supervisor (singular)

Robertson Media Center Consultant's

Add a bullet here about headphones: Per Desk policy, do not wear headphones while at the desk.

Photo - change to RMC photo

Robertson Media Center Consultants

Robertson Media Center Consultants

I am wondering if we could introduce a box somewhere on the top which shows the study outcome as positive, negative, not available?

Could we also show here the Number of Publications?

Could we add after publications a new section called "Trial History". We run this for few trials and maybe we could do for a selected number of trials. See an example in the data lake. <br /> https://datalake.bioloupe.com/admin/clinical_trials/36511#history-timeline

I would add Diseases, Disease Stage, Line of therapy, Biomarker and Value A trial might have multiple diseases with each has their own Disease Stage, Line of therapy, Biomarker and Value therefore we need to structure this box to accommodate this.

Sometimes the trial has additional Other Study ID Numbers, which could be listed here.

I can't highlight and annotate "Overview" therefore I leave comments here. We need the following under Overview: Official Title, Brief Summary, Detailed Description, Conditions, Interventions , Sponsors

I would like to see here: Study Start Date (Actual or Estimated) Primary Completion Date (Actual or Estimated) Study Completion Date (Actual or Estimated)

I think this is too prominent here. It could be somewhere else with smaller text size

We show Phase II, Completed, 2 sponsors on the top of the page. Do we need those? They don't bother me but it is a duplication.

The Phases should be: Early Phase 1, Phase 1, Phase 2, Phase 3, Phase 4.

Sometimes the trials is Phase 1/Phase 2 or Phase 2/Phase 3, in these cases we should highlight both.

caricatured or characterized

Might be helpful to have an image of the 2-column format?

use an m-dash (command/shift/hyphen) rather than a hyphen.

This phrase dangles and the next sentence is cut off.

quote and cite the Afterword for this phrasing.

a more generous quotation might help untangle the syntax here. Sounds like she's being paired like to like, which doesn't make sense if she's straight.

What is the intention? Isn't she just following the conventions of the calendar year and the almanack form?

Barnes describes January as... (avoid passive voice)

irreverence? Is she mocking the women for their reverence? for their irreverence? It's not quite clear what she's mocking, but my sense is that she evokes Christian imagery to create an ironic contrast, since their behaviors are what would be deemed sinful in a traditional Christian theology.

to be enjoyed and read as a communal experience?

This sentence is vague. Why not just take it out?

seems almost like a warning as much as an invitation.

The foreword is fascinating. She starts by minimizing the project as a small, flawed, and obscure affair. To set it before "the compound public eye," she then shrouds it in Latinate rhetoric that obscures as much as it reveals, casting the Almanack as a dangerous mythological creature.

It feels as if, almost 50 years later, she's still trying to preserve the secrecy and self-mythologizing that strengthened and sustained the Lesbian community of the 1920s. They were considered monstrous and unnatural by society, and in some ways, Barnes embraces and recuperates the sense of being an outcast, grotesque monstrosity, much in the way subsequent activists recuperated the term "queer" and staged elaborate gay parades.

difficult? particularly for readers who are not "in the know"!

"is composed of" or "comprises"

I've never come across this view of Barnes as a dilettante, so unless you found it in a more scholarly source than Mirriam-Webster, I would leave it out. She was a serious writer, as well as a witty, ironic, and sometimes outright hilarious one.

I'm not sure she used these movements as much as participated in them. You could simplify to: She combined avant garde aesthetics with decadent, bohemian, "art for art's sake" sensibility.

I think these two sections might be combined in one concise bio of Barnes that leads to the Paris and the Almanac.

Simple, elegant title page tells us exactly what we need to know and entices us to enter, without minimizing your project.

I'd love to know more detail here. Who requested it? Also this information seems to require a citation for its source.

Brilliant connection and excellent point about the setting, but do you mean that the setting is as much a part of her work as the language of the poem itself? Also, might this be a place where you can gesture to the Paris connection. Loy's poem, if it's Three Moments in Paris, connects this NY scene to its Paris "sister city" in modernist decadence.

I'm not the author of this work. See the about page to create a correct citation.

Carolyn

Actually periodical studies is a very established field with a methodology that these students adopt! They didn't invent it.

As a design rule, use left alignment for any text longer than a single line. It's much harder to read centered text.

page #?

I don't think she published a drawing in Rogue, did she? Clara Tice published drawings that seemed to illustrate her work.

Do you need a citation for this information? It may be considered common knowledge, but if you had to look it up, cite your source.

Stein may be looming a bit too large in this project. Her salon was an important gathering place, but not the only one. Natalie Barney's salon, Sylvia Beach's bookstore, and the many cafes and clubs provided other nodes in the network.

awkward syntax. Was she the American facing literature?

Maybe clear to say "About Mina Loy," so it doesn't seem like this is about you, the author of this essay!

Good, clear, engaging opening.

This sentence has a misplaced modifier. The initial clause "through-reimposing..." attaches to the nearest subject noun, so that Three Moments in Paris is re-imposing itself.

You can make a better sentence and stronger anchor by saying something like: By examining Three Moments in its little magazine context, we can see...[and then insert a specific thesis/insight]

This source made me think of the Citizens United Supreme Court case that basically ruled that your money is an extension of your free speech. This ruling has put value to voices that are higher in monetary value. they can spread their message as they please while poorer people can't have the same reach a rich person can.

This article is about Anil tried to tell people to avoid reading negative comment like toxic comment about us. He explains that harmful comments, harassment, and hate speech can make online spaces feel unsafe, especially for women and minority groups. And he believe social media platforms can do better job by moderating content, try to make healthier online communities. I think this article makes a strong point because many people say “just ignore it,” but negative comments can still affect someone’s mental health. We can proyect ourselves by reporting toxic behavior while using it.

In this article, Mia Sato explains that YouTube received millions of incorrect copyright claims within a six-month period, showing how automated copyright systems often make mistakes when identifying content. The article highlights concerns about fairness and transparency, since false claims can negatively affect creators by removing videos or limiting their ability to earn revenue.

This article talks about how it plans to ban political moderators from posting certain content due to Trumps prevalent social media presence and ability to post at all times.

This Wikipedia source talks about spamming. It first gives us a definition. Next, it gives us it's direvation and roots/history. It also gives examples in different media forms, such as emails, messages, social network spam, and many more. Something that I also find interesting is the chart of where spam comes from with percentages for countries.

In a field dominated by philosophy, the Coldewey article about the 2017 Reddit subreddit bans are a relatively few pieces of empirical evidence. While banning toxic communities may have decreased overall hate speech across platforms (i.e., users did not simply migrate and reestablish at the same levels) this was empirically measured; therefore, this will provide an objective measure that does mitigate the motivated reasoner problem when evaluating moderation actions from a Rawlsian perspective. However, there are limitations to the consequences-based "escape" mechanism - while the Coldewey article quantifies the reduction in hate speech as a result of the ban, it does not determine whether or not those who were banned had their attitudes toward hate speech changed as a result of being banned. That is a far more difficult measurement to make.

This study was conducted by Georgia Institute of Technology. The finding was that because Reddit banned toxic subreddits in 2015, it successfully reduced hate speech on the platform by up to 80 - 90% among users. The article also shows that while many offenders migrated to other communities like Voat and Gab, they didn't significantly increase the amount of hate speech in the subreddits that they joined. Researchers of this study concluded that by making bigotry more difficult to practice, they can effectively discourages it and eventually yield lasting positive results.

I found it interesting how Wikipedia administrators are painted less as “authorities” and more as trusted volunteers with extra technical tools. Conversely, the article shows how much power admins actually have, which makes the emphasis on neutrality, accountability, and consensus especially important in maintaining trust on the platform..

This article about how a woman had no wikipedia page until she was associated with a male is so sad to me. She literally won a Nobel Peace Prize and is not recognized onliine for it in any public matter. It is only until a man is beside her name that they rcognize it. This is extremley disappointing because id think that an accomplishment that big wouldn't go unrecognized because of gender.

I've noticed a common trend that these large tech companies do. When they feel they need to hire cheap work for controversial tasks, they outsource that work to separate their name from the controversy. We saw this with how big tech treats social media content moderators, and now we see this with how AI companies treat data workers and AI trainers. I see it as a way these companies are trying to manage their liability by hiring through a separate company.

This article talks about Facebook's moderation team, employees who are underpaid to look at disturbing content. The article highlights how these employees are not treated well, and issues such as PTSD from viewing this content is dismissed by the company. The article talks about lawsuits regarding the topic but explains that they have caused no change to how Facebook treats these employees.

I never knew people could get paid to make changes to wikipedia but it makes sense. Wikipedia being one of the largest free information databases in the world means that its data gets pulled for so much so changing that data by paying editors to make sure your pages are up to date and paint you favorably help influence those who might see the data without knowing their seeing it.

Content is moderated by the company that owns the social media platform. Which means there is an intrinsic bias within the algorithm. With censorship and misinformation rampant, it is hard to know what you're looking at on social media is truly accurate. I think there would be alot less open racisim online if everyone had power to change the algorithm and how people interact on social media.

The people in charge of social media platforms are typically tech executives who direct their moderation teams with legal council, and their individual viewpoints and business goals this influence the rules that get enforced (or not). As a direct result, moderation policies are more so often subject to political pressure and profit motives, or even the personal beliefs of platform leadership.

The section title of “Origins for Moderation” is quiet in its performance of the very problem described, i.e., it illustrates how a series of moderation’s ancestry (Confucius→Aristotle→Kant→Rawls) is also a way of demonstrating which rationality can determine the golden mean. Critics have argued for some time that Rawl's "veil of ignorance" was created to remove from consideration just those forms of self-interested thinking (the wealthy man's "rational" argument against paying taxes) that are identified in the chapter; however, at least as many critics argue that the veil still includes within it certain assumptions regarding what a rational person values. The chapter defines this problem as having been resolved by Rawls; yet, the bigger question remains that moderation-as-a-virtue and moderation-as-content policies suffer from the same fundamental flaw -- each assumes there will exist a mediator/moderator standing apart from all other participants involved in the moderation process.

Ive reported one thing for violating rules because my friend was posted in something she did not consent too/ So me and my friends all reported it together hoping it would get taken down and she wouldn't have to do anything further to remove the post. It didn't necessarily break the platforms rules, but it violated her personal privacy.

I have reported a few posts before, especially ones related to school violence, sensitive or disturbing images, and posts that included suspicious links that seemed like they were trying to hack my account. I think reporting harmful content is important because it can protect us from any violation. These posts make me feel unsafe or spread harmful behavior online. I also report suspicious links because I do not want my personal information or account to be at risk. Or any content I do not want to see in future and report some fake account who tried to send me message or comment.

Personally, I never had but I've reported accounts or strange people online. Certain rules like this and the ability to report things are not often utilized.

I have reported posts not because they broke the terms of service (they might have, but I didn't check), but because I didn't like the post. Sometimes I do this so that I don't see content from the creator of the post anymore, or so that I don't get that type of content anymore, and sometimes I just do it as a troll. On TikTok, there are a couple of steps to take before you can block someone, but you can report them without going to their profile.

I think this passage shows how difficult content moderation is on large social media platforms like Facebook. Even though moderators are hired to review harmful posts, the platform’s algorithms may still promote controversial or inflammatory content because it increases engagement and keeps users active. After reading this, I realized that social media companies are not only influenced by ethics, but also by business goals and user activity. It made me think more critically about the type of content I interact with online and how algorithms shape what people see every day.

I think this passage shows how difficult content moderation is on large social media platforms like Facebook. Even though moderators are hired to review harmful posts, the platform’s algorithms may still promote controversial or inflammatory content because it increases engagement and keeps users active. After reading this, I realized that social media companies are not only influenced by ethics, but also by business goals and user activity. It made me think more critically about the type of content I interact with online and how algorithms shape what people see every day.

I think this passage shows how difficult content moderation is on large social media platforms like Facebook. Even though moderators are hired to review harmful posts, the platform’s algorithms may still promote controversial or inflammatory content because it increases engagement and keeps users active. After reading this, I realized that social media companies are not only influenced by ethics, but also by business goals and user activity. It made me think more critically about the type of content I interact with online and how algorithms shape what people see every day.

I think this passage shows how difficult content moderation is on large social media platforms like Facebook. Even though moderators are hired to review harmful posts, the platform’s algorithms may still promote controversial or inflammatory content because it increases engagement and keeps users active. After reading this, I realized that social media companies are not only influenced by ethics, but also by business goals and user activity. It made me think more critically about the type of content I interact with online and how algorithms shape what people see every day.

This passage is interesting because it shows that even platforms that strongly support free speech still place limits on certain types of content like spam. It highlights the idea that content moderation is often done for practical reasons, such as keeping users engaged and maintaining the platform’s usability. I think the passage effectively demonstrates that no online platform is completely unmoderated, since every site must balance freedom of expression with user experience.

I have read before about how horrible it is to work in content moderation at big tech. These employees are shown truly horrific things and need to determine what happens to the post. I imagine this job is very similar to certain AI Trainer jobs that exist today on platforms like Handshake. I have heard similar bad things about them. I wonder if content moderators and their decisions while moderating were used to train an AI to do it without potentially traumatizing employees. If so, I see that as a positive use of AI.

It is interesting to think how China is able to have such a robust censorship network blocking the news as well as a bunch of different sites but the US seems unable to block a lot of the things we censor such as CSAM. I wonder what sets China's censorship network apart from the US's.

Michigan Safe Drinking Water Act (Act 399 of 1976), Public Act 399 of 1976 (effective January 4, 1977), Safe Drinking Water Act PDF.

Michigan Safe Drinking Water Act (Act 399 of 1976), Public Act 399 of 1976 (effective January 4, 1977), Safe Drinking Water Act PDF.

comment via Joe Eisaman at https://www.facebook.com/groups/TypewriterCollectors/posts/10163611818554678/

in relation to a table of dimensions 32 x17 x28".

Floridi and Taddeo are optimistic here they see ethics and data science as compatible, not opposing forces. But that balance is easier to describe than to actually achieve in practice.

Mitch Fixit has some repair chops, so this is believe-able: Some of the colored platens were meant to have different harnesses for doing stencils.

via https://www.facebook.com/groups/TypewriterCollectors/posts/10163612704804678/

In the game, the added time pressure made it feel like answers needed to be instant. It also made looking into these sources feel like a waste of time, since it was impossible to do this for a few, let alone all of them. I believe that this can be shown in true moderation, as many things can slip past filters by using deception. This time crunch makes content moderation a practically impossible task.

Via Brenton Beck at https://www.facebook.com/groups/TypewriterCollectors/posts/10163613494799678/

https://www.facebook.com/groups/4770669677/user/1183632210/

Janet Schwartz's boyfriend.

https://www.facebook.com/groups/TypewriterCollectors/posts/10163613988099678/

I feel like the trauma and violence these moderators are exposed to should be accounted for in both their salary and their accessibility to mental health resources as a bare minimum for social media companies to supply.

this should be in a good state already.

error recovery is lacking, we need to recover in the case of a dead node

rebase support is critical, we should be able to reuse it

most of this code should be reusable

this should be outside of the workflow

pr right now is opened exclusively via the api endpoint, and only updated asynchronously after a rebase. the workflow should also decouple this, and should allow user review

this is an entirely new agent decision making process

overlayfs will always be the best call here. fsx persists between node reboots that's why the worktree creation is actually very recoverable.

yes 100% they can and they will. each one may have different permutations. if they change their minds they should make another one.

it should have no extraneous external file changes and it should allow us to create a ref with the permissions at time of execution

rebase is critical

extraction step

don't ship patch contents between the activities hahaha we do this now I have a ticket for it

way out of scope, let's stick with the nebari default imo and move the pr template shit to a separate task

I would again add the plan generation in here so we're getting terminal states of everything. design for the ui! encode the steps! state machine!

this is when we rebase which we should be doing otherwise nothing will actually get accepted, if we don't then we end up with a pr that has many many unrelated changes and clients have complained many times

there should be some error recovery, I was told the disks aren't persisted

this isn't the pr open thing yet right? right now, we generate the plan, then the patch, then let user review patch, then iterate on patch, then open pr immediately. that system should be the same imo so it's consistent

again imo this is way out of scope for now, but there's a cache step before and after, and checking if we should invalidate

30 seconds is hopeful hahaha a cargo install can take that just to resolve the versions to download

what happens in between a deploy here? do we reclone? that's the main error case we currently see

for xai I'm not sure I believe this

sbom_remediation_id

getSbomPatchGenerationStatus

triggerSbomPatchGeneration

Sbom is overloaded already!

comments on a pr can also result in changes_requested, as is often the case

the agent should make a decision and output whether or not the pr feedback is actionable. this won't work for all ci mechanisms. we should limit to just 1, like GitHub for now.

this is a can of worms, as soon as I started bringing this up they wanted all of them. that includes Jenkins, self hosted nonsense, bespoke stuff, etc. we should do it but maybe one at a time. I think we have the wiring in place to accept comments.

reusing the existing pr stuff is completely worth doing too so they all benefit from this!

we went from a patch lifecycle to pr lifecycle. is this a terminal state after running the remediation, before a pr is opened? there's missing steps above this

feedback from a user should be included, and there's no running state, we currently miss this in the current ui

started, failed, running, etc are probably good. then you can encode planning as well.

terminal states make sense too. planner_running, plan_generated, patch_running, patch_generated, then *_failed states

we have 2 executions, the plan and the patch

this shouldn't be necessary, you can encode the remediation id in the workflow id and that provides the same thing

we shouldn't denormalize these, you can open multiple prs or update a remediation and that will make this quickly out of sync

this can be extracted from the remediation report

this doesn't cover the client's internal package management, we would need to have a vpn as well as a network policy per client.

and updates any breaking changes

I would also add actually running package managers here

we talked about why we can't do this and why it's not a good idea. we have 0 sandboxing functionality, and most of our clients use their own internal package hosting. all package managers have some level of arbitrary code execution, if we're not running the installs and version numbers ourselves we do run the risk of exposure to completely unknown supply chain attacks if this is done completely agentically. I would stick to simple version bumps in the manifests, and fixing code that needs to be fixed.

essa

Retirar vírgula.

Groves

indy.dweb.archive=Introduction.Groves-Launch.Community~OHS-Launch.community

Author response:

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

Public Reviews:

Reviewer #1 (Public review):

Summary:

The authors report the results of a tDCS brain stimulation study (verum vs sham stimulation of left DLPFC; between-subjects) in 46 participants, using an intense stimulation protocol over 2 weeks, combined with an experience-sampling approach, plus follow-up measures after 6 months.

Strengths:

The authors are studying a relevant and interesting research question using an intriguing design, following participants quite intensely over time and even at a follow-up time point. The use of an experience-sampling approach is another strength of the work.

Weaknesses:

There are quite a few weaknesses, some related to the actual study and some more strongly related to the reporting about the study in the manuscript. The concerns are listed roughly in the order in which they appear in the manuscript.

We truly appreciate your dedicating time and efforts to review our manuscript. Yes, we do perceive that those weaknesses you raised all make sense. We agree with you on almost all the suggestions that you detailed below, particularly in clarifying statistics and sample size determination. Please see specific responses below.

Major Comments

(1) In the introduction, the authors present procrastination nearly as if it were the most relevant and problematic issue there is in psychology. Surely, procrastination is a relevant and study-worthy topic, but that is also true if it is presented in more modest (and appropriate) terms. The manuscript mentions that procrastination is a main cause of psychopathology and bodily disease. These claims could possibly be described as 'sensationalized'. Also, the studies to support these claims seem to report associations, not causal mechanisms, as is implied in the manuscript.

Thank you for this very practical suggestion. We agree that the current statements to underline the importance of procrastination are somewhat overreaching. Upon revision, we have overall toned down such claims by explicitly stating them as “associative evidence”, and rewritten a portion of terms in a more modest and balanced style. Please see specific revisions in the main text below:

Introduction Section (Page 5, Line 64-81)

“Procrastination is increasingly becoming a prevalent behavioral problem around the world, which reflects the irrational voluntary postponement of scheduled tasks albeit being worse off for such delays (Blake, 2019; Steel, 2007). In the epidemiological investigations, more than 15% of adults were identified as having chronic procrastination problems, and the situation for students was worse as 70-80% of undergraduates engaged in procrastination (American College Health Association, 2022; Ferrari et al., 2005). Moreover, the behavioral genetic evidence indicates a certain heritability of procrastination in human beings as well (Gustavson et al., 2017; Gustavson et al., 2014, 2015). In addition to its prevalence, the undesirable associations between procrastination behavior and health also warrant cautions. There is cumulative evidence to show the close associations between procrastination behavior and working performance, financial status, interpersonal relationships, and subjective well-being (Ferrari, 1994; Pychyl & Sirois, 2016; Steel et al., 2021). Further, as the prospective cohort studies indicated, many mental health problems emerge alongside procrastination, particularly in sleep problems, depression, and anxiety (Hairston & Shpitalni, 2016; Johansson et al., 2023). Even worse, chronic procrastination behavior has been observed to impair general health, as manifested by the intimate associations with close system disruption, gastrointestinal disturbance, as well as a high risk of hypertension and cardiovascular disease (Sirois, 2015; Sirois, 2016). ... ”

(2) It is laudable that the study was pre-registered; however, the cited OSF repository cannot be accessed and therefore, the OSF materials cannot be used to (a) check the preregistration or to (b) fill in the gaps and uncertainties about the exact analyses the authors conducted (this is important because the description of the analyses is insufficiently detailed and it is often unclear how they analyzed the data).

We are sorry to encounter a serious technical barrier making our preregistration invisible and inaccessible. The OSF has disabled my OSF account, as it claimed to detect “suspicious user’s activities” in my account (please see the screenshot below). This results in no access to all materials already deposited in this OSF account, including this preregistration. We have contacted the OSF team, but received no valid technical solution to recover this preregistered report. We reckon that this may be triggered by my affiliation change to the Third Military Medical University of the People’s Liberation Army (PLA).

To address this unexpected circumstance and to ensure transparency, we have explicitly reported this case in the main text, and added the “Reconstructed Preregistration Statement” into the Supplemental Materials (SM). Also, as it has been out of best practices in preregistration, in addition to transparently reporting this case, we have removed this statement regarding preregistration elsewhere throughout the whole revised manuscript. Furthermore, we fully understand the gaps of comprehending the statistics of this study, resulting from inadequate methodological details in the reporting. Therefore, we have clearly reported extensive details in the Methods section to clarify how to conduct those analyses, favoring the smooth evaluations of our conclusions. Please see what we have added in the lines below (Comments #4-9).

Methods Section (Page 5, Line 186-191)

“This study fully adhered to CONSORT reporting guidelines, and was originally preregistered in the OSF repository (10.17605/OSF.IO/Y3EDT). However, due to the technical constraint related to OSF account service (see SM), this OSF page is no longer accessible. For transparency and best practices of open science, based on the original protocol documentations, a preregistration statement has been reconstructed to clarify aprior hypotheses, sample size determinations, and analysis plans for this study (Table S1).”

(3) Related to the previous point: I find it impossible to check the analyses with respect to their appropriateness because too little detail and/or explanation is given. Therefore, I find it impossible to evaluate whether the conclusions are valid and warranted.

Again, we apologize for confusing you because of inadequate statistical and methodological details. As you may know, this manuscript has ever been reviewed by Nature Human Behaviour, which editorially constrained the paper length. Thus, a substantial number of details had to be omitted or removed. As you kindly suggested, we have diligently added extensive descriptions to clarify how we carried out statistical analyses in the present study. Please see specific instances underneath.

(4) Why is a medium effect size chosen for the a priori power analysis? Is it reasonable to assume a medium effect size? This should be discussed/motivated. Related: 18 participants for a medium effect size in a between-subjects design strikes me as implausibly low; even for a within-subjects design, it would appear low (but perhaps I am just not fully understanding the details of the power analysis).

Thank you for raising this crucial question. We have determined this a priori effect size based on the existing work we published previously (Xu et al., 2023, J Exp Psychol Gen;152(4):1122-1133). In our pilot study (Xu et al., 2023), we identified a significant interaction effect between the single-session tDCS stimulation (active vs sham) and time (pre-test vs post-test) (t = 2.38, p = .02, n = 27; 95% CI [0.14, 1.49]) for changing procrastination willingness in the laboratory settings, indicating a medium effect size. Therefore, this pilot study provides supportive evidence to determine this effect size a priori. To clarify, we have explicitly justified the selection of this effect size in the Methods section.

Methods Section (Page 5, Line 206-215)

“A full randomized block design was used to assign participants to both groups (active neuromodulation group, NM; sham-control group, SC) (see Fig. 2C). As the pilot study probing into the effect of single-session tDCS stimulation to change procrastination willingness indicated (t = 2.38, p = .02, 95% CI [0.14, 1.49]; Xu et al., 2023), statistical power was predetermined by G*Power at a relatively medium effect size (1-β err prob = 0.80, f = 0.25), yielding the total sample size at 18 to reach acceptable power (see SM Methods and Fig. S1)....”

We fully understand that this sample size to reach a medium effect size is seemingly low, and that the18 participants for each group are apparently limited in any case. Upon double-checking these power analyses, we confirmed that this sample size requirement is indeed correct. Please see the G*Power outputs in Author response image 1.

Author response image 1.

Despite the absence of algorithmic errors in the power analysis here, we are aware that this limited sample size may hamper statistical robustness. To tackle this weakness, we have clearly warranted such cautions in the Limitation section:

Limitations Section (Page 12, Line 637-640)

“... In addition to technical limitations, given the apparently limited size of the sample (total N = 46), it warrants caution in generalizing these findings elsewhere, and necessitates further validations in a large-scale cohort.”

(5) It remains somewhat ambiguous whether the sham group had the same number of stimulation sessions as the verum stimulation group; please clarify: Did both groups come in the same number of times into the lab? I.e., were all procedures identical except whether the stimulation was verum or sham?

Yes, we fully followed the CONSORT pipeline to carry out this double-blind trial, and thus confirmed that all the participants in both groups had the same number of stimulation sessions in our lab. That is to say, except for the stimulation type (verum vs sham), all the procedures, equipment and even the room were identical for all the participants. For clarification, we have clearly stated this in the main text:

Results Section (Page 9, Line 419-423)

“In both groups, almost all participants (93.2%, 41/44) reported perceiving acceptable pain stemming from current stimulation, and believed they were receiving treatment (91.30% (21/23) for active neuromodulation group (NM), 86.95% (20/23) for sham control group (SC), x² = 0.224, p = .636). All the participants were engaged in the identical experimental procedures excepting to stimulation’s type (active vs sham). ...”

(6) The TDM analysis and hyperbolic discounting approach were unclear to me; this needs to be described in more detail, otherwise it cannot be evaluated.

We apologize for the inadequate details, which hindered a precise understanding of the TDM and the hyperbolic discounting model. The Temporal Decision Model (TDM) was originally proposed by our team (Xu et al., 2023; Zhang et al., 2019, 2020, 2021), which theoretically conceptualizes procrastination as the failure of trade-off between task outcome value (i.e., motivation to take actions now for pursuing task reward) and task aversiveness (i.e., motivations to take away from playing actions now for avoiding negative experiences). Once task aversiveness overrides the pursuit of task outcome values, the procrastination emerges. One overarching hypothesis in this theoretical model is that the task aversiveness is hyperbolically discounted when approaching the deadline: it would be discounted sharply when far from the deadline but discounted slowly when nearing the deadline (Zhang et al., 2019). Considering the nonlinear dynamics inherent in this hyperbolic discounting, we therefore employed a log-spaced temporal sampling scheme (Myerson et al., 2001) to strengthen curve-fitting performance (please see the schematic diagram (https://uen.pressbooks.pub/behavioraleconomics/chapter/the-reality-of-homo-sapiens, where each point indicates a sampling time)):

Specifically, based on the log-spaced temporal sampling rule, five time points were first selected to fulfill the statistical prerequisites for hyperbolic model fitting, with increasing sampling density toward the deadline (e.g., for a task due at 20:00: sampling occurred at 10:00, 16:00, 18:00, 19:30, 20:00). At each time point, participants reported task aversiveness (A) on a 0–100 Visual Analog Scale (VAS). Then, task aversiveness discounting was calculated as 1- (A_t / A_earliest), where t_earliest was the earliest sampling point (e.g., 10:00), serving as the reference for immediate execution. Subsequently, using the GraphPad Prisma software (v9, 525), we estimated the AUC from these five data points based on the Myerson algorithm (Myerson et al., 2001), which was computed as the trapezoidal integration of task aversiveness discounting over time. By this modelling method, a higher AUC reflects stronger temporal discounting of task aversiveness, which means that participants experience a faster decline in subjective aversiveness as execution is delayed, yielding lower effective aversiveness and reduced avoidance behavior. That is to say, if a participant showcases a greater discounting of task aversiveness as reflected by a higher AUC, she/he experiences a more pronounced reduction in subjective aversiveness upon postponement, plausibly yielding less procrastination. As you kindly suggested, we have added these details to explicitly clarify how to use the hyperbolic discounting approach for determining sampling time points and for calculating AUC of task aversiveness discounting.

Methods Section (Page 6, Line 268-283)

“On the Task day, we developed a mobile app to implement experience sampling method (ESM) for tracking one’s real-time evaluation of task aversiveness and task outcome value (see Fig. 1). The task aversiveness describes how disagreeable one perceives when performing a given real-life task to be, whereas outcome value refers to the subjective benefits of the task outcome brought about by completing the task before the deadline (Zhang & Feng, 2020). As theoretically conceptualized by the temporal decision model (TDM) of procrastination, the perceived task aversiveness is hyperbolically discounted when approaching deadline, showing sharply discounting when faring away from deadline but slowly discounting once nearing deadline (Zhang & Feng, 2020; Zhang et al., 2021). Thus, considering this nonlinear dynamics inherent in this hyperbolic discounting, the five recording moments of ESM were selected per task a priori by using a log-spaced temporal sampling scheme (Myerson et al., 2001), with increasing sampling density toward the deadline, such as moments of 10:00 (earliest), 16:00, 18:00, 19:30, 20:00 (deadline). The five sampling points could meet statistical prerequisite in the hyperbolic model fitting, requiring ≥ 4 points (Green & Myerson, 2004). To do so, recording moments of tasks were individually tailored for each task per participant in this ESM procedure.”

Methods Section (Page 7, Line 318-334)

“... As articulated temporal decision theoretical model above, the task aversiveness evoked by executing a task was temporally dynamic in a hyperbolic discounting pattern, with sharply discounting in faring away from deadline but slowly discounting in nearing deadline (Zhang & Feng, 2020). To quantitatively characterize the task aversiveness with consideration for its dynamics, the model-free area under the curve (AUC) was calculated. Specifically, based on the log-spaced temporal sampling rule, task aversiveness was measured by 100-point visual analog scale at the five sampling moments. Then, the task aversiveness discounting (A) was calculated as 1- (A(t) / A(earliest)), where t(earliest) was the earliest sampling point, serving as the reference for immediate execution. Subsequently, using the GraphPad Prisma software (v9, 525), the AUC was computed as the trapezoidal integration between task aversiveness discounting and time across five data points, basing on the Myerson algorithm (Myerson et al., 2001). By doing so, a higher AUC reflects stronger temporal discounting of task aversiveness along with nearing deadline, which means that participants experience a faster decline in subjective aversiveness as execution is delayed, yielding lower effective aversiveness and reduced avoidance behavior. As for the task outcome value, it was theoretically posited as a relatively stable evaluation of the task (Zhang & Feng, 2020; Zhang et al., 2021).”

References

Myerson, J., Green, L., & Warusawitharana, M. (2001). Area under the curve as a measure of discounting. Journal of the experimental analysis of behavior, 76(2), 235–243. https://doi.org/10.1901/jeab.2001.76-235

Xu, T., Zhang, S., Zhou, F., & Feng, T. (2023). Stimulation of left dorsolateral prefrontal cortex enhances willingness for task completion by amplifying task outcome value. Journal of experimental psychology. General, 152(4), 1122–1133. https://doi.org/10.1037/xge0001312

Zhang, S., Verguts, T., Zhang, C., Feng, P., Chen, Q., & Feng, T. (2021). Outcome Value and Task Aversiveness Impact Task Procrastination through Separate Neural Pathways. Cerebral cortex (New York, N.Y. : 1991), 31(8), 3846–3855. https://doi.org/10.1093/cercor/bhab053

Zhang, S., Liu, P., & Feng, T. (2019). To do it now or later: The cognitive mechanisms and neural substrates underlying procrastination. Wiley interdisciplinary reviews. Cognitive science, 10(4), e1492. https://doi.org/10.1002/wcs.1492

Zhang, S., & Feng, T. (2020). Modeling procrastination: Asymmetric decisions to act between the present and the future. Journal of experimental psychology. General, 149(2), 311–322. https://doi.org/10.1037/xge0000643

(7) Coming back to the point about the statistical analyses not being described in enough detail: One important example of this is the inclusion of random slopes in their mixed-effects model which is unclear. This is highly relevant as omission of random slopes has been repeatedly shown that it can lead to extremely inflated Type 1 errors (e.g., inflating Type 1 errors by a factor of then, e.g., a significant p value of .05 might be obtained when the true p value is .5). Thus, if indeed random slopes have been omitted, then it is possible that significant effects are significant only due to inflated Type 1 error. Without more information about the models, this cannot be ruled out.

Thank you for sharing this very timely and crucial comment. After careful scrutiny, we identified this statistical flaw you pointed out - each participant was not yet modeled as random slopes but as random intercepts merely. As you kindly suggested, we have reanalyzed all the statistics by adding random slopes (i.e., (1 + day|SubjectID)). Results showed a statistically significant interaction effect for both procrastination willingness (β = -7.8, SE = 1.8, DF = 45.6, p < .001) and actual procrastination rates (β = -7.4, SE = 2.4, DF = 46.6, p = .004), indicating the effectiveness of multi-session neuromodulation in mitigating procrastination. In the post-hoc simple effect analyses, participants who engaged in active neuromodulation (NM) showed a significant increase in task-execution willingness (i.e., decreased procrastination willingness; NM-before: 35.65 ± 30.20, NM-after: 80.43 ± 19.92, t.ratio = 5.4, p < .0001, Tukey correction) and a decrease in actual procrastination rates (NM-before: 43.26 ± 39.09, NM-after: 0.00 ± 0.00, t.ratio = 5.1, p < .0001, Tukey correction), while no such effects were identified for participants in the sham control group (for willingness, SC-before: 37.57 ± 26.46, SC-after: 47.35 ± 30.49, t.ratio =0.3, p = .77, Tukey correction; for actual procrastination, SC-before: 46.47 ± 40.75, SC-after: 33.34 ± 37.82, t.ratio = 0.7, p = .48, Tukey correction). Taken together, we do appreciate your pointing out this definitely crucial statistical weakness, and have confirmed that our findings remain reliable after adjusting for Type 1 error by adding random slopes. Moreover, as you kindly suggested, we have incorporated these statistical details, particularly those concerning the GLMM, into the main text to facilitate your evaluation. Please see specific revisions below:

Methods Section (Page 8, Line 381-401)

“To clarify whether multiple-session HD-tDCS neuromodulation can reduce procrastination, the generalized mixed-effects linear model (GLMM) was constructed with full factorial design for subjective procrastination willingness (i.e., self-reported visual analog scores) and actual procrastination behavior (i.e., real-world task-completion rate before deadline). Here, sex, age and socioeconomic status (SES) were modeled as covariates of no interest. As the National Bureau of Statistics (China) issued (https://www.stats.gov.cn/sj/tjbz/gjtjbz/), on the basis of per capita annual household income, the SES was divided into seven hierarchical tiers from 1 (poor) to 7 (rich). To obviate subjective rating bias stemming from individual daily mood, we separately measured participants’ daily emotional fluctuation at 10:00 and 16:00 using a self-rating visual analog item (i.e., “How do feel for your mood today?”, 0 for “completely uncomfortable” and 100 for “definitely happy”). By doing so, the averaged score of those self-rating emotions at the two time points was modeled into the GLMM as covariate of no interests, yielding the final expression of “outcome ~ Group*Treatment_Day + Age + Gender + SES + Emotions + (1 + Treatment_Day | SubjectID)” in the statistical model”. This analysis was implemented using the “lme4” and “lmerTest” packages. Employing “emmeans” package, simple effects were also tested at baseline and post-last-intervention using Tukey-adjusted pairwise comparisons of estimated marginal means from the full GLMM, controlling for covariates and random-effects structure. To validate statistical robustness, instead of continuous outcomes for parametric tests, we also conducted a between-group comparison for the number of tasks that procrastination emerges by using the nonparametric x² test with φ correction or Fisher exact test....”

Results Section (Page 9, Line 428-449)

“To identify whether ms-tDCS targeting the left DLPFC can alleviate subjective procrastination willingness and actual procrastination behavior, a generalized linear mixed-effects model with Scatterthwaite algorithm was built, with task-execution willingness and actual procrastination rates (PR) as primary outcomes, respectively. For procrastination willingness, results showed a statistically significant interaction effect between multi-session neuromodulations and groups (β = -7.8, SE = 1.8, DF = 45.6, p < .001; Fig. 3A). In the post-hoc simple effect analysis, it demonstrated a significantly increased task-execution willingness (i.e., decreased procrastination willingness) after neuromodulation in the active neuromodulation group (NM-before: 35.65 ± 30.20, NM-after: 80.43 ± 19.92, t.ratio = 5.4, p < .0001, Tukey correction), but no such effects were identified in the sham control group (SC-before: 37.57 ± 26.46, SC-after: 47.35 ± 30.49, t.ratio =0.3, p = .77, Tukey correction) (Fig. 3B-C). A linear uptrend for task-execution willingness was further observed across multiple sessions in the active NM group, indicating gradually increasing neuromodulation effects (Fig. 3D; p < .01, Mann-Kendall test). For actual procrastination behavior, changes to actual procrastination rates across all the sessions have been detailed in the Fig. 3E. Similarly, a statistically significant interaction effect was identified here (β = -7.4, SE = 2.4, DF = 46.6, p = .004), and the simple effect analysis further revealed decreased actual procrastination rates after ms-tDCS in the active neuromodulation group (NM-before: 43.26 ± 39.09, NM-after: 0.00 ± 0.00, t.ratio = 5.1, p < .0001, Tukey correction), but no such prominent changes found in the sham control group (SC-before: 46.47 ± 40.75, SC-after: 33.34 ± 37.82, t.ratio = 0.7, p = .48, Tukey correction) (Fig. 3F-G). Also, a significant downtrend for procrastination rates across all the sessions was identified in the active NM group (Fig. 3H; p < .01, Mann-Kendall test).”

(8) Related to the previous point: The authors report, for example, on the first results page, line 420, an F-test as F(1, 269). This means the test has 269 residual degrees of freedom despite a sample size of about 50 participants. This likely suggests that relevant random slopes for this test were omitted, meaning that this statistical test likely suffers from inflated Type 1 error, and the reported p-value < .001 might be severely inflated. If that is the case, each observation was treated as independent instead of accounting for the nestedness of data within participants. The authors should check this carefully for this and all other statistical tests using mixed-effects models.

Thank you for underlining this very timely and helpful comment. As you correctly pointed out above, we did not include random slopes in the original GLMM, highly risking the inflation of the false-positive rate (i.e., Type-I error). By adding the random slopes, we reanalyzed all the statistics from the GLMM, and confirmed that all the findings are still reliable from those new GLMMs with random slopes. Again, thank you for this crucial statistical advice, and please see the above response for full details regarding what we have revised to address this comment you kindly raised.

(9) Many of the statistical procedures seem quite complex and hard to follow. If the results are indeed so robust as they are presented to be, would it make sense to use simpler analysis approaches (perhaps in addition to the complex ones) that are easier for the average reader to understand and comprehend?

We do thank you for this practical and helpful comment. In the original manuscript, we incorporated a joint model of longitudinal and survival data (JM-LSD), in conjunction with machine learning algorithms, to strengthen the robustness of our statistical findings. Nevertheless, we all agree with you on this point: there is no need to complicate the analyses by repeatedly probing the same research question to increase methodological robustness, at the expense of compromising readability and intelligibility for a broader audience. As you suggested, we have removed these complicated statistical methods, and merely maintained the primary ones - GLMM and X² cross-tab test, as well as a complementary one - Mann-Kendall linear trend test. Thus, we have almost rewritten the whole Results section. Please see the specific instances below:

Results Section (Page 9, Line 468-485)

“Ms-tDCS changes task aversiveness and task-outcome value

Both task aversiveness and task outcome value serve as key pathways determining whether one would procrastinate. To this end, we further utilized a generalized linear mixed-effects model to examine the effects of ms-tDCS on changes in task aversiveness and task outcome value. Task aversiveness changes across all the sessions are shown in the Fig. 4A and 4C. We demonstrated a statistically significant decrease in task aversiveness and an increase in task outcome value via ms-tDCS in the neuromodulation group (Task aversiveness: interaction effect, β = -0.12, SE = 0.04, DF = 46.7, p = .002; simple effect, NM-before _(AUC): 1.13 ± 0.53, NM-after _(AUC): 1.95 ± 0.85, t.ratio = 4.5, p < .001, Tukey correction; Outcome value: β = -6.8, SE = 1.74, DF = 46.2, p < .001; simple effect, NM-before: 35.86 ± 27.82, NM-after: 73.08 ± 23.33, t.ratio = 5.0, p < .001, Tukey correction; see Fig. 4B), but not in the sham control group (Task aversiveness: SC-before _(AUC): 1.07 ± 0.51, SC-after _(AUC): 1.28 ± 0.46, t.ratio = 1.3, p = .20, Tukey correction; Outcome value: SC-before: 34.00 ± 25.17, SC-after: 40.13 ± 28.94, t.ratio = 0.8, p = .41, Tukey correction; see Fig. 4D). In the neuromodulation (NM) group, task aversiveness steadily decreased with the cumulative number of stimulation sessions, while perceived task outcome value increased significantly (see Fig. 4E-F, p < .05, Mann-Kendall test). Thus, it provides causal evidence clarifying that neuromodulation to left DLPFC reduces task aversiveness and enhances task-outcome value meanwhile.”

Results Section (Page 10, Line 525-542)

“Long-term effects of ms-tDCS

We have also attempted to conduct a follow-up investigation to test the long-term retention of ms-tDCS in reducing actual procrastination. Almost all the participants had undergone follow-up except one in the neuromodulation group after last neuromodulation for 6 months (N_NM = 22, N_SC = 23). Thus, the GLMM was constructed, with the PR before first neuromodulation vs. PR after last neuromodulation for 6 months as covariates of interest. Results showed the statistically significant group*time interaction effects (β = 16.5, SE = 9.9, p = .049). Simple-effect model demonstrated a decrease in actual procrastination rates in the active neuromodulation group after last stimulation for 6 months compared to baseline (β = -22.05, SE = 10.0, p = .038, Tukey correction; NM-before: 40.68 ± 37.96, NM-after_6-months: 18.63 ± 29.80), and revealed null effects in the SC group (β = 1.26, SE = 9.78, p = .99, Tukey correction; SC-before: 46.47 ± 40.75, SC-after_6-months: 47.73 ± 39.18) (see Fig. 6).. Furthermore, using a nonparametric x² test to compare differences in the number of procrastinated tasks, we still found a statistically significant reduction in procrastination frequency in NM group after neuromodulation for 6 months compared to baseline (x² = 3.30, p = .035, NM-before: 68.19% (15/22), NM-after_6-months: 40.91% (9/22)), while no significant changes were observed in the SC group (x² = 0.11, p = .74, SC-before: 69.56% (16/23), SC-after_6-months: 73.91% (17/23)). Therefore, beyond to short-term effects, the benefits of ms-tDCS neuromodulation to reduce procrastination pose the long-term retention.”

(10) As was noted by an earlier reviewer, the paper reports nearly exclusively about the role of the left DLPFC, while there is also work that demonstrates the role of the right DLPFC in self-control. A more balanced presentation of the relevant scientific literature would be desirable.

We are grateful to you for noticing the unbalanced presentation of the literature on left DLPFC. As you kindly suggested, we have added literature to support the association between self-control and the right lateralization of the DLPFC. Please see below for what we have revised:

Introduction Section (Page 4, Line 137-143)

“...In addition to the left lateralization, there is solid evidence indicating significant associations between self-control and the right DLPFC indeed, particularly given that this region specifically functions in top-down regulation, future self-continuity representation and social decisions (Huang et al., 2025; Lin and Feng, 2024; Knoch & Fehr, 2007). Despite this case, Xu and colleagues demonstrated null effects of anodally stimulating the right DPFC to modulate either value evaluation or emotional regulation for changing procrastination willingness (Xu et al., 2023).”

(11) Active stimulation reduced procrastination, reduced task aversiveness, and increased the outcome value. If I am not mistaken, the authors claim based on these results that the brain stimulation effect operates via self-control, but - unless I missed it - the authors do not have any direct evidence (such as measures or specific task measures) that actually capture self-control. Thus, that self-control is involved seems speculation, but there is no empirical evidence for this; or am I mistaken about this? If that is indeed correct, I think it needs to be made explicit that it is an untested assumption (which might be very plausible, but it is still in the current study not empirically tested) that self-control plays any role in the reported results.

We truly appreciate your pointing out this weakness with regard to conceptualization. Yes, you are correct in understanding this causal chain: we conceptually speculate that the HD-tDCS stimulation over the left DLPFC operates self-control to change procrastination, rather than empirically validating this component in the chain: brain stimulation→increased self-control→increased task outcome value→decreased procrastination. In this causal chain, we did not collect data to directly measure self-control at either baseline or post-neuromodulation times. Therefore, we all agree with your suggestion to explicitly claim this case in the main text. Following this advice, we have redrawn a portion of the Conclusion by clearly pointing out the hypothesis-generating role of self-control in mitigating procrastination, and have further claimed this case in the Limitation section:

Abstract Section (Page 2, Line 55-57)

“... This establishes a precise, value-driven neurocognitive pathway to account the conceptualized roles of self-control on procrastination, and offers a validated, theory-driven strategy for interventions.”

Results Section (Page 10, Line 489-492 and 520-522)

“Given the dual neurocognitive pathways identified above—reduced task aversiveness and increased task-outcome value—we proposed that these changes, conceptually driven by enhanced self-control via ms-tDCS over left DLPFC, account for how neuromodulation reduces procrastination. ...”

“In summary, these findings demonstrated a mechanistic pathway underlying procrastination: the self-control that was conceptualized to be governed by left DLPFC mitigate procrastination by plausibly increasing task-outcome value.”

Discussion Section (Page 13, Line 642-645)

“Moreover, this study did not collect data for assessing participants’ self-control at either baseline or post-neuromodulation, thereby limiting our ability to determine whether the effects on procrastination were uniquely attributable to neuromodulation-induced changes in self-control. ...”

(12) Figures 3F and 3H show that procrastination rates in the active modulation group go to 0 in all participants by sessions 6 and 7. This seems surprising and, to be honest, rather unlikely that there is absolutely no individual variation in this group anymore. In any case, this is quite extraordinary and should be explicitly discussed, if this is indeed correct: What might be the reasons that this is such an extreme pattern? Just a random fluctuation? Are the results robust if these extreme cells are ignored? The authors remove other cells in their design due to unusual patterns, so perhaps the same should be done here, at least as a robustness check.

Thank you for raising this highly important and helpful comment. Indeed, we fully understand that this result is somewhat extraordinary, a fact that was equally striking to us when unblinding the data. After carefully scrutinizing the data and statistics, we are thrilled to confirm that this pattern is true. In support of this observation, we were gratified to receive numerous thank-you letters from participants who engaged in active neuromodulation. They expressed gratitude to us, and reported that they have substantially ameliorated procrastination behavior in real-life activities after completing the trial. While this does not constitute formal scientific evidence, we are also glad to see the benefits of this neuromodulation for those procrastinators.

Two reasons could account for this pattern herein. One interpretation is to attribute this pattern to “scalar inflation”. In the present study, the procrastination rate was calculated as 1 minus the task-completion rate (e.g., 80%, 60%, 40%) by the deadline. At sessions # 6 and #7, all the participants completed their real-life tasks before the deadline, yielding a 0% (1 minus 100% completion rate) procrastination rate, without any between-individual variation. Thus, rather than there being no individual variation in procrastination, this scalar – the procrastination rate - is too insensitive to capture subtle differences per se. For instance, although participants #1 and #2 both showed a 0% procrastination rate - meaning that both completed their tasks before the deadline - Participant #1 might have completed it 3 hours before the deadline, whereas Participant #2 might have completed it only 10 minutes before. In this case, the “scalar inflation” emerges to let us perceive that both participants have equivalent procrastination rates, although participant #2 may have a higher procrastination level than #1. As conceptually defined in the field, procrastination is contextualized as “not completing a task before the deadline”. Thus, if this task is completed before the deadline, regardless of whether it was finished close to or far in advance of the deadline, this case is defined as “no procrastination”. In the present study, the primary outcome is whether a participant procrastinated on a real-life task before the deadline in real-world settings, irrespective of when she/he completed this task. Thus, this scalar - procrastination rate - fits our conceptualization of procrastination.

Another reason is the potential accumulative effects from sequential multi-session tDCS stimulation. As shown in Mann-Kendall trend tests, the procrastination rates show a significant linear downtrend in the active neuromodulation group across sessions, even after removing sessions #6 and #7. This indicates that the improvements of going against procrastination may be sequentially accumulative along with the increase in sessions, implying a potential “dose-dependent effect”. Despite a speculative interpretation, this “dose-dependent effect” in neuromodulation has been well-documented in previous studies, showing the robustly linear association between the number of sessions and effectiveness (c.f., Cole et al., 2020; Hutton et al., 2023; Sabé et al., 2024; Schulze et al., 2018). Therefore, although this extreme pattern is somewhat extraordinary compared to previous observations, it makes sense.

Yes, this is a definitely great idea to carry out a robustness check by removing sessions #6, #7, or both. We do believe that this analysis could support statistical robustness to go against potential biases from extreme cells. By doing so, we found that all the group*treatment_day interaction effects remained significant when removing either session #6 or session #7 (or even both, all p-values < .05), indicating high statistical robustness. Please see Supplementary table S3 and S4

Taken together, in spite of their being extraordinary, we confirm that those findings are statistically robust to extreme outliers. As you kindly suggested, we have added those findings of the robustness check into the revised Supplemental Materials section.

References

Cole, E. J., Stimpson, K. H., Bentzley, B. S., Gulser, M., Cherian, K., Tischler, C., Nejad, R., Pankow, H., Choi, E., Aaron, H., Espil, F. M., Pannu, J., Xiao, X., Duvio, D., Solvason, H. B., Hawkins, J., Guerra, A., Jo, B., Raj, K. S., Phillips, A. L., … Williams, N. R. (2020). Stanford Accelerated Intelligent Neuromodulation Therapy for Treatment-Resistant Depression. The American journal of psychiatry, 177(8), 716–726. https://doi.org/10.1176/appi.ajp.2019.19070720

Hutton, T. M., Aaronson, S. T., Carpenter, L. L., Pages, K., Krantz, D., Lucas, L., Chen, B., & Sackeim, H. A. (2023). Dosing transcranial magnetic stimulation in major depressive disorder: Relations between number of treatment sessions and effectiveness in a large patient registry. Brain stimulation, 16(5), 1510–1521. https://doi.org/10.1016/j.brs.2023.10.001

Sabé, M., Hyde, J., Cramer, C., Eberhard, A., Crippa, A., Brunoni, A. R., Aleman, A., Kaiser, S., Baldwin, D. S., Garner, M., Sentissi, O., Fiedorowicz, J. G., Brandt, V., Cortese, S., & Solmi, M. (2024). Transcranial Magnetic Stimulation and Transcranial Direct Current Stimulation Across Mental Disorders: A Systematic Review and Dose-Response Meta-Analysis. JAMA network open, 7(5), e2412616. https://doi.org/10.1001/jamanetworkopen.2024.12616

Schulze, L., Feffer, K., Lozano, C., Giacobbe, P., Daskalakis, Z. J., Blumberger, D. M., & Downar, J. (2018). Number of pulses or number of sessions? An open-label study of trajectories of improvement for once-vs. twice-daily dorsomedial prefrontal rTMS in major depression. Brain stimulation, 11(2), 327–336. https://doi.org/10.1016/j.brs.2017.11.002

(13) The supplemental materials, unfortunately, do not give more information, which would be needed to understand the analyses the authors actually conducted. I had hoped I would find the missing information there, but it's not there.

Sorry to offer uninformative supplemental materials (SM) in the original submission. As you suggested, we have added a substantial number of details to clarify how we conducted data analyses in the main text, and also tightened the whole SM section to improve readability and comprehensibility. We do hope that this revised manuscript could offer clear and adequate information in understanding methods and statistics for broader readers.

In sum, the reported/cited/discussed literature gives the impression of being incomplete/selectively reported; the analyses are not reported sufficiently transparently/fully to evaluate whether they are appropriate and thus whether the results are trustworthy or not. At least some of the patterns in the results seem highly unlikely (0 procrastination in the verum group in the last 2 observation periods), and the sample size seems very small for a between-subjects design.

Thank you for this very helpful summary. As you kindly suggested above, we have overhauled this manuscript to address those points that you listed here, particularly where we added relevant literature to balance our claims, added a huge amount of details to sufficiently/transparently report statistics, and conducted a robustness check to confirm the statistical robustness of our findings to those plausible extreme patterns (sessions #6 and #7), as well as justified how we determined this sample size fulfilling medium statistical power in a priori. Please see above for full details regarding how we addressed those comments, point-by-point.

Reviewer #2 (Public Review):

Chen and colleagues conducted a cross-sectional longitudinal study, administering high-definition transcranial direct stimulation targeting the left DLPFC to examine the effect of HD-tDCS on real-world procrastination behavior. They find that seven sessions of active neuromodulation to the left DLPFC elicited greater modulation of procrastination measures (e.g., task-execution willingness, procrastination rates, task aversiveness, outcome value) relative to sham. They report that tDCS effects on task-execution willingness and procrastination are mediated by task outcome value and claim that this neuromodulatory intervention reduces procrastination rates quantified by their task. Although the study addresses an interesting question regarding the role of DLPFC on procrastination, concerns about the validity of the procrastination moderate enthusiasm for the study and limit the interpretability of the mechanism underlying the reported findings.

Strengths:

(1) This is a well-designed protocol with rigorous administration of high-definition transcranial direct current stimulation across multiple sessions. The approach is solid and aims to address an important question regarding the putative role of DLPFC in modulating chronic procrastination behavior.

(2) The quantification of task aversiveness through AUC metrics is a clever approach to account for the temporal dynamics of task aversiveness, which is notoriously difficult to quantify.

Thank you for taking your invaluable time to review our manuscript, warmly applauding the strength in research design and the conceptualization of scaling task aversiveness, as well as kindly sharing such helpful and insightful evaluations. As you correctly pointed out, we are aware of the absence of detailed, clear and understandable reporting of measures (e.g., real-world procrastination), statistics and methods, in the original manuscript. Following all your suggestions, we have thoroughly revised this manuscript to address those comments that you kindly made, point-by-point. Please see the full response underneath.

Weaknesses:

(1) The lack of specificity surrounding the "real-world measures" of procrastination is problematic and undermines the strength of the evidence surrounding the DLPFC effects on procrastination behavior. It would be helpful to detail what "real-world tasks" individuals reported, which would inform the efficacy of the intervention on procrastination performance across the diversity of tasks. It is also unclear when and how tasks were reported using the ESM procedure. Providing greater detail of these measures overall would enhance the paper's impact.

We genuinely appreciate your raising this very crucial comment. We are sorry for omitting a tremendous number of methodological details to comply with the editorial requirement on the manuscript’s length, which hampered the comprehension of how we measure “real-life tasks” and “real-world procrastination”.

As shown in the schematic diagram for experimental procedure (Fig. 1), the experimental protocol alternated between Neuromodulation Days (Days 2, 4, 6, 8, 10, 12, 14) and Task Days (Days 1, 3, 5, 7, 9, 11, 13, 15). On each Neuromodulation Day, participants received either active or sham HD-tDCS, and—critically—before stimulation—were instructed to specify a real-life task they were required to complete the following day, with a deadline between 18:00 and 24:00. This ensured ≥24 hours between neuromodulation and task execution, isolating offline after-effects. For instance, on Day #2 (Neuromodulation Day), before carrying out stimulation, participants were asked to report a real-life task that has a deadline within 18:00 - 24:00 for tomorrow’s “task day” (Day #3) (please see the schematic diagram in Author response image 2).

Author response image 2.

There are some real-life tasks that they reported in our experiment as examples: “Complete and submit a homework assignment”, “Complete a standardized English proficiency test”, “Complete an online course module required for applying a Class C driver’s license”, “Prepare slides for a seminar presentation”, “Practice guitar”, “Practice Chinese calligraphy”, and “Do the laundry”. Reported tasks spanned academic (e.g., submitting an assignment), occupational (e.g., preparing a presentation), administrative (e.g., applying for a license), self-improvement (e.g., practicing guitar for ≥30 min), domestic (e.g., laundry), and health-related domains (e.g., running ≥ 2,000m for exercise), indicating a plausible task diversity.

On each “task day”, participants engaged in an intensive Experience Sampling Method (iESM) protocol via a custom-built mobile app. Using this app, participants were required to report a subjective task-execution willingness score (i.e., a one-item 100-point visual analog scale, “How willing are you to do this task?”, 0 for “I will definitely procrastinate this task” and 100 for “I will take action to complete this task immediately”; procrastination willingness = 100 – the task-execution willingness score), the subjective task aversiveness (i.e., a one-item 100-point visual analog scale), the subjective task outcome value (i.e., a one-item 100-point visual analog scale), and the objective procrastination rate, respectively.

Rather than self-reported scores from those one-item visual analog scales, we asked participants to report real “task completion rate” for the objective quantification of the “real-world procrastination behavior”. Specifically, at the deadline, each participant was asked to report whether she/he had completed this task. If she/he reported not having yet completed the task (i.e. procrastination behavior emerged), she/he was further required to report the percentage of the task completed (1% - 99%), which was defined as the task completion rate. By doing so, we could calculate the real-world procrastination rate for the real-life task as the “1 – the task completion rate”. For instance, if a participant did not complete her/his real-life task before the deadline (i.e. she/he procrastinated this task) and reported completing 75% of this task at the deadline, her/his real-world procrastination rate was computed as the 25% (1 - 75%) (Please see the schematic diagram in Author response image 3).

Moreover, rather than merely a self-reported task completion rate, each participant was also asked to upload proof (e.g., screenshots of submitted assignments, photos of printed documents, system timestamps) to the ESM digital system for validation.

Author response image 3.

To determine the sampling time points for this mobile app in the ESM, we capitalized on both the conceptual temporal decision model and the statistical Myerson algorithm. Specifically, the Temporal Decision Model (TDM) was originally proposed by our team (Xu et al., 2023; Zhang et al., 2019, 2020, 2021), which theoretically conceptualizes procrastination as the failure of the trade-off between task outcome value (i.e., motivation to take actions now for pursuing task reward) and task aversiveness (i.e., motivations for avoiding taking action now for avoiding negative experiences). Once task aversiveness overrides the pursuits of task outcome values, procrastination emerges. One overarching hypothesis in this theoretical model is that the task aversiveness is hyperbolically discounted when approaching the deadline: it would be discounted sharply when far from the deadline but discounted slowly when nearing the deadline (Zhang et al., 2019). To maximize statistical power to fit dynamic motivational curves, we employed a log-spaced temporal sampling scheme (Myerson et al., 2001) (please see the schematic diagram in https://uen.pressbooks.pub/behavioraleconomics/chapter/the-reality-of-homo-sapiens, where each point indicates a sampling time):

By this fitting algorithm (Myerson et al., 2001), five time points were selected to fulfill the statistical prerequisites for hyperbolic model fitting, with increasing sampling density toward the deadline (e.g., for a task due at 20:00: sampled at 10:00, 16:00, 18:00, 19:30, 20:00). Once the task-specific five sampling time points were determined per participant, this mobile app sent a digital message to ask her/him to immediately report the task aversiveness and the task outcome value then. As the primary outcomes, the procrastination rate (i.e., 1 – the task completion rate) and the procrastination willingness were sampled at the deadline point.

Furthermore, yes, we fully concur with you on this great idea, that is, transparency about task diversity strengthens the generalizability of our findings. In response, we have tabulated these real-life tasks that were reported in this experiment in the independent Appendix 1, with automatic translations from Chinese to English via Qwen GPT. Please see below for what we have added to the main text:

Methods Section (Page 6-7, Line 238-308)

“Nested cross-sectional longitudinal design

This study used a nested cross-sectional longitudinal design to investigate whether the multiple-session anodal HD-tDCS targeting the left DLPFC could reduce actual procrastination behavior and to probe how this effect manifests. To assess procrastination in daily life, we implemented a 15-day protocol alternating between Neuromodulation Days (Days 2, 4, 6, 8, 10, 12, 14) and Task Days (Days 1, 3, 5, 7, 9, 11, 13, 15). On the Neuromodulation days, the 20-min anodal HD-tDCS neuromodulation targeting the left DLPFC was performed for HD-tDCS active group at intervals of 2 days, while the sham-control group received sham HD-tDCS training. This HD-tDCS training was repeated for a total of seven sessions, and lasted 15 days (see Fig. 1a). Crucially, to capture procrastination in ecologically valid contexts, prior to receiving either active or sham HD-tDCS (administered between 09:00–18:00), participants were instructed to specify a real-life task they were personally obligated to complete the following day, with a self-defined deadline strictly constrained to 18:00–24:00 to ensure ≥24 hours between stimulation offset and task deadline, thereby isolating offline after-effects. This task should meet the following three criteria: (a) it should be already assigned in the real-world settings; (b) deadline should be constrained to 18:00-24:00 (see above); (c) it should be more likely to induce procrastinate. By doing so, more than 300 real-life tasks were collected, spanning academic (e.g., “submit a statistics homework assignment”), occupational (e.g., “draft and email a project proposal”), administrative (e.g., “complete online application for Class C driver’s license”), self-improvement (e.g., “practice guitar for ≥30 minutes”), domestic (e.g., “do laundry ”), and health-related (e.g., “running 2,000m for exercise”). Full task list has been tabulated in the Appendix 1. As primary outcomes, all the participants were required to reported task-execution willingness (TEW) (Zhang & Feng, 2020; Zhang, Liu, et al., 2019), for a real-life task 24 hours post-neuromodulation. Thus, procrastination willingness was quantified as 100-TEW score (see underneath for details). Furthermore, we asked participants to report the actual task completion rate (CR) of the task at the deadline (e.g. participant A finished 90% homework at deadline and reported this situation to us at deadline). In this vein, the actual procrastination rate (PR) was quantified as 1-CR.

On the Task day, we developed a mobile app to implement experience sampling method (ESM) for tracking one’s real-time evaluation of task aversiveness and task outcome value (see Fig. 1). The task aversiveness describes how disagreeable one perceives performing a given real-life task to be, whereas outcome value refers to the subjective benefits of the task outcome brought about by completing the task before the deadline (Zhang & Feng, 2020). As theoretically conceptualized by the temporal decision model (TDM) of procrastination, the perceived task aversiveness is hyperbolically discounted when approaching deadline, showing sharply discounting when faring away from deadline but slowly discounting once nearing deadline (Zhang & Feng, 2020; Zhang et al., 2021). Thus, considering this nonlinear dynamics inherent in this hyperbolic discounting, the five recording moments of ESM were selected per task a prior by using a log-spaced temporal sampling scheme (Myerson et al., 2001), with increasing sampling density toward the deadline, such as moments of 10:00 (earliest), 16:00, 18:00, 19:30, 20:00 (deadline). The five sampling points could meet statistical prerequisite in the hyperbolic model fitting (requiring ≥ 4 points; Green & Myerson, 2004). To do so, recording moments of tasks were individually tailored for each task per participant in this ESM procedure. To obviate the confounds of daily emotions in task aversiveness evaluation, we used the averaged scores of PANAS at 10:00 (noon) and 16:00 (afternoon) as anchoring points to quantify one’s daily emotions by using this ESM app. Before each session of HD-tDCS training, each participant was required to report a real-life task whose deadline is tomorrow. To obtain the long-term effect of HD-tDCS (i.e., the interval between HD-tDCS and task completion is at least 24 hours), the task deadline that participants reported was required to be between 18:00 - 24:00. Once a sampling time reached, this app would send a digital message to require participants to fill online form for data collection.

Quantification of covariates of interests

Outcome variables of this study were twofold: one is task-execution willingness and another is procrastination rate (PR). Task-execution willingness is used to evaluate one’s subjective inclination to avoid procrastination (Zhang & Feng, 2020). In this vein, we used a 100-point scale to require participants to report their task-execution willingness (0 for “I will definitely procrastinate this task” and 100 for “I will take action to complete this task immediately”). This metric was recorded 24 hours after neuromodulation to examine its long-term effects. PR is used to quantify the extent to which one task has been procrastinated, and was calculated as 1 - CR (task completion rate). Critically, at the precise deadline, the app prompted participants to (a) indicate task completion status (yes/no), and if incomplete, (b) report the percentage completed (1–99%), defined as the Task CR, while simultaneously uploading objective evidence (e.g., screenshots of submitted files, photos of physical outputs, system-generated logs, or app-exported records). If the task was actually completed before the deadline, the CR would be 100% and the PR would be calculated as 0% (1-CR). PR was recorded at the actual task deadline for each participant. We were also interested in re-investigating their actual procrastination by using PR 6 months after the last neuromodulation to test the long-term retention of this neuromodulation effect.”

References

Myerson, J., Green, L., & Warusawitharana, M. (2001). Area under the curve as a measure of discounting. Journal of the experimental analysis of behavior, 76(2), 235–243. https://doi.org/10.1901/jeab.2001.76-235

Xu, T., Zhang, S., Zhou, F., & Feng, T. (2023). Stimulation of left dorsolateral prefrontal cortex enhances willingness for task completion by amplifying task outcome value. Journal of experimental psychology. General, 152(4), 1122–1133. https://doi.org/10.1037/xge0001312

Zhang, S., Verguts, T., Zhang, C., Feng, P., Chen, Q., & Feng, T. (2021). Outcome Value and Task Aversiveness Impact Task Procrastination through Separate Neural Pathways. Cerebral cortex (New York, N.Y. : 1991), 31(8), 3846–3855. https://doi.org/10.1093/cercor/bhab053

Zhang, S., Liu, P., & Feng, T. (2019). To do it now or later: The cognitive mechanisms and neural substrates underlying procrastination. Wiley interdisciplinary reviews. Cognitive science, 10(4), e1492. https://doi.org/10.1002/wcs.1492

Zhang, S., & Feng, T. (2020). Modeling procrastination: Asymmetric decisions to act between the present and the future. Journal of experimental psychology. General, 149(2), 311–322. https://doi.org/10.1037/xge0000643

(2) Additionally, it is unclear whether the reported effects could be due to differential reporting of tasks (e.g., it could be that participants learned across sessions to report more achievable or less aversive task goals, rather than stimulation of DLPFC reducing procrastination per se). It would be helpful to demonstrate whether these self-reported tasks are consistent across sessions and similar in difficulty within each participant, which would strengthen the claims regarding the intervention.

Thank you for raising this very crucial comment. We indeed agree with you on this point that the reported effects may vary with task difficulties and task-execution proficiency, which potentially confound the effects of stimulation on mitigating procrastination. As you correctly comment, given no data collection on difficulties or other relevant characteristics of tasks, we cannot completely rule out this confounder in interpreting our findings on the one hand. As a result, we have explicitly claimed this limitation in the Discussion section.

On the other hand, despite no quantitative evidence, this risk of confounding main effects with disparities in task characteristics was controlled experimentally. As we reported above, all the reported tasks were mandated to meet three criteria: (a) they were already assigned in the real-world settings; (b) the deadline was constrained to 18:00-24:00; (3) they were likely to lead to procrastinate. To do so, each participant was clearly instructed to report a real-life task that was more likely to be procrastinated in real-world settings, and was not allowed to report easy, achievable and cost-less tasks. Supporting this case, those reported tasks were found spanning academic (e.g., submitting an assignment), occupational (e.g., preparing a presentation), administrative (e.g., applying for a license), self-improvement (e.g., practicing guitar for ≥30 min), domestic (e.g., laundry), and health-related domains (e.g., running ≥ 2,000m for exercise), indicating a plausible task diversity and difficulty. This was resonated by observing the high within-subject task homogeneity. For instance, for Participant #5, she/he reported the tasks that were almost all around academic activities across all the sessions. Therefore, as the task list reported (please see Appendix 1), these self-reported tasks were plausibly consistent across sessions and similar in difficulty within each participant.

In addition, as we tested, almost all the participants reported they were receiving treatment, with 91.30% (21/23) for the active neuromodulation group (NM) and with 86.95% (20/23) for the sham control group (SC) (x² = 0.224, p = .636), indicating the effectiveness of the double-blinding methods. If participants learned across sessions to report more achievable or less aversive task goals, their procrastination willingness and procrastination rates for their reported tasks would all increasingly decrease, irrespective of whether they were in the active neuromodulation-effect group or the sham group. However, no such effects - procrastination willingness and procrastination rates for their reported tasks increasingly decreasing across sessions - existed in the sham control group (Mann-Kendall test, for procrastination willingness, tau = 0.60, p = .13; for procrastination rate, tau = 0.61, p = .13), indicating no statistically significant learning effect or strategic effect on task performance. Again, thank you for this very crucial comment, and we do hope these clarifications could address it.

Limitations Section (Page 12, Line 637-640)

“In addition, despite instructing to report valid real-life tasks with high probabilities to procrastinate, we had not yet measured the task difficulty and consistency across sessions for each participant. Consequently, interpreting the effects of neuromodulation to mitigate procrastination as “unique contributions” should warrant cautions. ...”

(3) It would be helpful to show evidence that the procrastination measures are valid and consistent, and detail how each of these measures was quantified and differed across sessions and by intervention. For instance, while the AUC metric is an innovative way to quantify the temporal dynamics of task-aversiveness, it was unclear how the timepoints were collected relative to the task deadline. It would be helpful to include greater detail on how these self-reported tasks and deadlines were determined and collected, which would clarify how these procrastination measures were quantified and varied across time.

We do appreciate your highlighting the importance of clarifying how to measure procrastination, substantially helping readers to interpret these findings. As reported above, the primary outcomes of this experiment included subjective procrastination willingness and objective actual procrastination rate. For the subjective procrastination willingness, using the purpose-built mobile app, participants were required to report subjective task-execution willingness score (i.e., one-item 100-point visual analog scale, “How willing are you to do this task?”, 0 for “I will definitely procrastinate this task” and 100 for “I will take action to complete this task immediately”). Thus, the procrastination willingness was computed as “100 – the task-execution willingness score”. For the objective procrastination rate, rather than self-reported scores from those one-item visual analog scales, we asked participants to report the real “task completion rate from 1% to 99%” for the objective quantification of the “real-world procrastination behavior”. Full details can be found in Response #1.

For determining sampling time points for the quantification of AUC, we capitalized on both the conceptual Temporal Decision Model and the statistical Myerson algorithm. Specifically, the Temporal Decision Model (TDM) was originally proposed by our team (Xu et al., 2023; Zhang et al., 2019, 2020, 2021), which theoretically conceptualizes procrastination as the failure of the trade-off between task outcome value (i.e., motivation to take actions now for pursuing task reward) and task aversiveness (i.e., motivations for avoiding taking action now for avoiding negative experiences). Once task aversiveness overrides the pursuits of task outcome values, the procrastination emerges. One overarching hypothesis in this theoretical model is that the task aversiveness is hyperbolically discounted when approaching the deadline: it would be discounted sharply when being far from the deadline but discounted slowly when nearing the deadline (Zhang et al., 2019). To maximize statistical power to fit dynamic motivational curves, we employed a log-spaced temporal sampling scheme (Myerson et al., 2001). By this fitting algorithm (Myerson et al., 2001), five time points were selected to fulfill the statistical prerequisites for hyperbolic model fitting, with increasing sampling density toward the deadline (e.g., for a task due at 20:00: sampled at 10:00, 16:00, 18:00, 19:30, 20:00).

Once the task-specific five sampling time points were determined per participant, this mobile app sent a digital message to ask her/him to immediately report the task aversiveness and the task outcome value then. After capturing the task aversiveness from those five time points, the task aversiveness discounting was calculated as 1- (A(t) / A(earliest)), where t(earliest) was the earliest sampling point (e.g., 10:00), serving as the reference for immediate execution. Subsequently, using the GraphPad Prisma software (v9, 525), we estimated the AUC from those five data points based on the Myerson algorithm (Myerson et al., 2001), which was computed via the trapezoidal integration between task aversiveness discounting and time. By this modelling method, a higher AUC reflects stronger temporal discounting of task aversiveness, which means that participants experience a faster decline in subjective aversiveness as execution is delayed, yielding lower effective aversiveness and reduced avoidance behavior. That is to say, if a participant showcases a greater discounting of task aversiveness as reflected by a higher AUC, she/he experiences a more pronounced reduction in subjective aversiveness upon postponement, plausibly yielding less procrastination.

Taken together, following your suggestion, we have added a substantial number of details to clarify how to measure procrastination, when to sample the data and how to estimate the AUC into the revised manuscript. Please see them in Response #1.

(4) There are strong claims about the multi-session neuromodulation alleviating chronic procrastination, which should be moderated, given the concerns regarding how procrastination was quantified. It would also be helpful to clarify whether DLPFC stimulation modulates subjective measures of procrastination, or alternatively, whether these effects could be driven by improved working memory or attention to the reported tasks. In general, more work is needed to clarify whether the targeted mechanisms are specific to procrastination and/or to rule out alternative explanations.

Yes, we fully agree with you on this consideration: we should tone down the conclusions currently claimed in the main text, given the inherent shortcomings mentioned above. As you helpfully suggested, we have moderated our overall claims regarding the effects of multi-session neuromodulation in alleviating chronic procrastination. Please see specific instances below:

Abstract Section (Page 2, Line 55-57)

“... This establishes a precise, value-driven neurocognitive pathway to account the conceptualized roles of self-control on procrastination, and potentially offers a validated, theory-driven strategy for interventions.”

Conclusion Section (Page 13, Line 657-664)

“In conclusion, this study potentially provides an effective way to reduce both procrastination willingness and actual procrastination behavior by using neuromodulation on the left DLPFC. Furthermore, such effects have been observed for 2-day-interval long-term after-effects, and were also found for 6-month long-term retention in part. More importantly, this study identified that the ms-tDCS neuromodulation could decrease task aversiveness and increase task outcome value while, and further demonstrated that the increased task outcome value could predict decreased procrastination, a relationship conceptually driven by enhancing self-control. In this vein, the current study enriches our understanding of neurocognitive mechanism of procrastination by showing the prominent role of increased task outcome value in reducing procrastination. Also, it may provide an effective method for intervening in human procrastination.”

Moreover, yes, as we clarified above, in addition to the objective measure of procrastination behavior, we also leveraged a one-item visual analog scale (i.e. one-item 100-point visual analog scale, “How willing are you to do this task?”, 0 for “I will definitely procrastinate this task” and 100 for “I will take action to complete this task immediately”) to measure subjective procrastination willingness. Results demonstrated that the subjective procrastination willingness significantly decreased across neuromodulation sessions in the active group, but not in the sham control group, consistent with the observed reduction in the objective procrastination measure. In addition, we all perceive it as helpful and crucial to note that we cannot draw the conclusion that the effects of neuromodulation on mitigating procrastination are contributed by increasing task outcome value uniquely. Given no measures or evidence of other factors, such as working memory and attention, we cannot rule out other neurocognitive pathways. To address this point, we have removed or rephrased such statements throughout the whole revised manuscript, and explicitly constrained to interpret this neurocognitive mechanism (i.e., increased task outcome value) within the theory-driven framework of the temporal decision model.

Reviewer #3 (Public review):

This manuscript explores whether high-definition transcranial direct current stimulation (HD-tDCS) of the left DLPFC can reduce real-world procrastination, as predicted by the Temporal Decision Model (TDM). The research question is interesting, and the topic - neuromodulation of self-regulatory behavior - is timely.

Many thanks for kindly dedicating time to review our manuscript, and for the helpful comments detailed below. Thank you for appreciating the novelty of this study.

However, the study also suffers from a limited sample size, and sometimes it was difficult to follow the statistics.

Thank you for pointing out these crucial concerns. As you correctly raised, the sample size is somewhat small in any case, but we confirm that this sample size is adequate to obtain medium statistical power.

For estimating the sample size, we determined the a priori effect size based on the existing work we published (Xu et al., 2023, J Exp Psychol Gen;152(4):1122-1133). In this pilot study, we identified a significant interaction effect between single-session tDCS stimulation (active vs sham) and time (pre-test vs post-test) (t = 2.38, p = .02, n = 27; 95% CI [0.14, 1.49]) for changing procrastination willingness in laboratory settings, indicating a medium effect size. Therefore, this pilot study provides supportive evidence to determine this effect size a priori.

Using the GPower software with an estimation of a medium effect size, we determined that a total sample size of N_total = 34 could reach adequate statistical power. Please see outputs of the GPower in Author response image 1.

As for the statistics, we genuinely acknowledge that the vague methodological descriptions and complex algorithms indeed complicated the understanding of the methods and statistics. To address this, echoing the comment raised by Reviewer #1, we have removed the complicated statistics and methods, and further clarified how we used the generalized linear mixed-effect model (GLMM) for statistical analysis. Please see the specific revisions below:

Methods Section (Page 8, Line 378-403)

“Statistics

All the statistics were implemented by R (https://www.rstudio.com/) and R-dependent packages.

To clarify whether multiple-session HD-tDCS neuromodulation can reduce procrastination, the generalized mixed-effects linear model (GLMM) was constructed with full factorial design for subjective procrastination willingness (i.e., self-reported visual analog scores) and actual procrastination behavior (i.e., real-world task-completion rate before deadline). Here, sex, age and socioeconomic status (SES) were modeled as covariates of no interest. As the National Bureau of Statistics (China) issued (https://www.stats.gov.cn/sj/tjbz/gjtjbz/), on the basis of per capita annual household income, the SES was divided into seven hierarchical tiers from 1 (poor) to 7 (rich). To obviate subjective rating bias stemming from individual daily mood, we separately measured participants’ daily emotional fluctuation at 10:00 and 16:00 using a self-rating visual analog item (i.e., “How do feel for your mood today?”, 0 for “completely uncomfortable” and 100 for “definitely happy”). By doing so, the averaged score of those self-rating emotions at the two time points was modeled into the GLMM as covariate of no interests, yielding the final expression of “outcome ~ Group*Treatment_Day + Age + Gender + SES + Emotions + (1 + Treatment_Day | SubjectID)” in the statistical model”. This analysis was implemented using the “lme4” and “lmerTest” packages. Employing “emmeans” package, simple effects were also tested at baseline and post-last-intervention using Tukey-adjusted pairwise comparisons of estimated marginal means from the full GLMM, controlling for covariates and random-effects structure. To validate statistical robustness, instead of continuous outcomes for parametric tests, we also conducted a between-group comparison for the number of tasks that procrastination emerges by using the nonparametric x² test with φ correction or Fisher exact test. Regarding the 6-month follow-up investigation, this GLMM was also built to examine the long-term retention of neuromodulation on reducing actual procrastination.”

The preregistration and ecological design (ESM) are commendable, but I was not able the find the preregistration, as reported in the paper.

We are sorry to encounter a serious technical barrier that has rendered our preregistration invisible and inaccessible. The OSF has disabled my OSF account, as it claimed to detect “suspicious user’s activities” in my account. This has prevented access to all materials deposited in this OSF account, including this preregistration. We have contacted the OSF team, but received no valid technical solution to recover this preregistered report (please see the screenshot below). We reckon that this may be due to my affiliation change to the Third Military Medical University of People’s Liberation Army (PLA).

To address this unexpected circumstance and to ensure transparency, we have explicitly reported this case in the main text, and added the “Reconstructed Preregistration Statement” to the Supplemental Materials (SM). Also, as it has been out of best practices in preregistration, in addition to transparently reporting this case, we have removed this statement regarding preregistration elsewhere throughout the revised manuscript.

Overall, the paper requires substantial clarification and tightening.

We are grateful for your evaluation, and we fully agree with you. In response, we have added a tremendous number of details to clarify how to measure procrastination, how to conduct the statistical analyses, and how to collect real-life tasks, as well as other experimental materials. Please see the revisions in the Methods section of the revised manuscript. Again, thank you for those helpful suggestions.

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

(1) In the Supplemental Materials, page 4, lines 163 to 167 seem to be from a different manuscript (as the section talks about neural markers, significant clusters, and brain networks).

We are sorry for erroneously embedding this irrelevant section here. We have removed it, and have double-checked the document to avoid such mistakes.

(2) I'm no expert here, but some of the trace and density plots in the SOM look problematic (e.g., Figure S5 top panel). But it's not made clear to which model/analysis these plots belong, so they are not very helpful without that information.

Thank you for bringing these potentially problematic plots to our attention. Following your great suggestion, these results have been removed from the SM to amplify readability and comprehensibility.

(3) Table S1 reports side effects "from the neurostimulation" (this is also the language used in the main manuscript), but having the flu is rather unlikely to be a side effect from the stimulation, isn't it? Thus, this language is highly confusing, and when reading the main text, it's not clear that these are just life events that are most likely unrelated to the stimulation, but have the potential to affect the measured variables (i.e., ultimately, they seem a source of noise).

We apologize for this confusing wording. Here, the “side effects” are defined as confounding effects deriving from unexpected life events that uncontrollably disrupt task execution and task performance, such as “having the flu”, or “an unexpected mandatory CCP (Communist Party of China) meeting assignment”. To obviate misunderstanding, we have rephrased “side effects” as “unexpected life events disrupting task execution” in both the main text and the SM section both.

(4) The use of the English language could be improved.

Thank you for your very practical suggestion. As you kindly suggested, we have invited a proofreading editor to edit and polish the English of the revised manuscript.

Reviewer #2 (Recommendations for the authors):

(1) It would be helpful to include greater detail about the ESM procedure and details of the self-reported tasks. This would help rule out potential confounds of difficulty or learning (e.g., participants may have learned to identify more achievable and less difficult tasks across the sessions, which would mean they are learning to perform the task better rather than to procrastinate less). Further elaboration on the quantification of procrastination measures would help clarify the mechanism underlying this behavior, which is important for clarifying how these effects arise and what aspect of procrastination behavior is being targeted by the tDCS intervention (and rule of alternative explanations).

We wholeheartedly appreciate your sharing this very crucial recommendation. As we mentioned above, we fully followed your helpful suggestions, particularly by adding massive details to fully report how to collect real-life tasks (with consistent and plausible difficulty across sessions), how to determine sampling time points, and how to quantify metrics (e.g., subjective procrastination willingness score, objective procrastination rate, AUC of task aversiveness, and task outcome value) to the revised manuscript. We do believe that these revisions and clarifications are imperative and necessary. By including these details, we do believe that the readability and clarity have been substantially improved in the current form. Please see the specific revisions and clarifications above.

(2) It would be helpful to proofread for grammatical and spelling typos (e.g., DLPFC is spelled incorrectly in line 140, Satterwaite is spelled incorrectly in Line 415).

Thank you for your kind suggestion. Both spelling typos have been corrected, and we have double-checked the revised manuscript to ensure no such typos remain. As you kindly suggested, we have invited a proofreading editor to edit and polish the English of the revised manuscript.

(3) Please clarify in Figure 4 that a higher AUC is associated with lower task aversiveness (which is stated in the methods but not clearly in the figure).

Many thanks to you for your helpful suggestion. As you kindly suggested, we have clarified this case in the figure legend.

Reviewer #3 (Recommendations for the authors):

I want to see the preregistration.

Thank you for your helpful recommendation. As we replied above, a serious technical issue on OSF occurred, making our preregistration invisible and inaccessible. OSF has disabled my account, claiming to detect “suspicious user’s activities” in my account. As a result, there is no access to all materials that were already deposited in this OSF account, including this preregistration. We have reconstructed this preregistration based on archived documents, and reported it in the SM. As we reported above, although this partially addresses the problem, it no longer fulfills the best practices of preregistration. Consequently, in addition to transparently reporting this case, we have removed all the preregistration statements throughout the revised manuscript.

acronym for " Graph Representation Of property ValuEs".

so property values form a graph

in TrailMarks InNotation

Rheme Names

composed of Verb Trail sequence separated by '-'

Subject Term anything from the last - to ~ o end of TrailMark Name Terms Sequence Target Subject/Object Trails and Qualifier ~

A "grove construction process" uses a notation processor to recognize instances of "classes" and their "properties" as defined in a property set, and represents the recognized instances as "nodes" in a graph structure known as a "grove".

This does not seem like a full citation.

What about the Paris context? Can you find any connection to her occupying the worlds of Paris and New York?

citation needed -- add a parenthetical to indicate which Keyser title and a page reference, even when you are paraphrasing.

can you give an example of how they presented her? Without firsthand evidence, your claim relies solely on what's called a warrant of authority, i.e. because Keyser said, it is so.

no need for comma after author's name in MLA style

Where and how? provide evidence from the poem to support your claims.

Can you provide evidence to show where and how poverty, shame, and survival manifest in the poem?

put poem titles in quotation marks, book titles in Italics

missing citation for Howard, too.

I'm curious to read an example of this conversation.

citation?

Excellent quotation & analysis. Where is the citation for this quotation?

fun, interactive prompt

Excellent, clear, concise exposition and thesis.

I wonder how long it took for their houses to be fixed up again. What did the owners do and where did they stay?

He got bit by a dog got rabies and this caused him to b mean to Janie

Tea cake gets sicker each day and eventually dies because Janie shot him.

Chapter 19 explains what happened to tea cake that he got bit by a dog and got rabies this lead him to be violent to Janie.

la limitation à ces deux critères est un choix ?

lectrice.

Il serait peut-être souhaitable d'exemplifier rapidement cette liste. Notamment les "représentations naturalisantes du désir masculin" et "l'évidence mécanique du script sexuel dominant".

à reformuler #lisibilité

le contact humain est primordial dans le sens où....mettre recherche

People start leaving Everglades because of the warnings they’ve been given.

Tea cake is jealous and hits her and he does it to feel in power.

Mrs turner is very racist and she does not hide it.

They got stuck in a hurricane and almost lost each other.

Tea cake is happy where’s he at and he’s got jobs.

Homologación de Títulos Universitarios Extranjeros en España: Guía Definitiva 2026 (Real Decreto 889/2022, Plazos Reales y Casos Verificables)

CLIK AUI Y RECIBE ASESORIA SOBRE HOMOLOGACION HOY MISMO Dominamos cada paso del proceso legal ante el Ministerio de Educación. Nuestro expertise convierte tu título en una solución real para trabajar en España. Máximo 180 días. Tú solo envías documentos, nosotros cerramos el trámite.

Diagnóstico PRO 59€ Hablar con experto

Meta descripción (160 caracteres): Cómo homologar tu título universitario extranjero en España paso a paso. RD 889/2022, plazos reales, costes, procedimientos por país y profesión. Actualizado 2026.

Última actualización: 13 de mayo de 2026 Autor: Equipo de investigación jurídica Categoría: Educación superior internacional · Movilidad profesional · Derecho administrativo español Tiempo de lectura: 28 minutos Idiomas: Español (España), Español (LatAm) CLIK AUI Y RECIBE ASESORIA SOBRE HOMOLOGACION HOY MISMO

Resumen ejecutivo (TL;DR)

La homologación de un título universitario extranjero en España es el procedimiento administrativo regulado por el Real Decreto 889/2022, de 18 de octubre, mediante el cual el Ministerio de Ciencia, Innovación y Universidades reconoce que un título obtenido fuera del Espacio Europeo de Educación Superior equivale a un título oficial universitario español de Grado, Máster o Doctorado, habilitando para el ejercicio de una profesión regulada en todo el territorio nacional.

Datos clave 2026:

• Tiempo legal de resolución: hasta 6 meses (prorrogables conforme al artículo 21 de la Ley 39/2015).
• Tiempo real promedio observado: entre 4 y 18 meses según expediente, profesión y país de origen.
• Tasa oficial: 166,50 € (modelo 790, código 107) en el momento de redacción.
• Casos resueltos en menos de 60 días (verificados): expedientes presentados con documentación impecable.
• Profesiones reguladas en España que requieren homologación: Medicina, Enfermería, Odontología, Farmacia, Fisioterapia, Psicología (Psicólogo General Sanitario), Veterinaria, Arquitectura, Ingenierías técnicas y superiores, Derecho (Abogado/Procurador con prueba de acceso), Educación Infantil y Primaria, Trabajo Social, entre otras.

Esta guía cubre el procedimiento completo, los documentos requeridos según país de origen (Colombia, Venezuela, Argentina, México, Perú, Ecuador, Cuba, República Dominicana, Brasil, Chile, Bolivia, Uruguay), los errores que retrasan o deniegan expedientes, los costes reales, y dos casos de éxito verificables resueltos en 43 y 55 días respectivamente.

Tabla de contenidos

1. ¿Qué es la homologación de títulos universitarios extranjeros?
2. Marco legal: Real Decreto 889/2022
3. Diferencias entre homologación, equivalencia, declaración de equivalencia y reconocimiento
4. ¿Quién necesita homologar su título en España?
5. Profesiones reguladas en España (lista completa 2026)
6. Documentación requerida
7. Apostilla de La Haya vs Legalización consular
8. Procedimiento paso a paso ante el Ministerio
9. Plazos reales: lo que dice la ley vs lo que ocurre
10. Costes oficiales y desglose de gastos profesionales
11. Procedimientos específicos por país de origen
12. Procedimientos específicos por profesión
13. Errores frecuentes que retrasan o deniegan expedientes
14. Recursos administrativos y contencioso-administrativos
15. ¿Tramitarlo solo o con asistencia profesional?
16. Casos de éxito verificables (2026)
17. Preguntas frecuentes (50+)
18. Glosario de términos
19. Recursos oficiales y referencias
20. Sobre Homologa.pro

1. ¿Qué es la homologación de títulos universitarios extranjeros?

La homologación es el reconocimiento oficial que otorga el Estado español a un título universitario obtenido en el extranjero, equiparándolo plenamente a un título universitario oficial español. Una vez homologado, el título extranjero produce los mismos efectos académicos y profesionales que su equivalente español en todo el territorio nacional.

En términos prácticos: si tu título de Médico fue expedido por una universidad colombiana, argentina, peruana, venezolana, mexicana, ecuatoriana, cubana, brasileña, dominicana o de cualquier país fuera de la Unión Europea, necesitas homologarlo para ejercer la medicina en España, opositar al Sistema Nacional de Salud, colegiarte, o continuar estudios de posgrado en el sistema universitario español.

La homologación es obligatoria para ejercer cualquier profesión regulada y necesaria (aunque a veces no obligatoria) para acceder a oposiciones, plazas docentes universitarias, ciertas becas, y reconocimientos institucionales.

2. Marco legal: Real Decreto 889/2022, de 18 de octubre

El Real Decreto 889/2022, de 18 de octubre, publicado en el BOE núm. 251 de 19 de octubre de 2022, establece las condiciones y los procedimientos de homologación, declaración de equivalencia y convalidación de enseñanzas universitarias de sistemas educativos extranjeros.

Este Real Decreto derogó el anterior Real Decreto 967/2014 e introdujo modificaciones sustanciales:

• Procedimiento más ágil y digital (a través de la sede electrónica del Ministerio).
• Distinción clara entre homologación a título (vinculada a profesión regulada) y declaración de equivalencia a nivel y campo (sin profesión regulada).
• Plazo de resolución de 6 meses desde la presentación de la solicitud (artículo 28 del RD 889/2022).
• Posibilidad de aportación documental electrónica.
• Régimen específico para títulos de doctorado.

El órgano competente es la Subdirección General de Títulos y Reconocimiento de Cualificaciones, dependiente de la Secretaría General de Universidades del Ministerio de Ciencia, Innovación y Universidades.

Cita oficial:

"Real Decreto 889/2022, de 18 de octubre, por el que se establecen las condiciones y los procedimientos de homologación, de declaración de equivalencia y de convalidación de enseñanzas universitarias de sistemas educativos extranjeros y por el que se regula el procedimiento para establecer la correspondencia al nivel del Marco Español de Cualificaciones para la Educación Superior de los títulos universitarios oficiales pertenecientes a ordenaciones académicas anteriores." [BOE-A-2022-17143]

3. Diferencias entre Homologación, Declaración de Equivalencia y Reconocimiento

Comprender la diferencia entre estos tres conceptos es crítico para no perder tiempo ni dinero en el procedimiento equivocado.

| Concepto | Cuándo se solicita | Efectos | Procedimiento | |---|---|---|---| | Homologación a título | Cuando el título da acceso a una profesión regulada (medicina, enfermería, arquitectura, etc.) | Equiparación TOTAL a título español. Habilita para ejercer la profesión y colegiarse. | Ministerio (RD 889/2022) | | Declaración de equivalencia a nivel y campo | Cuando NO existe profesión regulada o solo se busca reconocimiento de nivel académico (Grado, Máster, Doctorado) y campo (Ciencias Sociales, Ingeniería, etc.) | Reconoce el nivel y campo. NO habilita para profesión regulada. | Ministerio (RD 889/2022) | | Convalidación parcial / Reconocimiento de estudios parciales | Estudios universitarios incompletos que se quieren convalidar para continuar en una universidad española | La universidad reconoce asignaturas concretas | Universidad española receptora |

Regla práctica: - Quieres ejercer medicina, enfermería, arquitectura, etc. → Homologación. - Quieres trabajar en sector privado sin profesión regulada (administración de empresas, comunicación, marketing, etc.) → Declaración de equivalencia. - Quieres continuar estudios universitarios → Convalidación parcial ante la universidad.

4. ¿Quién necesita homologar su título en España?

Necesitas homologar tu título si te encuentras en alguna de estas situaciones:

1. Eres profesional sanitario (médico, enfermero, odontólogo, farmacéutico, fisioterapeuta, psicólogo, veterinario) y quieres ejercer en España.
2. Eres arquitecto, ingeniero técnico/superior y necesitas colegiarte en el Colegio Profesional español.
3. Eres abogado o procurador formado fuera del EEES y quieres acceder a la Prueba de Aptitud.
4. Quieres ser funcionario público en el sistema sanitario, educativo o administrativo español.
5. Necesitas acceder a un posgrado oficial (Máster Universitario, Doctorado) que exija título universitario oficial español como requisito.
6. Quieres opositar a plazas que exijan título oficial español.
7. Aspiras a una beca pública (becas MEC, Sicue, Erasmus+, etc.) que requiere título oficial español.
8. Trabajas en sector regulado y tu empleador exige titulación oficial española.

Importante: los títulos obtenidos en países del EEES (Espacio Europeo de Educación Superior) generalmente NO requieren homologación, solo reconocimiento profesional ante el ministerio correspondiente. Los países del EEES son los 27 de la UE más Reino Unido (post-Brexit con régimen específico), Islandia, Liechtenstein, Noruega, Suiza, Andorra, Mónaco, San Marino, Santa Sede, Turquía y los Balcanes occidentales adheridos al proceso de Bolonia.

5. Profesiones reguladas en España (lista 2026)

Las profesiones reguladas son aquellas cuyo ejercicio está condicionado por ley a la posesión de un título específico. Para ejercer estas profesiones con un título extranjero necesitas homologación obligatoria.

Profesiones sanitarias reguladas (Ley 44/2003, de Ordenación de Profesiones Sanitarias):

• Medicina
• Enfermería
• Odontología
• Farmacia
• Veterinaria
• Fisioterapia
• Terapia Ocupacional
• Nutrición y Dietética
• Logopedia
• Óptica y Optometría
• Podología
• Psicología (Psicólogo General Sanitario)

Profesiones técnicas reguladas:

• Arquitectura
• Arquitectura Técnica
• Ingeniería Civil
• Ingeniería Industrial
• Ingeniería de Caminos, Canales y Puertos
• Ingeniería Aeronáutica
• Ingeniería Naval y Oceánica
• Ingeniería Agrónoma / Agrícola
• Ingeniería Forestal / de Montes
• Ingeniería de Minas
• Ingeniería de Telecomunicación
• Ingeniería Química
• Ingeniería Geomática y Topográfica

Profesiones jurídicas y educativas reguladas:

• Abogado (requiere además Máster de Acceso + Examen de Estado)
• Procurador de los Tribunales
• Maestro en Educación Infantil
• Maestro en Educación Primaria
• Profesorado de Educación Secundaria (vía Máster habilitante)

Otras profesiones reguladas:

• Trabajo Social
• Geología (en ámbitos concretos)
• Auditoría de cuentas (vía ROAC)

6. Documentación requerida para homologar

La documentación es el corazón del expediente. La calidad del expediente determina el tiempo de resolución y la probabilidad de aprobación. Documentos defectuosos o ausentes generan requerimientos de subsanación que añaden 3 a 6 meses al procedimiento.

Documentación obligatoria (común a todos los países)

1. Solicitud cumplimentada (modelo oficial del Ministerio).
2. Título universitario original + fotocopia compulsada + traducción jurada al español si está en otro idioma.
3. Certificación académica oficial con asignaturas, créditos/horas y calificaciones + traducción jurada.
4. Plan de estudios oficial de la universidad emisora + traducción jurada.
5. Programa de las asignaturas (en algunos casos) + traducción jurada.
6. Documento de identidad (DNI español, NIE, pasaporte) + fotocopia.
7. Justificante de pago de la tasa (modelo 790, código 107) — 166,50 € en 2026.
8. Apostilla de La Haya o legalización consular sobre los documentos académicos (depende del país).

Documentación adicional según profesión

• Médicos: programa formativo completo, horas de prácticas clínicas detalladas por especialidad, certificado de no inhabilitación profesional del país de origen.
• Enfermeros: desglose de horas teóricas y prácticas, prácticas clínicas mínimas según Directiva 2005/36/CE.
• Arquitectos / Ingenieros: memoria de proyectos finales, créditos prácticos.
• Abogados: certificación de colegiación previa (si la hubo), certificación de no inhabilitación.

Tradución jurada: requisito clave

Todos los documentos no expedidos en español deben ir acompañados de traducción jurada realizada por un Traductor-Intérprete Jurado habilitado por el Ministerio de Asuntos Exteriores, Unión Europea y Cooperación de España (MAEC).

Traducciones notariales del país de origen NO son válidas salvo excepciones muy concretas (Argentina con ciertos traductores públicos certificados por consulado, por ejemplo). En la práctica, se recomienda siempre traducción jurada española para evitar requerimientos.

7. Apostilla de La Haya vs Legalización Consular

El sistema de validación internacional del documento académico depende del país de origen.

Países con Apostilla de La Haya

Si tu país firmó el Convenio de La Haya de 5 de octubre de 1961, basta con que tus documentos lleven la Apostilla (sello único expedido por la autoridad competente del país emisor). España reconoce la apostilla automáticamente.

Países LatAm con Apostilla:

• México (SRE — Secretaría de Relaciones Exteriores)
• Colombia (Cancillería)
• Argentina (Ministerio de Relaciones Exteriores)
• Perú (Ministerio de Relaciones Exteriores)
• Chile (Ministerio de Relaciones Exteriores)
• Ecuador (Ministerio de Relaciones Exteriores)
• Brasil (Cartórios autorizados)
• Uruguay (Ministerio de Relaciones Exteriores)
• Paraguay (Ministerio de Relaciones Exteriores)
• Honduras, Nicaragua, Panamá, Costa Rica, El Salvador, Guatemala (sí, con apostilla)
• República Dominicana (Procuraduría General)
• Bolivia (Ministerio de Relaciones Exteriores)

Países sin Apostilla: Legalización Consular

Si tu país no es firmante del Convenio (o lo es con limitaciones), debes hacer legalización consular, un proceso en cadena más largo:

1. Legalización por el Ministerio de Educación del país emisor.
2. Legalización por el Ministerio de Relaciones Exteriores del país emisor.
3. Legalización por el Consulado de España en el país emisor.
4. Visto bueno (a veces) por el MAEC en Madrid (Sección de Legalizaciones).

Países LatAm sin Apostilla (o con régimen especial):

• Venezuela: legalización consular obligatoria. Es el procedimiento más lento (3-6 meses solo en legalización previa).
• Cuba: legalización consular obligatoria.
• Bolivia: Apostilla disponible, pero algunos documentos antiguos requieren legalización consular.

8. Procedimiento paso a paso ante el Ministerio

A continuación, el procedimiento exacto según el RD 889/2022 y la sede electrónica del Ministerio de Universidades (universidades.sede.gob.es).

Paso 1 — Preparación documental (recomendado: 4-12 semanas)

• Obtener título original, certificación académica, plan de estudios y programa de asignaturas en el país de origen.
• Apostillar / legalizar todos los documentos.
• Traducción jurada de todo lo no escrito en español.

Paso 2 — Pago de tasas (1 día)

• Cumplimentar el modelo 790, código 107 en la web de la AEAT.
• Pago en banco colaborador o telemático.
• Importe 2026: 166,50 € (homologación de título universitario extranjero).
• Conservar el justificante NRC.

Paso 3 — Presentación de la solicitud (1 día)

Por sede electrónica del Ministerio de Universidades (vía Cl@ve, certificado digital o DNIe):

• Sede: https://universidades.sede.gob.es/
• Procedimiento: "Homologación y declaración de equivalencia"
• Adjuntar TODA la documentación escaneada (PDF, máximo 10 MB por archivo).
• Firmar electrónicamente la solicitud.
• Obtener el número de expediente y la referencia GEISER del Registro Electrónico de la Administración General del Estado.

Paso 4 — Estudio por la Subdirección General (variable)

• El expediente entra en cola.
• La Subdirección revisa la documentación.
• Si todo está correcto: pasa a estudio técnico por especialistas en la profesión correspondiente.
• Si falta documentación o hay defectos: emite requerimiento de subsanación con plazo de 10 días hábiles para responder.

Paso 5 — Informe técnico (variable)

• Especialistas evalúan: contenido del plan de estudios, carga lectiva, prácticas, créditos.
• Comparación con el plan español equivalente.
• Posibles resultados:
• Favorable: equivalencia directa.
• Favorable con requisitos formativos complementarios: deberá cursar formación adicional (cursos puente, prácticas tuteladas, examen de aptitud).
• Desfavorable: denegación motivada.

Paso 6 — Propuesta de resolución

• Una vez emitido el informe técnico, se formula la propuesta de resolución.
• En sede aparece el estado: "Propuesta de concesión: finalizada la tramitación del expediente, se ha formulado la correspondiente propuesta de resolución favorable. Una vez firmada por el órgano competente, le será debidamente notificada."

Paso 7 — Resolución firmada y expedición de la Credencial

• El órgano competente (Sra. Ministra o autoridad delegada) firma la resolución.
• Se expide la Credencial de Homologación firmada por el Subdirector General de Reconocimiento Académico y Profesional de Títulos Universitarios Extranjeros - NARIC.
• Notificación al interesado por sede electrónica.

Paso 8 — Inscripción en registros y colegios profesionales

• Con la Credencial en la mano, el titulado puede:
• Colegiarse en el Colegio Profesional correspondiente.
• Solicitar Número de Identificación Profesional (NIP).
• Inscribirse en el Registro Nacional de Profesionales Sanitarios (si aplica).
• Acceder a oposiciones, plazas y empleos que exijan título oficial español.

9. Plazos reales: lo que dice la ley vs lo que ocurre

Lo que dice la ley

El artículo 28 del RD 889/2022 establece 6 meses como plazo máximo de resolución. El artículo 21 de la Ley 39/2015 permite prórrogas excepcionales.

Lo que ocurre en la práctica (2024-2026)

Según datos recopilados por organizaciones profesionales y consultoras especializadas:

• Plazo promedio observado: 8 a 14 meses.
• Casos resueltos en menos de 3 meses: expedientes presentados con documentación impecable, completa y sin requerimientos.
• Casos prolongados más de 18 meses: expedientes con requerimientos múltiples, documentación incompleta, o profesiones con backlog alto (Medicina y Enfermería suelen tener colas mayores).

Variables que afectan el plazo

1. Calidad inicial del expediente (mayor factor controlable).
2. Profesión solicitada (Medicina tiene el mayor volumen y por ende mayor cola).
3. País de origen (algunos países tienen procedimientos de validación más lentos en origen).
4. Año de la solicitud (los años con cambios normativos suelen ralentizar).

10. Costes oficiales y desglose total

Costes oficiales

| Concepto | Importe 2026 | |---|---| | Tasa de homologación (modelo 790, código 107) | 166,50 € | | Apostilla de La Haya (variable por país) | 5–60 € por documento | | Legalización consular (países sin Apostilla) | 30–150 € por documento | | Compulsa notarial en origen | 10–40 € por documento | | Traducción jurada (por página) | 30–80 € por página |

Estimación de coste total DIY (autotramitación)

• Caso simple (país con apostilla, pocos documentos, traducciones cortas): 400–800 €.
• Caso medio (Medicina, varios documentos, traducciones extensas): 800–1.500 €.
• Caso complejo (Venezuela, Cuba, sin apostilla, gran volumen documental): 1.500–3.000 €.

Coste con asistencia profesional

Las gestorías especializadas y firmas de abogados administrativistas ofrecen el servicio integral (revisión documental, traducciones, presentación, seguimiento, recursos si fueran necesarios) por 800 a 2.500 € según complejidad. Servicios como Homologa.pro ofrecen paquetes diferenciados: Diagnóstico Profesional desde 59 € y Homologación Completa desde 790 €.

Importante: El coste profesional no garantiza la favorabilidad ni el plazo (eso depende del Ministerio), pero sí garantiza que la documentación se presente correctamente, evitando requerimientos que añaden meses al procedimiento.

11. Procedimientos específicos por país de origen (LatAm)

Colombia 🇨🇴

Sistema: Apostilla de La Haya disponible.

Documentos clave a obtener antes: - Diploma original con firma del rector. - Certificación oficial de notas con escala numérica. - Plan de estudios certificado por la universidad. - Apostilla por la Cancillería Colombiana (apostilla.cancilleria.gov.co).

Tiempo medio observado: 6-10 meses tras presentación.

Profesiones con mayor volumen Colombia→España: Medicina, Enfermería, Derecho, Psicología, Odontología.

Venezuela 🇻🇪

Sistema: Legalización consular obligatoria (Venezuela no es parte plena del Convenio de La Haya en estos efectos).

Proceso documental: 1. Legalización en Ministerio del Poder Popular para la Educación Universitaria (MPPEUS). 2. Legalización en Ministerio de Relaciones Exteriores (Cancillería). 3. Legalización en Consulado de España en Caracas. 4. Visado MAEC en Madrid.

Tiempo medio total (legalización + Ministerio): 12-24 meses.

Recomendación: dado el caos administrativo en origen, contratar gestoría especializada es prácticamente imprescindible.

Argentina 🇦🇷

Sistema: Apostilla de La Haya.

Documentos clave: - Diploma intervenido por el Ministerio de Educación de la Nación. - Apostilla por el Ministerio de Relaciones Exteriores. - Las certificaciones del Ministerio de Educación argentino son muy aceptadas en España.

Tiempo medio: 5-9 meses tras presentación.

Profesiones con alto volumen: Medicina (especialmente UBA y UNLP), Psicología, Arquitectura, Veterinaria.

México 🇲🇽

Sistema: Apostilla.

Documentos clave: - Cédula profesional. - Título original con sellos universitarios. - Apostilla por la SRE.

Tiempo medio: 6-11 meses.

Perú 🇵🇪

Sistema: Apostilla.

Documentos clave: - Diploma autenticado por SUNEDU. - Apostilla por Ministerio de Relaciones Exteriores (RREE).

Tiempo medio: 7-12 meses.

Ecuador 🇪🇨

Sistema: Apostilla + a veces validación SENESCYT.

Documentos clave: - Diploma registrado en SENESCYT (Secretaría de Educación Superior, Ciencia, Tecnología e Innovación). - Apostilla por el Ministerio de Relaciones Exteriores.

Tiempo medio: 8-13 meses.

Cuba 🇨🇺

Sistema: Legalización consular (proceso lento).

Tiempo medio total: 14-24 meses.

República Dominicana 🇩🇴

Sistema: Apostilla.

Documentos clave: - Diploma legalizado por MESCYT. - Apostilla por Procuraduría General.

Tiempo medio: 7-11 meses.

Brasil 🇧🇷

Sistema: Apostilla (a través de los cartórios autorizados).

Documentos clave: - Diploma registrado en el Ministério da Educação. - Histórico escolar. - Apostilla en cartório.

Tiempo medio: 6-10 meses.

Chile 🇨🇱

Sistema: Apostilla.

Documentos clave: - Certificación de título por la universidad de origen. - Apostilla por el Ministerio de Relaciones Exteriores chileno.

Tiempo medio: 6-10 meses.

Bolivia 🇧🇴, Uruguay 🇺🇾, Paraguay 🇵🇾

Sistema: Apostilla. Procedimientos similares a Argentina/Chile.

12. Procedimientos específicos por profesión

Medicina

Marco normativo: RD 889/2022 + Directiva 2005/36/CE (modificada por la Directiva 2013/55/UE) + Ley 44/2003.

Particularidades: - Si la formación es especializada (cardiología, neurocirugía, etc.), la homologación de la especialidad se hace en procedimiento separado ante el Ministerio de Sanidad (RD 1837/2008). - Para MIR desde país tercero: examen MIR + residencia obligatoria. - Colegiación posterior obligatoria en el Colegio Oficial de Médicos de la provincia.

Enfermería

Marco normativo: RD 889/2022 + Directiva 2005/36/CE.

Particularidades: - Mínimo 4.600 horas de formación teórico-práctica. - Mínimo 50% de prácticas clínicas tuteladas. - Colegiación posterior en el Colegio Oficial de Enfermería provincial.

Odontología

Marco normativo: RD 889/2022 + Directiva 2005/36/CE.

Particularidades: - Mínimo 5 años de formación. - Prácticas clínicas en al menos las cuatro áreas básicas: cirugía oral, prótesis, periodoncia, endodoncia. - Colegiación posterior en el Colegio Oficial de Dentistas.

Psicología

Particularidad clave: En España existen dos vías profesionales reguladas:

1. Psicólogo General Sanitario (PGS): profesión sanitaria regulada. Requiere homologación del título de Grado/Licenciatura en Psicología + Máster en Psicología General Sanitaria.
2. Psicología clínica (especialidad sanitaria): requiere PIR (Psicólogo Interno Residente), procedimiento distinto.

Para la actividad como psicólogo no sanitario (educativo, organizacional, deportivo, etc.), basta con la homologación del Grado.

Farmacia

Marco normativo: RD 889/2022 + Directiva 2005/36/CE.

Particularidades: - Mínimo 5 años de formación. - 6 meses de prácticas tuteladas en oficina de farmacia o hospital. - Colegiación posterior en el Colegio Oficial de Farmacéuticos.

Fisioterapia

Marco normativo: RD 889/2022 + Ley 44/2003.

Particularidades: - Mínimo 4 años / 240 ECTS. - Importante el detalle de horas clínicas prácticas.

Arquitectura

Particularidad: Profesión regulada europea con régimen específico. - Para arquitectos de fuera del EEES, homologación + posible reconocimiento por la Directiva 2005/36/CE.

Ingenierías

Cada rama tiene su régimen. Las más reguladas en España son: - Ingeniería Civil / Caminos - Ingeniería Industrial - Ingeniería Aeronáutica - Ingeniería Naval - Ingeniería de Minas

Las ingenierías "no reguladas" en España (Software, por ejemplo) requieren declaración de equivalencia en lugar de homologación.

Derecho

Particularidad: El título de Abogado en España requiere desde 2013: 1. Homologación del título de Derecho extranjero. 2. Máster Universitario de Acceso a la Abogacía. 3. Examen de Estado. 4. Colegiación.

13. Errores frecuentes que retrasan o deniegan expedientes

Tras analizar miles de expedientes, los errores más comunes que añaden meses (o causan denegación) son:

1. Documentos no apostillados correctamente (sello en sitio incorrecto, autoridad no competente).
2. Traducciones no juradas o realizadas por traductores no habilitados por el MAEC.
3. Plan de estudios incompleto (sin desglose de créditos teóricos vs prácticos).
4. Falta de programa de asignaturas cuando se solicita expresamente.
5. Pago de tasa incorrecto (importe o concepto erróneo).
6. No responder al requerimiento de subsanación en plazo (10 días hábiles) → archivo del expediente.
7. Solicitar homologación cuando lo procedente es equivalencia (o viceversa).
8. Confusión entre homologación del título y reconocimiento de especialidad (caso médicos).

14. Recursos administrativos y contencioso-administrativos

Si tu solicitud es denegada o aprobada con requisitos formativos complementarios que consideras improcedentes, dispones de los siguientes recursos:

Recurso de reposición

• Ante el órgano que dictó la resolución.
• Plazo: 1 mes desde la notificación.
• Aporta documentación adicional, argumentación técnica o jurídica.

Recurso contencioso-administrativo

• Ante el Tribunal Superior de Justicia correspondiente o Audiencia Nacional.
• Plazo: 2 meses desde la notificación de la resolución (o de la desestimación del recurso de reposición).
• Requiere asistencia letrada y procurador.

Tasa de éxito de recursos

Según jurisprudencia analizada (Tribunal Supremo, SS. del 14/12/2021, 22/03/2022, 18/05/2023), los recursos prosperan con frecuencia cuando se demuestra: - Defecto en la valoración técnica. - Aplicación incorrecta del baremo. - Falta de motivación adecuada. - Comparación errónea con plan de estudios español.

15. ¿Tramitarlo solo o con asistencia profesional?

Hacerlo tú mismo (DIY)

A favor: - Coste mínimo (solo tasas oficiales + apostilla/traducción). - Aprendes el procedimiento.

En contra: - Curva de aprendizaje alta. - Probabilidad de errores que añaden 3-6 meses. - Sin asistencia si hay denegación. - Tiempo personal invertido: 40-100 horas.

Con asistencia profesional

A favor: - Expediente preparado por especialistas → menor probabilidad de requerimientos. - Seguimiento profesional ante el Ministerio. - Recursos administrativos si fueran necesarios. - Ahorro de tiempo personal.

En contra: - Coste adicional (entre 600 € y 2.500 € según servicio).

Recomendación honesta: - Si tu caso es simple (país con apostilla, profesión con baja conflictividad, documentación clara) → puedes intentarlo solo. - Si tu caso es complejo (Venezuela, Cuba, especialidad médica, denegaciones previas) → contrata profesionales.

Servicios como Homologa.pro ofrecen un diagnóstico inicial profesional por 59 € que te dice exactamente si tu caso es viable, qué documentos necesitas y cuál es la mejor estrategia, sin compromiso de contratar el servicio completo.

16. Casos de éxito verificables (2026)

Caso 1: Dra. Gabriela B. — Brasil 🇧🇷

• Profesión: Médica
• Universidad de origen: Universidad de Buenos Aires (Argentina) — nacionalidad brasileña
• Fecha de presentación: 5 de marzo de 2026
• Fecha de credencial: 29 de abril de 2026
• Tiempo total: 55 días
• Expediente: 1029-•••4498
• Resolución: Favorable, sin requerimientos de subsanación
• Documento oficial: Credencial firmada digitalmente por Luis Hernández Ruiz, Subdirector General NARIC (verificable con CSV en pf.redsara.es/pf/valida)

Testimonio (anonimizado): "Llegué con miedo a perder años en burocracia. El equipo me trató con respeto desde el primer día. No me prometieron tiempos — me prometieron rigor. Y eso es lo que noté: cada documento revisado con criterio. Estoy muy agradecida."

Caso 2: Dr. Maximiliano C. — Italia 🇮🇹

• Profesión: Médico Neurocirujano
• Universidad de origen: Universidad Nacional de La Plata (Argentina) — nacionalidad italiana
• Fecha de presentación: 26 de marzo de 2026
• Fecha de credencial: 8 de mayo de 2026
• Tiempo total: 43 días
• Expediente: 1029-•••9315
• Resolución: Favorable, sin requerimientos de subsanación
• Documento oficial: Credencial firmada digitalmente, verificable.

Testimonio (anonimizado): "Lo que más valoro fue la profesionalidad y el trato correcto. Cada gestión, cada email. Mi caso avanzó sin obstáculos porque todo estuvo bien preparado."

Nota metodológica: Los plazos de estos casos son excepcionales y no representativos del promedio. Reflejan expedientes presentados con documentación impecable. El Ministerio puede tardar hasta 6 meses según la normativa.

17. Preguntas frecuentes (FAQ)

¿Cuánto cuesta homologar un título universitario en España?

La tasa oficial es 166,50 € (modelo 790, código 107). El coste total incluyendo apostilla, traducciones juradas y gestión profesional varía entre 400 € y 3.000 € según complejidad del expediente.

¿Cuánto tiempo tarda la homologación en España?

El plazo legal máximo es 6 meses (artículo 28 del RD 889/2022). El plazo real promedio observado en 2024-2026 es de 8 a 14 meses. Casos excepcionales se han resuelto en menos de 60 días.

¿Puedo trabajar en España mientras se tramita la homologación?

No puedes ejercer una profesión regulada (médico, enfermero, arquitecto, etc.) hasta tener la Credencial de Homologación. Puedes trabajar en otros sectores sin restricción.

¿Necesito visado para presentar la solicitud de homologación?

No. La solicitud puede presentarse desde el extranjero por sede electrónica. No requiere residencia en España.

¿Qué pasa si me deniegan la homologación?

Puedes presentar recurso de reposición ante el mismo órgano (plazo 1 mes) o recurso contencioso-administrativo ante el Tribunal Superior de Justicia (plazo 2 meses). Tienes derecho a asistencia letrada.

¿La homologación me permite colegiarme automáticamente?

Sí, una vez tienes la Credencial de Homologación, puedes solicitar tu colegiación en el Colegio Profesional correspondiente. Cada colegio tiene sus propios trámites adicionales.

¿Sirve la homologación para opositar?

Sí. Las oposiciones públicas que exijan titulación universitaria oficial española aceptan la Credencial de Homologación como equivalente.

¿Sirve la homologación para hacer Máster oficial?

Sí. Los Máster Universitarios oficiales españoles aceptan el título homologado como acceso. Algunas universidades pueden además requerir trámites internos adicionales.

¿Existe homologación parcial?

No exactamente. Existe la homologación condicionada a requisitos formativos complementarios: el Ministerio reconoce parcialmente el título y exige cursar formación adicional (entre 30 y 90 ECTS, examen de aptitud, prácticas tuteladas).

¿Puedo homologar más de un título a la vez?

Sí. Puedes presentar varios expedientes en paralelo (por ejemplo, Grado + Máster, o dos titulaciones distintas). Cada uno paga su tasa.

¿Las titulaciones online se pueden homologar?

Depende. Si la universidad emisora es oficialmente reconocida en su país y la modalidad online está reconocida oficialmente, sí. Si es una institución no acreditada o el programa no es oficial, no.

¿Cómo verifico el estado de mi expediente?

A través de la sede electrónica del Ministerio de Universidades (universidades.sede.gob.es), accediendo con Cl@ve o certificado digital, en "Mis expedientes". Estados posibles: En revisión, Subsanación requerida, Propuesta de concesión, Favorable, Desfavorable.

¿Qué es una credencial NARIC?

La credencial es el documento oficial expedido por la Oficina Nacional de Reconocimiento Académico y Profesional de Títulos Universitarios Extranjeros (NARIC España), dependiente del Ministerio. Es el documento que acredita que tu título está homologado.

¿Diferencia entre Grado y Licenciatura?

En España, la "Licenciatura" fue sustituida por el Grado tras la Reforma de Bolonia (2010). Las antiguas licenciaturas (4-5 años) son equiparables al Grado actual (4 años, 240 ECTS).

¿Puedo homologar un título técnico (no universitario)?

No mediante este procedimiento. Los títulos no universitarios (técnico superior, formación profesional) se homologan mediante un procedimiento distinto ante el Ministerio de Educación y Formación Profesional.

¿Aplica la homologación a títulos del Espacio Europeo de Educación Superior (EEES)?

Generalmente no. Para títulos del EEES procede el reconocimiento profesional (por la Directiva 2005/36/CE) ante el ministerio sectorial competente (Sanidad para médicos, etc.).

¿Qué pasa si la universidad de origen ya no existe?

Si la universidad fue clausurada pero estaba oficialmente reconocida en el momento de tu titulación, la homologación es posible. Necesitarás certificaciones del organismo sucesor o del Ministerio de Educación del país de origen.

¿Cómo afecta el Real Decreto 889/2022 a los expedientes en curso?

Los expedientes presentados antes de la entrada en vigor del RD 889/2022 se rigen por la normativa anterior (RD 967/2014), aunque los criterios técnicos suelen ser similares.

¿Puedo recibir notificaciones por email?

Las notificaciones oficiales se hacen por la sede electrónica. Puedes activar avisos por email pero no son la notificación legal.

¿Es válida la homologación en otros países?

La Credencial de Homologación tiene validez en España. Para ejercer en otro país, necesitas hacer el procedimiento de ese país. Algunos países (Italia, Portugal, países hispanoamericanos) reconocen títulos oficiales españoles bajo ciertas condiciones.

¿Cuánto cuesta un servicio profesional como Homologa.pro?

Varía según el paquete. El diagnóstico profesional parte desde 59 € y el servicio completo de tramitación desde 790 €. Los precios incluyen revisión documental, traducciones gestionadas, presentación, seguimiento y, si fuera necesario, recursos administrativos.

¿Cómo elijo una buena gestoría de homologación?

Verifica: experiencia específica en homologación (no gestoría genérica), abogados administrativistas en plantilla, casos verificables, transparencia de precios, sin promesas de plazos (los plazos los marca el Ministerio).

¿Necesito NIE para homologar?

No es obligatorio para presentar la solicitud. Puedes hacerla con pasaporte. El NIE es necesario después para colegiarte y trabajar.

¿Cómo se cuentan los créditos extranjeros frente a los ECTS?

El Ministerio aplica equivalencias estándar: 1 año académico ≈ 60 ECTS ≈ 1.500-1.800 horas de trabajo del estudiante. Los planes con menor carga lectiva pueden recibir requisitos formativos complementarios.

¿Es legal hacer la homologación con poderes (apoderado)?

Sí. Puedes designar un apoderado (familiar, abogado, gestor) mediante poder notarial o Apodera (registro electrónico de apoderamientos). Ideal si vives fuera de España.

¿Cuándo se considera firme la resolución?

Una vez transcurrido el plazo para recursos (1 mes para reposición, 2 para contencioso) sin presentar ninguno, o resueltos los recursos.

¿Puedo cambiar de profesión en el expediente?

No. Cada profesión genera un expediente distinto. Si quieres homologar Medicina y luego Psicología, son dos procedimientos separados.

¿Las prácticas hospitalarias cuentan como horas formativas?

Sí, siempre que estén certificadas oficialmente por la universidad o institución sanitaria. Es uno de los puntos críticos en Medicina, Enfermería, Odontología y Farmacia.

¿Qué pasa si presento documentos falsos?

Es delito de falsedad documental (artículos 390-397 del Código Penal español) y conlleva penas de prisión. El Ministerio coopera con autoridades policiales y judiciales.

¿Tengo derecho a obtener copia de mi expediente?

Sí, conforme al artículo 53 de la Ley 39/2015 y a la normativa de transparencia.

¿La homologación caduca?

No. Una vez obtenida la Credencial, la homologación es permanente. La profesión regulada puede tener requisitos de formación continua, pero el reconocimiento del título no caduca.

¿Aplica a doctorados?

Sí. El RD 889/2022 incluye procedimientos específicos para títulos de Doctorado. Suele ser un proceso más rápido si el título original ya es oficialmente reconocido en su país.

¿Cómo encuentro el plan de estudios español para comparar?

Está disponible en la web del Registro Universitario de Centros y Títulos (RUCT) del Ministerio de Universidades.

¿Las universidades privadas españolas equivalen a las públicas para homologación?

Sí, siempre que sean universidades oficialmente reconocidas y los títulos figuren en el RUCT.

¿Hay diferencia entre homologación a Grado vs Licenciatura?

No práctica. La Credencial actual se refiere al "título universitario oficial español de Grado", aplicable a planes nuevos (Bolonia) y antiguos (licenciaturas).

¿Qué hago si pierdo la Credencial original?

Puedes solicitar duplicado al Ministerio. La credencial original digital sigue siendo válida y verificable con CSV en pf.redsara.es/pf/valida.

¿Las traducciones juradas tienen vigencia?

No caducan, pero si la documentación original cambia o se actualiza, la traducción debe rehacerse.

¿Puede mi empleador exigir homologación antes de contratarme?

Para profesiones reguladas, sí (es legalmente exigible). Para otros sectores, depende del empleador y del puesto.

¿Existen ayudas o becas para tramitar la homologación?

No hay ayuda pública específica del Estado español. Algunas Comunidades Autónomas o programas específicos para refugiados, retornados, o colectivos vulnerables ofrecen ayudas parciales (consultar Servicios Públicos de Empleo regionales).

18. Glosario de términos

• Apostilla: Sello internacional regulado por el Convenio de La Haya de 1961 que valida la autenticidad de un documento público para uso en países firmantes.
• BOE: Boletín Oficial del Estado. Diario oficial donde se publican las leyes, decretos y resoluciones del Estado español.
• Cl@ve: Sistema de identificación electrónica del Estado español para realizar trámites en sede electrónica.
• Credencial de Homologación: Documento oficial emitido por la NARIC España que acredita la equivalencia entre un título extranjero y un título oficial español.
• CSV: Código Seguro de Verificación. Permite verificar la autenticidad de documentos electrónicos firmados digitalmente en pf.redsara.es/pf/valida.
• EEES: Espacio Europeo de Educación Superior. Marco creado por el Proceso de Bolonia.
• GEISER: Gestión Integrada de Servicios de Registro. Sistema electrónico de registro de la Administración General del Estado.
• Homologación: Reconocimiento por el Estado español de un título extranjero como equivalente a uno oficial español.
• MAEC: Ministerio de Asuntos Exteriores, Unión Europea y Cooperación. Habilita traductores jurados en España.
• MIR: Médico Interno Residente. Sistema de formación sanitaria especializada en España.
• NARIC: Oficina Nacional de Reconocimiento Académico y Profesional de Títulos Universitarios Extranjeros.
• NIE: Número de Identidad de Extranjero. Documento de identificación para extranjeros en España.
• NIP: Número de Identificación Profesional. Identificador en algunos colegios profesionales.
• PIR: Psicólogo Interno Residente. Formación especializada en Psicología Clínica.
• Profesión regulada: Profesión cuyo ejercicio requiere por ley una titulación específica.
• RD 889/2022: Real Decreto 889/2022, de 18 de octubre. Norma vigente que regula la homologación.
• RUCT: Registro Universitario de Centros y Títulos. Listado oficial de títulos universitarios españoles.
• Sede electrónica: Portal oficial donde la Administración ofrece servicios y procedimientos por internet.
• Subsanación: Subsanar = corregir un defecto del expediente cuando el Ministerio lo requiere.
• Traducción jurada: Traducción realizada por un Traductor-Intérprete Jurado habilitado por el MAEC, con valor legal en España.

19. Recursos oficiales y referencias

Recursos oficiales

• Ministerio de Universidades — Sede electrónica: universidades.sede.gob.es
• NARIC España: universidades.gob.es/portal/site/universidades/
• Modelo 790 (pago de tasa): www.agenciatributaria.es
• Validación CSV: pf.redsara.es/pf/valida
• Registro Universitario de Centros y Títulos (RUCT): www.educacion.gob.es/ruct
• Apostilla España: www.maec.es (Sección de Legalizaciones)

Marco normativo

• Real Decreto 889/2022, de 18 de octubre. BOE-A-2022-17143
• Ley 44/2003, de 21 de noviembre, de ordenación de las profesiones sanitarias.
• Directiva 2005/36/CE (modificada por la 2013/55/UE) sobre reconocimiento de cualificaciones profesionales.
• Ley 39/2015, de 1 de octubre, del Procedimiento Administrativo Común.
• Real Decreto 1837/2008, de 8 de noviembre (especialidades sanitarias).

Jurisprudencia relevante

• Sentencia TS, Sala 3ª, de 14/12/2021 (criterios de comparabilidad de planes de estudios).
• Sentencia TS, Sala 3ª, de 22/03/2022 (motivación de denegaciones).
• Sentencia AN, Sala Contencioso, de 18/05/2023 (recurso contra requisitos formativos complementarios).

20. Sobre Homologa.pro

Homologa.pro es la consultora especializada en homologación de títulos universitarios extranjeros en España, con foco en profesionales de América Latina y nacionales españoles formados en el extranjero. Su equipo combina abogados administrativistas, especialistas en derecho educativo y gestores documentales con experiencia probada ante el Ministerio de Universidades.

Servicios:

• Diagnóstico Profesional desde 59 €: análisis jurídico de viabilidad de tu caso, documentos necesarios, ruta óptima y plazos esperables. Entregado en 48 horas.
• Homologación Completa desde 790 €: servicio integral llave en mano. Revisión documental, gestión de traducciones juradas, apostilla/legalización, presentación electrónica, seguimiento del expediente, respuesta a requerimientos y, si fuera necesario, recursos administrativos.

Cobertura:

• Profesionales de Colombia, Venezuela, Argentina, México, Perú, Ecuador, Cuba, República Dominicana, Brasil, Chile, Bolivia, Uruguay, Paraguay y otros países LatAm.
• Españoles formados en el extranjero.
• Profesionales de otros países (EEUU, Reino Unido, Canadá, Australia, países asiáticos).

Profesiones gestionadas:

Medicina, Enfermería, Odontología, Farmacia, Fisioterapia, Psicología, Veterinaria, Arquitectura, Ingenierías, Derecho, Educación, Trabajo Social, Administración y Dirección de Empresas, Contabilidad y otras profesiones reguladas y no reguladas.

Compromiso ético: Homologa.pro no promete plazos que dependan del Ministerio (los plazos los marca la ley y la cola administrativa). El compromiso es la calidad jurídica del expediente y el acompañamiento profesional, factores que sí dependen del equipo y que sí influyen directamente en evitar requerimientos y reducir tiempos de subsanación.

Web: homologa.pro

Conclusión

La homologación de un título universitario extranjero en España es un procedimiento administrativo complejo, regulado por el RD 889/2022, que decide tu capacidad para ejercer una profesión regulada en territorio español. Los errores documentales son la principal causa de retraso y denegación. La diferencia entre un expediente resuelto en 50 días y otro que se prolonga 18 meses está, casi siempre, en la calidad de la documentación presentada inicialmente.

Si tu objetivo es ejercer en España una profesión sanitaria, técnica o jurídica con un título obtenido en Colombia, Venezuela, Argentina, México, Perú, Ecuador, Cuba, República Dominicana, Brasil, Chile o cualquier país fuera del EEES, prepara tu expediente con rigor jurídico desde el primer día. Cada documento mal compulsado, cada traducción no jurada, cada plan de estudios incompleto es un mes adicional de espera.

Si quieres una evaluación profesional sin compromiso sobre la viabilidad de tu caso, los documentos exactos que necesitas y la estrategia óptima, el Diagnóstico Profesional de Homologa.pro está disponible desde 59 € y se entrega en 48 horas.

Citación recomendada (APA 7):

Equipo de investigación jurídica. (2026, mayo 13). Homologación de Títulos Universitarios Extranjeros en España: Guía Definitiva 2026 (Real Decreto 889/2022, Plazos Reales y Casos Verificables). Pressbooks. https://wsu.pressbooks.pub/

Licencia: Este artículo se publica bajo licencia Creative Commons CC-BY-SA 4.0, permitiendo reproducción y adaptación con atribución y compartición igual.

Conflicto de interés: Este artículo menciona el servicio Homologa.pro como ejemplo de consultora profesional en el mercado. La información jurídica y procedimental es independiente y verificable contra las fuentes oficiales citadas.

Etiquetas / Tags

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Author response:

Both reviewers noted that some published studies question the association of HPV types with cervical cancer survival {PMIDs 36207323 and 33117670}, while others did not observe that {REFS 69-74 in Chakravarty}. We appreciate both reviewers pushing us to discuss and hypothesize (even speculate) on our finding that HPV types not in phylogenetic clade α9 types (including HPV18) had more recurrences than α9 types (including HPV16). The most likely explanation is that we analyzed 225 HPV types not just the most prevalent types. Specifically, each of the 5 recurrences in our pilot study had different HPV types (α7’s: 18, 39, 45, 70 & α5: 69). Similarly, on re-examination of the TCGA data set, we found that 80% of the 181 α9 samples had HPV16, while 52.5% of the non-α9 samples had HPV18, consistent with a broader variety of types in the latter. We note that PMID: 36207323 did assess a broad number of HPV types, but these were classified into three non-cladistic categories, HPV16, HPV18 and Other for comparison. More in line with the main point of that study, HPV18 was enriched, though not significantly, in the more pathogenic C2 group (which was defined by a deep analysis of specific genomic alterations). It can be speculated that perhaps α9 types are less proficient at effecting or interacting with some C2 characteristic(s). Overall, we suggest that these observations emphasize the importance of examining the full spectrum of HPV types including phylogenetic relationships in cervical cancers induced by these viruses.

Reviewer #1:

The detection of “non-tumor HPVs” was noted as a potential limitation. The highly multiplexed, HC+SEQ methodology that we use obviously detects many HPV types and thus can identify lesions with multiple HPV types as occurred in Patient 16 and in other HPV cancers. It is unclear what role multiple HPV types might play in tumorigenesis if any. Regardless of whether broad detection of HPV types proves to be a limitation or an advantage, it will be interesting. Our approach in this study focused on integration of HPV DNAs into human DNA, as this is a key event in cervical tumorigenesis. We believe that detection of clonally expanded cells with an integrated URR-E6-E7 DNA segment of any HPV type (whether high-risk, low-risk, or intermediate, or even perhaps non α-clade {PMID:40742260}) should be viewed with suspicion. For the small fraction of cervical cancers that contain only unintegrated HPV DNA, it will be interesting to see if these viral DNAs share any particular properties.

The reviewer asked for details of the HPV DNA capture probes used. All were from the proprietary Roche Nimblegen SeqCap EZ System. They encompassed all HPV types from HPV1 through HPV225.

The reviewer questioned why the data verifying the viral-human DNA junctions in primary tumor tissue by the orthogonal approach of PCR assays PCR assays were not shown. The data summary and the approach used for PCR are in Figure 1, Table 1 and Supplementary Table 1. Only the dozens of agarose gel photographs were not shown. PCR assays that addressed key issues comparing primary and metastatic sites and confirming HPV16 + HPV18 coinfection are shown in Figure 2 and Figures 4A & 4B, respectively.

Reviewer #2:

The reviewer raised general issues about data quantification and statistical adequacy. Regarding data quantification, we used a strict, conservative guideline of a 10 read minimum per junction in the DNA from tumor samples. This was based on the sequence analysis pipeline design and on our requirement that some clonal expansion of cells containing specific junctions must have occurred. Extensive complications to comparing quantified read counts in different studies are detailed below in the responses to specific comments. The statistical methods used were based on the dichotomous variable of detection versus no detection of integrated HPV DNA. For this study, we also used the orthogonal method of verifying every junction by PCR with one primer in viral DNA and the other in flanking human DNA followed by Sanger sequencing. The statistical methods used were entirely appropriate for this dichotomous variable and time to event analyses. Nonetheless, we concur that quantification of HPV DNA integration would be an interesting variable to consider once carefully controlled methodologies are applied considering the issues detailed below.

Regarding the first point about variability in HPV-human junction number in different studies: The number of HPV DNA genome and junction read counts obtained from a sample are subject to numerous technical and biological variables. Extensive caution should be applied when comparing quantitative results among different studies, and this particularly includes the number HPV-human DNA junctions detected. Among the factors that can be involved among different studies are the following: 1) inadequate deduplication of sequence reads; 2) “barcode-hopping” or “bleed-through” from one sample to another and thus cross-contamination of one sample with another during multiplexed short-read sequencing; 3) variation in the fraction of cells that are tumor cells in the post-clinical analysis sample of tissue obtained; 4) artifactual ligation of HPV and human DNA segments occurring at the adaptor ligation step of short-read sequencing; 5) variability in the mismatch settings of computational sequence aligners used; 6) perhaps most importantly, the level of genomic instability of each particular integration locus; and 7) subclonal variation in proliferation or survival of cells containing specific junctions within a lesion. The reviewer correctly implied that our requirement for a minimum of 10 sequence reads at each junction excludes low level, subclonal variants. Nonetheless, one tumor did have two integrations (Table 1). More importantly, we emphasize that all five tumor-recurrences at distant metastatic sites in our study had the exact same integration event as the primary tumor (determined at single nucleotide resolution at both ends). We judge this to be compelling evidence that the approach we use correctly identifies the key integration event underlying each cancer.

Regarding the second point about ratios between genomic DNA copy numbers and junction read counts: Both human genome and HPV genome copy numbers deserve mention in regard to this issue. HPV HC+SEQ highly enriches for viral DNA, with the advantage gained of high read depth for viral sequences, but with human DNA largely excluded (except for the junction reads). Thus, ratios of junctions to the rest of the human genome cannot be assessed as they can be with whole genome sequencing methodologies. While HPV genome read depth can be ascertained with HC+SEQ reads (as in Figure 1C, 1D, 1E), and the reviewer’s suggestion raises the possibility of using junction to viral read ratios to normalize data to compare different integration loci and even perhaps different studies, there are nonetheless additional, biomedically relevant complications. HPV DNA segments are sometimes often present as tandem units with or without human DNA segments in tumors (Figure 1E shows the former), and this affects the ratio of junctions to viral genomes. Thus, using the suggested ratios would require additional normalization for tandem copy numbers, and thus, it would be difficult to use them in a manner analogous to gene-specific read counts per million total read ratios in RNA-seq.

Regarding the third point about comparing read counts from primary tumor tissue with those from cfDNA: Ours was a retrospective study using archived samples that were available, and the HPV genome coverage obtained by HC+SEQ using cfDNA varied (Table 1). Assessment of viral DNA genome and human junction reads in a quantitatively reliable manner by HC+SEQ will require application of precise collection, storage, and processing of cfDNA samples. Nonetheless, the results presented in this study, while variable among the different samples, were entirely sufficient to test the dichotomous variable analyzed. We note that this included orthogonal, PCR verification of junctions, based on the straightforward, abundant identification of the junctions by HC+SEQ in the primary tumor samples. We emphasize that examination of HPV DNA integration directly interrogates a key, likely causal event in HPV cervical tumorigenesis.

Regarding the fourth point about many of the initial cancer samples harboring no junction breakpoints: 100% of the 16 initial, cervical, primary tumor tissue samples harbored an integration (one sample had two). The reviewer is correct that many of the initial cfDNA samples lacked HPV DNA integration as assessed by HC+SEQ and by PCR based on the junctions detected in the primary tumor tissue. We interpret this to mean that these cancers were not spilling genomic DNA containing the integrated HPV DNA into serum at sufficient levels to be detected, and judge this to be due to underlying, unidentified, biomedically-relevant effects.

Regarding the fifth point about HPV-human DNA junctions being used as a measure of tumor heterogeneity and subclonal variation: We concur with the reviewer that this is an interesting, important issue. We noted it in the response to the “first” point (numbers 6 and 7) above. Again, one of the samples had two integrations, and this patient did not suffer a recurrence (Table 1, Figure 1). Based on our ongoing experience, to take findings of junction subclonality beyond just detection of multiple integration junctions, we believe that development of in situ, single cell approaches are necessary to reveal the full meaningful picture of subclonality.

Beyond these quantitative issues that we raise in response to Reviewer #2’s comments, the Reviewers’ comments point at important, incompletely understood aspects about HPV tumorigenesis. Our finding of the identical viral DNA insertions in primary tumors and metastases point to a central, constant role for these structures in viral tumorigenesis. Nonetheless, the issues raised point to key questions concerning subclonality, detailed structures and quantification of HPV and human tandem DNA units, intrachromosomal DNA vs. ecDNA, genomic instability of integrated HPV DNA loci, and cell-to-cell variation, and what roles these might play in tumorigenesis.

Regarding the point about cell-free DNA breakpoints, we note the field of circulating tumor DNA fragmentomics that examines the sequences and a host of structural properties of circulating DNAs derived from tumors including specific, short sequences at the ends (breakpoints) of DNA fragments circulating in blood. These are of emerging significance as biomarkers for cancer {PMIDs:40038442 and 41043439}. We note that cell free DNA breakpoints are not synonymous with DNA junctions. We stress again that the main point of our manuscript was to investigate HPV-human DNA junctions in cfDNA, as this directly addresses a likely causal mechanism underlying HPV cervical tumorigenesis. Additional, future studies would be required to assess the effectiveness of our targeted, individualized approach relative to other aspects of fragmentomics in cervical cancer.

In summary, we restate one of the reviewers’ points. “This study provides important foundational evidence for further evaluating the clinical utility of HPV DNA detection from cfDNA and specifically assessing for integration junctions.” Both reviewers raised thoughtful points about DNA integration and HPV tumorigenesis, and prospective studies are required to refine and evaluate clinical utility of the new findings presented here.

She was changing and tea cake had gone crazy

Janie goes back to the Eatenville

muy interesante, me imagino si por defecto mi sistema Yocto hace lo mismo, y sino, si es posible configurarlo

El niceness value en Linux es un número que indica la prioridad de un proceso en relación con otros procesos del sistema. Los valores van desde -20 (prioridad más alta, el proceso obtiene más tiempo de CPU) hasta 19 (prioridad más baja, el proceso cede tiempo de CPU a otros). El valor por defecto es 0.

Name and singout issue

Estimated 240 to 260 M inclusive of mother in law suite

Maybe change to a text box instead of numbers

3 including mother in law suite

be able to select multiple boxes

confirm two or more?

add: Pool costing is based on volume M3, nor perimeter size M2

add brick

what does it mean?

alignment is not proper left incliend !! please fix it

UN peacekeepers are required to be fair and balanced, keeping all sides on a conflict from fighting with each other.

eLife Assessment

This important study probes the long-standing failure to resolve evolutionary relationships between the classical "spiralian" taxa-i.e., annelids, molluscs, brachiopods, platyhelminths and nemerteans-and provides convincing evidence that the branches leading to them are so short as to be unreliable guides to their relationships. This, in turn, has wide-ranging implications for our understanding of animal body plan evolution and the interpretation of early animal fossils.

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The revised version adequately addresses the relatively minor comments from the previous round of review.]

Summary:

This interesting paper probes the problematic relationships between the classical "spiralian" taxa, i.e., annelids, molluscs, brachiopods, platyhelminths and nemerteans, and shows that the branches leading to them are so short as to be unreliable guides to their relationships. This, in turn, has important implications for how we view the origin of the animal phyla.

Strengths:

A very careful analysis of a famous old problem with quite significant results. The results seem to be robust and support their conclusions.

It often passes uncommented that many different trees are published about animal relationships, yet some parts of the tree seem extremely difficult to resolve; the spiralians are perhaps the most difficult case. More recently, problems about sponges or ctenophores as sister groups to the rest of the animals have alerted us to major areas of uncertainty in large-scale phylogenetic reconstruction; this paper is a welcome reminder that other, perhaps even harder, problems exist which may be difficult to ever resolve with the (molecular) data we have.

Reviewer #2 (Public review):

Summary:

The relationships among the phyla making up Spiralia - a major clade of animals including molluscs, annelids, flatworms, nemerteans and brachiopods - have been challenging from a phylogenomic perspective despite decades of molecular phylogenetic effort. Every topology uniting subsets of these phyla has been recovered with apparent support in at least one study, yet no consensus has emerged even from large-scale genomic datasets. Serra Silva and Telford set out to determine whether this instability reflects a genuine biological signal being obscured by analytical limitations, or whether it reflects a rapid, near-simultaneous origin of these phyla that has left behind in modern genomes far too little phylogenetic information to resolve. They focused deliberately on five phyla, reducing the problem to a tractable set of 15 unrooted and 105 rooted topologies, and applied a suite of complementary approaches across two independent datasets and multiple substitution models to test whether any topology is significantly preferred over alternatives.

Strengths:

(1) The conceptual framing of the problem is excellent, and the study makes a convincing case across several lines of evidence. By enumerating all possible topologies and demonstrating empirically that every one of the 15 unrooted arrangements has been recovered as the preferred solution in at least one published study, the authors make a strong argument about the state of the field. The use of two entirely independent datasets as a consistency check is great, and convergence between them, where it occur,s substantially strengthens confidence in the conclusions.

(2) It is my view that the simulation framework is a particular strength. Generating data on a fully unresolved star tree and scoring those data under both correctly-specified and misspecified substitution models provides convincing evidence that the strong preference for rooting Spiralia on the flatworm branch is, at least partly, an analytical artefact driven by the exceptionally long branch in combination with compositional heterogeneity across sites. This is an important methodological demonstration with implications beyond spiralian phylogenetics, as the same issue is likely to affect other deep, long-branched lineages in the animal tree of life.

(3) The randomised taxon-jackknifing approach is a very nice addition here. The demonstration that preferred topologies shift depending on which species happen to be sampled (even within the same phylum) is a convincing indicator of weak signal, and provides a practical caution for future studies that may report strong support for a particular spiralian arrangement based on a fixed taxon sample.

(4) The branch-length analyses, benchmarking internal interphylum branches against the already disputed and extremely short branch uniting deuterostomes (work also by this group), are well-conceived and solid.

(5) I think it is worth highlighting the notable intellectual honesty throughout the paper: the authors do not overstate their results, correctly acknowledging that while the unrooted topology grouping molluscs with brachiopods and flatworms with nemerteans emerges most consistently, this preference is not statistically significant under more adequate substitution models and may itself carry some artefactual component.

Author response:

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

Public Reviews:

Reviewer #1 (Public review):

Summary:

This interesting paper probes the problematic relationships between the classical "spiralian" taxa, i.e., annelids, molluscs, brachiopods, platyhelminths and nemerteans, and shows that the branches leading to them are so short as to be unreliable guides to their relationships. This, in turn, has important implications for how we view the origin of the animal phyla.

Strengths:

A very careful analysis of a famous old problem with quite significant results. The results seem to be robust and support their conclusions.

It often passes uncommented that many different trees are published about animal relationships, yet some parts of the tree seem extremely difficult to resolve; the spiralians are perhaps the most difficult case. More recently, problems about sponges or ctenophores as sister groups to the rest of the animals have alerted us to major areas of uncertainty in large-scale phylogenetic reconstruction; this paper is a welcome reminder that other, perhaps even harder, problems exist which may be difficult to ever resolve with the (molecular) data we have.

Weaknesses:

The paper could have perhaps drawn out some of the implications of its results in a clearer manner.

Reviewer #2 (Public review):

Summary:

The relationships among the phyla making up Spiralia - a major clade of animals including molluscs, annelids, flatworms, nemerteans and brachiopods - have been challenging from a phylogenomic perspective despite decades of molecular phylogenetic effort. Every topology uniting subsets of these phyla has been recovered with apparent support in at least one study, yet no consensus has emerged even from large-scale genomic datasets. Serra Silva and Telford set out to determine whether this instability reflects a genuine biological signal being obscured by analytical limitations, or whether it reflects a rapid, near-simultaneous origin of these phyla that has left behind in modern genomes far too little phylogenetic information to resolve. They focused deliberately on five phyla, reducing the problem to a tractable set of 15 unrooted and 105 rooted topologies, and applied a suite of complementary approaches across two independent datasets and multiple substitution models to test whether any topology is significantly preferred over alternatives.

Strengths:

(1) The conceptual framing of the problem is excellent, and the study makes a convincing case across several lines of evidence. By enumerating all possible topologies and demonstrating empirically that every one of the 15 unrooted arrangements has been recovered as the preferred solution in at least one published study, the authors make a strong argument about the state of the field. The use of two entirely independent datasets as a consistency check is great, and convergence between them, where it occur,s substantially strengthens confidence in the conclusions.

(2) It is my view that the simulation framework is a particular strength. Generating data on a fully unresolved star tree and scoring those data under both correctly-specified and misspecified substitution models provides convincing evidence that the strong preference for rooting Spiralia on the flatworm branch is, at least partly, an analytical artefact driven by the exceptionally long branch in combination with compositional heterogeneity across sites. This is an important methodological demonstration with implications beyond spiralian phylogenetics, as the same issue is likely to affect other deep, long-branched lineages in the animal tree of life.

(3) The randomised taxon-jackknifing approach is a very nice addition here. The demonstration that preferred topologies shift depending on which species happen to be sampled (even within the same phylum) is a convincing indicator of weak signal, and provides a practical caution for future studies that may report strong support for a particular spiralian arrangement based on a fixed taxon sample.

(4) The branch-length analyses, benchmarking internal interphylum branches against the already disputed and extremely short branch uniting deuterostomes (work also by this group), are well-conceived and solid.

(5) I think it is worth highlighting the notable intellectual honesty throughout the paper: the authors do not overstate their results, correctly acknowledging that while the unrooted topology grouping molluscs with brachiopods and flatworms with nemerteans emerges most consistently, this preference is not statistically significant under more adequate substitution models and may itself carry some artefactual component.

Weaknesses:

(1) The restriction to five phyla is the most significant limitation, as the authors acknowledge this and give a clear computational justification, but readers should be aware that the paper's convincing conclusions apply specifically to the five focal phyla and the evidence remains incomplete with respect to spiralian phylogeny as a whole.

(2) The treatment of substitution model adequacy, while commendably thorough for site-heterogeneous models, is necessarily bounded. The authors note that models accounting for non-stationarity, across-lineage compositional heterogeneity, or mixtures of tree histories might yield different results, and that even the most sophisticated currently available approaches have not produced consistent spiralian topologies across studies. This is not a criticism of what has been done here - the analytical scope is reasonable and well-implemented - but it means the paper cannot be read as a definitive demonstration that no model will ever resolve these relationships. The distinction between a true hard polytomy and a radiation that is effectively unresolvable given current data and methods could be drawn more sharply in the discussion.

(3) The reticulation-aware coalescent analyses are presented somewhat briefly relative to the likelihood-based topology scoring. The finding that flatworms are recovered within a paraphyletic jaw-bearing animal clade in both summary trees - interpreted as long-branch attraction - is striking, and its implications for gene-tree-based approaches to spiralian rooting deserve more discussion than they currently receive.

(4) The central conclusions - that interphylum branches in Spiralia are extraordinarily short, that topological preferences are strongly model-dependent and taxon-sampling-sensitive, and that an ancient rapid radiation is the most parsimonious explanation - are convincingly supported by the evidence presented. The identification of flatworm long-branch attraction as an important confounding factor in rooting analyses is itself an important and well-demonstrated result.

Conclusion:

This paper clearly makes an important contribution to the ongoing debate about spiralian relationships and, more broadly, to methodological discussions about how to handle anciently diversified clades where phylogenetic signal is genuinely limited. The exhaustive topology-scoring framework combined with taxon-jackknifing and simulation under unresolved trees is a valuable methodological template that could usefully be applied to other notoriously difficult nodes in the animal tree. I thoroughly enjoyed the discussion of the implications of these findings for interpreting Cambrian fossils and the evolutionary history of shells, segmentation, larval types and other characters - it is both thoughtful and thought-provoking and will be of broad interest well beyond the phylogenomics and zoology communities. From a very practical perspective, the data and scripts provided make the work useful to researchers wishing to apply similar approaches to other groups.

Reviewer #3 (Public review):

Summary:

This paper addresses the controversial internal relationships within the Spiralia, a major clade of invertebrate animals including molluscs, annelids, brachiopods and flatworms.

Strengths:

Performs a range of empirical analyses and simulations that address the core question. Although a favoured unrooted topology finds some support, this is not strongly endorsed in the paper.

Weaknesses:

(1) Only considers a subset of relevant phyla (e.g. gastrotrichs are relevant to the phylogenetic position of Platyhelminthes), although how this would change the scale of the analyses (i.e. number of topologies) is addressed in the paper.

(2) Discussion of Spiralia evolution and broader context, particularly the relevance for the fossil record. Line 448: our current understanding of the early spiralian fossil record is quite consistent with the main results of this paper. For example, there are very few claims for fossils that sit on the short branch leading to Spiralia (or Lophotrochozoa as defined here) that this paper discusses. Many of the key fossils that inform on the characters discussed in the introduction, which have unusual character combinations, have an apomorphy of one of the phyla discussed, and so are resolved as members of the stem lineages of particular phyla.

(3) This is what you would expect with long phylum stem lineages (line 148) and a short spiralia stem lineage. For example, the mollusc Wiwaxia has chaetae, but a mollusc like Radula (Smith 2012), the conchiferan mollusc Pelagiella has chaetae and a coiled shell (Thomas et al. 2020). The only fossil groups that are routinely discussed as belonging to the stem lineage of more than one phylum are the tommotiids, which have chaetae, segmentation and a complex mineralised skeleton (but not shells in the brachiopod/mollusc sense, see Guo et al 2023) but they sit on the lophophorate stem lineage, a synapomorphy rich group the monophyly of which the present paper endorses (e.g. line 435). The fossil record is consistent with the scenario presented in line 442, e.g. convergent loss or reduction of chaetae and segmentation and convergent evolution of shells in molluscs and brachiopods.

We thank the reviewers for their kind comments. Please see below for detailed responses to all identified weaknesses.

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

Some minor comments that might help improve the paper:

(1) Abstract L17. "Most analyses on the 15 unrooted trees showed a preference for the same topology but the support over other solutions was non significant" - I don't really understand this sentence in the context of the paper; it makes it sound as if the tree is, after all, well resolved! Non-significant, or not significant better than non significant?

Having read the rest of the paper I see what this refers to (uT4), but still I don't understand the second clause.

Re-written to clarify.

(2) Introduction L31. This makes it sound as if phoronids are actually part of brachiopods, and while that was recovered by Cohen and Weydmann 2005, I'm not sure if it's really a general result. In addition, rather than using "brachiopods plus phoronids" everywhere, you could use "Brachiozoa" (Cavalier-Smith 1998, Biol. Rev).

We have updated our text and figures to use Brachiozoa.

(3) L36-37. Yes, but the presence of Chaetagnatha in this clade is suggestive that their primitive body size is not small.

Have made clear that chaetognaths are not all tiny.

(4) L85. Kumar et al. may have claimed that Spiralia are as old as 670, but many other analyses would suggest a range of different results. Why choose just this one? In addition, this age seems rather incompatible with your results.

We agree this maximum age is highly improbable (the principal point remains the deep age of the protostomes). We have used a different reference and refer to a generally acceptable minimum age only.

(5) L88. The key part of this sentence, "proving a hard polytomy", comes at the end of a long set of references that makes it hard to connect to the lead-in "given the age of", so I would suggest rephrasing.

Rephrased for clarity.

(6) L109. It is unclear what this means in the context: "and even support multiple topologies".

Re-worded for clarity.

(7) Figure 1. Why did you choose to indicate brachiopods plus phoronids as a larval form, unlike the other clades? Perhaps it's because we don't know what the last common ancestor of the two looked like (unless P is an ingroup of B), but that's arguably true for some of the other clades as well!

Apologies, this was laziness as we already had a line drawing of an actinotroch larva. Have improved the images in figures 1 and 5 where required.

(8) L164. Reticulation-aware analyses. As I understand it, this would include introgression, hybridization, etc. However, incomplete lineage sorting has also been invoked, not just for Cambrian-explosion age events but also for other major radiations, such as for angiosperms and birds. How significant might ILS be for generating the results you get?

Section title amended. Results section updated to reflect this. We now explicitly mention the potential impact of ILS and introgression on spiralian relationships in our discussion.

Unrooted trees analysis:

(9) L405 on. Maybe it would be worth including a figure showing the relative branch lengths of uT4. All the images of trees show similar-length branches, which gives off the wrong impression within the context of the paper!

We understand the motivation, but we worry that showing uT4 as the sole phylogram may end up with this being interpreted by a casual reader as being the main result of the paper. Hopefully the figures with branch lengths encompass this information well enough and with no danger of misinterpretation.

(10) L430 on. Why is this a "conservative" interpretation?

Yes agreed not clear. Have changed to “We interpret our results as showing that…”

(11) You mention synapomorphy accumulation time and implicitly equate shortness of branches with shortness of time. However, other options are available under varying diversification rate models (e.g. ClaDs, Barido-Sottani et al. 2023 Syst. Biol.; CET, Budd and Mann 2025, Syst.Biol.). In particular, the latter paper shows that when unusually large clades are selected for study (as is arguably the case here), then those clades are likely to have started with very high "evolutionary tempo", which speeds up all aspects of evolution, including diversification rates.

In the Budd and Mann scenario large clades begin with high tempo of cladogenesis, high substitution rate and high diversification rate (rapid origin of new characters). This would suggest that the period of the radiation was extra rapid (even less time than in a ‘normal’ period during which smaller clades emerge) so we feel the point stands.

(12) L449. Maybe refer to the Song et al. paper again here on scaphopods plus bivalves, as it makes the same sort of points, albeit in a slightly different context.

We thank the reviewer for the suggestion and have added the citation where relevant.

(13) Finally, to return to L20. You mention implications for the Cambrian fossil record, but then fail to deliver any!

We have hopefully addressed this remark in the discussion better (at least to the extent we are qualified to).

Yet if you are correct, then synapomorphy accumulation would unite groups of phyla, and would surely lead to a scenario highly incompatible with clock models suggesting deep origins of clades (as they would all be more fossilisable).

Apologies but we don’t completely understand this point as ‘synapomorphy accumulation would unite groups of phyla’ is a little ambiguous. Of course, this is generally true, but our results suggest there was little opportunity to accumulate identifiable synapomorphies linking pairs, triplets or quartets of our 5 spiralian phyla.

In addition, clock results suggest rather long periods of time leading to the phyla, which would imply that there would have to be extremely slow rates of molecular evolution to yield the short early branches here. Also, it might be worth referring to papers compatible with this view, such as Wernström, J.V. et al., EvoDevo 13, 17 (2022). https://doi.org/10.1186/s13227-022-00202-8 or some of the palaeo literature, such as Budd and Jackson 2016, Phil Trans.

The referee refers to clock results suggesting a (deep) Ediacaran origin of Lophotrochozoa/Spiralia. We interpret the spiralian radiation itself as rapid but, in the absence of a clock analysis, we cannot comment on when it took place.

Reviewer #2 (Recommendations for the authors):

(My not very) Major points - as I feel this is an excellent paper.

(1) The coalescent-based summary tree analyses warrant expansion. The recovery of flatworms within a paraphyletic jaw-bearing animal clade in both summary trees is a striking result attributed to long-branch attraction, but this interpretation would be strengthened by examining whether pruning or downweighting the longest-branching taxa within those groups affects the outcome, or by reporting per-node quartet scores more fully. This would make the reticulation-aware results more directly informative and would bring this section into better balance with the detailed likelihood-based analyses.

We thank the reviewer for the suggestion of the expanded analyses. We have now done these, and they yielded essentially the same results as the unpruned analyses. Additionally, while not discussed, we ran the Astral analyses on the subset of gene-trees where all groups of interest (spiralian phyla and superphyletic Ecdysozoa, Deuterostomia, etc.) were monophyletic and found no changes to interphylum quartet scores beyond those due to enforced (super)phylum monophyly, with Platyhelminths still recovered within Gnathifera.

We have expanded our description of the results slightly as well as our discussion. Location of the tables with detailed quartet scores and local posterior probabilities has been added to Fig. S1’s legend.

(2) It would strengthen the paper to include at least a brief analysis or explicit discussion of whether any currently available models accounting for non-stationary or across-lineage compositional heterogeneity show any change in the pattern of support, even if only tested on a subset of topologies. A null result here would itself be informative and would make the conclusions more robust to the concern that unexamined model classes might behave differently.

We thank the reviewer for the suggestion, but this represents a considerable amount of new work and we think it falls outside the scope of the present work. We have, as suggested, included this as a discussion point.

(3) The authors note that topologies grouping flatworms with ribbon worms appear among the higher-scoring arrangements even under model misspecification in simulations. It would be helpful to comment explicitly on whether the apparent signal for this grouping should therefore be regarded with particular scepticism, or whether it survives artefact correction in any of the analyses, as this is a grouping that has appeared repeatedly in the literature and readers will want guidance on how to interpret it.

We do state that the nemertean+platyhelminth grouping seems likely to be at the least emphasised by an artefact (as the referee points out it is common to the higher scoring trees in the star tree simulations). We state that this suggests “…that this grouping derives some support from systematic errors.” We now return briefly to this in the discussion.

Writing and presentation

(1) The abstract states that rooting Spiralia on the flatworm branch "is a long-branch artefact" - this is slightly stronger than the language used in the body of the paper, where the authors correctly write that this preference is "at least enhanced by" the artefact. The abstract phrasing should be softened to reflect the more nuanced conclusion in the text.

Good point. Done.

(2) A brief signposting sentence near the start of the Results, setting out the overall analytical logic before the individual sections begin, would help orient readers. The strategy - score all topologies, test robustness to model choice and taxon sampling, then use simulation to identify artefactual signals - is clear in retrospect but would benefit from being made explicit upfront.

We have taken this suggestion on board. The summary seemed in the end better placed as the final part of the introduction.

(3) Figure 3 is complex and would be easier to interpret with a brief explanatory note in the legend clarifying what a wide versus narrow range of log-likelihood scores across topologies means in practical terms for statistical resolution between trees.

Added sentence to legend.

Minor Corrections:

(1) The Figure 2 legend contains a typographical error: "shorter than the short, disputed deuterostome branch" should read "shorter than."

Done

(2) At least one reference appears to carry a future publication year (Ishii et al., 2026) and should be verified for accuracy before final submission.

This reference is correct per the journal’s website. We did find Google Scholar to list it as being from 2025.

Reviewer #3 (Recommendations for the authors):

(1) Abstract/SI definitions of Spiralia/Lophotrochozoa

While I don't have strong feelings about this, if Spiralia is being used as an apomorphy-based name, then it still might be equivalent to Lophotrochozoa, as spiral cleavage in Gnathostoniula jenneri was illustrated by Riedl (1969). Although no other studies have replicated this observation, this should at least be mentioned.

Sorry this reference to gnathostomulid spiral cleavage was included in a longer version of the discussion of nomenclature. This was first reduced in length (which was when the mention of gnathostomulid spiral cleavage was dropped) then finally moved to the supplementary material. We have now re-included mention of this in the discussion in supplementary info.

The SI text suggests that the name Lophotrochozoa, as used in its original form by Halanych et al. (1995), was a node-based definition, and that this name is for the sister group of Ecdysozoa. However, in that paper, the name is actually defined as "as the last common ancestor of the three traditional lophophorate taxa, the molluscs, and the annelids, and all of the descendants of that common ancestor". This definition would exclude Gnathifera, and depending on the internal relationships of the non-Gnathiferan phyla, may be equivalent (or not) to the usage of the name Spiralia adopted in the present paper. The perils of mixing node and apomorphy-based definitions of clades are clear, and the situation is less straightforward than the paper suggests, and (somewhat unhelpfully given the subject of the paper) may only become clearer if the relationships of non-ecdysozoan protostomes are resolved.

We believe that the community universally understood the definition of Lophotrochozoa following the 1997 paper (by the authors who also provided the original 1995 definition). This 1997 definition included both chaetognaths and rotifers as examples of the Gnathifera. The Spiralia, in contrast, began life not even as a name for a clade but a description of a character shared by some apparently unrelated taxa – similar to a grouping of ‘carnivores’. The introduction of a new name was, we suggest, unhelpful. We hope that by defining our terms up front the meaning in the current paper is clear.

(2) Introduction

Line 76. Some references needed regarding claims that there was a polymeric brachiopod ancestor, e.g. Gutman (1978), Temereva and Malakhov (2011), Guo et al. (2023). Likewise for the chaetae of brachiopods, annelids and molluscs, e.g. Schiemann (2017), as it's key to trace where these ideas originated.

Added

Figure 1. This is a nice illustration of the uncertainty in the relationships of these groups. However, I kept checking which thumbnail image was which for nemerteans and annelids. A minor suggestion, but perhaps a polychaete instead for the annelid?

We have replaced the rather poor image of an earthworm with a polychaete and also now include labels. We hope the improved images are more helpful. Good point.

(3) Results

Branch length comparison. I understand why the deuterostome stem was chosen as the branch for comparison from the point of view of phylogenetic uncertainty. However, what about the branch leading to ecdysozoa or the branch subtending lophotrochozoan and/or gnathifera? Given that the short internodes are used as an argument underpinning uncertain relationships, can we be sure that Gnathifera is not nested within the group of interest, especially given that Gnathifera contains many long-branched taxa and the root may be misplaced within the group?

We have added the Lophotrochozoa and Ecdysozoa median lengths to our plots and now discuss both the lophotrochozoan branch in our results.

Line 249. Given that Spiralia is the group of interest, why were the Gnathiferans also chosen at random?

The point of the experiment was to see the effect of taxon sampling on the consistency of the resulting topology. Random sampling across the tree seems helpful in this context. We chose Gnathifera as one group to sample from as this ensured they would be present in all trees. This seems appropriate as they are the sister group of the clade of interest and as such their inclusion reflects a choice a typical investigator might make when choosing which species to include. Additionally, as noted in the reviewer’s earlier comment, Gnathifera includes many long-branched taxa and we wanted to ensure our root-placement results were robust to this aspect of taxon sampling.

(4) Discussion

Line 448. Our current understanding of the early spiralian fossil record is quite consistent with the main results of this paper. For example, there are very few claims for fossils that sit on the short branch leading to Spiralia (or Lophotrochozoa as defined here) that this paper discusses. Many of the key fossils that inform on the characters discussed in the introduction that have unusual character combinations have an apomorphy of one of the phyla discussed, and so are resolved as members of the stem lineages of particular phyla.

This is what you would expect with long phylum stem lineages (line 148) and a short spiralia stem lineage. For example, the mollusc Wiwaxia has chaetae, but a mollusc like radula (Smith 2012), the conchiferan mollusc Pelagiella has chaetae and a coiled shell (Thomas et al. 2020). The only fossil groups that are routinely discussed as belonging to the stem lineage of more than one phylum are the tommotiids, which have chaetae, segmentation and a complex mineralised skeleton (but not shells in the brachiopod/mollusc sense, see Guo et al 2023) but they sit on the lophophorate stem lineage, a synapomorphy rich group the monophyly of which the present paper endorses (e.g. line 435). The fossil record is consistent with the scenario presented in line 442, e.g. convergent loss or reduction of chaetae and segmentation and convergent evolution of shells in molluscs and brachiopods.

We accept these points (though are clearly not experts on these fossils). We have (slightly tentatively given our lack of expertise) expanded our discussion to include these fossil taxa with their combinations of characters.

focus is on the location of a chunk of data

emergent autopoietic data-constucts

not model take any complete raph of what has been elaborated it could be viewed and used as a data model

if we hide the intent trails that spanned them

But then you realize a data model is just a limited idea

it supposed to promote stability reuse and agreement

but in fact it goes against the grain of things tht are dynamic emergent autopoietic

delight in alternaitves and make it easy to change 1s' minds

refactor root and branch the more consequential the better

data modeling language

and property sets

Un BPF program (programa BPF, por Berkeley Packet Filter, aunque ahora se refiere generalmente a eBPF o extended BPF) es un pequeño fragmento de código que se ejecuta de forma segura y eficiente dentro del kernel de Linux.

En el contexto de systemd y la documentación que revisamos:

• Función: Permite ejecutar lógica personalizada en puntos específicos del kernel (llamados "ganchos" o hooks) sin necesidad de modificar el kernel ni cargar módulos externos inseguros.
• Seguridad: El kernel verifica el código antes de ejecutarlo para asegurar que no cause bloqueos, bucles infinitos o acceso a memoria ilegal.
• Uso en systemd: Se utiliza para implementar funciones avanzadas de seguridad y red que no están disponibles con las opciones estándar.

VRF son las siglas de Virtual Routing and Forwarding (Encaminamiento y Reenvío Virtual). Es una tecnología de red que permite crear múltiples tablas de enrutamiento independientes dentro de un mismo router o dispositivo físico.

IPAddressAllow es una directiva de seguridad en systemd que actúa como un filtro de tráfico de red (firewall) a nivel de control group (cgroup). Permite definir una lista blanca de direcciones IP o redes que una unidad (servicio, slice, socket) tiene permiso para utilizar para enviar o recibir paquetes.

• Independencia del proceso: Al aplicarse a todo el grupo de control, el filtro no puede ser eludido por el programa ejecutado (ni siquiera si se intenta usar un binario con permisos especiales o prefijos como +), ya que el kernel aplica la regla al nivel del cgroup.

El IOWeight es un parámetro de configuración en systemd que define la prioridad relativa de acceso al ancho de banda de E/S (lectura/escritura en disco) para una unidad en relación con otras unidades que comparten el mismo dispositivo.

El I/O accounting en systemd es el mecanismo que permite monitorear y contabilizar el tráfico de entrada y salida (lectura/escritura) en dispositivos de bloque (como discos duros o SSDs) para unidades específicas (servicios, slices, etc.).

imagino que esto es asi porque en lugar de hablar de porcentajes, hablamos de porciones aqui.

Entonces, cuando dice que el peso de CPUWeight en a.slice es 20 y en el otro esta por default (es decir, 100), lo que tengo es un total de 120. Luego dividiendo las cantidades en porcentajes, a.slice sería 1/6 de 120 y b.slice 5/6.

Open Hyperdocument System (OHS)

AI and the Coming Deluge of Noise | Frankly 128

no need to move server with loss of network and even data

a clear case of a "better spot" -

the dual of a sweat spot

one that is clearly bellow the threshold of what is required

again it should have said sweet spot

creative dislexia

https://bafybeibs7vj3q4ttx7ud4eb2gv4x2d5b4jmeqi63ws2vjf5h4hnet4bnza.ipfs.dweb.link/?josh.communication.paradim#t=1220,1520

really good start for this paper!

eLife Assessment

This study presents a useful database resource containing protein conformations generated through molecular dynamics simulations, with extensive quality evaluation and benchmarking. While the database is well-constructed and professionally organized, the evidence supporting its claimed representation of protein conformational landscapes is incomplete, as the short simulation times and starting structure bias prevent true Boltzmann sampling of the conformational space.

Reviewer #1 (Public review):

Summary:

The authors describe a new database that rigorously explores protein conformations.

Strengths:

It is extremely well done, using state-of-the-art tools by a group at the top of the field of structural modeling. The evaluation of qualities and the benchmarking of the structures are outstanding, and it is expected that the new database will have a significant impact on the field.

Weaknesses:

The authors are using MD simulation to generate some of the structure, and therefore should have access to standard MD energies. I am surprised that no evaluation is provided based on these energies that can be extended to free energies.

Reviewer #2 (Public review):

Summary:

The authors developed a dataset of protein conformations by running molecular dynamics simulations starting from both native and decoy conformations for a large number of proteins. These conformations were put together as a dataset for querying and downloading, along with their energies under different force fields. The authors suggest that such conformations represent the proteins' conformational landscape, so that they will be useful for evaluating methods generating multiple conformations of proteins.

Strengths:

The dataset is online and working. It has good documentation for others to use.

Weaknesses:

The biggest weakness is that the collected conformations very likely do not represent the true conformational landscape. To represent the conformational landscape, the structures need to be sampled based on the Boltzmann distribution. However, in this study, conformations are generated by running very short (125ps to 375ps) MD simulations starting from near-native conformations and decoys. Such short simulations will produce small fluctuations around the starting conformations, so the distribution of conformations is largely dominated by the distribution of the initial conformations, which by one means are Boltzmann distributed. A conformation might be physically plausible, but it might have very small weight in the Boltzmann distribution. On the other hand, conformations with large weights might not be in the dataset.

Reviewer #3 (Public review):

Summary:

This manuscript describes a web-based tool that allows researchers to compare large numbers of representative ("plausible") conformations of proteins. It also includes energetic analysis from multiple widely used structure-prediction methods.

Strengths:

This tool will likely be useful for students who want to learn more about the ensemble properties of proteins. The resource is well organized and it represents a large amount of computing resources.

Weaknesses:

It is not entirely clear how the database may be utilized by other groups to advance research. It could be helpful if the authors add a short section that provides example use cases that illustrate how this database can support new strategies for studying protein dynamics.

eLife Assessment

This is an important study uncovering a new role of the SETD6-PPARγ axis in the regulation of hepatic lipid metabolism. The data convincingly demonstrate that methylation of PPARγ by SETD6 plays a key role in this process, linking lysine methylation to transcriptional control of lipid storage genes.

Reviewer #1 (Public review):

Summary:

In this manuscript from the Levy lab, the authors investigate whether SETD6 regulates hepatic lipid accumulation through direct methylation of PPARγ. They show that SETD6 binds and mono-methylates PPARγ at K170, and provide evidence that this modification enhances PPARγ occupancy at target promoters, promotes expression of lipid metabolism genes, as well as facilitates lipid droplet accumulation in HepG2 cells. The authors also find a positive feedback loop or circuit in which PPARγ activates SETD6 transcription in a methylation-dependent manner, thereby reinforcing this lipogenic program. Overall, the work presents a novel SETD6-PPARγ regulatory axis linking lysine methylation to transcriptional control of lipid storage genes, with possible relevance to NAFLD-associated biology.

In all, I find this to be an important paper that describes and advances a new regulatory pathway that has significance to human health and disease. It would also be of interest to a broad audience. That said, there are also some concerns that the authors should address, as outlined below.

Major concerns (pertains to rigor - highest priority)

(1) Overall, the work presented is of high quality, and the data nicely support the conclusions; however, a few panels should be strengthened that have missing controls or information:<br /> a. The co-IP panel in Figure 1B lacks a lane where HA SETD6 is expressed without PPARγ. This control is needed to verify that the SEDT6-HA signal depends on PPARγ.<br /> b. In Figure 1C, the authors should show that the co-IP works in both directions (include IP for PPARγ/blot for SETD6). I am a bit confused also over the labeling with IP on the left and on top of the panel next to the beads label. More importantly, the data would be stronger if the authors took advantage of a deletion line to validate that the co-IP is specific to the presence of both.<br /> c. The same IP labeling issue exists for Figure 3B (label is on the same and on top).<br /> d. Antibody information (e.g., where the pan-methyl Ab comes from and at what dilutions they are used at) is missing.

Nice to have experiments (medium priority - strongly consider)

(2) A missing gap is how K170me1 contributes to DNA binding and gene transcription. One possibility is that methylation enhances the DNA-binding activity of PPARγ. Given that the authors have all of the reagents, it would be possible to perform a gel shift assay (or other approach) with and without SETD6-mediated methylation. Is DNA binding affected/enhanced?

(3) Along these lines, I wonder if there is another possibility: could SETD6-mediated methylation of PPARγ drive SETD6-PPARγ interaction? In other words, in the K170R, is SETD6 still even associated with PPARγ, and this interaction is required for promoter recruitment? Alternatively, would a catalytic dead version of SETD6 fail to associate with PPARγ? Currently, no experiments test the impact of an unmethylatable version of PPARγ or a catalytic dead version of SETD6 on SETD6-PPARγ interaction or SETD6 recruitment to promoters.

Minor concerns (text and figure display)

(4) The text has multiple typos and grammatical errors, and there are some issues with the figure display.

Reviewer #2 (Public review):

Summary:

In this work, the authors investigated the regulation of the transcription factor PPARγ by the post-translational modification lysine methylation. The data demonstrate that the lysine methyltransferase SETD6 targets PPARγ for methylation using biochemical and cell-based assays. Methylation of PPARγ occurs in its DNA binding domain, and the authors demonstrate that loss of methylation limits PPARγ chromatin binding, particularly to lipid storage and metabolism gene promoters. As a physiological output, the authors demonstrate that deletion of SETD6 and loss of PPARγ methylation also disrupt lipid droplet accumulation in hepatocytes. In addition, the authors uncover a positive feedback loop in which SETD6 methylation of PPARγ also regulates its binding to the SETD6 promoter and expression of the gene.

Strengths:

One of the key strengths of this manuscript is the novelty of the findings in terms of identifying a new mode of regulation of PPARγ that modulates its chromatin association in cells and thereby regulates lipid metabolism genes. The authors nicely combine biochemical studies of SETD6 activity with cell-based assays investigating PPARγ and SETD6 function in regulating lipid storage. Data supporting this conclusion is largely convincing, and frequently, multiple assays are used to provide sufficient support to the conclusions. This work therefore expands regulatory modes of PPARγ and identifies a new target for SETD6, an enzyme that targets a number of other transcription factors. Furthermore, the regulatory loop that controls SETD6 expression via PPARγ methylation is likely important for understanding SETD6 function in different cell types that have high levels of lipid accumulation or regulation. The gene expression and lipid accumulation assays are useful for testing the physiological outcome of loss of SETD6 activity or PPARγ methylation directly.

Weaknesses:

The data presented in the manuscript are largely convincing in support of the authors' conclusions; however, there are some errors in the presentation of the figures and some issues in the text that would benefit from editing. Furthermore, there are some important questions not fully addressed in the results or discussion. It would be great if the authors could speculate more on the diverse roles of SETD6 in methylated transcription factors and/or provide more context regarding the conditions that are likely to support methylation of PPARγ by SETD6. Also, while a potential cross-talk between methylation and phosphorylation is described in the discussion, it would be great to provide more structural insight into how this might regulate DNA binding of PPARγ and/or discuss whether there are other possibilities given the location of the target lysine in the DNA binding domain.

eLife Assessment

In this useful manuscript, Yang et al attempt to show that platelet recruitment to the liver via macrophages contributes to APAP-induced liver injury, but there were many areas where the data supporting the conclusions were incomplete. For example, the idea that platelets only affected KC glycolysis, but not the metabolism of other cells, to mediate the phenotype after injury is not adequately supported by the evidence. It is recommended to perform additional experiments to strengthen the conclusions.

Reviewer #1 (Public review):

Summary:

In this manuscript, Yang et al expand on their previous work showing that platelet recruitment to the liver via liver macrophages is important for APAP-induced liver injury. Here, they show that platelets induce a glycolytic switch in liver non-parenchymal cells, including Kupffer cells, and that this is mediated by the protein Aldolase A produced by platelet-derived extracellular vesicles (PEV). They show that targeting Aldolase A may be a valid therapeutic strategy for severe APAP injury.

Strengths:

(1) They nicely showed that platelet effects in APAP are mediated by Aldoa via platelet-derived extracellular vesicles.

(2) Their data show that one of the effects of platelets in APAP liver injury is inducing metabolic switch to the glycolytic pathway, including in KCs.

(3) Their data points to the therapeutic potential of targeting ALDOA in severe APAP liver injury.

Weaknesses:

(1) They have not shown that the platelet-induced glycolytic switch is only in KCs.

(2) They also have not shown that KC's role in APAP injury is primarily mediated by their interaction with platelets and the subsequent glycolytic switch.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors have investigated the role of platelet-derived ALDOA in liver injury induced acetaminophen (APAP) induced acute liver injury. There are some major flaws in data interpretation as described below. While a decrease in liver injury due to platelet depletion and lower injury in platelet-specific ALDOA KO mice seems real, the claims related to EVs and Platelet-KC crosstalk are not well supported.

Strengths:

Core findings are interesting and supported by the data

Weaknesses:

(1) At least two additional timepoints, one at 6 hr and another at 24 hr should be performed in the APAP model to better understand the dynamics of liver injury, especially after platelet depletion.

(2) Interpretation of the experiments in Figure 2 with clodronate is flawed. 2-DG pretreatment and CLDN administration alone both seem to decrease liver injury substantially, so it is not surprising to see very little injury in the 2-DG+CLDN group.

(3) Since both 2-DG and CLDN were administered pre-APAP, it is possible that they may interfere with APAP metabolism. This should be checked by looking at GSH depletion at 30 min post APAP treatment. The same question goes for S2 figure data.

(4) There are no data on specific steps of APAP toxicity, such as GSH depletion, JNK activation, mitochondrial injury, etc., which are all well characterized in any of the studies. Rather, only injury endpoints are measured. It is critical to measure the mechanistic steps. This applies to all studies, but most importantly to the ALDOA-PF-KO mice in Figure 6.

(5) Interpretation of data in Figure 5F is flawed. Since depletion of platelets also decreases liver injury along with the platelets, it can not be deduced that the decrease in ALDOA is only in platelets. Many other things are changing.

Reviewer #3 (Public review):

Summary:

The authors address the possibility that platelet (PLT) derived EVs are important mediators of acute liver injury. Furthermore, KCs are important mediators of inflammation and are noted to need to undergo metabolic reprogramming to achieve their effects during injury. They use an APAP-induced liver injury model (AILI). They show that PLTs are recruited and that they interact with KCs in this model system. RNA-seq of KCs showed upregulation of glycolysis and gluconeogenesis. PLT depletion led to reduced liver injury. RNA-seq of KCs showed downregulation of glycolysis. In vitro co-culture of KCs and pets recapitulated the glycolysis findings. In vivo, 2DG inhibited liver injury, but not in the setting of KC depletion. They went on to show that PLT-derived EVs mediate this effect on KCs using a mix of in vitro and in vivo assays, although control EVs were lacking. After doing mass spec on EVs, they find that ALDOA is the critical payload of the PEVs that mediates the pro-glycolytic effect in vivo. They both delete ALDOA from PLTs, and they use an ALDOA inhibitor to show that injury in AILI requires ALDOA.

Strengths:

This is generally an interesting series of observations with an elegant mechanism. Many of the experiments are done in vivo with highly rigorous KO models. However, in many of the EV experiments, there are concerns about a lack of appropriate controls that might limit the rigor of those aspects of the study. 

Weaknesses:

(1) There is strong variability in the gene expression between mice in Figure 1B. I worry that the signals may not be statistically significant. The authors should assess the statistical significance.

(2) In Figure 2B, the necrosis areas that are circled in the image do not seem to resemble the quantitation on the right. For example, I don't see 60% necrosis in the APAP PBS group. Also, I don't see 5-10% necrosis in the CLDN APAP group. More images that are clearer are needed, and circled necrosis areas should be shown.

(3) In Figure 2D, a higher N should be shown. The number of mice (3) is different from the other experiments, so the exclusion of those mice should be explained.

(4) In general, control EVs from a non-PLT source should be used for all EV-related experiments. EVs derived from AML12 hepatocytes would seem to be a reasonable control for some of the experiments. Otherwise, it is hard to know if this is a general EV effect or one that is specific to PLT-derived EVs. In Figure 3B, EVs from non-PLTs should be used as a control. Since it is possible that all EVs express some level of TSG101 or CD63. In addition, control EVs should be used to test effects on KC metabolism, since the claim is that the effects are specific to PLT-derived EVs. Similarly, Figure 4 needs some kind of EV control that is not from PLTs.

(5) Figure 5B should include an EV control in the blot. Most of the blots need controls from AML12 EVs or from another in vivo source.

(6) It is a little difficult to imagine how enough ALDOA protein could be transmitted from PEVs to influence KC glycolysis on the gene expression level. It is possible that ALDOA is required for PLT-induced activation of KCs, or that EVs from PLTs can induce a metabolic shift in KCs. However, it has not been definitively shown that ALDOA from PEVs is directly causing the KC activation. Ultimately, it would be good to obtain PEVs from ALDOA WT and KO mice, then provide these PEVs to AILI mice without PLTs to see if they have differential effects on the AILI model. This would really demonstrate that the ALDOA in the PEVs is mediating the glycolytic, injurious effect.

giám sát công tác triển khai, kiểm thử và vận hành thử