-NB—applied to monthly dengue case data from Freetown, Sierra Leone (2015–2025). The study addresses an important gap by evaluating mechanistic, statistical, and deep-learning models under aligned, leakage-safe conditions. While the work is comprehensive and technically strong, several critical issues affect its accessibility, interpretability, and broader applicability.

Strengths The study excels in methodological rigor. Its strict leakage safeguards, careful feature-timing rules, and use of expanding-window rolling-origin evaluation significantly strengthen reliability. The inclusion of proper scoring rules, interval coverage, sharpness metrics, PIT histograms, and Diebold–Mariano tests provides a complete probabilistic evaluation rarely seen in dengue forecasting studies. The horizon-specific findings—INGARCH-NB outperforming at 1–2 months and BiLSTM-NB excelling at 3 months—are well supported by aligned comparisons and statistical significance tests. The transparency of data, code, and alignment artefacts enhances reproducibility and credibility. Additionally, the manuscript offers practical guidance for operational forecasting, including a realistic “light climate” input strategy suitable for resource-limited settings.

Limitations Despite its strengths, the manuscript is heavily technical, with extensive mathematical exposition in the main text. This may limit accessibility for public-health practitioners who are likely part of the target audience. The mechanistic renewal model is presented as a baseline but is arguably underspecified; the use of a short, fixed 3-month kernel may not realistically capture dengue’s generation interval dynamics, likely contributing to its poor performance. This limits the interpretive value of the mechanistic comparison. This limitation should be addressed. The study’s climate treatment, while intentionally conservative, may underexploit important environmental drivers. Although justified operationally, this constraint restricts exploration of potentially meaningful lag structures or seasonal climate anomalies. The analysis is limited to a single city and monthly data frequency, raising questions about generalizability across geographies with different climate patterns and dengue transmission dynamics. Moreover, the monthly temporal resolution may obscure rapid outbreak shifts, possibly disadvantaging mechanistic and hybrid models that rely on finer-grained dynamics. This should be addressed. The manuscript makes a valuable and original contribution to dengue forecasting, offering robust methodological innovations and practical insights for real-time surveillance systems. However, improved clarity, stronger justification for mechanistic assumptions, and expanded discussion of generalizability would enhance its usefulness and scholarly impact. With revisions to improve accessibility and contextual depth, the study is well positioned for publication and for informing operational forecasting practice in similar settings.

Reviewer #2: 1. What is PIT in the abstract stand for? The authors should avoid using abbreviations in the abstract. 2. The authors should providing some additional analysis, such as experimenting with alternative or longer serial-interval kernels, or simple sensitivity checks (e.g., different window lengths, or, if possible, finer temporal resolution). 3. Please, justifies the small climate feature set, mentioning any exploratory work with larger sets. 4. The authors should add a clearly labelled missing-data handling subsection that specifies: The imputation method, the number of imputed months, and how they were used in training/evaluation, plus any sensitivity. 5. While the architecture, optimization, and calibration steps are described, the process for choosing hyperparameters is not fully audit-ready. 6. I recommend that the authors conduct an additional experiment to demonstrate the generalizability of the proposed model.

I agree with this, and this limitation was exemplified by when I was going through a command line maze, but the directories used spaces instead of dashes or underscores, which initially led to a bit of friction in me figuring out how to proceed to the next terminal (I used quotes).

Reviewer #1 (Public review):

Summary:

In the work from Qiu et al., a workflow aimed at obtaining the stabilization of a simple small protein against mechanical and chemical stressors is presented.

Strengths:

The workflow makes use of state-of-the-art AI-driven structure generation and couples it with more classical computational and experimental characterizations in order to measure its efficacy. The work is well presented, and the results are thorough and convincing.

Weaknesses:

I will comment mostly on the MD results due to my expertise.

The Methods description is quite precise, but is missing some important details:

(1) Version of GROMACS used.

(2) The barostat used.

(3) pH at which the system is simulated.

(4) The pulling is quite fast (but maybe it is not a problem)

(5) What was the value for the harmonic restraint potential? 1000 is mentioned for the pulling potential, but it is not clear if the same value is used for the restraint, too, during pulling.

(6) The box dimensions.

From this last point, a possible criticism arises: Do the unfolded proteins really still stay far enough away from themselves to not influence the result? This might not be the major influence, but for correctness, I would indicate the dimensions of the box in all directions and plot the minimum distance of the protein from copies of itself across the boundary conditions over time.

Additionally, no time series are shown for the equilibration phases (e.g., RMSD evolution over time), which would empower the reader to judge the equilibration of the system before either steered MD or annealing MD is performed.

Organization is key to getting your point across.

Connection: Mental disorders causing distress or disability really shows up for me in how hard it can be to balance school and staying physically active at the same time. When my mental health is struggling, even things I want to do—like going to class prepared, studying, or working out—start to feel overwhelming. Some days my body feels heavy, my motivation drops, and it becomes harder to stay consistent, even though I know movement usually helps my mental health.

This connection helps me see that these challenges aren’t about laziness or lack of discipline, but about how mental health directly affects functioning. Trying to meet academic expectations while pushing myself to stay active can create a lot of internal pressure, especially when I feel like I should be able to “handle it all.” Recognizing this helps me give myself more grace and reminds me that needing balance, flexibility, and rest is part of taking care of both my mental and physical well-being.

Taking ownership of your learning is one of the many keys to success.

Most agreed!

How best do you suggest I create these? I have done DTC and they don't convert well...probably because they look amature.

Any AI strategies to make them high quality while also being time effective?

Why is it difficult to do your research on your secondary source without writing any field notes? I am still confused on what exactly we can research. I was thinking of doing something related to the feeling people get when watching scary movies, but I wonder how it can relate to culture.

This is something I will definitely take note of. By making sure my sources are relevant I can fully utilize them and make sure that they fit and make sense in my paper. I wonder how I can effectively use my secondary source to strengthen my primary source.

I like this thought but I don't like it. It makes me feel as though I'm always looking to fill my time with something, in actuality, we are, however just thinking about it feels stressful.

The number show the massive scale of death caused by Spanish actions, almost an entire population wiped out.

Encountering the Skrelling must have been tense and shows how uncertain life in a new land can be.

This shows that Native American societies were organized and capable of building large cities, not just small villages.

I often wonder how early hominids figured out which animals were safe to eat and which were not, as well as how different animals were hunted. While much of this knowledge likely came from trial and error, how was it communicated among group members to help everyone avoid danger? How did they learn to hunt animals like rhinos? A rhino is massive and certainly not a friendly creature. These hominids must have learned through deliberate, calculated attempts rather than random attacks. Of course, scavenging from already deceased animals was an option, but I imagine their curiosity and ingenuity eventually led them taking on such formidable beasts as a challenge. I find that idea incredibly fascinating.

So is this simple substitution Cipher uncrackable? Well, let's wait a minute here. It's not, for example, one of the pieces of information we can use in analyzing simple substitution is the letter frequencies of the English language or any language If you looked at a histogram of English letter frequencies, you'd see that e is the most frequent letter just above 12 percent, T is the second most frequent at somewhere around nine percent, a is very frequent at more than eight percent and so forth, so you would see this familiar pattern in any text that you encrypted. For example, if you encrypted it using the simple substitution Cipher, you might get this pattern, but you'd still see a peak where the letter that was substituted for e occurs. And maybe this is the peak for T, and maybe this is the peak for a. By analyzing those peaks and valleys, you can determine how the message was encrypted, can figure out the key. But, wait a minute… frequency analysis works!<br /> Slide 21, 22 chart

E.G. If you sorted by frequencies. Now, you can see this very clearly if you sort the two histograms, they're practically identical, and that's what lets the analyst with some effort, of course, figure out the key and break the message so you can break simple substitution cipher using frequency analysis. That makes Eve happy, Alice and Bob are not very happy about that. Eve wins … you don’t need brute force. Frequency analysis will break simple substitution. slide 23, 24 chart

Well, let's look at a slightly more complex Cipher, another example, of what's called a simple substitution Cipher, which means generally that you randomly mix up the alphabet to get a cipher alphabet and then you substitute plain letters with shuffled letters, so we're gonna use a little trick here that we're going to have a keyword that'll help us (one way to) construct our Cipher alphabet, which is our actual key by putting the keyword at the beginning and then putting all the letters that aren't in the word, zebrafish following it in alphabetical order. Now, obviously, there are lots of ways we could do this, but that gives us an easy way to transmit the key between Alice and Bob. Alice just tells Bob zebrafish and he knows how to construct this alphabet. But if they wanted, Alice could simply create a permutation or shuffling of this alphabet, not using the keyword and pass that along to Bob. Once you've created the cipher alphabet, encrypting and decrypting, in simple substitution cipher works the same as it did in Caesar Cypher. For each letter in the plane text message, you replace it with the corresponding letter from the cipher alphabet. Of course, you have many more possible Cipher alphabets because the alphabets aren't merely a shifting of the original plain alphabet. chart

These are not tangible, so not only does the working environment include physical visual things it includes the things we cannot see, but what we feel.

I agree, I personally find that where I choose, or am able to complete my work is very important in keeping me focused and lesses distractions.

There should be coping techniques when anxiety arises, as it can be debilitating.

We can relate this to the discussions we had in class about why did inmigrants decide to come to the US. It's interesting how a period with a lot of immigration in the US was because of the government policies and corruption in different countries. But, here in the US, people also face governments with corrupt politicians. But I guess there was a lot less than in other countries.

The Spaniard inflexibility to local religion makes sense, as Catholicism during this time was very much “Respect authority! Don’t question!” It’s clear that these religious traits appeared into the demeanors of the Spanish missionaries in Mesoamerica.

A war that I have not learned much about. This is considered one of the first modern wars due to its widespread violence and impact, large armies, and economic impact. It shows how Christianity, like other religions, have internal conflict and yet still remain relatively stable. This war also gave birth to Switzerland and the Dutch Republic after its conclusion.

I think it is very interesting to see all the different forms of Christianity across the world. They all worshiped the same God just a different way.

I thought it was interesting that the Catholic Church sought out to “correct” the corruption within the church, but increased censorship.

Apparently, a big part of this censorship was banning a Bible in 1546 that contained commentary which “could be read as critical authority.”

https://hob.gseis.ucla.edu/HoBCoursebook_Ch_6.html

It is interesting that we still make distinctions between the advancements "western" and "eastern" science, technology, and medicine when both "fields" emerged at a similar time, but used for different purposes.

The reformation and the spread of religion boomed over the past years. The main help of this fact spreading religion was the printing press and how it would transform texts to different languages. This is what English protestant said was the word or what "God has appointed" to help give the voice of religion and God voice through the Pope. it most boomed through German but it also spread through France, Switzerland, and England.

Even though I am religious and Christian, I think it's interesting to learn throughout history how Christian beliefs have impacted the way that empires view everything that they are doing, even if it maybe morally wrong. God says not to kill, but here their success in wars shows them how powerful their God is.

I think this is interesting because it shows that the Ottoman Empire did not reject science, but used it differently than Europeans did. Instead of focusing on how astronomy might challenge religious or philosophical beliefs, Ottomans focused on what was useful for everyday needs. This helps explain why ideas like a sun centered universe did not cause major controversy there the way they did in Europe.

This line stands out because Marx is saying socialism is not just a political belief, but something that history will naturally lead to. He treats social change like a scientific process driven by class conflict, not by individual choices or moral arguments. This shows a big shift away from Enlightenment ideas that focused on reason and independent individuals as the main drivers of progress.

This line shows why the Scientific Revolution was so unsettling for people at the time. If the earth was no longer at the center of the universe, it challenged the idea that humans held a special place in God’s plan. I think this explains why new scientific ideas caused fear and resistance, not just because they changed science, but because they forced people to rethink religion and humanity’s role in the universe.

As I become more familiar with the definitions of provenance, this particular instance compels me as I can see many examples of this in some of the media that I consume -

For instance, there is a zine called Sex Change USA by Daisy Thursday [https://luma.com/o1iss5rd] that is a collection of “stories where transgender people were covered in the National Esquire, Sun, and Weekly World News tabloids from 1993-2002.”

What I took away from Sex Change USA was not only a better understanding of the different contexts the pieces from the zine have lived in and do currently live in but a better understanding of the context of it’s current time and how those pieces interact with and inform each other.

I thought this was a really interesting point, because as we discovered last week, meaning comes from the whole. The record on its own may have some personal value, but the records place in contributing to the whole picture is what makes it important to the archive. This is also where the question of where archives belong in terms of study; humanities? Social Science? It depends on how the record is serving as evidence, and to what purpose. Like Furner claims, they can be used for a wide range of users, and records may serve as different types of evidence to different people.

I find this pluralist view of records to be very interesting. It reminds me of the recordings of interviews and oral histories I helped document and preserve while working at my last job. I wonder if those scholars pushing for a more evidence-based definition of records would even consider them to be records.

What resonated most with me in this passage was Cook’s emphasis on collective civic accountability and responsibility in archival practice. Traditionally, archival spaces have frequently functioned as exclusive environments, where access was limited and interaction with records was restricted to a specific, skilled group of professionals. I do not agree that this model serves the greater good. If materials are preserved but remain inaccessible to the communities they serve, the archival mission is then a failure. Cook’s argument reinforces the idea that archives should reflect the perspectives, experiences, and sentiments of the communities they serve. I was affected by the example of Canadian archival initiatives. The Canadian archival system demonstrates how a coordinated and collaborative system can bring together institutions, professionals, and communities in order to support more inclusive access and stewardship. In contrast, the current standings of archival work in the United States appear to be moving in the opposite direction, especially regarding access and preservation. This passage made me reflect on how openness and collaboration have the potential to revitalize archives and align them more closely with the needs of society.

This observation highlights a real issue in data analysis known as data dredging or p-hacking: when people search through large amounts of data without a clear hypothesis, they can often find patterns that look meaningful but are actually just coincidences.

This observation highlights a real issue in data analysis known as data dredging or p-hacking: when people search through large amounts of data without a clear hypothesis, they can often find patterns that look meaningful but are actually just coincidences.

When working with large data sets, it becomes clear how easy it is to find patterns that are misleading. Two variables may appear to move together, but this relationship can be caused by chance or by other hidden factors. Psychology has a similar idea captured by the phrase “correlation does not imply causation.” This reminds me that seeing a pattern in data is not the same as understanding why it exists, and that conclusions should be made carefully rather than based on surface-level relationships.

This solution seems to revolve around the following

• Loot being constant but not generous. This menas the player will always be picoing things up but everything matters.
• Loot being losable. So that everything they have muat be guarded but of course that playing the game is inevitably risking losing it.
• Interdependent. This means that there's no 'win button'. Very little will actually win you the game and as such you're looking for something thatauits your needs. And when you don't find it you're doing your best to use what you have.
• Indirectly supportive og your goal. The racing game here is an excellent example because going faster won't help you win if your turning circle is rubbish. So the core challenge or test must require an interaction of different abilities to overcome.

Supports my podcast by displaying a similar one that was actually able to help release a man who was wrongfully convicted. This shows that not only are the podcasts trustworthy, but also helps in the outside world.

Podcast hosts can gain credibility not just by being truthful but also by being authentic.

With how revealing metadata can be, it makes me wonder why platforms even include the metadata in posts. And should media outlets should be more responsible for removing metadata before publishing content that could put people at risk like this example?

I was surprised that privacy violations don’t only come from hacking, but also from normal everyday systems and data practices. Things like unclear rules, metadata, or “anonymous” datasets can still expose people without them realizing it. The example of photo metadata revealing someone’s hidden location shows how small technical details can create serious risks. This reminds me that data mining and sharing data always have hidden consequences, so companies should be much more responsible and transparent.

This part stood out to me because it shows how fragile “anonymization” actually is. Even when obvious identifiers are removed, patterns in the data can still point back to real people. It makes anonymized data feel a lot less safe than it’s usually presented to be.

I would like to say that I have a suspicion that our privacy was never secured or private, especially to the companies that are running the social media platform. The reason is that I feel like our activities are always under surveillance to prevent anything bad from happening or is going to happen.

This reminds me of how teenagers at times would screenshot dms. A lot of times it was evidence for an argument, but other times it would be malicious. This isn't wholly a bad thing however, this could be used to expose creeps.

This section made me realize that privacy violations don’t always involve hacking or illegal access. Even data that seems harmless—like metadata or anonymized datasets—can still expose people in ways they never agreed to. I was especially surprised by how companies can infer new information or create shadow profiles about both users and non-users, which shows how limited individual control over personal data really is.

This list shows how privacy risks often come less from a single bad action and more from how data travels and persists across systems. Even when users think they are acting safely or anonymously, metadata, inference, and platform ownership can quietly undermine consent and control, making privacy feel fragile and conditional rather than guaranteed.

I also connected this to what I see in popular culture and social media. A lot of online “allyship” looks loud and performative, but not always relational. Sue et al.’s point about microinterventions being about reassurance and not leaving someone alone in their experience feels very different from posting something just to be seen as on the right side. It makes me think about how real resistance happens in everyday moments, not just big statements.

One big connection I’m making is personal. Reading about microaffirmations reminded me of times when someone didn’t directly “fix” a situation, but still made me feel seen. Rolón-Dow’s idea that affirmation can be as simple as listening well really stuck with me. I’ve noticed that when people actually pause, ask follow-up questions, and don’t rush to give advice, it feels way more supportive than someone jumping in with a solution.

I made a connection during this section, especially the idea that power is usually unspoken but predictable. The examples about the types of rules reminded me of groups that I have seen in school and at work. It is when certain peoples preferences automatically get prioritized even when they dont have an offical supirior title like professor or manager. It connects to the idea that power doesnt come from a title, it can come from personality, populatirty, or confidence. It helped me to better understand how informational power show up everyday settings. It also made me realized how easiy it is to follow this pattern.

I also made a connection to cumulative stress and identity based harm. The sections on micro affirmations and micro interventions stood out because they go beyond just identifying harm and instead focusing on smaller, more practical actions people can take. That makes the topic feel more like action, instead of just theoretical , especially for people in this field.

If the target is comfortable with sharing their experience with a family member or friend, then they can give them support and encouragement. An example from my personal life would be like from my example in my previous paragraph but after I called my mom and she assured me and offered encouragement. This gave me the motivation I needed to go back to class and sit with a new group of people and make new friends.

I think I could be comfortably uncomfortable in trying to "Open the Front Door" more often. I am someone who very much avoids confrontation, but I have tried to make it a goal for myself to be kindly confrontational in situations that warrant it. I think microaggressions are things that I can address in this way. Hopefully, using this strategy of microresistance is away I can help people be aware of what they might do unintentionally.

I think the part that scares me the most about this, aside from the confrontation, is providing relevant data. I think this is the best way to back up a point, but I find myself being hesitant of quoting the research wrong, so I say nothing at all. Hopefully by practicing this, I can get more confident in using this strategy. I also think the desire part of this strategy can be tricky because I don't find it easy to request things of other people, but I am finding that good leaders need to be able to communicate in this way, so I am motivated to get better at it.

When people are singled out in a group, they seem to be ignored above all things. Even the people that what to claim that they are exclusive also want to show that they are being "inclusive" to the one singled out by choice. I've seen a lot of people purposefully act a different way to the one known as different to show they rest of the public that their interactions aren't truly genuine and related. A lot of us want to be friends with the "outcast" but not associated with them or their group I believe, and this is even noticeable in the most loving communities. It makes me feel uncomfortable, but I can also relate to those insecurities. It is human nature to want to flip in, and this is where the necessity for countering culture comes in.

From the first grounding question in the beginning of the chapter, the basic definition of micro aggressions was sort of how I predicted to to be, but this example I found to be a surprise. I didn't think that this is what microagressions would look like but more so derogatory comments in school or exclusion, so I need to learn more about the specific of what microaggression could look like to truly notice it. For questions 2 and 3, at first I didn't believe that I've seen microaggressions often in my life, but now I'm rethinking that. In addition, I thought I would be the person to stand up for others in situations of microaggressions, but in examples similar to this one about the siblings, I would probably be uncomfortable saying anything.

Seeing all of these bases make power feel so much more dangerous then just the singular word. When I think of power, I immediately think of diplomatic events/conflict, striving for power in the workplace, or the government. If I had to guess these different categories I would've first thought of the "reward", "coercive" and "informational" branch, but I didn't initially reflect on how common people not in higher positions can hold a lot of power as well. The "expert" and "referent" categories are the ones that I see majority of the general community use to increase their status because those are the two besides legitimate that can be displayed more outwardly. Things like bribery, violence, force or secrecy have to be more hidden. I wonder how each of these bases are shown or micro manners as well to where they wouldn't necessarily be frowned upon.

Now this could relate to authoritative and parental figures, but how does this specific branch differ between cultures? What do each of these branches teach a person about another's culture? Are there certain people that bleed into multiple bases of power?

I feel like I have seen this very prominently growing up, but I am wondering what this looks like practically? Where can this be seen differently between parent relationships, friendships and relationships between authoritative figures like parents?

•   Bronchitis Treatment: Inhaling moist air from a humidifier or steamy shower can help loosen and thin mucus, making breathing easier.
•   Bronchitis Symptoms: Coughing, sore throat, chest congestion, and coughing up thick mucus.
•   Bronchitis Cause: Usually caused by viruses, not bacteria, so antibiotics are generally ineffective.
•   Bronchitis Definition: Inflammation of the bronchial tubes, causing narrowing and excessive mucus production.
•   Mucus Function and Problem: Mucus traps pathogens but excessive production hinders airflow, leading to coughing.
•   Bronchitis Treatment: Thinning mucus for effective coughing through fluids, humidifiers, steam, and expectorants, while avoiding cough suppressants.
•   Reason for Pulse Oximetry: To check Sacheen’s blood oxygen level and ensure clogged airways weren’t impacting her oxygen intake.
•   Difference Between Acute and Chronic Bronchitis: Acute bronchitis is a short-term condition often caused by a cold or flu, while chronic bronchitis is a long-term condition often caused by smoking and associated with COPD.
•   Smoking Cessation Advice: Dr. Tsosie strongly advised Sacheen to quit smoking to prevent future respiratory infections, COPD, and lung cancer.
•   Respiratory System Function: Critical for gas exchange and protecting the body from harmful substances in the air.
•   Respiratory System Vulnerability: Prone to infections and damage from allergens, mold, air pollution, and cigarette smoke.
•   Respiratory System Overview: Comprises the upper respiratory tract (nasal cavity, pharynx, larynx) for air conduction and the lower respiratory tract (trachea, bronchi, bronchioles, lungs) for conduction and gas exchange.
•   Respiratory System Defense: The mucociliary escalator, consisting of mucus-producing cells and cilia, protects the lungs by trapping and expelling harmful particles and pathogens.
•   Breathing Regulation: The respiratory system, controlled by the brain, regulates breathing rate based on carbon dioxide levels in the blood to maintain homeostasis.
•   Breathing Mechanics: Breathing involves inhaling (active process driven by diaphragm contraction) and exhaling (passive process driven by lung elasticity).
•   Gas Exchange Definition: The biological process of transferring gases across cell membranes for entering or leaving the blood.
•   Gas Exchange Mechanism: Occurs by diffusion across cell membranes, moving down a concentration gradient from high to low concentration.
•   Lung Gas Exchange: Takes place in alveoli, where deoxygenated blood picks up oxygen and releases carbon dioxide.
•   Smoking and COPD: Smoking is the primary cause of COPD, reducing lung elasticity and impairing exhalation.
•   Smoking and Lung Cancer: Smoking is the leading cause of lung cancer, a malignant tumor characterized by uncontrolled cell growth in the lungs.
•   Health Risks of Smoking: Smoking poses numerous health risks, including increased risk of various cancers, cardiovascular disease, and other adverse effects.
•   Respiratory System Function: The respiratory system facilitates gas exchange, bringing oxygen into the body and removing carbon dioxide.
•   Gas Exchange Mechanism: Oxygen and carbon dioxide flow across membranes based on concentration gradients, moving from areas of higher to lower concentration.
•   COPD and Blood pH: COPD can lead to elevated carbon dioxide levels, causing respiratory acidosis and prompting the body to compensate by increasing breathing rate.
•   Bronchitis Treatment: Changes to the environment, such as more frequent cleaning, would not help asthma caused by a gene.
•   Bronchitis Definition: Bronchitis is an inflammation of the bronchi, the large and medium-sized airways in the lungs that carry air from the trachea.
•   Bronchodilator Definition: A medication that opens constricted airways.
•   Funding Sources: Department of Education Open Textbook Pilot Project, UC Davis Office of the Provost, UC Davis Library, California State University Affordable Learning Solutions Program, Merlot, and National Science Foundation.
•   Support: NICE CXone Expert and LibreTexts libraries.
•   Contact Information: info@libretexts.org.

In broken aesthetics, traces of repair show the relationship between people and objects, and the passage of time. This reminds me of the debate in heritage restoration about whether to restore the old to look new or to keep the marks of time. For example, many ancient Chinese Buddhist statues are not repainted with bright colors（their original colors), but keep the color shaped by time.

What he means is that teachers want to see their students succeed, therefore teach them to write in a way that will give them a high SAT score and hopefully get into a good college. But this approach stunts the student, because they are not thinking critically about what they are writing.

I don't know who Rilke is, but I can connect with this quote. We have so many examples of beautiful works of art that were inspired by tragedy. For example Amanda Gorman wrote "the Hill we Climb", ultimately addressing the fact that our country in in poor shape but we will rise to the occasion to fix it.

This is a good question. It reminds me that certain objects not only have functions but also carry other meanings, for example, a sweater made by a family member, or Chinese bronze vessels that represent a hierarchical system. When preserving or repairing objects that have a clear relationship with people, what is being repaired may also be the relationship behind them.

I would be the most interested in the gardening activity because I already enjoy gardening on my own, so learning how to do it in a way that's healthier for the environment, but also me and the crops I grow would be an awesome thing to learn and incorporate into my everyday life.

Once more, despite the difference in race and the effects of the time, Mrs. Shelby stands up for Tom, Harry, and even Eliza, questioning her husband's decision of choosing to sell them and how they would risk their lives for him, while he would not do the same.

This whole paragraph brilliantly showcases to the audience how Stowe expertly uses motherhood, appealing to the audience's sympathy by presenting how Harry's mother is willing to sacrifice herself and get into deeper trouble if it means sparing her son from being sold off and taken from her.

This shows that, although Tom doesn't have formal education or social power, people respond to him because he is sincere. This challenges hierarchies based on race and class as Stowe shows that moral authority does not belong solely to white or educated people.

No matter how strong the password is, as the context suggested, social media companies may not be able to secure our data privacy, this is because the detection of password is outdated as it mentioned brute force, that a program that can generate millions of pattern to break the account security lock.

People have many things wanted to be private, personal life, messages between friends and more, privacy is very important in modern years, especially in recent years as more and more things have begun to go digital, it highlights even further then importance of our data privacy, but data leaking is always inevitable...

Your thesis should be detailed but not overly detailed to the point where it overwhelms the reader.

in 1944

But in reality not so much

The south is not static, but most southerns ideological beliefs are...

But not in the south, explains why they are so far behind today

Author response:

Weaknesses:

(1) Several conclusions are insufficiently supported at this point. For example, evidence that the Hiw foci represent bona fide liquid-liquid phase (LLP) separated condensates is limited. Sensitivity to 1,6-hexanediol is not definitive proof of their liquid condensate nature, and their recovery kinetics after 1,6-hexanediol wash-out and their morphology are inconsistent with a pure liquid behaviour. Furthermore, the claim that the Hiw foci are non-vesicular is not strongly supported, as it is only based on the lack of colocalization with a handful of endosomal proteins.

We agree that, at the current stage of the manuscript, we have presented data only on Hiw foci in the VNC and shown that they are sensitive to 1,6-HD but not to 2,5-HD. To further provide definitive proof that these are bona fide condensates, we will now perform in vitro analysis of different domains of Hiw and the Hiw IDR region. In addition, we will also investigate the Hiw-GFP behavior in non-neuronal and transiently transfected cell lines using FRAP and other protocols previously applied to condensate-forming proteins.

Finally, we will perform an in-depth analysis of the Hiw condensates for their colocalization with endocytic proteins and cellular compartments and determine whether they are part of any known vesicular structures.

(2) Importantly, the appearance of the putative condensates is correlative rather than causative for synaptic overgrowth, and in the absence of a mechanistic link between endocytosis and Hiw condensation, the causality is difficult to address. Of note is that the putative condensates are already present (albeit to a lesser extent) in the absence of endocytic defects and that the conclusions rely heavily on overexpressed GFP-Hiw, which may perturb normal protein behaviour and artificially induce condensation or aggregation.

To investigate the formation of condensates and their relation to synaptic growth, we will perform a time-course analysis of changes at the NMJ and correlate with the Hiw condensate appearance in the VNC of shi^ts expressing GFP-Hiw, along with appropriate controls. The GFP transgene used is a functional transgene and well established for studying Hiw behaviour. The Hiw condensates do not form when expressed on an otherwise wild-type background. We will further assess the formation of Hiw condensates in other endocytic mutants with appropriate controls.

(3) The use of hypomorphic mutants in genetic experiments also introduces some ambiguity in their interpretation, as the results may reflect dosage effects from multiple pathways rather than pathway order. Finally, the manuscript would benefit from a more comprehensive reference to relevant literature on JNKKKs and BMP signalling, as well as on the recycling endosome function in synaptic growth and the regulation of the aforementioned pathways.

We will perform genetic analysis using homozygous mutants of the wit and saxophone genes to further support epistatic interactions between the BMP signaling pathway and synaptic growth. We will strengthen the discussion part.

Hetherington (2005)- political trust is rooted in the perception that the government will act within the public's interests - ensure transparency, authenticity and accountability are more than ideals; but principles that are actively practiced

Reviewer #2 (Public review):

Summary:

Stanojcic et al. investigate the origins of DNA replication in the unicellular parasite Trypanosoma brucei. They perform two experiments, stranded SNS-seq and DNA molecular combing. Further, they integrate various publicly available datasets, such as G4-seq and DRIP-seq, into their extensive analysis. Using this data, they elucidate the structure of the origins of replication. In particular, they find various properties located at or around origins, such as polynucleotide stretches, G-quadruplex structures, regions of low and high nucleosome occupancy, R-loops, and that origins are mostly present in intergenic regions. Combining their population-level SNS-seq and their single-molecule DNA molecular combing data, they elucidate the total number of origins as well as the number of origins active in a single cell.

Strengths:

(1) A very strong part of this manuscript is that the authors integrate several other datasets and investigate a large number of properties around origins of replication. Data analysis clearly shows the enrichment of various properties at the origins, and the manuscript concludes with a very well-presented model that clearly explains the authors' understanding and interpretation of the data.

(2) The DNA combing experiment is an excellent orthogonal approach to the SNS-seq data. The authors used the different properties of the two experiments (one giving location information, one giving single-molecule information) well to extract information and contrast the experiments.

(3) The discussion is exemplary, as the authors openly discuss the strengths and weaknesses of the approaches used. Further, the discussion serves its purpose of putting the results in both an evolutionary and a trypanosome-focused context.

Weaknesses:

I have major concerns about the origin of replication sites determined from the SNS-seq data. As a caveat, I want to state that, before reading this manuscript, SNS-seq was unknown to me; hence, some of my concerns might be misplaced.

(1) I do not understand why SNS-seq would create peaks. Replication should originate in one locus, then move outward in both directions until the replication fork moving outward from another origin is encountered. Hence, in an asynchronous population average measurement, I would expect SNS data to be broad regions of + and -, which, taken together, cover the whole genome. Why are there so many regions not covered at all by reads, and why are there such narrow peaks?

(2) I am concerned that up to 96% percent of all peaks are filtered away. If there is so much noise in the data, how can one be sure that the peaks that remain are real? Specifically, if the authors placed the same number of peaks as was measured randomly in intergenic regions, would 4% of these peaks pass the filtering process by chance?

(3) There are 3 previous studies that map origins of replication in T. brucei. Devlin et al. 2016, Tiengwe et al. 2012, and Krasiļņikova et al. 2025 (https://doi.org/10.1038/s41467-025-56087-3), all with a different technique: MFA-seq. All three previous studies mostly agree on the locations and number of origins. The authors compared their results to the first two, but not the last study; they found that their results are vastly different from the previous studies (see Supplementary Figure 8A). In their discussion, the authors defend this discrepancy mostly by stating that the discrepancy between these methods has been observed in other organisms. I believe that, given the situation that the other studies precede this manuscript, it is the authors' duty to investigate the differences more than by merely pointing to other organisms. A conclusion should be reached on why the results are different, e.g., by orthogonally validating origins absent in the previous studies.

(4) Some patterns that were identified to be associated with origins of replication, such as G-quadruplexes and nucleosomes phasing, are known to be biases of SNS-seq (see Foulk et al. Characterizing and controlling intrinsic biases of lambda exonuclease in nascent strand sequencing reveals phasing between nucleosomes and G-quadruplex motifs around a subset of human replication origins. Genome Res. 2015;25(5):725-735. doi:10.1101/gr.183848.114).

Are the claims well substantiated?:

My opinion on whether the authors' results support their conclusions depends on whether my concerns about the sites determined from the SNS-seq data can be dismissed. In the case that these concerns can be dismissed, I do think that the claims are compelling.

Impact:

If the origins of replication prove to be distributed as claimed, this study has the potential to be important for two fields. Firstly, in research focused on T. brucei as a disease agent, where essential processes that function differently than in mammals are excellent drug targets. Secondly, this study would impact basic research analyzing DNA replication over the evolutionary tree, where T. brucei can be used as an early-divergent eukaryotic model organism.

Author response:

eLife Assessment

The authors use sequencing of nascent DNA (DNA linked to an RNA primer, "SNS-Seq") to localise DNA replication origins in Trypanosoma brucei, so this work will be of interest to those studying either Kinetoplastids or DNA replication. The paper presents the SNS-seq results for only part of the genome, and there are significant discrepancies between the SNS-Seq results and those from other, previously-published results obtained using other origin mapping methods. The reasons for the differences are unknown and from the data available, it is not possible to assess which origin-mapping method is most suitable for origin mapping in T. brucei. Thus at present, the evidence that origins are distributed as the authors claim - and not where previously mapped - is inadequate.

We would like to clarify a few points regarding our study. Our primary objective was to characterise the topology and genome-wide distribution of short nascent-strand (SNS) enrichments. The stranded SNS-seq approach provides the high strand-specific resolution required to analyse origins. The observation that SNS-seq peaks (potential origins) are most frequently found in intergenic regions is not an artefact of analysing only part of the genome; rather, it is a result of analysing the entire genome.

We agree that orthogonal validation is necessary. However, neither MFA-seq nor TbORC1/CDC6 ChIP-on-chip has yet been experimentally validated as definitive markers of origin activity in T. brucei, nor do they validate each other. 

Public Reviews:

Reviewer #1 (Public review):

In this paper, Stanojcic and colleagues attempt to map sites of DNA replication initiation in the genome of the African trypanosome, Trypanosoma brucei. Their approach to this mapping is to isolate 'short-nascent strands' (SNSs), a strategy adopted previously in other eukaryotes (including in the related parasite Leishmania major), which involves isolation of DNA molecules whose termini contain replication-priming RNA. By mapping the isolated and sequenced SNSs to the genome (SNS-seq), the authors suggest that they have identified origins, which they localise to intergenic (strictly, inter-CDS) regions within polycistronic transcription units and suggest display very extensive overlap with previously mapped R-loops in the same loci. Finally, having defined locations of SNS-seq mapping, they suggest they have identified G4 and nucleosome features of origins, again using previously generated data.

Though there is merit in applying a new approach to understand DNA replication initiation in T. brucei, where previous work has used MFA-seq and ChIP of a subunit of the Origin Replication Complex (ORC), there are two significant deficiencies in the study that must be addressed to ensure rigour and accuracy.

(1) The suggestion that the SNS-seq data is mapping DNA replication origins that are present in inter-CDS regions of the polycistronic transcription units of T. brucei is novel and does not agree with existing data on the localisation of ORC1/CDC6, and it is very unclear if it agrees with previous mapping of DNA replication by MFA-seq due to the way the authors have presented this correlation. For these reasons, the findings essentially rely on a single experimental approach, which must be further tested to ensure SNS-seq is truly detecting origins. Indeed, in this regard, the very extensive overlap of SNS-seq signal with RNA-DNA hybrids should be tested further to rule out the possibility that the approach is mapping these structures and not origins.

(2) The authors' presentation of their SNS-seq data is too limited and therefore potentially provides a misleading view of DNA replication in the genome of T. brucei. The work is presented through a narrow focus on SNS-seq signal in the inter-CDS regions within polycistronic transcription units, which constitute only part of the genome, ignoring both the transcription start and stop sites at the ends of the units and the large subtelomeres, which are mainly transcriptionally silent. The authors must present a fuller and more balanced view of SNS-seq mapping across the whole genome to ensure full understanding and clarity.

Regarding comparisons with previous work:

Two other attempts to identify origins in T. brucei —ORC1/CDC6 binding sites (ChIP-on-chip, PMID: 22840408) and MFA-seq (PMID: 22840408, 27228154)—were both produced by the McCulloch group. These methods do not validate each other; in fact, MFA-seq origins overlap with only 4.4% of the 953 ORC1/CDC6 sites (PMID: 29491738). Therefore, low overlap between SNS-seq peaks and ORC1/CDC6 sites cannot disqualify our findings. Similar low overlaps are observed in other parasites (PMID: 38441981, PMID: 38038269, PMID: 36808528) and in human cells (PMID: 38567819).

We also would like to emphasize that the ORC1/CDC6 dataset originally published (PMID: 22840408) is no longer available; only a re-analysis by TritrypDB exists, which differs significantly from the published version (personal communication from Richard McCulloch). While the McCulloch group reported a predominant localization of ORC1/CDC6 sites within SSRs at transcription start and termination regions, our re-analysis indicates that only 10.3% of TbORC1/CDC6-12Myc sites overlapped with 41.8% of SSRs.

MFA-seq does not map individual origins, it rather detects replicated genomic regions by comparing DNA copy number between S- and G1-phases of the cell cycle (PMID: 36640769; PMID: 37469113; PMID: 36455525). The broad replicated regions (0.1–0.5 Mbp) identified by MFA-seq in T. brucei are likely to contain multiple origins, rather than just one. In that sense we disagree with the McCulloch's group who claimed that there is a single origin per broad peak. Our analysis shows that up to 50% of the origins detected by stranded SNS-seq locate within broad MFA-seq regions. The methodology used by McCulloch’s group to infer single origins from MFA-seq regions has not been published or made available, as well as the precise position of these regions, making direct comparison difficult.

Finally, the genomic features we describe—poly(dA/dT) stretches, G4 structures and nucleosome occupancy patterns—are consistent with origin topology described in other organisms.

On the concern that SNS-seq may map RNA-DNA hybrids rather than replication origins: Isolation and sequencing of short nascent strands (SNS) is a well-established and widely used technique for high-resolution origin mapping. This technique has been employed for decades in various laboratories, with numerous publications documenting its use. We followed the published protocol for SNS isolation (Cayrou et al., Methods, 2012, PMID: 22796403). RNA-DNA hybrids cannot persist through the multiple denaturation steps in our workflow, as they melt at 95°C (Roberts and Crothers, Science, 1992; PMID: 1279808). Even in the unlikely event that some hybrids remained, they would not be incorporated into libraries prepared using a single-stranded DNA protocol and therefore would not be sequenced (see Figure 1B and Methods).

Furthermore, our analysis shows that only a small proportion (1.7%) of previously reported RNA-DNA hybrids overlap with SNS-seq origins. It is important to note that RNA-primed nascent strands naturally form RNA-DNA hybrids during replication initiation, meaning the enrichment of RNA-DNA hybrids near origins is both expected and biologically relevant.

On the claim that our analysis focuses narrowly on inter-CDS regions and ignores other genomic compartments: this is incorrect. We mapped and analyzed stranded SNS-seq data across the entire genome of T. brucei 427 wild-type strain (Müller et al., Nature, 2018; PMID: 30333624), including both core and subtelomeric regions. Our findings indicate that most origins are located in intergenic regions, but all analyses were performed using the full set of detected origins, regardless of location.

We did not ignore transcription start and stop sites (TSS/TTS). The manuscript already includes origin distribution across genomic compartments as defined by TriTrypDB (Fig. 2C) and addresses overlap with TSS, TTS and HT in the section “Spatial coordination between the activity of the origin and transcription”. While this overlap is minimal, we have included metaplots in the revised manuscript for clarity.

Reviewer #2 (Public review):

Summary: 

Stanojcic et al. investigate the origins of DNA replication in the unicellular parasite Trypanosoma brucei. They perform two experiments, stranded SNS-seq and DNA molecular combing. Further, they integrate various publicly available datasets, such as G4-seq and DRIP-seq, into their extensive analysis. Using this data, they elucidate the structure of the origins of replication. In particular, they find various properties located at or around origins, such as polynucleotide stretches, G-quadruplex structures, regions of low and high nucleosome occupancy, R-loops, and that origins are mostly present in intergenic regions. Combining their population-level SNS-seq and their single-molecule DNA molecular combing data, they elucidate the total number of origins as well as the number of origins active in a single cell.

Strengths:

(1) A very strong part of this manuscript is that the authors integrate several other datasets and investigate a large number of properties around origins of replication. Data analysis clearly shows the enrichment of various properties at the origins, and the manuscript concludes with a very well-presented model that clearly explains the authors' understanding and interpretation of the data.

We sincerely thank you for this positive feedback.

(2) The DNA combing experiment is an excellent orthogonal approach to the SNS-seq data. The authors used the different properties of the two experiments (one giving location information, one giving single-molecule information) well to extract information and contrast the experiments.

Thank you very much for this remark.

(3) The discussion is exemplary, as the authors openly discuss the strengths and weaknesses of the approaches used. Further, the discussion serves its purpose of putting the results in both an evolutionary and a trypanosome-focused context.

Thank you for appreciating our discussion.

Weaknesses:

I have major concerns about the origin of replication sites determined from the SNS-seq data. As a caveat, I want to state that, before reading this manuscript, SNS-seq was unknown to me; hence, some of my concerns might be misplaced.

(1) I do not understand why SNS-seq would create peaks. Replication should originate in one locus, then move outward in both directions until the replication fork moving outward from another origin is encountered. Hence, in an asynchronous population average measurement, I would expect SNS data to be broad regions of + and -, which, taken together, cover the whole genome. Why are there so many regions not covered at all by reads, and why are there such narrow peaks?

Thank you for asking these questions. As you correctly point out, replication forks progress in both directions from their origins and ultimately converge at termination sites. However, the SNS-seq method specifically isolates short nascent strands (SNSs) of 0.5–2.5 kb using a sucrose gradient. These short fragments are generated immediately after origin firing and mark the sites of replication initiation, rather than the entire replicated regions. Consequently: (i) SNS-seq does not capture long replication forks or termination regions, only the immediate vicinity of origins. (ii) The narrow peaks indicate the size of selected SNSs (0.5–2.5 kb) and the fact that many cells initiate replication at the same genomic sites, leading to localized enrichment. (iii) Regions without coverage refer to genomic areas that do not serve as efficient origins in the analyzed cell population. Thus, SNS-seq is designed to map origin positions, but not the entire replicated regions.

(2) I am concerned that up to 96% percent of all peaks are filtered away. If there is so much noise in the data, how can one be sure that the peaks that remain are real? Specifically, if the authors placed the same number of peaks as was measured randomly in intergenic regions, would 4% of these peaks pass the filtering process by chance?

Maintaining the strandness of the sequenced DNA fibres enabled us to filter the peaks, thereby increasing the probability that the filtered peak pairs corresponded to origins. Two SNS peaks must be oriented in a way that reflects the topology of the SNS strands within an active origin: the upstream peak must be on the minus strand and followed by the downstream peak on the plus strand.

As suggested by the reviewer, we tested whether randomly placed plus and minus peaks could reproduce the number of filter-passing peaks using the same bioinformatics workflow. Only 1–6% of random peaks passed the filters, compared with 4–12% in our experimental data, resulting in about 50% fewer selected regions (origins). Moreover, the “origins” from random peaks showed 0% reproducibility across replicates, whereas the experimental data showed 7–64% reproducibility. These results indicate that the retainee peaks are highly unlikely to arise by chance and support the specificity of our approach. Thank you for this suggestion.

(3) There are 3 previous studies that map origins of replication in T. brucei. Devlin et al. 2016, Tiengwe et al. 2012, and Krasiļņikova et al. 2025 (https://doi.org/10.1038/s41467-025-56087-3), all with a different technique: MFA-seq. All three previous studies mostly agree on the locations and number of origins. The authors compared their results to the first two, but not the last study; they found that their results are vastly different from the previous studies (see Supplementary Figure 8A). In their discussion, the authors defend this discrepancy mostly by stating that the discrepancy between these methods has been observed in other organisms. I believe that, given the situation that the other studies precede this manuscript, it is the authors' duty to investigate the differences more than by merely pointing to other organisms. A conclusion should be reached on why the results are different, e.g., by orthogonally validating origins absent in the previous studies.

The MFA-seq data for T. brucei were published in two studies by McCulloch’s group: Tiengwe et al. (2012) using TREU927 PCF cells, and Devlin et al. (2016) using PCF and BSF Lister427 cells. In Krasilnikova et al. (2025), previously published MFA-seq data from Devlin et al. were remapped to a new genome assembly without generating new MFA-seq data, which explains why we did not include that comparison.

Clarifying the differences between MFA-seq and our stranded SNS-seq data is essential. MFA-seq and SNS-seq interrogate different aspects of replication. SNS-seq is a widely used, high-resolution method for mapping individual replication origins, whereas MFA-seq detects replicated regions by comparing DNA copy number between S and G1 phases. MFA-seq identified broad replicated regions (0.1–0.5 Mb) that were interpreted by McCulloch’s group as containing a single origin. We disagree with this interpretation and consider that there are multiple origins in each broad peaks; theoretical considerations of replication timing indicate that far more origins are required for complete genome duplication during the short S-phase. Once this assumption is reconsidered, MFA-seq and SNS-seq results become complementary: MFA-seq identifies replicated regions, while SNS-seq pinpoints individual origins within those regions. Our analysis revealed that up to 50% of the origins detected by stranded SNS-seq were located within the broad MFA peaks. This pattern—broad MFA-seq regions containing multiple initiation sites—has also recently been found in Leishmania by McCulloch’s team using nanopore sequencing (PMID: 26481451). Nanopore sequencing showed numerous initiation sites within MFA-seq regions and additional numerous sites outside these regions in asynchronous cells, consistent with what we observed using stranded SNS-seq in T. brucei. We will expand our discussion and conclude that the discrepancy arises from methodological differences and interpretation. The two approaches provide complementary insights into replication dynamics, rather than ‘vastly different’ results.

We recognize the importance of validating our results in future using an alternative mapping method and functional assays. However, it is important to emphasize that stranded SNS-seq is an origin mapping technique with a very high level of resolution. This technique can detect regions between two divergent SNS peaks, which should represent regions of DNA replication initiation. At present, no alternative technique has been developed that can match this level of resolution.

(4) Some patterns that were identified to be associated with origins of replication, such as G-quadruplexes and nucleosomes phasing, are known to be biases of SNS-seq (see Foulk et al. Characterizing and controlling intrinsic biases of lambda exonuclease in nascent strand sequencing reveals phasing between nucleosomes and G-quadruplex motifs around a subset of human replication origins. Genome Res. 2015;25(5):725-735. doi:10.1101/gr.183848.114).

It is important to note that the conditions used in our study differ significantly from those applied in the Foulk et al. Genome Res. 2015. We used SNS isolation and enzymatic treatments as described in previous reports (Cayrou, C. et al. Genome Res, 2015 and Cayrou, C et al. Methods, 2012). Here, we enriched the SNS by size on a sucrose gradient and then treated this SNS-enriched fraction with high amounts of repeated λ-exonuclease treatments (100u for 16h at 37oC - see Methods). In contrast, Foulk et al. used sonicated total genomic DNA for origin mapping, without enrichment of SNS on a sucrose gradient as we did, and then they performed a λ-exonuclease treatment. A previous study (Cayrou, C. et al. Genome Res, 2015, Figure S2, which can be found at https://genome.cshlp.org/content/25/12/1873/suppl/DC1) has shown that complete digestion of G4-rich DNA sequences is achieved under the conditions we used.

Furthermore, the SNS depleted control (without RNA) was included in our experimental approach. This control represents all molecules that are difficult to digest with lambda exonuclease, including G4 structures. Peak calling was performed against this background control, with the aim of removing false positive peaks resulting from undigested DNA structures. We explained better this step in the revised manuscript.

The key benefit of our study is that the orientation of the enrichments (peaks) remains consistent throughout the sequencing process. We identified an enrichment of two divergent strands synthesised on complementary strands containing G4s. These two divergent strands themselves do not, however, contain G4s (see Fig. 8 for the model). Therefore, the enriched molecules detected in our study do not contain G4s. They are complementary to the strands enriched with G4s. This means that the observed enrichment of

G4s cannot be an artefact of the enzymatic treatments used in this study. We added this part in the discussion of the revised manuscript.

We also performed an additional control which is not mentioned in the manuscript. In parallel with replicating cells, we isolated the DNA from the stationary phase of growth, which primarily contains non-replicating cells. Following the three λ-exonuclease treatments, there was insufficient DNA remaining from the stationary phase cells to prepare the libraries for sequencing. This control strongly indicated that there was little to no contaminating DNA present with the SNS molecules after λ-exonuclease enrichment.

A strong research question should be focused but meaningful, and it should require analysis and interpretation—not just finding basic information.

I feel like this sentence is accurately getting at and spelling out the author's "point" or purpose in writing this essay (which seems extremely difficult as a travel blog to find some deeper meaning rather than just summarizing the experience). I also feel that this sentence summarizes the contrast that was built up in the previous paragraphs (Mount Fuji as a conventional tourist attraction vs Mount Fuji as a significant cultural icon–but then I suppose this juxtaposition could be related to all of the common/well-known landmarks across the world, thus making this experience seem more relatable to readers).

Love this line. It ties into the idea of materialism and tourism disrupting the beauty of nature. But this is someone who converted to a conceptualist even though the original intent was to do it for tourist-like reasons.

I'm hoping the long sentences are just done on purpose now that I'm reading more. I'm reading this and feeling the same way I do whenever a child tries to tell me what they did on the weekend. A few times feels purposeful, but the lack of a break makes my head spin.

Reviewer #1 (Public review):

Summary:

The study examines human biases in a regime-change task, in which participants have to report the probability of a regime change in the face of noisy data. The behavioral results indicate that humans display systematic biases, in particular, overreaction in stable but noisy environments and underreaction in volatile settings with more certain signals. fMRI results suggest that a frontoparietal brain network is selectively involved in representing subjective sensitivity to noise, while the vmPFC selectively represents sensitivity to the rate of change.

Strengths:

The study relies on a task that measures regime-change detection primarily based on descriptive information about the noisiness and rate of change. This distinguishes the study from prior work using reversal-learning or change-point tasks in which participants are required to learn these parameters from experiences. The authors discuss these differences comprehensively.

The study uses a simple Bayes-optimal model combined with model fitting, which seems to describe the data well. The model is comprehensively validated.

The authors apply model-based fMRI analyses that provide a close link to behavioral results, offering an elegant way to examine individual biases.

Weaknesses:

The authors have adequately addressed my prior concerns.

Reviewer #3 (Public review):

This study concerns how observers (human participants) detect changes in the statistics of their environment, termed regime shifts. To make this concrete, a series of 10 balls are drawn from an urn that contains mainly red or mainly blue balls. If there is a regime shift, the urn is changed over (from mainly red to mainly blue) at some point in the 10 trials. Participants report their belief that there has been a regime shift as a % probability. Their judgement should (mathematically) depend on the prior probability of a regime shift (which is set at one of three levels) and the strength of evidence (also one of three levels, operationalized as the proportion of red balls in the mostly-blue urn and vice versa). Participants are directly instructed of the prior probability of regime shift and proportion of red balls, which are presented on-screen as numerical probabilities. The task therefore differs from most previous work on this question in that probabilities are instructed rather than learned by observation, and beliefs are reported as numerical probabilities rather than being inferred from participants' choice behaviour (as in many bandit tasks, such as Behrens 2007 Nature Neurosci).

The key behavioural finding is that participants over-estimate the prior probability of regime change when it is low, and under estimate it when it is high; and participants over-estimate the strength of evidence when it is low and under-estimate it when it is high. In other words participants make much less distinction between the different generative environments than an optimal observer would. This is termed 'system neglect'. A neuroeconomic-style mathematical model is presented and fit to data.

Functional MRI results how that strength of evidence for a regime shift (roughly, the surprise associated with a blue ball from an apparently red urn) is associated with activity in the frontal-parietal orienting network. Meanwhile at time-points where the probability of a regime shift is high, there is activity in another network including vmPFC. Both networks show individual differences effects, such that people who were more sensitive to strength of evidence and prior probability show more activity in the frontal-parietal and vmPFC-linked networks respectively.

Strengths

(1) The study provides a different task for looking at change-detection and how this depends on estimates of environmental volatility and sensory evidence strength, in which participants are directly and precisely informed of the environmental volatility and sensory evidence strength rather than inferring them through observation as in most previous studies

(2) Participants directly provide belief estimates as probabilities rather than experimenters inferring them from choice behaviour as in most previous studies

(3) The results are consistent with well-established findings that surprising sensory events activate the frontal-parietal orienting network whilst updating of beliefs about the word ('regime shift') activates vmPFC.

Weaknesses

(1) The use of numerical probabilities (both to describe the environments to participants, and for participants to report their beliefs) may be problematic because people are notoriously bad at interpreting probabilities presented in this way, and show poor ability to reason with this information (see Kahneman's classic work on probabilistic reasoning, and how it can be improved by using natural frequencies). Therefore the fact that, in the present study, people do not fully use this information, or use it inaccurately, may reflect the mode of information delivery.

In the response to this comment the authors have pointed out their own previous work showing that system neglect can occur even when numerical probabilities are not used. This is reassuring but there remains a large body of classic work showing that observers do struggle with conditional probabilities of the type presented in the task.

(2) Although a very precise model of 'system neglect' is presented, many other models could fit the data.

For example, you would get similar effects due to attraction of parameter estimates towards a global mean - essentially application of a hyper-prior in which the parameters applied by each participant in each block are attracted towards the experiment-wise mean values of these parameters. For example, the prior probability of regime shift ground-truth values [0.01, 0.05, 0.10] are mapped to subjective values of [0.037, 0.052, 0.069]; this would occur if observers apply a hyper-prior that the probability of regime shift is about 0.05 (the average value over all blocks). This 'attraction to the mean' is a well-established phenomenon and cannot be ruled out with the current data (I suppose you could rule it out by comparing to another dataset in which the mean ground-truth value was different).

More generally, any model in which participants don't fully use the numerical information they were given would produce apparent 'system neglect'. Four qualitatively different example reasons are: 1. Some individual participants completely ignored the probability values given. 2. Participants did not ignore the probability values given, but combined them with a hyperprior as above. 3. Participants had a reporting bias where their reported beliefs that a regime-change had occurred tend to be shifted towards 50% (rather than reporting 'confident' values such 5% or 95%). 4. Participants underweighted probability outliers, resulting in underweighting of evidence in the 'high signal diagnosticity' environment (10.1016/j.neuron.2014.01.020 )

In summary I agree that any model that fits the data would have to capture the idea that participants don't differentiate between the different environments as much as they should, but I think there are a number of qualitatively different reasons why they might do this - of which the above are only examples - hence I find it problematic that the authors present the behaviour as evidence for one extremely specific model.

(3) Despite efforts to control confounds in the fMRI study, including two control experiments, I think some confounds remain.

For example, a network of regions is presented as correlating with the cumulative probability that there has been a regime shift in this block of 10 samples (Pt). However, regardless of the exact samples shown, Pt always increases with sample number (as by the time of later samples, there have been more opportunities for a regime shift)? To control for this the authors include, in a supplementary analysis, an 'intertemporal prior.' I would have preferred to see the results of this better-controlled analysis presented in the main figure. From the tables in the SI it is very difficult to tell how the results change with the includion of the control regressors.

On the other hand, two additional fMRI experiments are done as control experiments and the effect of Pt in the main study is compared to Pt in these control experiments. Whilst I admire the effort in carrying out control studies, I can't understand how these particular experiment are useful controls. For example, in experiment 3 participants simply type in numbers presented on the screen - how can we even have an estimate of Pt from this task?

(4) The Discussion is very long, and whilst a lot of related literature is cited, I found it hard to pin down within the discussion, what the key contributions of this study are. In my opinion it would be better to have a short but incisive discussion highlighting the advances in understanding that arise from the current study, rather than reviewing the field so broadly.

Author response:

The following is the authors’ response to the current reviews

eLife Assessment

This study offers valuable insights into how humans detect and adapt to regime shifts, highlighting dissociable contributions of the frontoparietal network and ventromedial prefrontal cortex to sensitivity to signal diagnosticity and transition probabilities. The combination of an innovative instructed-probability task, Bayesian behavioural modeling, and model-based fMRI analyses provides a solid foundation for the main claims; however, major interpretational limitations remain, particularly a potential confound between posterior switch probability and time in the neuroimaging results. At the behavioural level, reliance on explicitly instructed conditional probabilities leaves open alternative explanations that complicate attribution to a single computational mechanism, such that clearer disambiguation between competing accounts and stronger control of temporal and representational confounds would further strengthen the evidence.

Thank you. In this revision, we will focus on addressing Reviewer 3’s concern on the potential confound between posterior probability and time in neuroimaging results. First, we will present whole-brain results of subjects’ probability estimates (their subjective posterior probability of switch) after controlling for the effect of time on probability of switch (the intertemporal prior). Second, we will compare the effect of probability estimates (Pt) on vmPFC and ventral striatum activity—which we found to correlate with Pt—with and without including intertemporal prior in the GLM. Third, to address Reviewer 3’s comment that from the Tables of activation in the supplement vmPFC and ventral striatum cannot be located, we will add slice-by-slice image of the whole-brain results on Pt in the Supplemental Information in addition to the Tables of Activation.

Public Reviews:

Reviewer #1 (Public review):<br /> Summary:

The study examines human biases in a regime-change task, in which participants have to report the probability of a regime change in the face of noisy data. The behavioral results indicate that humans display systematic biases, in particular, overreaction in stable but noisy environments and underreaction in volatile settings with more certain signals. fMRI results suggest that a frontoparietal brain network is selectively involved in representing subjective sensitivity to noise, while the vmPFC selectively represents sensitivity to the rate of change.

Strengths:

The study relies on a task that measures regime-change detection primarily based on descriptive information about the noisiness and rate of change. This distinguishes the study from prior work using reversal-learning or change-point tasks in which participants are required to learn these parameters from experiences. The authors discuss these differences comprehensively.

The study uses a simple Bayes-optimal model combined with model fitting, which seems to describe the data well. The model is comprehensively validated.

The authors apply model-based fMRI analyses that provide a close link to behavioral results, offering an elegant way to examine individual biases.

Weaknesses:

The authors have adequately addressed my prior concerns.

Thank you for reviewing our paper and providing constructive comments that helped us improve our paper.

Reviewer #3 (Public review):

Thank you again for reviewing the manuscript. In this revision, we will focus on addressing your concern on the potential confound between posterior probability and time in neuroimaging results. First, we will present whole-brain results of subjects’ probability estimates (Pt, their subjective posterior probability of switch) after controlling for the effect of time on probability of switch (the intertemporal prior). Second, we will compare the effect of probability estimates (Pt) on vmPFC and ventral striatum activity—which we found to correlate with Pt—with and without including intertemporal prior in the GLM. These results will be summarized in a new figure (Figure 4).

Finally, to address that you were not able to locate vmPFC and ventral striatum from the Tables of activation, we will add slice-by-slice image of the whole-brain results on Pt in the supplement in addition to the Tables of Activation.

This study concerns how observers (human participants) detect changes in the statistics of their environment, termed regime shifts. To make this concrete, a series of 10 balls are drawn from an urn that contains mainly red or mainly blue balls. If there is a regime shift, the urn is changed over (from mainly red to mainly blue) at some point in the 10 trials. Participants report their belief that there has been a regime shift as a % probability. Their judgement should (mathematically) depend on the prior probability of a regime shift (which is set at one of three levels) and the strength of evidence (also one of three levels, operationalized as the proportion of red balls in the mostly-blue urn and vice versa). Participants are directly instructed of the prior probability of regime shift and proportion of red balls, which are presented on-screen as numerical probabilities. The task therefore differs from most previous work on this question in that probabilities are instructed rather than learned by observation, and beliefs are reported as numerical probabilities rather than being inferred from participants' choice behaviour (as in many bandit tasks, such as Behrens 2007 Nature Neurosci).

The key behavioural finding is that participants over-estimate the prior probability of regime change when it is low, and under estimate it when it is high; and participants over-estimate the strength of evidence when it is low and under-estimate it when it is high. In other words participants make much less distinction between the different generative environments than an optimal observer would. This is termed 'system neglect'. A neuroeconomic-style mathematical model is presented and fit to data.

Functional MRI results how that strength of evidence for a regime shift (roughly, the surprise associated with a blue ball from an apparently red urn) is associated with activity in the frontal-parietal orienting network. Meanwhile at time-points where the probability of a regime shift is high, there is activity in another network including vmPFC. Both networks show individual differences effects, such that people who were more sensitive to strength of evidence and prior probability show more activity in the frontal-parietal and vmPFC-linked networks respectively.

Strengths

(1) The study provides a different task for looking at change-detection and how this depends on estimates of environmental volatility and sensory evidence strength, in which participants are directly and precisely informed of the environmental volatility and sensory evidence strength rather than inferring them through observation as in most previous studies

(2) Participants directly provide belief estimates as probabilities rather than experimenters inferring them from choice behaviour as in most previous studies

(3) The results are consistent with well-established findings that surprising sensory events activate the frontal-parietal orienting network whilst updating of beliefs about the word ('regime shift') activates vmPFC.

Weaknesses

(1) The use of numerical probabilities (both to describe the environments to participants, and for participants to report their beliefs) may be problematic because people are notoriously bad at interpreting probabilities presented in this way, and show poor ability to reason with this information (see Kahneman's classic work on probabilistic reasoning, and how it can be improved by using natural frequencies). Therefore the fact that, in the present study, people do not fully use this information, or use it inaccurately, may reflect the mode of information delivery.

In the response to this comment the authors have pointed out their own previous work showing that system neglect can occur even when numerical probabilities are not used. This is reassuring but there remains a large body of classic work showing that observers do struggle with conditional probabilities of the type presented in the task.

Thank you. Yes, people do struggle with conditional probabilities in many studies. However, as our previous work suggested (Massey and Wu, 2005), system-neglect was likely not due to response mode (having to enter probability estimates or making binary predictions, and etc.).

(2) Although a very precise model of 'system neglect' is presented, many other models could fit the data.

For example, you would get similar effects due to attraction of parameter estimates towards a global mean - essentially application of a hyper-prior in which the parameters applied by each participant in each block are attracted towards the experiment-wise mean values of these parameters. For example, the prior probability of regime shift ground-truth values [0.01, 0.05, 0.10] are mapped to subjective values of [0.037, 0.052, 0.069]; this would occur if observers apply a hyper-prior that the probability of regime shift is about 0.05 (the average value over all blocks). This 'attraction to the mean' is a well-established phenomenon and cannot be ruled out with the current data (I suppose you could rule it out by comparing to another dataset in which the mean ground-truth value was different).

We thank the reviewer for this comment. We do not disagree that there are alternative models that can describe over- and underreactions seen in the dataset. However, we do wish to point out that since we began with the normative Bayesian model, the natural progression in case the normative model fails to capture data is to modify the starting model. It is under this context that we developed the system-neglect model. It was a simple extension (a parameterized version) of the normative Bayesian model.

Regarding the hyperprior idea, even if the participants have a hyperprior, there has to be some function that describes/implements attraction to the mean. Having a hyperprior itself does not imply attraction to this hyperprior. We therefore were not sure why the hyperprior itself can produce attraction to the mean.

We do look further into the possibility of attraction to the mean. First, as suggested by the reviewer, we looked into another dataset with different mean ground-truth value. In Massey and Wu (2005), the transition probabilities were [0.02 0.05 0.1 0.2], which is different from the current study [0.01 0.05 0.1], and there they also found over- and underreactions as well. Second, we reason that for the attraction to the mean idea to work subjects need to know the mean of the system parameters. This would take time to develop because we did not tell subjects about the mean. If this is caused by attraction to the mean, subjects’ behavior would be different in the early stage of the experiment where they had little idea about the mean, compared with the late stage of the experiment where they knew about the mean. We will further analyze and compare participants’ data at the beginning of the experiment with data at the end of the experiment.

More generally, any model in which participants don't fully use the numerical information they were given would produce apparent 'system neglect'. Four qualitatively different example reasons are: 1. Some individual participants completely ignored the probability values given. 2. Participants did not ignore the probability values given, but combined them with a hyperprior as above. 3. Participants had a reporting bias where their reported beliefs that a regime-change had occurred tend to be shifted towards 50% (rather than reporting 'confident' values such 5% or 95%). 4. Participants underweighted probability outliers, resulting in underweighting of evidence in the 'high signal diagnosticity' environment (10.1016/j.neuron.2014.01.020 )

We thank the reviewer for pointing out these potential explanations. Again, we do not disagree that any model in which participants don’t fully use numerical information they were given would produce system neglect. It is hard to separate ‘not fully using numerical information’ from ‘lack of sensitivity to the numerical information’. We will respond in more details to the four example reasons later.

In summary I agree that any model that fits the data would have to capture the idea that participants don't differentiate between the different environments as much as they should, but I think there are a number of qualitatively different reasons why they might do this - of which the above are only examples - hence I find it problematic that the authors present the behaviour as evidence for one extremely specific model.

Again, we do not disagree with the reviewer on the modeling statement. However, we also wish to point out that the system-neglect model we had is a simple extension of the normative Bayesian model. Had we gone to a non-Bayesian framework, we would have faced the criticism of why we simply do not consider a simple extension of the starting model. In response, we will add a section in Discussion summarizing our exchange on this matter.

(3) Despite efforts to control confounds in the fMRI study, including two control experiments, I think some confounds remain.

For example, a network of regions is presented as correlating with the cumulative probability that there has been a regime shift in this block of 10 samples (Pt). However, regardless of the exact samples shown, Pt always increases with sample number (as by the time of later samples, there have been more opportunities for a regime shift)? To control for this the authors include, in a supplementary analysis, an 'intertemporal prior.' I would have preferred to see the results of this better-controlled analysis presented in the main figure. From the tables in the SI it is very difficult to tell how the results change with the includion of the control regressors.

Thank you. In response, we will add a new figure, now Figure 4, showing the results of Pt and delta Pt from GLM-2 where we added the intertemporal prior as a regressor to control for temporal confounds. We compared Pt and delta Pt results in vmPFC and ventral striatum between GLM-1 and GLM-2. We also will show the results of intertemporal prior on vmPFC and ventral striatum under GLM-2.

On the other hand, two additional fMRI experiments are done as control experiments and the effect of Pt in the main study is compared to Pt in these control experiments. Whilst I admire the effort in carrying out control studies, I can't understand how these particular experiment are useful controls. For example, in experiment 3 participants simply type in numbers presented on the screen - how can we even have an estimate of Pt from this task?

We thank the reviewer for this comment. On the one hand, the effect of Pt we see in brain activity can be simply due to motor confounds and the purpose of Experiment 3 was to control for them. Our question was, if subjects saw the similar visual layout and were just instructed to press buttons to indicate two-digit numbers, would we observe the vmPFC, ventral striatum, and the frontoparietal network like what we did in the main experiment (Experiment 1)?

On the other hand, the effect of Pt can simply reflect probability estimates of that the current regime is the blue regime, and therefore not particularly about change detection. In Experiment 2, we tested that idea, namely whether what we found about Pt was unique to change detection. In Experiment 2, subjects estimated the probability that the current regime is the blue regime (just as they did in Experiment 1) except that there were no regime shifts involved. In other words, it is possible that the regions we identified were generally associated with probability estimation and not particularly about probability estimates of change. We used Experiment 2 to examine whether this were true.

To make the purpose of the two control experiments clearer, we updated the paragraph describing the control experiments on page 9:

“To establish the neural representations for regime-shift estimation, we performed three fMRI experiments ( subjects for each experiment, 90 subjects in total). Experiment 1 was the main experiment, while Experiments 2 to 3 were control experiments that ruled out two important confounds (Fig. 1E). The control experiments were designed to clarify whether any effect of subjects’ probability estimates of a regime shift, , in brain activity can be uniquely attributed to change detection. Here we considered two major confounds that can contribute to the effect of . First, since subjects in Experiment 1 made judgments about the probability that the current regime is the blue regime (which corresponded to probability of regime change), the effect of  did not particularly have to do with change detection. To address this issue, in Experiment 2 subjects made exactly the same judgments as in Experiment 1 except that the environments were stationary (no transition from one regime to another was possible), as in Edwards (1968) classic “bookbag-and-poker chip” studies. Subjects in both experiments had to estimate the probability that the current regime is the blue regime, but this estimation corresponded to the estimates of regime change only in Experiment 1. Therefore, activity that correlated with probability estimates in Experiment 1 but not in Experiment 2 can be uniquely attributed to representing regime-shift judgments. Second, the effect of  can be due to motor preparation and/or execution, as subjects in Experiment 1 entered two-digit numbers with button presses to indicate their probability estimates. To address this issue, in Experiment 3 subjects performed a task where they were presented with two-digit numbers and were instructed to enter the numbers with button presses. By comparing the fMRI results of these experiments, we were therefore able to establish the neural representations that can be uniquely attributed to the probability estimates of regime-shift.”

To further make sure that the probability-estimate signals in Experiment 1 were not due to motor confounds, we implemented an action-handedness regressor in the GLM, as we described below on page 19:

“Finally, we note that in GLM-1, we implemented an “action-handedness” regressor to directly address the motor-confound issue, that higher probability estimates preferentially involved right-handed responses for entering higher digits. The action-handedness regressor was parametric, coding -1 if both finger presses involved the left hand (e.g., a subject pressed “23” as her probability estimate when seeing a signal), 0 if using one left finger and one right finger (e.g., “75”), and 1 if both finger presses involved the right hand (e.g., “90”). Taken together, these results ruled out motor confounds and suggested that vmPFC and ventral striatum represent subjects’ probability estimates of change (regime shifts) and belief revision.”

(4) The Discussion is very long, and whilst a lot of related literature is cited, I found it hard to pin down within the discussion, what the key contributions of this study are. In my opinion it would be better to have a short but incisive discussion highlighting the advances in understanding that arise from the current study, rather than reviewing the field so broadly.

Thank you. We thank the reviewer for pushing us to highlight the key contributions. In response, we added a paragraph at the beginning of Discussion to better highlight our contributions:

“In this study, we investigated how humans detect changes in the environments and the neural mechanisms that contribute to how we might under- and overreact in our judgments. Combining a novel behavioral paradigm with computational modeling and fMRI, we discovered that sensitivity to environmental parameters that directly impact change detection is a key mechanism for under- and overreactions. This mechanism is implemented by distinct brain networks in the frontal and parietal cortices and in accordance with the computational roles they played in change detection. By introducing the framework in system neglect and providing evidence for its neural implementations, this study offered both theoretical and empirical insights into how systematic judgment biases arise in dynamic environments.”

**Recommendations for the authors:

Reviewer #3 (Recommendations for the authors):**

Thank you for pointing out the inclusion of the intertemporal prior in glm2, this seems like an important control that would address my criticism. Why not present this better-controlled analysis in the main figure, rather than the results for glm1 which has no effective control of the increasing posterior probability of a reversal with time?

Thank you for this suggestion. We added a new figure (Figure 4) that showed results from GLM-2. In this new figure, we showed whole-brain results on Pt and delta Pt, ROI results of vmPFC and ventral striatum on Pt, delta Pt, and intertemporal prior.

The reason we kept results from GLM-1 (Figure 3) was primarily because we wanted to compare the effect of Pt between experiments under identical GLM. In other words, the regressors in GLM-1 was identical across all 3 experiments. In Experiments 1 and 2, Pt and delta Pt were respectively probability estimates and belief updates that current regime was the Blue regime. In Experiment 3, Pt and delta Pt were simply the number subjects were instructed to press (Pt) and change in number between successive periods (delta Pt).

As a further point I could not navigate the tables of fMRI activations in SI and recommend replacing or supplementing these with images. For example I cannot actually find a vmPFC or ventral striatum cluster listed for the effect of Pt in GLM1 (version in table S1), which I thought were the main results? Beyond that, comparing how much weaker (or not) those results are when additional confound regressors are included in GLM2 seems impossible.

The vmPFC and ventral striatum were part of the cluster labeled as Central Opercular cortex. In response, we will provide information about coordinates on the local maxima within the cluster. We will also add slice-by-slice images showing the effect of Pt.

The following is the authors’ response to the original reviews

eLife Assessment

This study offers valuable insights into how humans detect and adapt to regime shifts, highlighting distinct contributions of the frontoparietal network and ventromedial prefrontal cortex to sensitivity to signal diagnosticity and transition probabilities. The combination of an innovative task design, behavioral modeling, and model-based fMRI analyses provides a solid foundation for the conclusions; however, the neuroimaging results have several limitations, particularly a potential confound between the posterior probability of a switch and the passage of time that may not be fully controlled by including trial number as a regressor. The control experiments intended to address this issue also appear conceptually inconsistent and, at the behavioral level, while informing participants of conditional probabilities rather than requiring learning is theoretically elegant, such information is difficult to apply accurately, as shown by well-documented challenges with conditional reasoning and base-rate neglect. Expressing these probabilities as natural frequencies rather than percentages may have improved comprehension. Overall, the study advances understanding of belief updating under uncertainty but would benefit from more intuitive probabilistic framing and stronger control of temporal confounds in future work.

We thank the editors for the assessment and we appreciate your efforts in reviewing the paper. The editors added several limitations in the assessment based on the new reviewer 3 in this round, which we would like to clarify below.

With regard to temporal confounds, we clarified in the main text and response to Reviewer 3 that we had already addressed the potential confound between posterior probability of a switch and passage of time in GLM-2 with the inclusion of intertemporal prior. After adding intertemporal prior in the GLM, we still observed the same fMRI results on probability estimates. In addition, we did two other robustness checks, which we mentioned in the manuscript.

With regard to response mode (probability estimation rather than choice or indicating natural frequencies), we wish to point out that the in previous research by Massey and Wu (2005), which the current study was based on, the concern of participants showing system-neglect tendencies due to the mode of information delivery, namely indicating beliefs through reporting probability estimates rather than through choice or other response mode was addressed. Massy and Wu (2005, Study 3) found the same biases when participants performed a choice task that did not require them to indicate probability estimates.

With regard to the control experiments, the control experiments in fact were not intended to address the confounds between posterior probability and passage of time. Rather, they aimed to address whether the neural findings were unique to change detection (Experiment 2) and to address visual and motor confounds (Experiment 3). These and the results of the control experiments were mentioned on page 18-19.

We also wish to highlight that we had performed detailed model comparisons after reviewer 2’s suggestions. Although reviewer 2 was unable to re-review the manuscript, we believe this provides insight into the literature on change detection. See “Incorporating signal dependency into system-neglect model led to better models for regime-shift detection” (p.27-30). The model comparison showed that system-neglect models that incorporate signal dependency are better models than the original system-neglect model in describing participants probability estimates. This suggests that people respond to change-consistent and change-inconsistent signals differently when judging whether the regime had changed. This was not reported in previous behavioral studies and was largely inspired by the neural finding on signal dependency in the frontoparietal cortex. It indicates that neural findings can provide novel insights into computational modeling of behavior.

To better highlight and summarize our key contributions, we added a paragraph at the beginning of Discussion:

“In this study, we investigated how humans detect changes in the environments and the neural mechanisms that contribute to how we might under- and overreact in our judgments. Combining a novel behavioral paradigm with computational modeling and fMRI, we discovered that sensitivity to environmental parameters that directly impact change detection is a key mechanism for under- and overreactions. This mechanism is implemented by distinct brain networks in the frontal and parietal cortices and in accordance with the computational roles they played in change detection. By introducing the framework in system neglect and providing evidence for its neural implementations, this study offered both theoretical and empirical insights into how systematic judgment biases arise in dynamic environments.”    

Public Reviews:

Reviewer #1 (Public review):

Summary:

The study examines human biases in a regime-change task, in which participants have to report the probability of a regime change in the face of noisy data. The behavioral results indicate that humans display systematic biases, in particular, overreaction in stable but noisy environments and underreaction in volatile settings with more certain signals. fMRI results suggest that a frontoparietal brain network is selectively involved in representing subjective sensitivity to noise, while the vmPFC selectively represents sensitivity to the rate of change.

Strengths:

- The study relies on a task that measures regime-change detection primarily based on descriptive information about the noisiness and rate of change. This distinguishes the study from prior work using reversal-learning or change-point tasks in which participants are required to learn these parameters from experiences. The authors discuss these differences comprehensively.

- The study uses a simple Bayes-optimal model combined with model fitting, which seems to describe the data well. The model is comprehensively validated.

- The authors apply model-based fMRI analyses that provide a close link to behavioral results, offering an elegant way to examine individual biases.

We thank the reviewer for the comments.

Weaknesses:

The authors have adequately addressed most of my prior concerns.

We thank the reviewer for recognizing our effort in addressing your concerns.

My only remaining comment concerns the z-test of the correlations. I agree with the non-parametric test based on bootstrapping at the subject level, providing evidence for significant differences in correlations within the left IFG and IPS.

However, the parametric test seems inadequate to me. The equation presented is described as the Fisher z-test, but the numerator uses the raw correlation coefficients (r) rather than the Fisher-transformed values (z). To my understanding, the subtraction should involve the Fisher z-scores, not the raw correlations.

More importantly, the Fisher z-test in its standard form assumes that the correlations come from independent samples, as reflected in the denominator (which uses the n of each independent sample). However, in my opinion, the two correlations are not independent but computed within-subject. In such cases, parametric tests should take into account the dependency. I believe one appropriate method for the current case (correlated correlation coefficients sharing a variable [behavioral slope]) is explained here:

Meng, X.-l., Rosenthal, R., & Rubin, D. B. (1992). Comparing correlated correlation coefficients. Psychological Bulletin, 111(1), 172-175. https://doi.org/10.1037/0033-2909.111.1.172

It should be implemented here:

Diedenhofen B, Musch J (2015) cocor: A Comprehensive Solution for the Statistical Comparison of Correlations. PLoS ONE 10(4): e0121945. https://doi.org/10.1371/journal.pone.0121945

My recommendation is to verify whether my assumptions hold, and if so, perform a test that takes correlated correlations into account. Or, to focus exclusively on the non-parametric test.

In any case, I recommend a short discussion of these findings and how the authors interpret that some of the differences in correlations are not significant.

Thank you for the careful check. Yes. This was indeed a mistake from us. We also agree that the two correlations are not independent. Therefore, we modified the test that accounts for dependent correlations by following Meng et al. (1992) suggested by the reviewer. We updated in the Methods section on p.56-57:

“In the parametric test, we adopted the approach of Meng et al. (1992) to statistically compare the two correlation coefficients. This approach specifically tests differences between dependent correlation coefficients according to the following equation

Where N is the number of subjects, z_ri is the Fisher z-transformed value of r_i,(r₁ = r_blue and r₂ = r_red), and r_x is the correlation between the neural sensitivity at change-consistent signals and change-inconsistent signals. The computation of h is based on the following equations

Where is the mean of the , and f should be set to 1 if > 1.”

We updated on the Results section on p.29:

“Since these correlation coefficients were not independent, we compared them using the test developed in Meng et al. (1992) (see Methods). We found that among the five ROIs in the frontoparietal network, two of them, namely the left IFG and left IPS, the difference in correlation was significant (one-tailed z test; left IFG: z = 1.8908, p = 0.0293; left IPS: z = 2.2584, p = 0.0049). For the remaining three ROIs, the difference in correlation was not significant (dmPFC: z = 0.9522, p = 0.1705; right IFG: z = 0.9860, p = 0.1621; right IPS: z = 1.4833, p = 0.0690).”

We added a Discussion on these results on p.41:

“Interestingly, such sensitivity to signal diagnosticity was only present in the frontoparietal network when participants encountered change-consistent signals. However, while most brain areas within this network responded in this fashion, only the left IPS and left IFG showed a significant difference in coding individual participants’ sensitivity to signal diagnosticity between change-consistent and change-inconsistent signals. Unlike the left IPS and left IFG, we observed in dmPFC a marginally significant correlation with behavioral sensitivity at change-inconsistent signals as well. Together, these results indicate that while different brain areas in the frontoparietal network responded similarly to change-consistent signals, there was a greater degree of heterogeneity in responding to change-inconsistent signals.”

Reviewer #3 (Public review):

This study concerns how observers (human participants) detect changes in the statistics of their environment, termed regime shifts. To make this concrete, a series of 10 balls are drawn from an urn that contains mainly red or mainly blue balls. If there is a regime shift, the urn is changed over (from mainly red to mainly blue) at some point in the 10 trials. Participants report their belief that there has been a regime shift as a % probability. Their judgement should (mathematically) depend on the prior probability of a regime shift (which is set at one of three levels) and the strength of evidence (also one of three levels, operationalized as the proportion of red balls in the mostly-blue urn and vice versa). Participants are directly instructed of the prior probability of regime shift and proportion of red balls, which are presented on-screen as numerical probabilities. The task therefore differs from most previous work on this question in that probabilities are instructed rather than learned by observation, and beliefs are reported as numerical probabilities rather than being inferred from participants' choice behaviour (as in many bandit tasks, such as Behrens 2007 Nature Neurosci).

The key behavioural finding is that participants over-estimate the prior probability of regime change when it is low, and under estimate it when it is high; and participants over-estimate the strength of evidence when it is low and under-estimate it when it is high. In other words participants make much less distinction between the different generative environments than an optimal observer would. This is termed 'system neglect'. A neuroeconomic-style mathematical model is presented and fit to data.

Functional MRI results how that strength of evidence for a regime shift (roughly, the surprise associated with a blue ball from an apparently red urn) is associated with activity in the frontal-parietal orienting network. Meanwhile, at time-points where the probability of a regime shift is high, there is activity in another network including vmPFC. Both networks show individual differences effects, such that people who were more sensitive to strength of evidence and prior probability show more activity in the frontal-parietal and vmPFC-linked networks respectively.

We thank the reviewer for the overall descriptions of the manuscript.

Strengths

(1) The study provides a different task for looking at change-detection and how this depends on estimates of environmental volatility and sensory evidence strength, in which participants are directly and precisely informed of the environmental volatility and sensory evidence strength rather than inferring them through observation as in most previous studies

(2) Participants directly provide belief estimates as probabilities rather than experimenters inferring them from choice behaviour as in most previous studies

(3) The results are consistent with well-established findings that surprising sensory events activate the frontal-parietal orienting network whilst updating of beliefs about the word ('regime shift') activates vmPFC.

Thank you for these assessments.

Weaknesses

(1) The use of numerical probabilities (both to describe the environments to participants, and for participants to report their beliefs) may be problematic because people are notoriously bad at interpreting probabilities presented in this way, and show poor ability to reason with this information (see Kahneman's classic work on probabilistic reasoning, and how it can be improved by using natural frequencies). Therefore the fact that, in the present study, people do not fully use this information, or use it inaccurately, may reflect the mode of information delivery.

We appreciate the reviewer’s concern on this issue. The concern was addressed in Massey and Wu (2005) as participants performed a choice task in which they were not asked to provide probability estimates (Study 3 in Massy and Wu, 2005). Instead, participants in Study 3 were asked to predict the color of the ball before seeing a signal. This was a more intuitive way of indicating his or her belief about regime shift. The results from the choice task were identical to those found in the probability estimation task (Study 1 in Massey and Wu). We take this as evidence that the system-neglect behavior the participants showed was less likely to be due to the mode of information delivery.

(2) Although a very precise model of 'system neglect' is presented, many other models could fit the data.

For example, you would get similar effects due to attraction of parameter estimates towards a global mean - essentially application of a hyper-prior in which the parameters applied by each participant in each block are attracted towards the experiment-wise mean values of these parameters. For example, the prior probability of regime shift ground-truth values [0.01, 0.05, 0.10] are mapped to subjective values of [0.037, 0.052, 0.069]; this would occur if observers apply a hyper-prior that the probability of regime shift is about 0.05 (the average value over all blocks). This 'attraction to the mean' is a well-established phenomenon and cannot be ruled out with the current data (I suppose you could rule it out by comparing to another dataset in which the mean ground-truth value was different).

We thank the reviewer for this comment. It is true that the system-neglect model is not entirely inconsistent with regression to the mean, regardless of whether the implementation has a hyper prior or not. In fact, our behavioral measure of sensitivity to transition probability and signal diagnosticity, which we termed the behavioral slope, is based on linear regression analysis. In general, the modeling approach in this paper is to start from a generative model that defines ideal performance and consider modifying the generative model when systematic deviations in actual performance from the ideal is observed. In this approach, a generative Bayesian model with hyper priors would be more complex to begin with, and a regression to the mean idea by itself does not generate a priori predictions.

More generally, any model in which participants don't fully use the numerical information they were given would produce apparent 'system neglect'. Four qualitatively different example reasons are: 1. Some individual participants completely ignored the probability values given. 2. Participants did not ignore the probability values given, but combined them with a hyperprior as above. 3. Participants had a reporting bias where their reported beliefs that a regime-change had occurred tend to be shifted towards 50% (rather than reporting 'confident' values such 5% or 95%). 4. Participants underweighted probability outliers resulting in underweighting of evidence in the 'high signal diagnosticity' environment (10.1016/j.neuron.2014.01.020)

In summary I agree that any model that fits the data would have to capture the idea that participants don't differentiate between the different environments as much as they should, but I think there are a number of qualitatively different reasons why they might do this - of which the above are only examples - hence I find it problematic that the authors present the behaviour as evidence for one extremely specific model.

Thank you for raising this point. The modeling principle we adopt is the following. We start from the normative model—the Bayesian model—that defined what normative behavior should look like. We compared participants’ behavior with the Bayesian model and found systematic deviations from it. To explain those systematic deviations, we considered modeling options within the confines of the same modeling framework. In other words, we considered a parameterized version of the Bayesian model, which is the system-neglect model and examined through model comparison the best modeling choice. This modeling approach is not uncommon in economics and psychology. For example, Kahneman and Tversky adopted this approach when proposing prospect theory, a modification of expected utility theory where expected utility theory can be seen as one specific model for how utility of an option should be computed.

(3) Despite efforts to control confounds in the fMRI study, including two control experiments, I think some confounds remain.

For example, a network of regions is presented as correlating with the cumulative probability that there has been a regime shift in this block of 10 samples (Pt). However, regardless of the exact samples shown, doesn't Pt always increase with sample number (as by the time of later samples, there have been more opportunities for a regime shift)? Unless this is completely linear, the effect won't be controlled by including trial number as a co-regressor (which was done).

Thank you for raising this concern. Yes, Pt always increases with sample number regardless of evidence (seeing change-consistent or change-inconsistent signals). This is captured by the ‘intertemporal prior’ in the Bayesian model, which we included as a regressor in our GLM analysis (GLM-2), in addition to Pt. In short, GLM-1 had Pt and sample number. GLM-2 had Pt, intertemporal prior, and sample number, among other regressors. And we found that, in both GLM-1 and GLM-2, both vmPFC and ventral striatum correlated with Pt.

To make this clearer, we updated the main text to further clarify this on p.18:

“We examined the robustness of P_t representations in these two regions in several follow-up analyses. First, we implemented a GLM (GLM-2 in Methods) that, in addition to P_t, included various task-related variables contributing to P_t as regressors (Fig. S7 in SI). Specifically, to account for the fact that the probability of regime change increased over time, we included the intertemporal prior as a regressor in GLM-2. The intertemporal prior is the natural logarithm of the odds in favor of regime shift in the t-th period, where q is transition probability and t = 1,…,10 is the period (see Eq. 1 in Methods). It describes normatively how the prior probability of change increased over time regardless of the signals (blue and red balls) the subjects saw during a trial. Including it along with P_t would clarify whether any effect of P_t can otherwise be attributed to the intertemporal prior. Second, we implemented a GLM that replaced P_t with the log odds of P_t, ln (P_t/(1-P_t)) (Fig. S8 in SI). Third, we implemented a GLM that examined  separately on periods when change-consistent (blue balls) and change-inconsistent (red balls) signals appeared (Fig. S9 in SI). Each of these analyses showed the same pattern of correlations between P_t and activation in vmPFC and ventral striatum, further establishing the robustness of the P_t findings.”

On the other hand, two additional fMRI experiments are done as control experiments and the effect of Pt in the main study is compared to Pt in these control experiments. Whilst I admire the effort in carrying out control studies, I can't understand how these particular experiment are useful controls. For example in experiment 3 participants simply type in numbers presented on the screen - how can we even have an estimate of Pt from this task?

We thank the reviewer for this comment. On the one hand, the effect of Pt we see in brain activity can be simply due to motor confounds and the purpose of Experiment 3 was to control for them. Our question was, if subjects saw the similar visual layout and were just instructed to press buttons to indicate two-digit numbers, would we observe the vmPFC, ventral striatum, and the frontoparietal network like what we did in the main experiment (Experiment 1)?

On the other hand, the effect of Pt can simply reflect probability estimates of that the current regime is the blue regime, and therefore not particularly about change detection. In Experiment 2, we tested that idea, namely whether what we found about Pt was unique to change detection. In Experiment 2, subjects estimated the probability that the current regime is the blue regime (just as they did in Experiment 1) except that there were no regime shifts involved. In other words, it is possible that the regions we identified were generally associated with probability estimation and not particularly about probability estimates of change. We used Experiment 2 to examine whether this were true.

To make the purpose of the two control experiments clearer, we updated the paragraph describing the control experiments on page 9:

“To establish the neural representations for regime-shift estimation, we performed three fMRI experiments (n\=30 subjects for each experiment, 90 subjects in total). Experiment 1 was the main experiment, while Experiments 2 to 3 were control experiments that ruled out two important confounds (Fig. 1E). The control experiments were designed to clarify whether any effect of subjects’ probability estimates of a regime shift, P_t, in brain activity can be uniquely attributed to change detection. Here we considered two major confounds that can contribute to the effect of . First, since subjects in Experiment 1 made judgments about the probability that the current regime is the blue regime (which corresponded to probability of regime change), the effect of P_t did not particularly have to do with change detection. To address this issue, in Experiment 2 subjects made exactly the same judgments as in Experiment 1 except that the environments were stationary (no transition from one regime to another was possible), as in Edwards (1968) classic “bookbag-and-poker chip” studies. Subjects in both experiments had to estimate the probability that the current regime is the blue regime, but this estimation corresponded to the estimates of regime change only in Experiment 1. Therefore, activity that correlated with probability estimates in Experiment 1 but not in Experiment 2 can be uniquely attributed to representing regime-shift judgments. Second, the effect of P_t can be due to motor preparation and/or execution, as subjects in Experiment 1 entered two-digit numbers with button presses to indicate their probability estimates. To address this issue, in Experiment 3 subjects performed a task where they were presented with two-digit numbers and were instructed to enter the numbers with button presses. By comparing the fMRI results of these experiments, we were therefore able to establish the neural representations that can be uniquely attributed to the probability estimates of regime-shift.”

To further make sure that the probability-estimate signals in Experiment 1 were not due to motor confounds, we implemented an action-handedness regressor in the GLM, as we described below on page 19:

“Finally, we note that in GLM-1, we implemented an “action-handedness” regressor to directly address the motor-confound issue, that higher probability estimates preferentially involved right-handed responses for entering higher digits. The action-handedness regressor was parametric, coding -1 if both finger presses involved the left hand (e.g., a subject pressed “23” as her probability estimate when seeing a signal), 0 if using one left finger and one right finger (e.g., “75”), and 1 if both finger presses involved the right hand (e.g., “90”). Taken together, these results ruled out motor confounds and suggested that vmPFC and ventral striatum represent subjects’ probability estimates of change (regime shifts) and belief revision.”

(4) The Discussion is very long, and whilst a lot of related literature is cited, I found it hard to pin down within the discussion, what the key contributions of this study are. In my opinion it would be better to have a short but incisive discussion highlighting the advances in understanding that arise from the current study, rather than reviewing the field so broadly.

Thank you. We thank the reviewer for pushing us to highlight the key contributions. In response, we added a paragraph at the beginning of Discussion to better highlight our contributions:

“In this study, we investigated how humans detect changes in the environments and the neural mechanisms that contribute to how we might under- and overreact in our judgments. Combining a novel behavioral paradigm with computational modeling and fMRI, we discovered that sensitivity to environmental parameters that directly impact change detection is a key mechanism for under- and overreactions. This mechanism is implemented by distinct brain networks in the frontal and parietal cortices and in accordance with the computational roles they played in change detection. By introducing the framework in system neglect and providing evidence for its neural implementations, this study offered both theoretical and empirical insights into how systematic judgment biases arise in dynamic environments.”

Recommendations for the authors:

Reviewer #3 (Recommendations for the authors):

Many of the figures are too tiny - the writing is very small, as are the pictures of brains. I'd suggest adjusting these so they will be readable without enlarging.

Thank you. We apologize for the poor readability of the figures. We had enlarged the figures (Fig. 5 in particular) and their font size to make them more readable.

Secondary sources provides information but is not a first hand account

This paragraph explains that writing uses a process to stay organized, but it isn’t always linear. Writing is recursive, so writers often revisit steps to revise and improve their work.

To me, this seems like she and the slave community do what they can, if there is a chance of some improvement in their condition. This is regardless of what "morals" are broken. I found it especially moving that she says the practice of morals is impossible due to their condition. I've never thought of this perspective before!

Reviewer #2 (Public review):

The article is very well written, and the new methodology is presented with care. I particularly appreciated the step-by-step rationale for establishing the approach, such as the relationship between K-means centers and the various parameters. This text is conveniently supported by the flow charts and t-SNE plots. Importantly, I thought the choice of state-of-the-art method was appropriate and the choice of dataset adequate, which together convinced me in believing the large improvement reported. I thought that the crossmodal feature-engineering solution proposed was elegant and seems exportable to other fields. Here are a few notes.<br /> While the validation data set was well chosen and of high quality, it remains a single dataset and also remains a non-recurrent network. The authors acknowledge this in the discussion, but I wanted to chime in to say that for the method to be more than convincing, it would need to have been tested on more datasets. It should be acknowledged that the problem becomes more complicated in a recurrent excitatory network, and thus the method may not work as well in the cortex or in CA3.

While the data is shown to work in this particular dataset (plus the two others at the end), I was left wondering when the method breaks. And it should break if the models are sufficiently mismatched. Such a question can be addressed using synthetic-synthetic models. This was an important intuition that I was missing, and an important check on the general nature of the method that I was missing.

While the choice of state-of-the-art is good in my opinion, I was looking for comments on the methods prior to that. For instance, methods such based on GLMs have been used by the Pillow, Paninski, and Truccolo groups. I could not find a decent discussion of these methods in the main text and thought that both their acknowledgement and rationale for dismissing were missing.

While most of the text was very clear, I thought that page 11 was odd and missing much in terms of introductions. Foremost is the introduction of the dataset, which is never really done. Page 11 refers to 'this dataset', while the previous sentence was saying that having such a dataset would be important and is challenging. The dataset needs to be properly described: what's the method for labeling, what's the brain area, what were the spike recording methodologies, what is meant by two labeling methodologies, what do we know about the idiosyncrasies of the particular network the recording came from (like CA1 is non-recurrent, so which connections)? I was surprised to see 'English et al.' cited in text only on page 13 since their data has been hailed from the beginning.

Further elements that needed definition are the Nsyn and i, which were not defined in the cortex of Equation 2-3: I was not sure if it referred to different samples or different variants of the synthetic model. I also would have preferred having the function f defined earlier, as it is defined for Equation 3, but appears in Equation 2.

When the loss functions are described, it would be important to define 'data' and 'labels' here. This machine learning jargon has a concrete interpretation in this context, and making this concrete would be very important for the readership.

While I appreciated that there was a section on robustness, I did not find that the features studied were the most important. In this context, I was surprised that the other datasets were relegated to supplementary, as these appeared more relevant.

Some of the figures have text that is too small. In particular, Figure 2 has text that is way too small. It seemed to me that the pseudo code could stand alone, and the screenshot of the equations did not need to be repeated in a figure, especially if their size becomes so small that we can't even read them.

Author response:

General Response

We thank the reviewers for their positive assessment of our work and for acknowledging the timeliness of the problem and the novelty of using domain adaptation to address model mismatch. We appreciate the constructive feedback regarding validation and clarity. In the revised manuscript, we will address these points as follows:

(1) Systematic Validation: We will design and perform systematic in silico experiments to evaluate the method beyond the single in vivo dataset , including robustness tests regarding recording length and network synchrony.

(2) Recurrent Networks & Failure Analysis: We will test our method on synthetic datasets generated from highly recurrent networks and analyze exactly when the method breaks as a function of mismatch magnitude.

(3) Method Comparisons: We will report the Matthews Correlation Coefficient (MCC) for the approach by English et al. (2017) and expand our comparison and discussion of GLM-based methods.

(4) Clarifications: We will rigorously define the dataset details (labeling, recording methodology), mathematical notation, and machine learning terminology ('data', 'labels').

(5) Discussion of Limitations: We will explicitly discuss the challenges and limitations inherent in generalizing to more recurrently connected regions.

Below are our more detailed responses:

Public Reviews:

Reviewer #1 (Public review):

Weaknesses:

(1) The validation of the approach is incomplete: due to its very limited size, the single ground-truth dataset considered does not provide a sufficient basis to draw a strong conclusion. While the authors correctly note that this is the only dataset of its kind, the value of this validation is limited compared to what could be done by carefully designing in silico experiments.

We thank the reviewer for acknowledging the scarcity of suitable in vivo ground-truth datasets and the limitations this poses. We agree that additional validation is necessary to draw strong conclusions. In the revised manuscript, we will systematically design and perform in silico experiments for evaluations beyond the single in vivo dataset.

(2) Surprisingly, the authors fail to compare their method to the approach originally proposed for the data they validate on (English et al., 2017).

We agree that this is an essential comparison. We will report the Matthews Correlation Coefficient (MCC) result of the approach by English et al. (2017) on the spontaneous period of the recording.

(3) The authors make a commendable effort to study the method's robustness by pushing the limits of the dataset. However, the logic of the robustness analysis is often unclear, and once again, the limited size of the dataset poses major limitations to the authors.

We appreciate the reviewer recognizing our initial efforts to evaluate robustness. In our original draft, we tested recording length, network model choices, and analyzed failure cases. However, we agree that the limited real data restricts the scope of these tests. To address this, we will perform more systematic robustness tests on the newly generated synthetic datasets in the revised version, allowing us to evaluate performance under a wider range of conditions.

(4) The lack of details concerning both the approach and the validation makes it challenging for the reader to establish the technical soundness of the study.

We will revise the manuscript thoroughly to better present the methodology of our framework and the validation pipelines. We will ensure that the figures and text clearly articulate the technical details required to assess the soundness of the study.

Although in the current form this study does not provide enough basis to judge the impact of DeepDAM in the broader neuroscience community, it nevertheless puts forward a valuable and novel idea: using domain adaptation to mitigate the problem of model mismatch. This approach might be leveraged in future studies and methods to infer connectivity.

We thank the reviewer again for acknowledging the novelty and importance of our work.

Reviewer #2 (Public review):

While the validation data set was well chosen and of high quality, it remains a single dataset and also remains a non-recurrent network. The authors acknowledge this in the discussion, but I wanted to chime in to say that for the method to be more than convincing, it would need to have been tested on more datasets. It should be acknowledged that the problem becomes more complicated in a recurrent excitatory network, and thus the method may not work as well in the cortex or in CA3.

We will carefully revise our text to specifically discuss this limitation and the challenges inherent in generalizing to more recurrently connected regions. Furthermore, to empirically address this concern, we will test our method extensively on synthetic datasets generated from highly recurrent networks to quantify performance in these regimes.

While the data is shown to work in this particular dataset (plus the two others at the end), I was left wondering when the method breaks. And it should break if the models are sufficiently mismatched. Such a question can be addressed using synthetic-synthetic models. This was an important intuition that I was missing, and an important check on the general nature of the method that I was missing.

We thank the reviewer for this insight regarding the general nature of the method. While we previously analyzed failure cases regarding strong covariation and low spike counts, we agree that a systematic analysis of mismatch magnitude is missing. Building on our planned experiments with synthetic data, we will analyze and discuss exactly when the method breaks as a function of the mismatch magnitude between datasets.

While the choice of state-of-the-art is good in my opinion, I was looking for comments on the methods prior to that. For instance, methods such based on GLMs have been used by the Pillow, Paninski, and Truccolo groups. I could not find a decent discussion of these methods in the main text and thought that both their acknowledgement and rationale for dismissing were missing.

As the reviewer noted, we extensively compared our method with a GLM-based method (GLMCC) and CoNNECT, whose superiority over other GLM-based methods, such as extend GLM method (Ren et al., 2020, J Neurophysiol), have already been demonstrated in their papers (Endo et al., Sci Rep, 2021). However, we acknowledge that the discussion of the broader GLM literature was insufficient. To make the comparison more thorough, we will conduct comparisons with additional GLM-based methods and include a detailed discussion of these approaches.

Endo, D., Kobayashi, R., Bartolo, R., Averbeck, B. B., Sugase-Miyamoto, Y., Hayashi, K., ... & Shinomoto, S. (2021). A convolutional neural network for estimating synaptic connectivity from spike trains. Scientific Reports, 11(1), 12087.

Ren, N., Ito, S., Hafizi, H., Beggs, J. M., & Stevenson, I. H. (2020). Model-based detection of putative synaptic connections from spike recordings with latency and type constraints. Journal of Neurophysiology, 124(6), 1588-1604.

While most of the text was very clear, I thought that page 11 was odd and missing much in terms of introductions. Foremost is the introduction of the dataset, which is never really done. Page 11 refers to 'this dataset', while the previous sentence was saying that having such a dataset would be important and is challenging. The dataset needs to be properly described: what's the method for labeling, what's the brain area, what were the spike recording methodologies, what is meant by two labeling methodologies, what do we know about the idiosyncrasies of the particular network the recording came from (like CA1 is non-recurrent, so which connections)? I was surprised to see 'English et al.' cited in text only on page 13 since their data has been hailed from the beginning.

Further elements that needed definition are the Nsyn and i, which were not defined in the cortex of Equation 2-3: I was not sure if it referred to different samples or different variants of the synthetic model. I also would have preferred having the function f defined earlier, as it is defined for Equation 3, but appears in Equation 2.

When the loss functions are described, it would be important to define 'data' and 'labels' here. This machine learning jargon has a concrete interpretation in this context, and making this concrete would be very important for the readership.

We thank the reviewer for these constructive comments on the writing. We will clarify the introduction of the dataset (labeling method, brain area, recording methodology) and ensure all mathematical terms (such as Nsyn, i, and function f) and machine learning terminology (definitions of 'data' and 'labels' in this context) are rigorously defined upon first use in the revised manuscript.

While I appreciated that there was a section on robustness, I did not find that the features studied were the most important. In this context, I was surprised that the other datasets were relegated to supplementary, as these appeared more relevant.

Robustness is an important aspect of our framework to demonstrate its applicability to real experimental scenarios. We specifically analyzed how synchrony between neurons, the number of recorded spikes and the choice of the network influence the performance of our method. We also agree that these aspects are limited by the one dataset we evaluated on. Therefore, we will test the robustness of our method more systematically on synthetic datasets.

With more extensive analysis on synthetic datasets, we believe that the results on inferring biophysical properties of single neuron and microcircuit models remain in the supplement, such that the main figures focus purely on synaptic connectivity inference.

Some of the figures have text that is too small. In particular, Figure 2 has text that is way too small. It seemed to me that the pseudo code could stand alone, and the screenshot of the equations did not need to be repeated in a figure, especially if their size becomes so small that we can't even read them.

We will remove the pseudo-code and equations from Figure 2 to improve readability. The pseudo-code will be presented as a distinct box in the main text.

why not write the test error as \mathcal{E}(h, \theta) = ... and then say for a fixed $\theta \in \Theta$ instead of burying the dependence on \theta? This is partially addressed in the note but it might make the note more intuitive. Also, \Theta is typically reserved for parameter space and \theta are instantiations of the parameters. Since we are not adopting this convention making we can introduce notation for a fixed \Theta and still incorporate it

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Reply to the reviewers

In our manuscript, we describe a role for the nuclear mRNA export factor UAP56 (a helicase) during metamorphic dendrite and presynapse pruning in flies. We characterize a UAP56 ATPase mutant and find that it rescues the pruning defects of a uap56 mutant. We identify the actin severing enzyme Mical as a potentially crucial UAP56 mRNA target during dendrite pruning and show alterations at both the mRNA and protein level. Finally, loss of UAP56 also causes presynapse pruning defects with actin abnormalities. Indeed, the actin disassembly factor cofilin is required for pruning specifically at the presynapse.

We thank the reviewers for their constructive comments, which we tried to address experimentally as much as possible. To summarize briefly, while all reviewers saw the results as interesting (e. g., Reviewer 3's significance assessment: "Understanding how post-transcriptional events are linked to key functions in neurons is important and would be of interest to a broad audience") and generally methodologically strong, they thought that our conclusions regarding the potential specificity of UAP56 for Mical mRNA was not fully covered by the data. To address this criticism, we added more RNAi analyses of other mRNA export factors and rephrased our conclusions towards a more careful interpretation, i. e., we now state that the pruning process is particularly sensitive to loss of UAP56. In addition, reviewer 1 had technical comments regarding some of our protein and mRNA analyses. We added more explanations and an additional control for the MS2/MCP system. Reviewers 2 and 3 wanted to see a deeper characterization of the ATPase mutant provided. We generated an additional UAP56 mutant transgene, improved our analyses of UAP56 localization, and added a biochemical control experiment. We hope that our revisions make our manuscript suitable for publication.

1. Point-by-point description of the revisions

This section is mandatory. *Please insert a point-by-point reply describing the revisions that were already carried out and included in the transferred manuscript. *

• *

Comments by reviewer 1.

Major comments

1.

For Figure 4, the MS2/MCP system is not quantitative. Using this technique, it is impossible to determine how many RNAs are located in each "dot". Each of these dots looks quite large and likely corresponds to some phase-separated RNP complex where multiple RNAs are stored and/or transported. Thus, these data do not support the conclusion that Mical mRNA levels are reduced upon UAP56 knockdown. A good quantitative microscopic assay would be something like smFISH. Additinally, the localization of Mical mRNA dots to dendrites is not convincing as it looks like regions where there are dendritic swellings, the background is generally brighter.

Our response

We indeed found evidence in the literature that mRNPs labeled with the MS2/MCP or similar systems form condensates (Smith et al., JCB 2015). Unfortunately, smFISH is not established for this developmental stage and would likely be difficult due to the presence of the pupal case. To address whether the Mical mRNPs in control and UAP56 KD neurons are comparable, we characterized the MCP dots in the respective neurons in more detail and found that their sizes did not differ significantly between control and UAP56 KD neurons. To facilitate interpretability, we also increased the individual panel sizes and include larger panels that only show the red (MCP::RFP) channel. We think these changes improved the figure. Thanks for the insight.

Changes introduced: Figure 5 (former Fig. 4): Increased panel size for MCP::RFP images, left out GFP marker for better visibility. Added new analysis of MCP::RFP dot size (new Fig. 5 I).

1.

Alternatively, levels of Mical mRNA could be verified by qPCR in the laval brain following pan-neuronal UAP56 knockdown or in FACS-sorted fluorescently labeled da sensory neurons. Protein levels could be analyzed using a similar approach.

Our response

We thank the reviewer for this comment. Unfortunately, these experiments are not doable as neuron-wide UAP56 KD is lethal (see Flybase entry for UAP56). From our own experience, FACS-sorting of c4da neurons would be extremely difficult as the GFP marker fluorescence intensity of UAP56 KD neurons is weak - this would likely result in preferential sorting of subsets of neurons with weaker RNAi effects. In addition, FACS-sorting whole neurons would not discriminate between nuclear and cytoplasmic mRNA.

The established way of measuring protein content in the Drosophila PNS system is immunofluorescence with strong internal controls. In our case, we also measured Mical fluorescence intensity of neighboring c1da neurons that do not express the RNAi and show expression levels as relative intensities compared to these internal controls. This procedure rules out the influence of staining variation between samples and is used by other labs as well.

1.

In Figure 5, the authors state that Mical expression could not be detected at 0 h APF. The data presented in Fig. 5C, D suggest the opposite as there clearly is some expression. Moreover, the data shown in Fig. 5D looks significantly brighter than the Orco dsRNA control and appears to localize to some type of cytoplasmic granule. So the expression of Mical does not look normal.

Our response

We thank the reviewer for this comment. In the original image in Fig. 5 C, the c4da neuron overlaps with the dendrite from a neighboring PNS neuron (likely c2da or c3da). The latter neuron shows strong Mical staining. We agree that this image is confusing and exchanged this image for another one from the same genotype.

Changes introduced: Figure 5 L (former Fig. 5 C): Exchanged panel for image without overlap from other neuron.

1.

Sufficient data are not presented to conclude any specificity in mRNA export pathways. Data is presented for one export protein (UAP56) and one putative target (Mical). To adequately assess this, the authors would need to do RNA-seq in UAP56 mutants.

Our response

We thank the reviewer for this comment. To address this, we tested whether knockdown of three other mRNA export factors (NXF1, THO2, THOC5) causes dendrite pruning defects, which was not the case (new Fig. S1). While these data are consistent with specific mRNA export pathways, we agree that they are not proof. We therefore toned down our interpretation and removed the conclusion about specificity. Instead, we now use the more neutral term "increased sensibility (to loss of UAP56)".

Changes introduced: Added new Figure S1: RNAi analyses of NXF1, THO2 and THOC5 in dendrite pruning. Introduced concluding sentence at the end of first Results paragraph: We conclude that c4da neuron dendrite pruning is particularly sensitive to loss of UAP56. (p. 6)

1.

In summary, better quantitative assays should be used in Figures 4 and 5 in order to conclude the expression levels of either mRNA or protein. In its current form, this study demonstrates the novel finding that UAP56 regulates dendrite and presynaptic pruning, potentially via regulation of the actin cytoskeleton. However, these data do not convincingly demonstrate that UAP56 controls these processes by regulating of Mical expression and defintately not by controlling export from the nucleus.

Our response

We hope that the changes we introduced above help clarify this.

1.

While there are clearly dendrites shown in Fig. 1C', the cell body is not readily identifiable. This makes it difficult to assess attachment and suggests that the neuron may be dying. This should be replaced with an image that shows the soma.

Our response

We thank the reviewer for this comment. Changes introduced: we replaced the picture in the panel with one where the cell body is more clearly visible.

1.

The level of knockdown in the UAS56 RNAi and P element insertion lines should be determined. It would be useful to mention the nature of the RNAi lines (long/short hairpin). Some must be long since Dcr has been co-expressed. Another issue raised by this is the potential for off-target effects. shRNAi lines would be preferable because these effects are minimized.

Our response

We thank the reviewer for this comment. Assessment of knockdown efficiency is a control to make sure the manipulations work the way they are intended to. As mRNA isolation from Drosophila PNS neurons is extremely difficult, RNAi or mutant phenotypes in this system are controlled by performing several independent manipulations of the same gene. In our case, we used two independent RNAi lines (both long hairpins from VDRC/Bloomington and an additional insertion of the VDRC line, see Table S1) as well as a mutant P element in a MARCM experiment, i. e., a total of three independent manipulations that all cause pruning defects, and the VDRC RNAi lines do not have any predicted OFF targets (not known for the Bloomington line). If any of these manipulations would not have matched, we would have generated sgRNA lines for CRISPR to confirm.

Minor comments:

1.

The authors should explain what EB1:GFP is marking when introduced in the text.

Our response

We thank the reviewer for this comment. Changes introduced: we explain the EB1::GFP assay in the panel with one where the cell body is more clearly visible.

1.

The da neuron images throughout the figures could be a bit larger.

Our response

We thank the reviewer for this comment. Changes introduced: we changed the figure organization to be able to use larger panels:

• the pruning analysis of the ATPase mutations (formerly Fig. 2) is now its own figure (Figure 3).

• we increased the panel sizes of the MCP::RFP images (Figure 5 A - I, formerly Fig. 4).

Reviewer #1 (Significance (Required)):

Strengths:

The methodology used to assess dendrite and presynaptic prunings are strong and the phenotypic analysis is conclusive.

Our response

We thank the reviewer for this comment.

Weakness:

The evidence demonstrating that UAP56 regulates the expression of Mical is unconvincing. Similarly, no data is presented to show that there is any specificity in mRNA export pathways. Thus, these major conclusions are not adequately supported by the data.

Our response

We hope the introduced changes address this comment.

__Reviewer #2 (Evidence, reproducibility and clarity (Required)): __

In this paper, the authors describe dendrite pruning defects in c4da neurons in the DEXD box ATPase UAP56 mutant or in neuronal RNAi knockdown. Overexpression UAP56::GFP or UAP56::GFPE194Q without ATPase activity can rescue dendrite pruning defects in UAP56 mutant. They further characterized the mis-localization of UAP56::GFPE194Q and its binding to nuclear export complexes. Both microtubules and the Ubiquitin-proteasome system are intact in UAP56RNAi neurons. However, they suggest a specific effect on MICAL mRNA nuclear export shown by using the MS2-MCP system., resulting in delay of MICAL protein expression in pruned neurons. Furthermore, the authors show that UAP56 is also involved in presynaptic pruning of c4da neuros in VNC and Mica and actin are also required for actin disassembly in presynapses. They propose that UAP56 is required for dendrite and synapse pruning through actin regulation in Drosophila. Following are my comments.

Major comments

1.

The result that UAP56::GFPE194Q rescues the mutant phenotype while the protein is largely mis-localized suggests a novel mechanism or as the authors suggested rescue from combination of residual activities. The latter possibility requires further support, which is important to support the role mRNA export in dendrite and pre-synapse pruning. One approach would be to examine whether other export components like REF1, and NXF1 show similar mutant phenotypes. Alternatively, depleting residual activity like using null mutant alleles or combining more copies of RNAi transgenes could help.

Our response

We thank the reviewer for this comment. We agree that the mislocalization phenotype is interesting and could inform further studies on the mechanism of UAP56. To further investigate this and to exclude that this could represent a gain-of-function due to the introduced mutation, we made and characterized a new additional transgene, UAP56::GFP E194A. This mutant shows largely the same phenotypes as E194Q, with enhanced interactions with Ref1 and partial mislocalization to the cytoplasm. In addition, we tested whether knockdown of THO2, THOC5 or NXF1 causes pruning defects (no).

Changes introduced:

• added new Figure S1: RNAi analyses of NXF1, THO2 and THOC5 in dendrite pruning.

• made and characterized a new transgene UAP56 E194A (new Fig. 2 B, E, E', 3 C, C', E, F).

1.

The localization of UAP56::GFP (and E194Q) should be analyzed in more details. It is not clear whether the images in Fig. 2A and 2B are from confocal single sections or merged multiple sections. The localization to the nuclear periphery of UAP56::GFP is not clear, and the existence of the E194Q derivative in both nucleus and cytosol (or whether there is still some peripheral enrichment) is not clear if the images are stacked.

Our response

We thank the reviewer for this comment. It is correct that the profiles in the old Figure 2 were from single confocal sections from the displayed images. As it was difficult to create good average profiles with data from multiple neurons, we now introduce an alternative quantification based on categories (nuclear versus dispersed) which includes data from several neurons for each genotype, including the new E194A transgene (new Fig 3 G). Upon further inspection, the increase at the nuclear periphery was not always visible and may have been a misinterpretation. We therefore removed this statement.

Changes introduced:

• added new quantitative analysis of UAP56 wt and E/A, E/Q mutant localization (new Fig 3 G).

1.

The Ub-VV-GFP is a new reagent, and its use to detect active proteasomal degradation is by the lack of GFP signals, which could be also due to the lack of expression. The use of Ub-QQ-GFP cannot confirm the expression of Ub-VV-GFP. The proteasomal subunit RPN7 has been shown to be a prominent component in the dendrite pruning pathway (Development 149, dev200536). Immunostaining using RPN7 antibodies to measure the RPN expression level could be a direct way to address the issue whether the proteasomal pathway is affected or not.

Our response

We thank the reviewer for this comment. We agree that it is wise to not only introduce a positive control for the Ub-VV-GFP sensor (the VCP dominant-negative VCP QQ), but also an independent control. As mutants with defects in proteasomal degradation accumulate ubiquitinated proteins (see, e. g., Rumpf et al., Development 2011), we stained controls and UAP56 KD neurons with antibodies against ubiquitin and found that they had similar levels (new Fig. S3).

Changes introduced:

• added new ubiquitin immunofluorescence analysis (new Fig. S3).

1.

Using the MS2/MCP system to detect the export of MICAL mRNA is a nice approach to confirm the UAP56 activity; lack of UAP56 by RNAi knockdown delays the nuclear export of MS2-MICAL mRNA. The rescue experiment by UAS transgenes could not be performed due to the UAS gene dosage, as suggested by the authors. However, this MS2-MICAL system is also a good assay for the requirement of UAP56 ATPase activity (absence in the E194Q mutant) in this process. Could authors use the MARCM (thus reduce the use of UAS-RNAi transgene) for the rescue experiment? Also, the c4da neuronal marker UAS-CD8-GFP used in Fig4 could be replaced by marker gene directly fused to ppk promoter, which can save a copy of UAS transgene. The results from the rescue experiment would test the dependence of ATPase activity in nuclear export of MICAL mRNA.

Our response

We thank the reviewer for this comment. This is a great idea but unfortunately, this experiment was not feasible due to the (rare) constraints of Drosophila genetics. The MARCM system with rescue already occupies all available chromosomes (X: FLPase, 2nd: FRT, GAL80 + mutant, 3rd: GAL4 + rescue construct), and we would have needed to introduce three additional ones (MCP::RFP and two copies of unmarked genomic MICAL-MS2, all on the third chromosome) that would have needed to be introduced by recombination. Any Drosophilist will see that this is an extreme, likely undoable project :-(

1.

The UAP56 is also involved in presynaptic pruning through regulating actin assembly, and the authors suggest that Mical and cofilin are involved in the process. However, direct observation of lifeact::GFP in Mical or cofilin RNAi knockdown is important to support this conclusion.

Our response

We thank the reviewer for this comment. In response, we analyzed the lifeact::GFP patterns of control and cofilin knockdown neurons and found that loss of cofilin also leads to actin accumulation (new Fig. 7 I, J).

Changes introduced:

• new lifeact analysis (new Fig. 7 I, J).

Minor comments:

1.

RNA localization is important for dendrite development in larval stages (Brechbiel JL, Gavis ER. Curr Biol. 20;18(10):745-750). Yet, the role of UAP56 is relatively specific and shown only in later-stage pruning. It would need thorough discussion.

Our response

We thank reviewer 2 for this comment. We added the following paragraph to the discussion: "UAP56 has also been shown to affect cytoplasmic mRNA localization in Drosophila oocytes (Meignin and Davis, 2008), opening up the possibility that nuclear mRNA export and cytoplasmic transport are linked. It remains to be seen whether this also applies to dendritic mRNA transport (Brechbiel and Gavis, 2008)." (p.13)

1.

Could authors elaborate on the possible upstream regulators that might be involved, as described in "alternatively, several cofilin upstream regulators have been described (Rust, 2015) which might also be involved in presynapse pruning and subject to UAP56 regulation" in Discussion?

Our response

We thank reviewer 2 for this comment. In the corresponding paragraph, we cite as example now that cofilin is regulated by Slingshot phosphatases and LIM kinase (p.14).

1.

In Discussion, the role of cofilin in pre- and post-synaptic processes was described. The role of Tsr/Cofilin regulating actin behaviors in dendrite branching has been described in c3da and c4da neurons (Nithianandam and Chien, 2018 and other references) should be included in Discussion.

Our response

We thank reviewer 2 for this comment. In response we tested whether cofilin is required for dendrite pruning and found that this, in contrast to Mical, is not the case (new Fig. S6). We cite the above paper in the corresponding results section (p.12).

Changes introduced:

• new cofilin dendrite pruning analysis (new Fig. S6).

• added cofilin reference in Results.

1.

The authors speculate distinct actin structures have to be disassembled in dendrite and presynapse pruning in Discussion. What are the possible actin structures in both sites could be elaborated.

Our response

We thank reviewer 2 for this comment. In response, we specify in the Discussion: "As Mical is more effective in disassembling bundled F-actin than cofilin (Rajan et al., 2023), it is interesting to speculate that such bundles are more prevalent in dendrites than at presynapses." (p14)

Reviewer #2 (Significance (Required)):

The study initiated a genetic screen for factors involved in a dendrite pruning system and reveals the involvement of nuclear mRNA export is an important event in this process. They further identified the mRNA of the actin disassembly factor MICAL is a candidate substrate in the exporting process. This is consistent with previous finding that MICAL has to be transcribed and translated when pruning is initiated. As the presynapses of the model c4da neuron in this study is also pruned, the dependence on nuclear export and local actin remodeling were also shown. Thus, this study has added another layer of regulation (the nuclear mRNA export) in c4da neuronal pruning, which would be important for the audience interested in neuronal pruning. The study is limited for the confusing result whether ATPase activity of the exporting factor is required.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

Summary: In the manuscript by Frommeyer, Gigengack et al. entitled "The UAP56 mRNA Export Factor is Required for Dendrite and Synapse Pruning via Actin Regulation in Drosophila" the authors surveyed a number of RNA export/processing factors to identify any required for efficient dendrite and/or synapse pruning. They describe a requirement for a general poly(A) RNA export factor, UAP56, which functions as an RNA helicase. They also study links to aspects of actin regulation.

Overall, while the results are interesting and the impact of loss of UAP56 on the pruning is intriguing, some of the data are overinterpreted as presented. The argument that UAP56 may be specific for the MICAL RNA is not sufficiently supported by the data presented. The two stories about poly(A) RNA export/processing and the actin regulation seem to not quite be connected by the data presented. The events are rather distal within the cell, making connecting the nuclear events with RNA to events at the dendrites/synapse challenging.

Our response

We thank reviewer 3 for this comment. To address this, we tested whether knockdown of three other mRNA export factors (NXF1, THO2, THOC5) causes dendrite pruning defects, which was not the case (new Fig. S1). While these data are consistent with specific mRNA export pathways, we agree that they are not proof. We therefore toned down our interpretation and removed the conclusion about specificity. Instead, we now use the more neutral term "increased sensibility (to loss of UAP56)".

We agree that it is a little hard to tie cofilin to UAP56, as we currently have no evidence that cofilin levels are affected by loss of UAP56, even though both seem to affect lifeact::GFP in a similar way (new Fig. 7 I, J). However, a dysregulation of cofilin can also occur through dysregulation of upstream cofilin regulators such as Slingshot and LIM kinase, making such a relationship possible.

Changes introduced:

• added new Figure S1: RNAi analyses of NXF1, THO2 and THOC5 in dendrite pruning.

• introduced concluding sentence at the end of first Results paragraph: "We conclude that c4da neuron dendrite pruning is particularly sensitive to loss of UAP56." (p. 6)

• add new lifeact::GFP analysis of cofilin KD (new Fig. I, J).

• identify potential other targets from the literature in the Discussion (Slingshot phosphatases and LIM kinase, p.14).

There are a number of specific statements that are not supported by references. See, for example, these sentences within the Introduction- "Dysregulation of pruning pathways has been linked to various neurological disorders such as autism spectrum disorders and schizophrenia. The cell biological mechanisms underlying pruning can be studied in Drosophila." The Drosophila sentence is followed by some specific examples that do include references. The authors also provide no reference to support the variant that they create in UAP56 (E194Q) and whether this is a previously characterized fly variant or based on an orthologous protein in a different system. If so, has the surprising mis-localization been reported in another system?

Our response

We thank reviewer 3 for this comment. We added the following references on pruning and disease:

1) Howes, O.D., Onwordi, E.C., 2023. The synaptic hypothesis of schizophrenia version III: a master mechanism. Mol. Psychiatry 28, 1843-1856.

2) Tang, G., et al., 2014. Loss of mTOR-dependent macroautophagy causes autistic-like synaptic pruning deficits. Neuron 83, 1131-43.

To better introduce the E194 mutations, we explain the position of the DECD motif in the Walker B domain, give the corresponding residues in the human and yeast homologues and cite papers demonstrating the importance of this residue for ATPase activity:

3) Saguez, C., et al., 2013. Mutational analysis of the yeast RNA helicase Sub2p reveals conserved domains required for growth, mRNA export, and genomic stability. RNA 19:1363-71.

4) Shen, J., et al., 2007. Biochemical Characterization of the ATPase and Helicase Activity of UAP56, an Essential Pre-mRNA Splicing and mRNA Export Factor. J. Biol. Chem. 282, P22544-22550.

We are not aware of other studies looking at the relationship between the UAP56 ATPase and its localization. Thank you for pointing this out!

Specific Comments:

Specific Comment 1: Figure 1 shows the impact of loss of UAP56 on neuron dendrite pruning. The experiment employs both two distinct dsRNAs and a MARCM clone, providing confidence that there is a defect in pruning upon loss of UAP56. As the authors mention screening against 92 genes that caused splicing defects in S2 cells, inclusion of some examples of these genes that do not show such a defect would enhance the argument for specificity with regard to the role of UAP56. This control would be in addition to the more technical control that is shown, the mCherry dsRNA.

Our response

We thank reviewer 3 for this comment. To address this, we included the full list of screened genes with their phenotypic categorization regarding pruning (103 RNAi lines targeting 64 genes) as Table S1. In addition, we also tested four RNAi lines targeting the nuclear mRNA export factors Nxf1, THO2 and THOC5 which do not cause dendrite pruning defects (Fig. S1).

Changes introduced:

• added RNAi screen results as a list in Table S1.

• added new Figure S1: RNAi analyses of NXF1, THO2 and THOC5 in dendrite pruning.

Specific Comment 2: Later the authors demonstrate a delay in the accumulation of the Mical protein, so if they assayed these pruning events at later times, would the loss of UAP56 cause a delay in these events as well? Such a correlation would enhance the causality argument the authors make for Mical levels and these pruning events.

Our response

We thank reviewer 3 for this comment. Unfortunately, this is somewhat difficult to assess, as shortly after the 18 h APF timepoint, the epidermal cells that form the attachment substrate for c4da neuron dendrites undergo apoptosis. Where assessed (e. g., Wang et al., 2017, Development) 144: 1851–1862), this process, together with the reduced GAL4 activity of our ppk-GAL4 during the pupal stage (our own observations), eventually leads to pruning, but the causality cannot be easily attributed anymore. We therefore use the 18 h APF timepoint essentially as an endpoint assay.

Specific Comment 3: Figure 2 provides data designed to test the requirement for the ATPase/helicase activity of UAP56 for these trimming events. The first observation, which is surprising, is the mislocalization of the variant (E194Q) that the authors generate. The data shown does not seem to indicate how many cells the results shown represent as a single image and trace is shown the UAP56::GFP wildtype control and the E194Q variant.

Our response

We thank reviewer 3 for this comment. It is correct that the traces shown are from single confocal sections. To better display the phenotypic penetrance, we now added a categorical analysis that shows that the UAP56 E194Q mutant is completely mislocalized in the majority of cells assessed (and the newly added E194A mutant in a subset of cells).

Changes introduced:

• added categorical quantification of UAP56 variant localization (new Fig. 2 G).

__Specific Comment 4: __Given the rather surprising finding that the ATPase activity is not required for the function of UAP56 characterized here, the authors do not provide sufficient references or rationale to support the ATPase mutant that they generate. The E194Q likely lies in the Walker B motif and is equivalent to human E218Q, which can prevent proper ATP hydrolysis in the yeast Sub2 protein. There is no reference to support the nature of the variant created here.

Our response

We thank reviewer 3 for this comment. To better introduce the E194 mutations, we explain the position of the DECD motif in the Walker B domain, give the corresponding residues in the human and yeast homologues (Sub2) and cite papers demonstrating the importance of this residue for ATPase activity:

1) Saguez, C., et al., 2013. Mutational analysis of the yeast RNA helicase Sub2p reveals conserved domains required for growth, mRNA export, and genomic stability. RNA 19:1363-71.

2) Shen, J., et al., 2007. Biochemical Characterization of the ATPase and Helicase Activity of UAP56, an Essential Pre-mRNA Splicing and mRNA Export Factor. J. Biol. Chem. 282, P22544-22550.

__Specific Comment 5: __Given the surprising results, the authors could have included additional variants to ensure the change has the biochemical effect that the authors claim. Previous studies have defined missense mutations in the ATP-binding site- K129A (Lysine to Alanine): This mutation, in both yeast Sub2 and human UAP56, targets a conserved lysine residue that is critical for ATP binding. This prevents proper ATP binding and consequently impairs helicase function. There are also missense mutations in the DEAD-box motif, (Asp-Glu-Ala-Asp) involved in ATP binding and hydrolysis. Mutations in this motif, such as D287A in yeast Sub2 (corresponding to D290A in human UAP56), can severely disrupt ATP hydrolysis, impairing helicase activity. In addition, mutations in the Walker A (GXXXXGKT) and Walker B motifs are can impair ATP binding and hydrolysis in DEAD-box helicases. Missense mutations in these motifs, like G137A (in the Walker A motif), can block ATP binding, while E218Q (in the Walker B motif)- which seems to be the basis for the variant employed here- can prevent proper ATP hydrolysis.

Our response

We thank reviewer 3 for this comment. Our cursory survey of the literature suggested that mutations in the Walker B motif are the most specific as they still preserve ATP binding and their effects have not well been characterized overall. In addition, these mutations can create strong dominant-negatives in related helicases (e. g., Rode et al., 2018 Cell Reports, our lab). To better characterize the role of the Walker B motif in UAP56, we generated and characterized an alternative mutant, UAP56 E194A. While the E194A variant does not show the same penetrance of localization phenotypes as E194Q, it also is partially mislocalized, shows stronger binding to Ref1 and also rescues the uap56 mutant phenotypes without an obvious dominant-negative effect, thus confirming our conclusions regarding E194Q.

Changes introduced:

• added biochemical, localization and phenotypic analysis of newly generated UAP56 E194A variant (new Figs. 2 B, 2 E, E', 3 C, C'). categorical quantification of UAP56 variant localization (new Fig. 2 G).

__Specific Comment 6: __The co-IP results shown in Figure 2C would also seem to have multiple potential interpretations beyond what the authors suggest, an inability to disassemble a complex. The change in protein localization with the E194Q variant could impact the interacting proteins. There is no negative control to show that the UAP56-E194Q variant is not just associated with many, many proteins. Another myc-tagged protein that does not interact would be an ideal control.

Our response

We thank reviewer 3 for this comment. To address this comment, we tried to co-IP UAP56 wt or UAP56 E194Q with a THO complex subunit THOC7 (new Fig. S2). The results show that neither UAP56 variant can co-IP THOC7 under our conditions (likely because the UAP56/THO complex intermediate during mRNA export is disassembled in an ATPase-independent manner (Hohmann et al., Nature 2025)).

Changes introduced:

• added co-IP experiment between UAP56 variants and THOC7 (new Fig. S2).

__Specific Comment 7: __With regard to Figure 3, the authors never define EB1::GFP in the text of the Results, so a reader unfamiliar with this system has no idea what they are seeing. Reading the Materials and Methods does not mitigate this concern as there is only a brief reference to a fly line and how the EB1::GFP is visualized by microscopy. This makes interpretation of the data presented in Figure 3A-C very challenging.

Our response

We thank reviewer 3 for pointing this out. We added a description of the EB1::GFP analysis in the corresponding Results section (p.8).

__Specific Comment 8: __The data shown for MICAL MS2 reporter localization in Figure 4 is nice, but is also fully expected on many former studies analyzing loss of UAP56 or UAP56 hypomorphs in different systems. While creating the reporter is admirable, to make the argument that MICAL localization is in some way preferentially impacted by loss of UAP56, the authors would need to examine several other transcripts. As presented, the authors can merely state that UAP56 seems to be required for the efficient export of an mRNA transcript, which is predicted based on dozens of previous studies dating back to the early 2000s.

Our response

Firstly, thank you for commenting on the validity of the experimental approach! The primary purpose of this experiment was to test whether the mechanism of UAP56 during dendrite pruning conforms with what is known about UAP56's cellular role - which it apparently does. We also noted that our statements regarding the specificity of UAP56 for Mical over other transcripts are difficult. While our experiments would be consistent with such a model, they do not prove it. We therefore toned down the corresponding statements (e. g., the concluding sentence at the end of first Results paragraphis now: "We conclude that c4da neuron dendrite pruning is particularly sensitive to loss of UAP56." (p. 6)).

Minor (and really minor) points:

In the second sentence of the Discussion, the word 'developing' seems to be mis-typed "While a general inhibition of mRNA export might be expected to cause broad defects in cellular processes, our data in develoing c4da neurons indicate that loss of UAP56 mainly affects pruning mechanisms related to actin remodeling."

Sentence in the Results (lack of page numbers makes indicating where exactly a bit tricky)- "We therefore reasoned that Mical expression could be more challenging to c4da neurons." This is a complete sentence as presented, yet, if something is 'more something'- the thing must be 'more than' something else. Presumably, the authors mean that the length of the MICAL transcript could make the processing and export of this transcript more challenging than typical fly transcripts (raising the question of the average length of a mature transcript in flies?).

Our response

Thanks for pointing these out. The typo is fixed, page numbers are added. We changed the sentence to: "Because of the large size of its mRNA, we reasoned that MICAL gene expression could be particularly sensitive to loss of export factors such as UAP56." (p.9) We hope this is more precise language-wise.

Reviewer #3 (Significance (Required)):

Understanding how post-transcriptional events are linked to key functions in neurons is important and would be of interest to a broad audience.

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

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Referee #3

Evidence, reproducibility and clarity

Summary:

In the manuscript by Frommeyer, Gigengack et al. entitled "The UAP56 mRNA Export Factor is Required for Dendrite and Synapse Pruning via Actin Regulation in Drosophila" the authors surveyed a number of RNA export/processing factors to identify any required for efficient dendrite and/or synapse pruning. They describe a requirement for a general poly(A) RNA export factor, UAP56, which functions as an RNA helicase. They also study links to aspects of actin regulation.

Overall, while the results are interesting and the impact of loss of UAP56 on the pruning is intriguing, some of the data are overinterpreted as presented. The argument that UAP56 may be specific for the MICAL RNA is not sufficiently supported by the data presented. The two stories about poly(A) RNA export/processing and the actin regulation seem to not quite be connected by the data presented. The events are rather distal within the cell, making connecting the nuclear events with RNA to events at the dendrites/synapse challenging.

There are a number of specific statements that are not supported by references. See, for example, these sentences within the Introduction- "Dysregulation of pruning pathways has been linked to various neurological disorders such as autism spectrum disorders and schizophrenia. The cell biological mechanisms underlying pruning can be studied in Drosophila." The Drosophila sentence is followed by some specific examples that do include references. The authors also provide no reference to support the variant that they create in UAP56 (E194Q) and whether this is a previously characterized fly variant or based on an orthologous protein in a different system. If so, has the surprising mis-localization been reported in another system?

Specific Comments:

Figure 1 shows the impact of loss of UAP56 on neuron dendrite pruning. The experiment employs both two distinct dsRNAs and a MARCM clone, providing confidence that there is a defect in pruning upon loss of UAP56. As the authors mention screening against 92 genes that caused splicing defects in S2 cells, inclusion of some examples of these genes that do not show such a defect would enhance the argument for specificity with regard to the role of UAP56. This control would be in addition to the more technical control that is shown, the mCherry dsRNA. Later the authors demonstrate a delay in the accumulation of the Mical protein, so if they assayed these pruning events at later times, would the loss of UAP56 cause a delay in these events as well? Such a correlation would enhance the causality argument the authors make for Mical levels and these pruning events.

Figure 2 provides data designed to test the requirement for the ATPase/helicase activity of UAP56 for these trimming events. The first observation, which is surprising, is the mislocalization of the variant (E194Q) that the authors generate. The data shown does not seem to indicate how many cells the results shown represent as a single image and trace is shown the UAP56::GFP wildtype control and the E194Q variant.

Given the rather surprising finding that the ATPase activity is not required for the function of UAP56 characterized here, the authors do not provide sufficient references or rationale to support the ATPase mutant that they generate. The E194Q likely lies in the Walker B motif and is equivalent to human E218Q, which can prevent proper ATP hydrolysis in the yeast Sub2 protein. There is no reference to support the nature of the variant created here.

Given the surprising results, the authors could have included additional variants to ensure the change has the biochemical effect that the authors claim. Previous studies have defined missense mutations in the ATP-binding site- K129A (Lysine to Alanine): This mutation, in both yeast Sub2 and human UAP56, targets a conserved lysine residue that is critical for ATP binding. This prevents proper ATP binding and consequently impairs helicase function. There are also missense mutations in the DEAD-box motif, (Asp-Glu-Ala-Asp) involved in ATP binding and hydrolysis. Mutations in this motif, such as D287A in yeast Sub2 (corresponding to D290A in human UAP56), can severely disrupt ATP hydrolysis, impairing helicase activity. In addition, mutations in the Walker A (GXXXXGKT) and Walker B motifs are can impair ATP binding and hydrolysis in DEAD-box helicases. Missense mutations in these motifs, like G137A (in the Walker A motif), can block ATP binding, while E218Q (in the Walker B motif)- which seems to be the basis for the variant employed here- can prevent proper ATP hydrolysis.

The co-IP results shown in Figure 2C would also seem to have multiple potential interpretations beyond what the authors suggest, an inability to disassemble a complex. The change in protein localization with the E194Q variant could impact the interacting proteins. There is no negative control to show that the UAP56-E194Q variant is not just associated with many, many proteins. Another myc-tagged protein that does not interact would be an ideal control.

With regard to Figure 3, the authors never define EB1::GFP in the text of the Results, so a reader unfamiliar with this system has no idea what they are seeing. Reading the Materials and Methods does not mitigate this concern as there is only a brief reference to a fly line and how the EB1::GFP is visualized by microscopy. This makes interpretation of the data presented in Figure 3A-C very challenging. The data shown for MICAL MS2 reporter localization in Figure 4 is nice, but is also fully expected on many former studies analyzing loss of UAP56 or UAP56 hypomorphs in different systems. While creating the reporter is admirable, to make the argument that MICAL localization is in some way preferentially impacted by loss of UAP56, the authors would need to examine several other transcripts. As presented, the authors can merely state that UAP56 seems to be required for the efficient export of an mRNA transcript, which is predicted based on dozens of previous studies dating back to the early 2000s.

Minor (and really minor) points:

In the second sentence of the Discussion, the word 'developing' seems to be mis-typed "While a general inhibition of mRNA export might be expected to cause broad defects in cellular processes, our data in develoing c4da neurons indicate that loss of UAP56 mainly affects pruning mechanisms related to actin remodeling."

Sentence in the Results (lack of page numbers makes indicating where exactly a bit tricky)- "We therefore reasoned that Mical expression could be more challenging to c4da neurons." This is a complete sentence as presented, yet, if something is 'more something'- the thing must be 'more than' something else. Presumably, the authors mean that the length of the MICAL transcript could make the processing and export of this transcript more challenging than typical fly transcripts (raising the question of the average length of a mature transcript in flies?).

Significance

Understanding how post-transcriptional events are linked to key functions in neurons is important and would be of interest to a broad audience.

Why do people who should be in-the-know make this mistake? This is one of the weirder variations—usually it's people thinking that Chrome is based on WebKit.

In this instance, they seem to be aware that Chrome isn't using WebKit, but do think that Safari is using "Chromium" (which is neither WebKit, nor Blink, i.e. the browser engine that Chrome is using—Chromium is an open source browser, not a browser engine…).

Reviewer #1 (Public review):

Summary:

The study of Drosophila mating behaviors has offered a powerful entry point for understanding how complex innate behaviors are instantiated in the brain. The effectiveness of this behavioral model stems from how readily quantifiable many components of the courtship ritual are, facilitating the fine-scale correlations between the behaviors and the circuits that underpin their implementation. Detailed quantification, however, can be both time-consuming and error-prone, particularly when scored manually. Song et al. have sought to address this challenge by developing DrosoMating, software that facilitates the automated and high-throughput quantification of 6 common metrics of courtship and mating behaviors. Compared to a human observer, DrosoMating matches courtship scoring with high fidelity. Further, the authors demonstrate that the software effectively detects previously described variations in courtship resulting from genetic background or social conditioning. Finally, they validate its utility in assaying the consequences of neural manipulations by silencing Kenyon cells involved in memory formation in the context of courtship conditioning.

Strengths:

(1) The authors demonstrate that for three key courtship/mating metrics, DrosoMating performs virtually indistinguishably from a human observer, with differences consistently within 10 seconds and no statistically significant differences detected. This demonstrates the software's usefulness as a tool for reducing bias and scoring time for analyses involving these metrics.

(2) The authors validate the tool across multiple genetic backgrounds and experimental manipulations to confirm its ability to detect known influences on male mating behavior.

(3) The authors present a simple, modular chamber design that is integrated with DrosoMating and allows for high-throughput experimentation, capable of simultaneously analyzing up to 144 fly pairs across all chambers.

Weaknesses:

(1) DrosoMating appears to be an effective tool for the high-throughput quantification of key courtship and mating metrics, but a number of similar tools for automated analysis already exist. FlyTracker (CalTech), for instance, is a widely used software that offers a similar machine vision approach to quantifying a variety of courtship metrics. It would be valuable to understand how DrosoMating compares to such approaches and what specific advantages it might offer in terms of accuracy, ease of use, and sensitivity to experimental conditions.

(2) The courtship behaviors of Drosophila males represent a series of complex behaviors that unfold dynamically in response to female signals (Coen et al., 2014; Ning et al., 2022; Roemschied et al., 2023). While metrics like courtship latency, courtship index, and copulation duration are useful summary statistics, they compress the complexity of actions that occur throughout the mating ritual. The manuscript would be strengthened by a discussion of the potential for DrosoMating to capture more of the moment-to-moment behaviors that constitute courtship. Even without modifying the software, it would be useful to see how the data can be used in combination with machine learning classifiers like JAABA to better segment the behavioral composition of courtship and mating across genotypes and experimental manipulations. Such integration could substantially expand the utility of this tool for the broader Drosophila neuroscience community.

(3) While testing the software's capacity to function across strains is useful, it does not address the "universality" of this method. Cross-species studies of mating behavior diversity are becoming increasingly common, and it would be beneficial to know if this tool can maintain its accuracy in Drosophila species with a greater range of morphological and behavioral variation. Demonstrating the software's performance across species would strengthen claims about its broader applicability.

Author response:

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

Public Reviews:

Reviewer #1 (Public review):

Summary:

This fundamental study identifies a new mechanism that involves a mycobacterial nucleomodulin manipulation of the host histone methyltransferase COMPASS complex to promote infection. Although other intracellular pathogens are known to manipulate histone methylation, this is the first report demonstrating the specific targeting of the COMPASS complex by a pathogen. The rigorous experimental design using state-of-the art bioinformatic analysis, protein modeling, molecular and cellular interaction, and functional approaches, culminating with in vivo infection modeling, provides convincing, unequivocal evidence that supports the authors' claims. This work will be of particular interest to cellular microbiologists working on microbial virulence mechanisms and effectors, specifically nucleomodulins, and cell/cancer biologists that examine COMPASS dysfunction in cancer biology.

Strengths:

(1) The strengths of this study include the rigorous and comprehensive experimental design that involved numerous state-of-the-art approaches to identify potential nucleomodulins, define molecular nucleomodulin-host interactions, cellular nucleomodulin localization, intracellular survival, and inflammatory gene transcriptional responses, and confirmation of the inflammatory and infection phenotype in a small animal model.

(2) The use of bioinformatic, cellular, and in vivo modeling that are consistent and support the overall conclusions is a strength of the study. In addition, the rigorous experimental design and data analysis, including the supplemental data provided, further strengthen the evidence supporting the conclusions.

Weaknesses:

(1) This work could be stronger if the MgdE-COMPASS subunit interactions that negatively impact COMPASS complex function were better defined. Since the COMPASS complex consists of many enzymes, examining the functional impact on each of the components would be interesting.

We thank the reviewer for this insightful comment. A biochemistry assays could be helpful to interpret the functional impact on each of the components by MgdE interaction. However, the purification of the COMPASS complex could be a hard task itself due to the complexity of the full COMPASS complex along with its dynamic structural properties and limited solubility.

(2) Examining the impact of WDR5 inhibitors on histone methylation, gene transcription, and mycobacterial infection could provide additional rigor and provide useful information related to the mechanisms and specific role of WDR5 inhibition on mycobacterial infection.

We thank the reviewer for the comment. A previous study showed that WIN-site inhibitors, such as compound C6, can displace WDR5 from chromatin, leading to a reduction in global H3K4me3 levels and suppression of immune-related gene expression (Hung et al., Nucleic Acids Res, 2018; Bryan et al., Nucleic Acids Res, 2020). These results closely mirror the functional effects we observed for MgdE, suggesting that MgdE may act as a functional mimic of WDR5 inhibition. This supports our proposed model in which MgdE disrupts COMPASS activity by targeting WDR5, thereby dampening host pro-inflammatory responses.

(3) The interaction between MgdE and COMPASS complex subunit ASH2L is relatively undefined, and studies to understand the relationship between WDR5 and ASH2L in COMPASS complex function during infection could provide interesting molecular details that are undefined in this study.

We thank the reviewer for the comment. In this study, we constructed single and multiple point mutants of MgdE at residues S⁸⁰, D²⁴⁴, and H²⁴⁷ to identify key amino acids involved in its interaction with ASH2L (Figure 5A and B; New Figure S4C). However, these mutations did not interrupt the interaction with MgdE, suggesting that more residues are involved in the interaction.

ASH2L and WDR5 function cooperatively within the WRAD module to stabilize the SET domain and promote H3K4 methyltransferase activity with physiological conditions (Couture and Skiniotis, Epigenetics, 2013; Qu et al., Cell, 2018; Rahman et al., Proc Natl Acad Sci U S A, 2022). ASH2L interacts with RbBP5 via its SPRY domain, whereas WDR5 bridges MLL1 and RbBP5 through the WIN and WBM motifs (Chen et al., Cell Res, 2012; Park et al., Nat Commun, 2019). The interaction status between ASH2L and WDR5 during mycobacterial infection could not be determined in our current study.

(4) The AlphaFold prediction results for all the nuclear proteins examined could be useful. Since the interaction predictions with COMPASS subunits range from 0.77 for WDR5 and 0.47 for ASH2L, it is not clear how the focus on COMPASS complex over other nuclear proteins was determined.

We thank the reviewer for the comment. We employed AlphaFold to predict the interactions between MgdE and the major nuclear proteins. This screen identified several subunits of the SET1/COMPASS complex as high-confidence candidates for interaction with MgdE (Figure S4A). This result is consistent with a proteomic study by Penn et al. which reported potential interactions between MgdE and components of the human SET1/COMPASS complex based on affinity purification-mass spectrometry analysis (Penn et al., Mol Cell, 2018).

Reviewer #2 (Public review):

Summary:

The manuscript by Chen et al addresses an important aspect of pathogenesis for mycobacterial pathogens, seeking to understand how bacterial effector proteins disrupt the host immune response. To address this question, the authors sought to identify bacterial effectors from M. tuberculosis (Mtb) that localize to the host nucleus and disrupt host gene expression as a means of impairing host immune function.

Strengths:

The researchers conducted a rigorous bioinformatic analysis to identify secreted effectors containing mammalian nuclear localization signal (NLS) sequences, which formed the basis of quantitative microscopy analysis to identify bacterial proteins that had nuclear targeting within human cells. The study used two complementary methods to detect protein-protein interaction: yeast two-hybrid assays and reciprocal immunoprecipitation (IP). The combined use of these techniques provides strong evidence of interactions between MgdE and SET1 components and suggests that the interactions are, in fact, direct. The authors also carried out a rigorous analysis of changes in gene expression in macrophages infected with the mgdE mutant BCG. They found strong and consistent effects on key cytokines such as IL6 and CSF1/2, suggesting that nuclear-localized MgdE does, in fact, alter gene expression during infection of macrophages.

Weaknesses:

There are some drawbacks in this study that limit the application of the findings to M. tuberculosis (Mtb) pathogenesis. The first concern is that much of the study relies on ectopic overexpression of proteins either in transfected non-immune cells (HEK293T) or in yeast, using 2-hybrid approaches. Some of their data in 293T cells is hard to interpret, and it is unclear if the protein-protein interactions they identify occur during natural infection with mycobacteria. The second major concern is that pathogenesis is studied using the BCG vaccine strain rather than virulent Mtb. However, overall, the key findings of the paper - that MgdE interacts with SET1 and alters gene expression are well-supported.

We thank the reviewer for the comment. We agree that the ectopic overexpression could not completely reflect a natural status, although these approaches were adopted in many similar experiments (Drerup et al., Molecular plant, 2013; Chen et al., Cell host & microbe, 2018; Ge et al., Autophagy, 2021). Further, the MgdE localization experiment using Mtb infected macrophages will be performed to increase the evidence in the natural infection.

We agree with the reviewer that BCG strain could not fully recapitulate the pathogenicity or immunological complexity of M. tuberculosis infection. We employed BCG as a biosafe surrogate model since it was acceptable in many related studies (Wang et al., Nat Immunol, 2025; Wang et al., Nat Commun, 2017; Péan et al., Nat Commun, 2017; Li et al., J Biol Chem, 2020).

Reviewer #3 (Public review):

In this study, Chen L et al. systematically analyzed the mycobacterial nucleomodulins and identified MgdE as a key nucleomodulin in pathogenesis. They found that MgdE enters into host cell nucleus through two nuclear localization signals, KRIR^108-111 and RLRRPR^300-305, and then interacts with COMPASS complex subunits ASH2L and WDR5 to suppress H3K4 methylation-mediated transcription of pro-inflammatory cytokines, thereby promoting mycobacterial survival. This study is potentially interesting, but there are several critical issues that need to be addressed to support the conclusions of the manuscript.

(1) Figure 2: The study identified MgdE as a nucleomodulin in mycobacteria and demonstrated its nuclear translocation via dual NLS motifs. The authors examined MgdE nuclear translocation through ectopic expression in HEK293T cells, which may not reflect physiological conditions. Nuclear-cytoplasmic fractionation experiments under mycobacterial infection should be performed to determine MgdE localization.

We thank the reviewer for this insightful comment. In the revised manuscript, we addressed this concern by performing nuclear-cytoplasmic fractionation experiments using M. bovis BCG-infected macrophages to assess the subcellular localization of MgdE (New Figure 2F) (Lines 146–155). Nuclear-cytoplasmic fractionation experiments showed that WT MgdE and the NLS single mutants (MgdE^ΔNLS1 and MgdE^ΔNLS2) could be detected both in the cytoplasm and in the nucleus, while the double mutant MgdE^ΔNLS1-2 was detectable only in the cytoplasm. These findings strongly indicate that MgdE is capable of translocating into the host cell nucleus during BCG infection, and that this nuclear localization relies on the dual NLS motifs.

(2) Figure 2F: The authors detected MgdE-EGFP using an anti-GFP antibody, but EGFP as a control was not detected in its lane. The authors should address this technical issue.

We thank the reviewer for this question. In the revised manuscript, we have included the uncropped immunoblot images, which clearly show the EGFP band in the corresponding lane. These have been provided in the New Figure 2E.

(3) Figure 3C-3H: The data showing that the expression of all detected genes in 24 h is comparable to that in 4 h (but not 0 h) during WT BCG infection is beyond comprehension. The issue is also present in Figure 7C, Figure 7D, and Figure S7. Moreover, since Il6, Il1β (pro-inflammatory), and Il10 (anti-inflammatory) were all upregulated upon MgdE deletion, how do the authors explain the phenomenon that MgdE deletion simultaneously enhanced these gene expressions?

We thank the reviewer for the comment. A relative quantification method was used in our qPCR experiments to normalize the WT expression levels in Figure 3C–3H, Figure 7C, 7D, and New Figure S6.

The concurrent induction of both types of cytokines likely represents a dynamic host strategy to fine-tune immune responses during infection. This interpretation is supported by previous studies (Podleśny-Drabiniok et al., Cell Rep, 2025; Cicchese et al., Immunological Reviews, 2018).

(4) Figure 5: The authors confirmed the interactions between MgdE and WDR5/ASH2L. How does the interaction between MgdE and WDR5 inhibit COMPASS-dependent methyltransferase activity? Additionally, the precise MgdE-ASH2L binding interface and its functional impact on COMPASS assembly or activity require clarification.

We thank the reviewer for this insightful comment. We cautiously speculate that the MgdE interaction inhibits COMPASS-dependent methyltransferase activity by interfering with the integrity and stability of the COMPASS complex. Accordingly, we have incorporated the following discussion into the revised manuscript (Lines 303-315):

“The COMPASS complex facilitates H3K4 methylation through a conserved assembly mechanism involving multiple core subunits. WDR5, a central scaffolding component, interacts with RbBP5 and ASH2L to promote complex assembly and enzymatic activity (Qu et al., 2018; Wysocka et al., 2005). It also recognizes the WIN motif of methyltransferases such as MLL1, thereby anchoring them to the complex and stabilizing the ASH2L-RbBP5 dimer (Hsu et al., Cell, 2018). ASH2L further contributes to COMPASS activation by interacting with both RbBP5 and DPY30 and by stabilizing the SET domain, which is essential for efficient substrate recognition and catalysis (Qu et al., Cell, 2018; Park et al., Nat Commun, 2019). Our work shows that MgdE binds both WDR5 and ASH2L and inhibits the methyltransferase activity of the COMPASS complex. Site-directed mutagenesis revealed that residues D²²⁴ and H²⁴⁷ of MgdE are critical for WDR5 binding, as the double mutant MgdE-D²²⁴A/H²⁴⁷A fails to interact with WDR5 and shows diminished suppression of H3K4me3 levels (Figure 5D).”

Regarding the precise MgdE-ASH2L binding interface, we attempted to identify the key interaction site by introducing point mutations into ASH2L. However, these mutations did not disrupt the interaction (Figure 5A and B; New Figure S4C), suggesting that more residues are involved in the interaction.

(5) Figure 6: The authors proposed that the MgdE-regulated COMPASS complex-H3K4me3 axis suppresses pro-inflammatory responses, but the presented data do not sufficiently support this claim. H3K4me3 inhibitor should be employed to verify cytokine production during infection.

We thank the reviewer for the comment. We have now revised the description in lines 220-221 and lines 867-868 "MgdE suppresses host inflammatory responses probably by inhibition of COMPASS complex-mediated H3K4 methylation."

(6) There appears to be a discrepancy between the results shown in Figure S7 and its accompanying legend. The data related to inflammatory responses seem to be missing, and the data on bacterial colonization are confusing (bacterial DNA expression or CFU assay?).

We thank the reviewer for the comment. New Figure S6 specifically addresses the effect of MgdE on bacterial colonization in the spleens of infected mice, which was assessed by quantitative PCR rather than by CFU assay.

We have now revised the legend of New Figure S6 as below (Lines 986-991):

“MgdE facilitates bacterial colonization in the spleens of infected mice. Bacterial colonization was assessed in splenic homogenates from infected mice (as described in Figure 7A) by quantifying bacterial DNA using quantitative PCR at 2, 14, 21, 28, and 56 days post-infection.”

(7) Line 112-116: Please provide the original experimental data demonstrating nuclear localization of the 56 proteins harboring putative NLS motifs.

We thank the reviewer for the comment. We will provide this data in the New Table S3.

Recommendations for the authors:

Reviewer #2 (Recommendations for the authors):

There are a few concerns about specific experiments:

Major Comments:

(1) Questions about the exact constructs used in their microscopy studies and the behavior of their controls. GFP is used as a negative control, but in the data they provide, the GFP signal is actually nuclear-localized (for example, Figure 1c, Figure 2a). Later figures do show other constructs with clear cytoplasmic localization, such as the delta-NLS-MgdE-GFP in Figure 2D. This raises significant questions about how the microscopy images were analyzed and clouds the interpretation of these findings. It is also not clear if their microscopy studies use the mature MdgE, lacking the TAT signal peptide after signal peptidase cleavage (the form that would be delivered into the host cell) or if they are transfecting the pro-protein that still has the TAT signal peptide (a form that would present in the bacterial cell but that would not be found in the host cell). This should be clarified, and if their construct still has the TAT peptide, then key findings such as nuclear localization and NLS function should be confirmed with the mature protein lacking the signal peptide.

We thank the reviewer for this question.  EGFP protein can passively diffuse through nuclear pores due to its smaller size (Petrovic et al., Science, 2022; Yaseen et al., Nat Commun, 2015; Bhat et al., Nucleic Acids Res, 2015). However, upon transfection with EGFP-tagged wild-type MdgE and its NLS deletion mutants (MdgE^ΔNLS1, MdgE^ΔNLS2, and MdgE^ΔNLS1-2), we observed significantly stronger nuclear fluorescence in cells expressing wild-type MdgE compared to the EGFP protein. Notably, the MdgE^ΔNLS1-2-EGFP mutant showed almost no detectable nuclear fluorescence (Figure 2C, D, and E). These results indicate that (i) MdgE-EGFP fusion protein could not enter the nucleus by passive diffusion, and (ii) EGFP does not interfere with the nuclear targeting ability of MdgE.

We did not construct a signal peptide-deleted MgdE for transfection assays. Instead, we performed an infection experiment using recombinant M. bovis BCG strains expressing Flag-tagged wild-type MgdE. The mature MgdE protein (signal peptide cleaved) can be detected in the nucleus fractionation (New Figure 2F), suggesting that the signal peptide does not play a role for the nuclear localization of MgdE.

(2) The localization of MdgE is not shown during actual infection. The study would be greatly strengthened by an analysis of the BCG strain expressing their MdgE-FLAG construct.

We thank the reviewer for the comment. In the revised manuscript, we constructed M. bovis BCG strains expressing FLAG-tagged wild-type MdgE as well as NLS deletion mutants (MdgE^ΔNLS1, MdgE^ΔNLS2, and MdgE^ΔNLS1-2). These strains were used to infect THP-1 cells, and nuclear-cytoplasmic fractionation was performed 24 hours post-infection.

Nuclear-cytoplasmic fractionation experiments showed that WT MgdE and the NLS single mutants could be detected both in the cytoplasm and in the nucleus by immunoblotting, while the double mutant MgdE^ΔNLS1-2 was detectable only in the cytoplasm (New Figure 2F) (Lines 146–155). These findings indicate that MdgE is capable of entering the host cell nucleus during BCG infection, and that this nuclear localization depends on the presence of both its N-terminal and C-terminal NLS motifs.

(3) Their pathogenesis studies suggesting a role for MdgE would be greatly strengthened by studying MdgE in virulent Mtb rather than the BCG vaccine strain. If this is not possible because of technical limitations (such as lack of a BSL3 facility), then at least a thorough discussion of studies that examined Rv1075c/MdgE in Mtb is important. This would include a discussion of the phenotype observed in a previously published study examining the Mtb Rv1075c mutant that showed a minimal phenotype in mice (PMID: 31001637) and would also include a discussion of whether Rv1075c was identified in any of the several in vivo Tn-Seq studies done on Mtb.

We thank the reviewer for this insightful comment. In the revised manuscript, we have incorporated a more thorough discussion of prior studies that examined Rv1075c/MgdE in Mtb, including the reported minimal phenotype of an Mtb MgdE mutant in mice (PMID: 31001637) (Lines 288–294).

In the latest TnSeq studies in M. tuberculosis, Rv1075c/MgdE was not classified as essential for in vivo survival or virulence (James et al., NPJ Vaccines, 2025; Zhang et al., Cell, 2013). However, this absence should not be interpreted as evidence of dispensability since these datasets also failed to identify some well characterized virulence factors including Rv2067c (Singh et al., Nat Commun, 2023), PtpA (Qiang et al., Nat Commun, 2023), and PtpB (Chai et al., Science, 2022) which were demonstrated to be required for the virulence of Mtb.

Minor Comments:

(1) Multiple figures with axes with multiple discontinuities used when either using log-scale or multiple graphs is more appropriate, including 3B, 7A.

We sincerely thank the reviewer for pointing this out. In the revised manuscript, we have updated Figure 3B and Figure 7A.

(2) Figure 1C - Analysis of only nuclear MFI can be very misleading because it is affected by the total expression of each construct. Ratios of nuclear to cytoplasmic MFI are a more rigorous analysis.

We thank the reviewer for this comment. We agree that analyzing the ratio of nuclear to cytoplasmic mean fluorescence intensity (MFI) provides a more rigorous quantification of nuclear localization, particularly when comparing constructs with different expression levels. However, the analysis presented in Figure 1C was intended as a preliminary qualitative screen to identify Tat/SPI-associated proteins with potential nuclear localization, rather than a detailed quantitative assessment.

(3) Figure 5C - Controls missing and unclear interpretation of their mutant phenotype. There is no mock or empty-vector control transfection, and their immunoblot shows a massive increase in total cellular H3K4me3 signal in the bulk population, although their prior transfection data show only a small fraction of cells are expressing MdgE. They also see a massive increase in methylation in cells transfected with the inactive mutant, but the reason for this is unclear. Together, these data raise questions about the specificity of the increasing methylation they observe. An empty vector control should be included, and the phenotype of the mutant explained.

We thank the reviewer for this comment. In the revised manuscript, we transfected HEK293T cells with an empty EGFP vector and performed a quantitative analysis of H3K4me3 levels. The results demonstrated that, at the same time point, cells expressing MdgE showed significantly lower levels of H3K4me3 compared to both the EGFP control and the catalytically inactive mutant MdgE (D²⁴⁴A/H²⁴⁷A) (New Figure 5D) (Lines 213–216). These findings support the conclusion that MdgE specifically suppresses H3K4me3 levels in cells.

(4) Figure S1A - The secretion assay is lacking a critical control of immunoblotting a cytoplasmic bacterial protein to demonstrate that autolysis is not releasing proteins into the culture filtrate non-specifically - a common problem with secretion assays in mycobacteria.

We thank the reviewer for this comment. To address the concerns, we examined FLAG-tagged MgdE and the secreted antigen Ag85B in the culture supernatants by monitoring the cytoplasmic protein GlpX. The absence of GlpX in the supernatant confirmed that there was no autolysis in the experiment. We could detect MgdE-Flag in the culture supernatant (New Figure S2A), indicating that MgdE is a secreted protein.

(5) The volcano plot of their data shows that the proteins with the smallest p-values have the smallest fold-changes. This is unusual for a transcriptomic dataset and should be explained.

We thank the reviewer for this comment. We are not sure whether the p-value is correlated with fold-change in the transcriptomic dataset. This is probably case by case.

Reviewer #3 (Recommendations for the authors):

There are several minor comments:

(1) Line 104-109: The number of proteins harboring NLS motifs and candidate proteins assigned to the four distinct pathways does not match the data presented in Table S2. Please recheck the details. Figure 1A and B, as well as Figure S1A and B, should also be corrected accordingly.

We thank the reviewer for the comment. We have carefully checked the details and the numbers were confirmed and updated.

(2) Please add the scale bar in all image figures, including Figure 1C, Figure 2D, Figure 5C, Figure 7B, and Figure S2.

We thank the reviewer for this suggestion. We have now added scale bars to all relevant image figures in the revised manuscript, including Figure 1C, New Figure 2C, Figure 5C, Figure 7B, and New Figure S2B.

(3) Please add the molecular marker in all immunoblotting figures, including Figure 2C, Figure 2F, Figure 4B, Figure 4C, Figure 5B, Figure 5D, and Figure S5.

We thank the reviewer for this suggestion. We have now added the molecular marker in all immunoblotting figures in the revised manuscript, including New Figure 2E–F, Figure 4B–C, Figure 5B and D, Figure S2A, New Figure S2E and New Figure S4C.

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Spanish court decision that algorithms used to decide about citizens by government entities, need to be transparant. Presented as landmark ruling with EU consequences, but I'm not sure if this isn't already true for public sector decision making under the AI Act. In NL the national algorithm register and tools like IAMA are aimed at this too, and have been in place for some time, even if not fully implemented yet.

eLife Assessment

This work describes a useful computational tool for automated morphometry of dynamic organelles from microscope images. However, the supporting evidence and novelty of the manuscript as presented are incomplete and could be improved. The work will be of interest to microscopists and bioimage analysts who are non-experts but wish to improve quantitative analysis of cellular structures.

Reviewer #2 (Public review):

Summary:

AutoMorphoTrack provides an end-to-end workflow for organelle-scale analysis of multichannel live-cell fluorescence microscopy image stacks. The pipeline includes organelle detection/segmentation, extraction of morphological descriptors (e.g., area, eccentricity, "circularity," solidity, aspect ratio), tracking and motility summaries (implemented via nearest-neighbor matching using cKDTree), and pixel-level overlap/colocalization metrics between two channels. The manuscript emphasizes a specific application to live imaging in neurons, demonstrated on iPSC-derived dopaminergic neuronal cultures with mitochondria in channel 0 and lysosomes in channel 1, while asserting adaptability to other organelle pairs.

The tool is positioned for cell biologists, including users with limited programming experience, primarily through two implemented modes of use: (i) a step-by-step Jupyter notebook and (ii) a modular Python package for scripted or batch execution, alongside an additional "AI-assisted" mode that is described as enabling analyses through natural-language prompts.

The motivation and general workflow packaging are clear, and the notebook-plus-modules structure is a reasonable engineering choice. However, in its current form, the manuscript reads more like a convenient assembly of standard methods than a validated analytical tool. Key claims about robustness, accuracy, and scope are not supported by quantitative evidence, and the 'AI-assisted' framing is insufficiently defined and attributes to the tool capabilities that are provided by external LLM platforms rather than by AutoMorphoTrack itself. In addition, several figure, metric, and statistical issues-including physically invalid plots and inconsistent metric definitions-directly undermine trust in the quantitative outputs.

Strengths:

(1) Clear motivation: lowering the barrier for organelle-scale quantification for users who do not routinely write custom analysis code.

(2) Multiple entry points: an interactive notebook together with importable modules, emphasizing editable parameters rather than a fully opaque black box.

(3) End-to-end outputs: automated generation of standardized visualizations and tables that, if trustworthy, could help users obtain quantitative summaries without assembling multiple tools.

Weaknesses:

(1) "AI-assisted / natural-language" functionality is overstated.

The manuscript implies an integrated natural-language interface, but no such interface is implemented in the software. Instead, users are encouraged to use external chatbots to help generate or modify Python code or execute notebook steps. This distinction is not made clearly and risks misleading readers.

(2) No quantitative validation against trusted ground truth.

There is no systematic evaluation of segmentation accuracy, tracking fidelity, or interaction/overlap metrics against expert annotations or controlled synthetic data. Without such validation, accuracy, parameter sensitivity, and failure modes cannot be assessed.

(3) Limited benchmarking and positioning relative to existing tools.

The manuscript does not adequately compare AutoMorphoTrack to established platforms that already support segmentation, morphometrics, tracking, and colocalization (e.g., CellProfiler) or to mitochondria-focused toolboxes (e.g., MiNA, MitoGraph, Mitochondria Analyzer). This is particularly problematic given the manuscript's implicit novelty claims.

(4) Core algorithmic components are basic and likely sensitive to imaging conditions.

Heavy reliance on thresholding and morphological operations raises concerns about robustness across varying SNR, background heterogeneity, bleaching, and organelle density; these issues are not explored.

(5) Multiple figure, metric, and statistical issues undermine confidence.

The most concerning include:<br /> (i) "Circularity (4πA/P²)" values far greater than 1 (Figures 2 and 7, and supplementary figures), which is inconsistent with the stated definition and strongly suggests a metric/label mismatch or computational error.

(ii) A displacement distribution extending to negative values (Figure 3B). This is likely a plotting artifact (e.g., KDE boundary bias), but as shown, it is physically invalid and undermines confidence in the motility analysis.

(iii) Colocalization/overlap metrics that are inconsistently defined and named, with axis ranges and terminology that can mislead (e.g., Pearson r reported for binary masks without clarification).

(iv) Figure legends that do not match the displayed panels, and insufficient reporting of Ns, p-values, sampling units, and statistical assumptions.

Reviewer #3 (Public review):

Summary:

AutoMorphoTrack is a Python package for quantitatively evaluating organelle shape, movement, and colocalization in high-resolution live cell imaging experiments. It is designed to be a beginning-to-end workflow from segmentation through metric graphing, which is easy to implement. The paper shows example results from their images of mitochondria and lysosomes within cultured neurons, demonstrating how it can be used to understand organelle processing.

Strengths:

The text is well-written and easy to follow. I particularly appreciate tables 1 and 2, which clearly define the goals of each module, the tunable parameters, and the input and outputs. I can see how the provided metrics would be useful to other groups studying organelle dynamics. Additionally, because the code is open-source, it should be possible for experienced coders to use this as a backbone and then customize it for their own purposes.

Weaknesses:

Unfortunately, I was not able to install the package to test it myself using any standard install method. This is likely fixable by the authors, but until a functional distribution exists, the utility of this tool is highly limited. I would be happy to re-review this work after this is fixed.

The authors claim that there is "AI-Assisted Execution and Natural-Language Interface". However, this is never defended in any of the figures, and from quickly reviewing the .py files, there does not seem to be any built-in support or interface for this. Without significantly more instructions on how to connect this package to a (free) LLM, along with data to prove that this works reproducibly to produce equivalent results, this section should be removed.

Additionally, I have a few suggestions/questions:

(1) Red-green images are difficult for colorblind readers. I recommend that the authors change all raw microscopy images to a different color combination.

(2) For all of the velocity vs displacement graphs (Figure 3C and subpart G of every supplemental figure), there is a diagonal line clearly defining a minimum limit of detected movement. Is this a feature of the dataset (drift /shakiness /etc) or some sort of minimum movement threshold in the tracking algorithm? This should be discussed in the text.

(3) Integrated Correlation Summary (Figure 5) - Pearson is likely the wrong metric for most of these metric pairs because even interesting relationships may be non-linear. Please replace with Spearman correlation, which is less dependent on linearity.

Author response:

Reviewer #1

We thank the reviewer for their thoughtful and constructive assessment of AutoMorphoTrack and for recognizing its potential utility as an open-source end-to-end workflow for organelle analysis.

(1) Novelty and relationship to existing tools / FIJI workflows

We appreciate this concern and agree that many of the underlying image-processing operations (e.g., thresholding, morphological cleanup, region properties) are well-established. Our goal with AutoMorphoTrack is not to introduce new segmentation algorithms, but rather to provide a curated, reproducible, and extensible end-to-end workflow that integrates segmentation, morphology, tracking, motility, and colocalization into a single, transparent pipeline tailored for live-cell organelle imaging.

While an experienced user could assemble similar analyses ad hoc using FIJI or custom scripts, our contribution lies in:

Unifying these steps into a single workflow with consistent parameterization and outputs

Generating standardized, publication-ready visualizations and tables at each step,

Enabling batch and longitudinal analyses across cells and conditions, and

Lowering the barrier for users who do not routinely write custom analysis code.

We note that the documentation-style presentation of the manuscript is intentional, as it serves both as a methods paper and a practical reference for users implementing the workflow. We agree, however, that the manuscript currently overemphasizes step-by-step execution at the expense of positioning. In revision, we will more explicitly frame AutoMorphoTrack as a workflow integration and usability contribution, rather than a fundamentally new algorithmic advance.

We will also cite and discuss the image.sc example referenced by the reviewer, clarifying conceptual overlap and differences in scope.

(2) Comparison to existing pipelines (Imaris, CellProfiler, CellPose, StarDist)

We agree and thank the reviewer for highlighting this omission. In the revised manuscript, we will expand the related-work and positioning section to explicitly compare AutoMorphoTrack with established commercial (e.g., Imaris) and open-source (e.g., CellProfiler, MiNA, MitoGraph) platforms, as well as learning-based segmentation tools such as CellPose and StarDist.

Rather than claiming superiority, we will clarify trade-offs, emphasizing that AutoMorphoTrack prioritizes:

Transparency and parameter interpretability,

Lightweight dependencies suitable for small live-imaging datasets

Direct integration of morphology, tracking, and colocalization in a single workflow, and

Ease of modification for domain-specific use cases.

(3) AI / chatbot integration

We appreciate this critique and agree that the current description is insufficiently precise. AutoMorphoTrack does not implement a native natural-language interface. Instead, our intent was to convey that the workflow can be executed and modified with assistance from external large language models (LLMs) in a notebook-based environment.

In revision, we will revise this section to:

Clearly distinguish AutoMorphoTrack’s functionality from that of external LLM tools,

Remove any implication of a built-in AI interface, and

Provide concrete, reproducible examples of how non-coding users may interact with the pipeline using natural-language prompts mediated by external tools.

Reviewer #2

We thank the reviewer for their detailed and technically rigorous evaluation. We appreciate the recognition of the workflow’s motivation and structure, and we agree that several aspects of validation, positioning, and quantitative reporting must be strengthened.

(1) AI-assisted / natural-language functionality

We agree with this critique. AutoMorphoTrack does not provide a native natural-language execution layer, and the manuscript currently overstates this aspect. In revision, we will explicitly scope any reference to AI assistance as external, optional support for code generation and parameter editing, with clearly documented examples and stated limitations.

We agree that conflating external LLM capabilities with the software itself risks misleading readers, and we will correct this accordingly.

(2) Lack of quantitative validation

We fully agree that the current manuscript lacks formal quantitative validation. In the revised version, we will add a dedicated validation section including:

Segmentation accuracy compared to expert annotations using overlap metrics (e.g., Dice / IoU),

Tracking fidelity assessed using manually annotated tracks and/or synthetic ground truth,

Sensitivity analyses for key parameters (e.g., thresholding and linking distance), and

Explicit discussion of failure modes and quality-control indicators.

We acknowledge that without such validation, claims of robustness are not sufficiently supported.

(3) Benchmarking and positioning relative to existing tools

We agree and will substantially strengthen AutoMorphoTrack’s benchmarking and positioning relative to existing platforms. Rather than framing novelty algorithmically, we will clarify that the primary contribution is a reproducible, integrated workflow designed specifically for two-organelle live imaging in neurons, with transparent parameters and standardized outputs.

We note that our goal is not to exhaustively benchmark against all available tools, but rather to provide representative comparisons that clarify operating regimes, assumptions, and trade-offs. We will add a comparative table and/or qualitative comparison highlighting strengths, assumptions, and limitations relative to existing tools.

(4) Core algorithms and robustness

We agree that reliance on threshold-based segmentation introduces sensitivity to imaging conditions. In revision, we will:

Explicitly discuss the operating regime and assumptions under which AutoMorphoTrack performs reliably,

Clarify that the framework is modular and can accept alternative segmentation backends, and

Include guidance on when outputs should be treated with caution.

(5) Figure, metric, and statistical issues

We thank the reviewer for identifying several critical issues and agree that these undermine confidence. In revision, we will correct all figure, metric-definition, and reporting inconsistencies, including:

Resolving circularity values exceeding 1 by correcting computation and/or labeling errors,

Revising physically invalid displacement plots and clarifying kernel-density limitations,

Ensuring colocalization metrics are consistently defined, named, and interpreted, with explicit clarification of whether calculations are intensity- or mask-based,

Correcting figure legends to match displayed panels, and

Clearly reporting sample size, sampling units, and statistical assumptions, including handling of multiple comparisons where applicable.

(6) Value-added demonstration

We agree that the manuscript would benefit from a clearer demonstration of value-added use cases. In revision, we will include at least one realistic example showing how AutoMorphoTrack enables a complete, reproducible analysis workflow with reduced setup burden compared to manually assembling multiple tools.

(7) Editorial suggestions

We agree and will streamline the Results section to reduce procedural repetition and focus more on validation, limitations, and quality-control guidance.

Reviewer #3

We thank the reviewer for their positive assessment of clarity and organization, and for the constructive practical feedback.

Installation issues

We appreciate the detailed report of installation failures and acknowledge that the current packaging and distribution are inadequate. Prior to revision, we will:

Fix the package structure to support standard installation methods,

Ensure all required files (e.g., setup configuration, README) are correctly included,

Test installation on clean environments across platforms, and

Correct broken links to notebooks and documentation.

We agree that without a functional installation pathway, the utility of the tool is severely limited.

AI-assisted claims

We agree with the reviewer and echo our responses above. The AI-assisted description will be clarified and appropriately scoped in the revised manuscript.

Additional suggestions

Color accessibility: We will revise all figures to use colorblind-safe palettes.

Velocity–displacement diagonal: We will explicitly explain the origin of this relationship, including whether it reflects dataset properties, tracking assumptions, or minimum detectable motion.

Integrated correlation metric: We agree that Spearman correlation is more appropriate for many of these relationships and will replace Pearson correlations accordingly.

Supplementary movies: We agree that providing raw movies would improve interpretability and will add representative examples as supplementary material.

Reference:

Preprints. (2024). Traditional ecological knowledge and environmental stewardship. https://doi.org/10.20944/preprints202406.1838.v1

“Practices rooted in Traditional Ecological Knowledge have contributed to long-term ecosystem resilience in various local contexts.”(Preprints,2024)

This idea can be connected to real world example like indigenous fire management practices . IFMP controlled burns that reduces wildlife risk and maintain ecosystem balance. These practices are based on long term observation of land and seasonal patterns instead of modern emergency responses. In many cases, when these practices ignored, then ecosystems became more vulnerable to environmental damage on large scale. This example shows that how TEK is applied in real world and it produces measurable environmental benefits. This example also supports the article that TEK is not just about theoretical knowledge but also effective practically in managing ecosystems and sustainability.

Reference:

Preprints. (2024). Traditional ecological knowledge and environmental stewardship. https://doi.org/10.20944/preprints202406.1838.v1

“Traditional Ecological Knowledge (TEK) represents a knowledge system grounded in lived experience and intergenerational learning.”(Preprints,2024)

This article connects strongly to our course because in class we will study sustainability and social-ecological systems, In class we already discussed about social ecological system where we learned that Environmental management is not just technical but it's also related to social and historical things. In class. we discussed about how ecosystems and humans influence each other, which is exactly what Traditional ecological knowledge is based on. TEK is defined as generations of observation, trial and error instead of short term scientific studies and policies. This article also connects to discussion about whose knowledge is considered valid in environmental decision making. The course gives the idea that ignoring indigenous people's knowledge leads to ineffective policies and wrong results. This article support the course argument that for effective environmental management multiple ways of knowing the TEK is necessary. This article also reinforces that sustainability is not just about protecting nature but also about respecting culture, people and historical experience.

Reference

Preprints. (2024). Traditional ecological knowledge and environmental stewardship. https://doi.org/10.20944/preprints202406.1838.v1

"Traditional Ecological Knowledge (TEK) refers to the cumulated wisdom, practices, and beliefs concerning their natural environment developed over centuries by indigenous and local communities"(Preprints,2024)

This definition explains that Traditional Ecological Knowledge (TEK) is not just a information about nature but it is a system that includes historical knowledge developed over past generations. The phrase "long term interaction" is important because it shows that TEK knowledge comes from repeated experience with same land over time. TEK focus on continuous observation and adaptation as compared to scientific research which focus on limited timeframes. This definition gave clarification that TEK is structured and intentional, not outdated or random knowledge. TEK challenges modern science that Environmental knowledge only comes from modern science.

wow we are leading history repeat it self by allowing this kinds of this happen. So why are there amendments if we don't respect them ?

Glad to become familiar with this term. I've heard it used before but hadn't been explained what it meant up until now.

This is something I really relate to also. The fact that I am considered myself a Christian doesnt mean I cannot do whatever I desire. I’ve heard this millions of times, and sometimes it bothers me, but then I start thinking, “they don’t know how really I am, they just see the “outside” of me”. And even thought I do try to show my inner me on my outside its hard, because not everyone knows how to read people in a sense where anyone can understand me instantly.

I relate to this a lot, because when were younger were taught to call our older people , ma’am and sir. Meanwhile I don’t disagree, since I take it as a sense of being respectful and also as someone who has manners. Other than those two “names”, I wouldn’t really know what to call my adults when talking to them. But it is something that I relate to since since young we are taught to talk like this.

This section explains how misinformation and too much information can confuse people and affect real curiosity. It shows that not everything online is trustworthy, and people can get stuck in false ideas. This makes me realize that I need to be more careful about what sources I believe and use for school.

This introduction explains how the internet has changed the way people look for information and satisfy their curiosity. It shows that humans have always been curious, but now we rely on technology to explore questions faster. I think this is true because most of the time when I'm curious about something, I immediately search it on my phone.

Still thinking about the comment made that SAT does not predict post-secondary success but rather it predicts future earned income potential.

I can see why many other may find challenges in digital annotating, but I believe once you get used to it, it becomes a lot easier.

It is important for educators to recognize that children with disabilities can learn not only from the teacher, but also from their peers. I have seen students thrive in inclusive classroom settings where peer interaction supports both academic and social growth. Individualized Education Plans (IEPs) play a critical role in a student’s learning because they are developed in collaboration with families and are designed to meet each student’s unique needs. When implemented effectively, IEPs help create the best possible learning environment for students.

Agrawal (1995) is critical about the unrealistic distinction between Traditional Ecological Knowledge (TEK) and scientific knowledge as a false distinction, which is socially constructed and not significant. As he stresses, TEK is complementary, not inferior, and provides useful place-based knowledge, which has been formed by experience over a long period. This view holds the stance that it is necessary to combine the two knowledge systems so as to produce more effective and culturally responsive environmental management practices.

I think understanding the difference between indexing and ranking is useful. Once the information is indexed, it is organized, while ranking is judgments made about quality, popularity and relevance. The use of neural language models is interesting, but there is still room for improvement. It makes me think about transparency and accountability, since we as users never see which results get priority over others.

This clarifies how AI processes language, and it is interesting how it is pieced together as opposed to simply being complete ideas. I do believe that it improves efficiency, but it does show a gap between human meaning and artificial intelligence. Once the language is broken up into tokens, I think it's easier to identify patterns, but it doesn't necessarily equate to better understanding which is an inherent weakness of ai.

This abstract lacks an explicit conclusions section. The abstract presents results, but doesn't explicitly state what these results mean for future applications.

That is very interesting, I wonder what he saw and or what gave him the idea of that. I also wonder what this idea would look like in our modern society

Since this relationship is new, there is not a ton to go off of, but our relationship has gone well so far. I want to continue that by having honesty, respect, and my dedication to the position. Apologies, and still expressing how much this intership means to you could also aid in the relationship to continue going well

no punishment for killing enslaved ppl

I found the donkey protest example helpful for understanding how responsibility can be separated from action. Just like the donkey does not understand the protest it carries, bots can perform actions without intention or awareness. This makes it harder to assign responsibility, since the people who design, deploy, or benefit from a bot may all have different roles and intentions.

This section helped clarify that not all automation on social media counts as a bot. I found it especially useful that the definition focuses on whether the account is operated by computer code rather than by humans, even if those humans behave mechanically, like in click farms. This distinction makes it easier to think more precisely about responsibility and accountability when automation affects online spaces.

how is this claim more than an opinion but a political legitmacy or a straight up fact?

(I'm trying to add the annotation on the microphone icon beside the search bar, but the website won't allow me to highlight it.) This speech to text function allows those living with motor disabilities to search verbally rather than use a keyboard.

resources to help stay organized.

My husband and his siblings were raised by the same mother and father. One son, my husband, the middle child, always stayed between the lines and followed tall of he rules, he was well liked, got good grades, put himself through college while working full time and became an aeronautical engineer.and would often accept punishment for deviant behavior committed by his brother to keep the peace.He also got the least attention. He is the most conscientious loving , trustworthy and loyal person I know. To me this contradicts Edwin Sutherlands differential association theory.

His older brother, began using drugs at a very early age, sniffed glue at 9, took downers or reds at 12, and essentially became sexually active at 12 or 13m because their adult neighbor seduced him. Much of this his parents were oblivious to. He was put on behavioral medications as a child, and commanded a lot of attention. As a young man he joined the military and after going AWOL several times was ulitimatley dishonorably discharged. In later life he became an i.v. meth user, contracted HIV from sharing needles, went through countless rehabs, and ultimately died as an overdose. To this day his parents are in denial about who he had become.

His youngest brother by 7 years also became sexually active at a very young age. The same neighbor sexually abused him. He became a womanizer often having 3 to 4 women who all thought the were the only one. He has never held a real job, Had two children that he loves but never really helped the Mom with any sort of support , financially or in caring for the kids. but has managed to find women with lots of money support him. He lived with their parents on and off into his 50's. Just recently at 60 years old he seems to have settled down with one woman. She is also a very wealthy woman who is happy to take care of him.

In the opinion of the religious right if a woman chooses to have an abortion they are murderers, where others strongly believe it's my body it's my choice.

Conformity ex: People who stay within the lines. they may be very goal oriented, will not go outside of the acceptable means to get there. Innovation exp: Also goal oriented, and will do whatever it takes to achieve those goals even it that means going outside of acceptable norms. Ritualism: These are people that just lower the bar and reduce their goals until they can reach whatever they can achieve within the acceptable means. Retreatism: These are people that for whatever reason just give up. they do not see themselves able or worthy to achieve or have any goals Many homeless people have retreated from society's goal of financial success. These could have been people that had resources, but perhaps were beaten down to feel that they were not worthy. Rebellion: People who rebel tend to reject societal norms, bringing there own agenda into place. I believe there can be both positive and negative forms of rebellion.

Sociologist Robert Merton agreed that deviance is an inherent part of a functioning society, but he expanded on Durkheim’s ideas by developing strain theory, What is strain theory. This is a new concept for me. investigate more!

A crime committed by a white person is often teated less harshly then it it were a person of color.

common sence, there is a time and a place for joking.

Other considerations- future expectations re AI and singers.

Argument and a bit of Method -- states which experts and areas are examined and used to formulate this analysis.