those with more money and resources help to cover those with less

QUESTION: how does insurance directly or indirectly result in someone increasing their health functioning and health agency?

QUESTION: who should this fall on- hospitals, governments, individuals?

emphasis on a no waste healthcare system (QUESTION: how could we monitor this- what is considered waste?)

great idea- saw this in Ypsilanti

everyone should be covered at all times (QUESTION: how would this affect those within the criminal justice system?)

cost can inhibit one's ability to flourish

QUESTION

we should prioritize need ivermectin ability to pay (completely flips the system?

people cannot afford high quality healthcare

potentially conflicts with a market based economy

why universal healthcare is central to the health capability paradigm

To be successful in your writing, before starting, see if you can quickly answer the 5 W's and H question.

Knowing what kind of source you're using helps find accurate information on the topic you're learning about.

I think this is a really good idea , even socializing preventive care which most of the time is inexpensive can be a game changer.

This is my general issue with universal health care. Ineffeciency with government is univeral around the world with a lot of waste around the beaurocracy thus leading to bad quality health care.

Universal healh care can be a mix of public and private parternship where healthcare is heavily subsidized for low income population , i think thats what obama care was meant to be.

Setting up universal healthcare at first could be a significant cost issue aswell as the challenge of chaning it to public system.

Article talks abour pros and cons of Universal health care.

Quizás en el ejemplo convendría poner como elegiste los y_{ij}, que valores les diste, e identificar el valor x_i\in{0,1}

Revisar la fórmula que se presenta, pues en la subsección precedente, el primer término es (D/Q)*S, y aquí se tiene a la inversa, es decir, Q/D. También D\beta C/Q está invertido. Corregir este error en las fórmulas. Por lo tanto también corregir los cálculos numéricos que se presentan, así como las conclusiones de esos cálculos numéricos.

La función es convexa si \sigma_L es constante, pero puede perder convexidad si depende de Q, es decir, si \sigma_L es función de Q.

En la fórmula, la sustitución del primer término está al revés, pues D/QS=1000/200100

En la fórmula, hay algunas variables y constantes que no están definidas explícitamente, por ejemplo que son Q, C .

Los objetos con los que trabajas son probabilísticos, pero mencionas que es determinista. En ese caso hay un pequeña imprecisión conceptual. Quiz'as si se aclara algo como este: "Se adopta una aproximación determinista basada en cuantiles de una distribución. Este enfoque permite formular un modelo de optimización no lineal determinista ".

een klier in het lichaam die hormonen afgeeft.

de belangrijkste zenuw van het parasympathische zenuwstelsel, die zorgt voor rust, herstel en spijsvertering.

Never seen these types of formulas be used....

interesting

Case#: 7-year-old boy

DiseaseAssertion: Atrial flutter (AFL), sick sinus syndrome (SSS), Brugada syndrome (BrS)

FamilyInfo: Family history of sudden death in maternal grandfather at age 30 years. Family testing identified the same SCN5A variant in the proband's mother and sister. The mother was asymptomatic but had a coved type ST elevation in V1 lead recorded at the 3rd intercostal position (Fig. 1e) and remained free of cardiac events until age 37 years. His sister's ECG was normal, and she remained free of cardiac events for 10 months

ParentalTesting: Mother was found to have the same LOF variant

CasePresentingHPOs: HP:0004749, HP:0011712, HP:0011704, HP:0011654

CaseHPOFreeText: AFL detected on ECG with right bundle branch block but no history of arrhythmia, congenital heart disease, or cardiomyopathy. Post-RFCA, patient had sinus arrest lasting up to 7s, leading to diagnosis of sick sinus syndrome (SSS). Post-ablation ECG following a second RFCA revealed Brugada-type patterns, raising suspicion of Brugada syndrome (BrS) which eventually lead to a diagnosis.

CaseNotHPOs: HP:0001638, HP:0001279, HP:0011675

CaseNotHPOFreeText: Cardiomyopathy, syncope, arrhythmia

CasePreviousTesting: NR

Genotyping Method: NR

FunctionalAnalysis: NR

Variant: c.2678G > A p.Arg893His

ClinVar: 67749

CAID: CA016396

gnomAD: https://gnomad.broadinstitute.org/variant/3-38585800-C-T?dataset=gnomad_r4 (v4.1.0 GrpMax FAF: 0.000003390 (European non-Finnish) )

PMID: 40697204

Gene: SCN5A

HGNC ID: 10593

Numbers literally dont speak for themselves...

page 1 Haltères

Décalé vers le bas, avec Philosophie (séparé des fonctions)

Décalé vers le bas, avec Aide (séparé des fonctions)

A mettre à côté de rosace

Mon projet (Plutôt que notre projet) Mes choix Mon budget Mon planning Mes documents Historique Messagerie Philosophie rosace Aide

Quelle différence avec météo?

Plutôt au dessus de Déconnexion dans la barre latérale en bas

A mettre plus en haut au dessus de l'adresse

Votre chargé d'affaires ou Chargé d'Affaires

Regrouper avec Votre conducteur de travaux

Gras, plus gros

Satisfaction Est ce bien cela?

Avancement (au lieu de météo)

This is really interesting because it implies that individual content grabs don't accumulate toward your limit of 50 NotebookLM sourcs

sentence relating to methodology

sentence relating to methodology

sentence relating to methodology

sentence relating to methodology

sentence relating to methodology

What are the 4I model of OL?

These questions are great because they help you narrow down to a specific topic. When you have the audience in mind you can chose a topic that may draw in more willing participants for surveys. The more participants you have the stronger your evidence will be to support your research.

This connects to my major (biology/pre med) because research is really important in science. Doctors and scientists need reliable information to make decisions. One thing I still wonder is how to always know if a source is 100% reliable, especially when different sources say different things.

I found out it interesting how the chapter explains the difference between primary and secondary research. This connects to our class because we sometimes use both, like doing surveys (primary) and reading articles (secondary). It helped me understand when to use each one depending on the assignment.

One thing I understood from this chapter is that research is not just searching things online. You actually have to think about your topic first, make a hypothesis, and ask good questions. This helps you stay focused and makes your work more organized and stronger.

Here is an annotation

https://www.youtube.com/watch?v=ivwX6bTpjJc

Als iemand niet goed kan begrijpen wat er gebeurt (bijv. door cognitieve problemen), moet je extra voorzichtig zijn bij toestemming voor onderzoek.

start observatie --> hypothese = exploratief

van data -> theorie

start theorie --> stelt hypothese --> test met data --> verwerpen of bevestigen h0

Een onafhankelijke maat buiten de test zelf Die iets zegt over het echte functioneren/gedrag Waarmee je testscore wordt vergeleken of voorspeld

Make these hyperlinks clickable

A manera de observación: En este capítulo incluyes conceptos y definiciones que obligan a pensar que trabajas con modelos aleatorios y con incertidumbre, sin embargo, en tu resumen o abstract, mencionas que se trabajarán modelos deterministas. Allí veo una inconsistencia.

Corregir numeración 3.4.4, pues se da en un capítulo posterior

No es necesario usar tildes en la v.a. X

Checar si estas condiciones garantizan unicidad. La positividad del Hessiano en un punto crítico es una condición suficiente de mínimo local estricto, y es relevante en el análisis local de convergencia de métodos de segundo orden, pero tengo entendido que la unicidad requiere más hipótesis. Toma f(x)=(x^2-1)^2, es definida positiva en sus dos minimos locales

Siempre y cuando también la función sea convexa sobre el conjunto convexo. Si el conjunto factible es convexo y la función objetivo es convexa, entonces todo mínimo local es global

Explain why we targeted this 'cross category' substitution. We understand it's initially counter-intuitive. TLDR: Impossible Beef is a defined category with fairly clear pricing and high quality, but chicken consumption is more animal-welfare-relevant than beef. But we have variants of this that are more within-category. Put the TLDR in a tooltip and a longer explanation in a folding box.

Some more detailed explanation at https://forum.effectivealtruism.org/s/kazWBBYXm2Rvya3y2/p/3Eh8MbqLwFBsD7GK2#Why_focus_on_chicken_consumption_ and https://forum.effectivealtruism.org/s/kazWBBYXm2Rvya3y2/p/3Eh8MbqLwFBsD7GK2#Why_focus_on_Impossible_Beyond_Beef_

I'd link the Metaculus question right next to each question here.

Ischaemic heart disease Hypertension Valvular heart disease (esp. mitral stenosis / regurgitation) Acute infections Electrolyte disturbance (hypokalaemia, hypomagnesaemia) Thyrotoxicosis Drugs (e.g. sympathomimetics) Alcohol Pulmonary embolus Pericardial disease Acid-base disturbance Pre-excitation syndromes Cardiomyopathies: dilated, hypertrophic. Phaeochromocytoma

The incident my be either a feature failure or service failure and it must be widespread and not isolated single incident before reporting.

Find out if there is already an incident report ticket live and loop in the incident manager again, if not create a new report and loop in the manager if it meets the requirements below.

this is a comment

This kind of fervor tells me they had more than the national interest in mind.

So, Venezuelans wanted to own the infrastructure, but have the oil companies run the business? I suppose that makes some sense in the short term...

This is the duration of his rule in Libya -- not his birth, and death!

If you try to make them all fit into one definition and then one doesn't, you will try to force it in artificially, or exclude it artificially. And what's the point of that? Why would this be useful? - why is the craving for generality so strong? - one potential answer: there is an instinct to treat philosophy as science (to generalize and theorize) when philosophy is not like science

Suppose someone said "all words mean something" - what is being asked is, what do all words have in common - what that persons is getting to is the "essence" of language - looking for generality

"what do you mean?" - the story must be hashed out

Handles may look alike but each handle plays a different role

There are all of these tools in the tool box and they look more or less alike, "Scarf", "Chloe", "Red", "The": they are all different but they look the same so it is easy to think that they are all the same.

context matters

helpful but not the purpose

how does the association between word and object happen? - maybe a picture develops in their mind when the word is uttered, and then they will know what is meant - "already there" : this is dangerous territory as it sounds like it is referring to the mental image - is it the purpose of the word to illicit an image?

accepts that words do refer to objects in some capacity

pattern recognition

/ culture

clear vision is impeded by a certain picture - we cannot see clearly due to a distorted filter (the job of the philosopher is to remove the filter to see things clearly --> Tractatus)

Task of philosopher is to come to an Übersehung (birds eye view): allows us to see things as they are (this is not a philosophical theory)

Example: If the essence of language is that words refer to objects, and someone asks, what about the number 5? Immediately, more theorising is required: well the word five refers to the number five, which does not exist in the real world. This requires believing in non-material objects. - In theorizing, problems come up, which need more story telling/ theorizing to solve

force all games into your description, or the things that fall out of it are not actually games --> same thing is being done with language

-both cases falsify what you're saying

-Frege did this falsely with concept/object

• because of the craving of generality (makes you ignore/miss out on nuances)
• Philosophy is not about theory (return to this later)

Does Augustine's description capture knowledge? - answer, yes, but not to a full extent (good for bread/butter/some proper names.) It does not, however, give us a good conception of the essence of language (essentialism)

Essentialism is natural for us - humans have a craving for generality

ostensive definition: a prior knowledge of a thing required before asking what it's called (kids can't have this if they are being told what things are called)

Authorities needed to talk to wife to make sure she wanted to sell propety as well

Putting out children into fosters homes was a joint responsibility

Диаграмму к согласованному виду

На диаграмме должно быть минимум Client 1, Client 2, т. к. диаграмма демонстрирует batch.

200 OK

Нужна диаграмма, т.к Event доходит до клиента. Например можно отправить сообщение через stream и его получат все подписчики стрима.

Кроме того, Event может пропагироваться до Edge через CDN, но этот функционал надо уточнить. Если есть то также нужна схема.

Диаграмма. Что такое sfuCallback? Должно быть действительное вебсокет сообщение.

Например: webRtcMetricsUpdate (уточнить)

Диаграмма. Что такое sfuCallback? Должно быть действительное вебсокет сообщение.

Например: webRtcMetricsUpdate (уточнить)

Сам ClickHouse ничего не собирает. Поэтому:

• Pushing RELS metrics
• Saving RELS metrics
• Sending RELS metrics

Нужна диаграмма.

RELS метрики записываются в

1. Файловую систему.
2. Базу данных ClickHouse

ClickHouse - участник диаграммы.

Transcoding stream

Label: Transcoding width height, gop, etc.

RTMP - это протокол, в него не транскодируют.

Диаграмма.

Тот же вопрос что и push/webrtc

Последовательность должна быть:

1. /startup
2. converting
3. pushing
4. 200 OK

Еще должна быть вторая диаграмма, т.к. если в параметрах будут указаны настройки width, height, то пуш пойдет с Транскодингом, т.е. появится еще один длительный процесс Transcoding перед Converting.

Нужна схема. На сервере запускается генератор, который длительно работает и генерит стрим.

Диаграмма

Publishing stream1

/mixer/startup

Mixer output stream 'mixed_stream' is created

200 OK

/mixer/add

stream1 is added to mixed_stream

200 OK

Playing mixed_stream

Label: The mixed_stream contains stream1 content

Нужна диаграмма:

1. Client соединяется с сервером и имеет sessionId
2. Для этого коннекта включается лог.
3. Лог пишется на стороне сервера для этого sessionId

Диаграмма

1. На серевре выполняется Job
2. Приходит запрос на отмену.
3. Job завершается (отменяется).

Не отображается диаграмма

Не отображается диаграмма

Нужна диаграмма

inject3 - инжектит статику inject2 - инжектит стримы

Поэтому у них будут разные диаграммы.

Нужна диаграмма.

1. Client - соединяется с сервером по вебсокету.

2. В сторону Client передается конкретное вебсокет сообщение, насколько помню OnDataEvent (проверить)

Нужна диаграмма.

1. Client1 Client2 - соединяются с сервером по вебсокету.

2. В сторону Client передается конкретное вебсокет сообщение, насколько помню OnDataEvent (проверить)

Диаграмма.

Приводим к согласованному виду (стрелки, лэйблы).

recht en samenleving

rechtspluralisme

savs hebben een eigen "rechtsorde"

recht en samenleving

We have a dismiss and cancel button. Why?

desires are clothed with words

But also if the office is lower down, ethnicity becomes an easier description

Certainly party lines are stronger than ethnic ones

Not what decides events on election day

represent

Surely going to be more dependent on economics

Both internally and in relation to each other

Partly due to assimilation no?

i.e poor

Political machines

The idiocy works

I mean look at trump today

It isn't the highest power but it can act as an in

Ethnic = white here

Ethnic differences are most salient at the beginning

Mobilize

Religion over ethnicity

Or at least political differences on salient issues

Already talked about how religion can shape law

differnce in policy but also day to day norms

Economics always rule

test

https://www.reddit.com/r/typewriters/comments/1cffdj8/the_typewriters_of_ripley/

see also, with little to add: https://www.reddit.com/r/typewriters/comments/1s471gq/typewriter_personality_key_to_a_mystery/

glycogains voor opslaan

is dus echt actief bij herstelfase van stress, en bij eten van stress, slaaptekort

1. 恢复整个 App 文件夹的所有权给你的用户

sudo chown -R ryanxiao:staff /Applications/GUI.for.SingBox.app

2. 去掉 GUI 程序误加的 SUID 位（如果有的话）

sudo chmod -s /Applications/GUI.for.SingBox.app/Contents/MacOS/GUI.for.SingBox

3. 再次确保隔离位已清除

sudo xattr -rd com.apple.quarantine /Applications/GUI.for.SingBox.app

1. 将该二进制文件的所有者更改为 root 用户

sudo chown root:wheel "/Users/ryanxiao/Library/Application Support/GUI.for.SingBox/sing-box/sing-box"

2. 给该文件加上 SUID 权限位（这是关键，让它在执行时拥有所有者的 root 权限）

sudo chmod +s "/Users/ryanxiao/Library/Application Support/GUI.for.SingBox/sing-box/sing-box"

This could be 40k for Claudia, Ravina. 2 weeks of work.

Anxiety Sympathomimetics Beta-agonists Excess caffeine Hypokalaemia Hypomagnesaemia Digoxin toxicity Myocardial ischemia

PVCs arising from the right ventricle have a left bundle branch block morphology (dominant S wave in V1) PVCs arising from the left ventricle have a right bundle branch block morphology (dominant R wave in V1)

Anxiety Sympathomimetics Beta-agonists Excess caffeine Hypokalaemia Hypomagnesaemia Digoxin toxicity Myocardial ischaemia

Need GL feedback - is aggressive enough?

Sick sinus syndrome Increased vagal tone (athletes) Vagal stimulation (surgery, pain) Inferior myocardial infarction Myocarditis Drugs: digoxin, beta-blockers, calcium channel blockers, amiodarone

What's the definition of human commensal? - Streptococcus oralis is marked as a non-commensal but is present on oral surfaces

Ventricular tachycardia Accelerated idioventricular rhythm Ventricular escape rhythm Ventricular-paced rhythm

Brugada syndrome – localised QRS widening in V1-2 with RBBB morphology. Arrhythmogenic right ventricular dysplasia (AVRD) – localised QRS widening in V1-2 plus epsilon waves and variable signs of right ventricular hypertrophy

Wolff-Parkinson-White syndrome – wide QRS plus delta waves.

Sodium-channel blocker toxicity (e.g. TCA overdose) – wide QRS plus positive R’ wave in aVR.

Hyperkalaemia

Left ventricular hypertrophy Right ventricular hypertrophy Biventricular enlargement Dilated cardiomyopathy

Left anterior fascicular block Left posterior fascicular block Left bundle branch block Right bundle branch block Bifascicular block Trifascicular block

Hyperkalaemia Tricyclic antidepressant poisoning.

He is trying to find out what is going on psychologically in musical experience, but in connection with musical performance or listening in practice, which he sees as being under researched.

Am I thinking about these wrong? I think I default to ttrpg conventions where classes are complex and long, and require internal flexibility to be differentiated (you don’t want every Paladin to play identically to every other Paladin, so you introduce subclasses, or feats, or archetypes in pathfinder, etc.). But in a lot of TRPGs the classes are much shorter sets of purchasable abilities, and differentiation comes from the combination of classes. What if classes were shorter, simpler, and arranged in more complex trees - ie these builds/themes like Juggernaut or Vivisectionist become classes into themselves, and Legionnaire/etc have to do less heavy lifting. Would that be more or less satisfying?

Ischaemic heart disease (40-60%) Structural heart disease (50-80% association) Aortic stenosis Anterior MI Lenègre-Lev disease Congenital heart disease Hyperkalaemia (resolves with treatment) Digoxin toxicity

Ischaemic heart disease (40-60% cases) Structural heart disease (50-80% association) Aortic stenosis Anterior MI (occurs in 5-7% of acute AMI) Lenègre-Lev disease Congenital heart disease Hyperkalaemia (resolves with treatment)

Right axis deviation (RAD) (> +90 degrees) rS complexes in leads I and aVL qR complexes in leads II, III and aVF Prolonged R wave peak time in aVF

bgwriter_delay -- 表示多久写入一次，默认200ms bgwriter_lru_maxpages -- 在单个轮次（即上述 delay 间隔后的一次运行）中，bgwriter 最多能写入多少个页面。 bgwriter_lru_multiplier -- 这是一个相对智能的比例系数，用于根据当前系统的繁忙程度动态估算下次需要写入的页面数。 调大（如 4.0 或更高）：bgwriter 会变得更“激进”，预估会产生更多空位，适合突发性写入较多的场景。

调小：写入更保守

shared_buffers：全局大仓库（缓存正式表数据）。

work_mem：查询加工间（负责排序和计算）。

maintenance_work_mem：重型维修车间（负责索引和清理）。

temp_buffers：临时寄存柜（负责临时表读写）

Left axis deviation (usually -45 to -90 degrees) qR complexes in leads I, aVL rS complexes in leads II, III, aVF Prolonged R wave peak time in aVL > 45ms

eLife Assessment

The use of DNA tethers is a useful advance for studying how motor proteins respond to load. The authors use a convincing methodology to investigate the detachment and reattachment kinetics of kinesin-1, 2, and 3 motors against loads oriented parallel to the microtubule. As the manuscript stands, the conclusions drawn from the experiments, as well as the overall interpretation of the results, are incompletely supported by the presented data, and the novelty over previous reports appears less clear.

Reviewer #1 (Public review):

Summary:

Noell et al have presented a careful study of the dissociation kinetics of Kinesin (1,2,3) classes of motors moving in vitro on a microtubule. These motors move against the opposing force from a ~1 micron DNA strand (DNA tensiometer) that is tethered to the microtubule and also bound to the motor via specific linkages (Figure 1A). The authors compare the time for which motors remain attached to the microtubule when they are tethered to the DNA, versus when they are not. If the former is longer, the interpretation is that the force on the motor from the stretched DNA (presumed to be working solely along the length of the microtubule) causes the motor's detachment rate from the microtubule to be reduced. Thus, the specific motor exhibits "catch-bond" like behaviour.

Strengths:

The motivation is good - to understand how kinesin competes against dynein through the possible activation of a catch bond. Experiments are well done, and there is an effort to model the results theoretically.

Weaknesses:

The motivation of these studies is to understand how kinesin (1/2/3) motors would behave when they are pitted in a tug of war against dynein motors as they transport cargo in a bidirectional manner on microtubules. Earlier work on dynein and kinesin motors using optical tweezers has suggested that dynein shows a catch bond phenomenon, whereas such signatures were not seen for kinesin. Based on their data with the DNA tensiometer, the authors would like to claim that (i) Kinesin1 and Kinesin2 also show catch-bonding and (ii) the earlier results using optical traps suffer from vertical forces, which complicates the catch-bond interpretation.

While the motivation of this work is reasonable, and the experiments are careful, I find significant issues that the authors have not addressed:

(1) Figure 1B shows the PREDICTED force-extension curve for DNA based on a worm-like chain model. Where is the experimental evidence for this curve? This issue is crucial because the F-E curve will decide how and when a catch-bond is induced (if at all it is) as the motor moves against the tensiometer. Unless this is actually measured by some other means, I find it hard to accept all the results based on Figure 1B.

(2) The authors can correct me on this, but I believe that all the catch-bond studies using optical traps have exerted a load force that exceeds the actual force generated by the motor. For example, see Figure 2 in reference 42 (Kunwar et al). It is in this regime (load force > force from motor) that the dissociation rate is reduced (catch-bond is activated). Such a regime is never reached in the DNA tensiometer study because of the very construction of the experiment. I am very surprised that this point is overlooked in this manuscript. I am therefore not even sure that the present experiments even induce a catch-bond (in the sense reported for earlier papers).

(3) I appreciate the concerns about the Vertical force from the optical trap. But that leads to the following questions that have not at all been addressed in this paper:

(i) Why is the Vertical force only a problem for Kinesins, and not a problem for the dynein studies?

(ii) The authors state that "With this geometry, a kinesin motor pulls against the elastic force of a stretched DNA solely in a direction parallel to the microtubule". Is this really true? What matters is not just how the kinesin pulls the DNA, but also how the DNA pulls on the kinesin. In Figure 1A, what is the guarantee that the DNA is oriented only in the plane of the paper? In fact, the DNA could even be bending transiently in a manner that it pulls the kinesin motor UPWARDS (Vertical force). How are the authors sure that the reaction force between DNA and kinesin is oriented SOLELY along the microtubule?

(4) For this study to be really impactful and for some of the above concerns to be addressed, the data should also have included DNA tensiometer experiments with Dynein. I wonder why this was not done?

While I do like several aspects of the paper, I do not believe that the conclusions are supported by the data presented in this paper for the reasons stated above.

Reviewer #2 (Public review):

Summary:

To investigate the detachment and reattachment kinetics of kinesin-1, 2, and 3 motors against loads oriented parallel to the microtubule, the authors used a DNA tensiometer approach comprising a DNA entropic spring attached to the microtubule on one end and a motor on the other. They found that for kinesin-1 and kinesin-2, the dissociation rates at stall were smaller than the detachment rates during unloaded runs. With regard to the complex reattachment kinetics found in the experiments, the authors argue that these findings were consistent with a weakly-bound 'slip' state preceding motor dissociation from the microtubule. The behavior of kinesin-3 was different and (by the definition of the authors) only showed prolonged "detachment" rates when disregarding some of the slip events. The authors performed stochastic simulations that recapitulate the load-dependent detachment and reattachment kinetics for all three motors. They argue that the presented results provide insight into how kinesin-1, -2, and -3 families transport cargo in complex cellular geometries and compete against dynein during bidirectional transport.

Strengths:

The present study is timely, as significant concerns have been raised previously about studying motor kinetics in optical (single-bead) traps where significant vertical forces are present. Moreover, the obtained data are of high quality, and the experimental procedures are clearly described.

Weaknesses:

However, in the present version of the manuscript, the conclusions drawn from the experiments, the overall interpretation of the results, and the novelty over previous reports appear less clear.

Major comments:

(1) The use of the term "catch bond" is misleading, as the authors do not really mean consistently a catch bond in the classical sense (i.e., a protein-protein interaction having a dissociation rate that decreases with load). Instead, what they mean is that after motor detachment (i.e., after a motor protein dissociating from a tubulin protein), there is a slip state during which the reattachment rate is higher as compared to a motor diffusing in solution. While this may indeed influence the dynamics of bidirectional cargo transport (e.g., during tug-of-war events), the used terms (detachment (with or without slip?), dissociation, rescue, ...) need to be better defined and the results discussed in the context of these definitions. It is very unsatisfactory at the moment, for example, that kinesin-3 is at first not classified as a catch bond, but later on (after tweaking the definitions) it is. In essence, the typical slip/catch bond nomenclature used for protein-protein interaction is not readily applicable for motors with slippage.

(2) The authors define the stall duration as the time at full load, terminated by >60 nm slips/detachments. Isn't that a problem? Smaller slips are not detected/considered... but are also indicative of a motor dissociation event, i.e., the end of a stall. What is the distribution of the slip distances? If the slip distances follow an exponential decay, a large number of short slips are expected, and the presented data (neglecting those short slips) would be highly distorted.

(3) Along the same line: Why do the authors compare the stall duration (without including the time it took the motor to reach stall) to the unloaded single motor run durations? Shouldn't the times of the runs be included?

(4) At many places, it appears too simple that for the biologically relevant processes, mainly/only the load-dependent off-rates of the motors matter. The stall forces and the kind of motor-cargo linkage (e.g., rigid vs. diffusive) do likely also matter. For example: "In the context of pulling a large cargo through the viscous cytoplasm or competing against dynein in a tug-of-war, these slip events enable the motor to maintain force generation and, hence, are distinct from true detachment events." I disagree. The kinesin force at reattachment (after slippage) is much smaller than at stall. What helps, however, is that due to the geometry of being held close to the microtubule (either by the DNA in the present case or by the cargo in vivo) the attachment rate is much higher. Note also that upon DNA relaxation ,the motor is likely kept close to the microtubule surface, while, for example, when bound to a vesicle, the motor may diffuse away from the microtubule quickly (e.g., reference 20).

(5) Why were all motors linked to the neck-coil domain of kinesin-1? Couldn't it be that for normal function, the different coils matter? Autoinhibition can also be circumvented by consistently shortening the constructs.

(6) I am worried about the neutravidin on the microtubules, which may act as roadblocks (e.g. DOI: 10.1039/b803585g), slip termination sites (maybe without the neutravidin, the rescue rate would be much lower?), and potentially also DNA-interaction sites? At 8 nM neutravidin and the given level of biotinylation, what density of neutravidin do the authors expect on their microtubules? Can the authors rule out that the observed stall events are predominantly the result of a kinesin motor being stopped after a short slippage event at a neutravidin molecule?

(7) Also, the unloaded runs should be performed on the same microtubules as in the DNA experiments, i.e., with neutravidin. Otherwise, I do not see how the values can be compared.

(8) If, as stated, "a portion of kinesin-3 unloaded run durations were limited by the length of the microtubules, meaning the unloaded duration is a lower limit." corrections (such as Kaplan-Meier) should be applied, DOI: 10.1016/j.bpj.2017.09.024.

(9) Shouldn't Kaplan-Meier also be applied to the ramp durations ... as a ramp may also artificially end upon stall? Also, doesn't the comparison between ramp and stall duration have a problem, as each stall is preceded by a ramp ...and the (maximum) ramp times will depend on the speed of the motor? Kinesin-3 is the fastest motor and will reach stall much faster than kinesin-1. Isn't it obvious that the stall durations are longer than the ramp duration (as seen for all three motors in Figure 3)?

(10) It is not clear what is seen in Figure S6A: It looks like only single motors (green, w/o a DNA molecule) are walking ... Note: the influence of the attached DNA onto the stepping duration of a motor may depend on the DNA conformation (stretched and near to the microtubule (with neutravidin!) in the tethered case and spherically coiled in the untethered case).

(11) Along this line: While the run time of kinesin-1 with DNA (1.4 s) is significantly shorter than the stall time (3.0 s), it is still larger than the unloaded run time (1.0 s). What do the authors think is the origin of this increase?

(12) "The simplest prediction is that against the low loads experienced during ramps, the detachment rate should match the unloaded detachment rate." I disagree. I would already expect a slight increase.

(13) Isn't the model over-defined by fitting the values for the load-dependence of the strong-to-weak transition and fitting the load dependence into the transition to the slip state?

(14) "When kinesin-1 was tethered to a glass coverslip via a DNA linker and hydrodynamic forces were imposed on an associated microtubule, kinesin-1 dissociation rates were relatively insensitive to loads up to ~3 pN, inconsistent with slip-bond characteristics (37)." This statement appears not to be true. In reference 37, very similar to the geometry reported here, the microtubules were fixed on the surface, and the stepping of single kinesin motors attached to large beads (to which defined forces were applied by hydrodynamics) via long DNA linkers was studied. In fact, quite a number of statements made in the present manuscript have been made already in ref. 37 (see in particular sections 2.6 and 2.7), and the authors may consider putting their results better into this context in the Introduction and Discussion. It is also noteworthy to discuss that the (admittedly limited) data in ref. 37 does not indicate a "catch-bond" behavior but rather an insensitivity to force over a defined range of forces.

Reviewer #3 (Public review):

Summary:

Several recent findings indicate that forces perpendicular to the microtubule accelerate kinesin unbinding, where perpendicular and axial forces were analyzed using the geometry in a single-bead optical trapping assay (Khataee and Howard, 2019), comparison between single-bead and dumbbell assay measurements (Pyrpassopoulos et al., 2020), and comparison of single-bead optical trap measurements with and without a DNA tether (Hensley and Yildiz, 2025).

Here, the authors devise an assay to exert forces along the microtubule axis by tethering kinesin to the microtubule via a dsDNA tether. They compared the behavior of kinesin-1, -2, and -3 when pulling against the DNA tether. In line with previous optical trapping measurements, kinesin unbinding is less sensitive to forces when the forces are aligned with the microtubule axis. Surprisingly, the authors find that both kinesin-1 and -2 detach from the microtubule more slowly when stalled against the DNA tether than in unloaded conditions, indicating that these motors act as catch bonds in response to axial loads. Axial loads accelerate kinesin-3 detachment. However, kinesin-3 reattaches quickly to maintain forces. For all three kinesins, the authors observe weakly attached states where the motor briefly slips along the microtubule before continuing a processive run.

Strengths:

These observations suggest that the conventional view that kinesins act as slip bonds under load, as concluded from single-bead optical trapping measurements where perpendicular loads are present due to the force being exerted on the centroid of a large (relative to the kinesin) bead, needs to be reconsidered. Understanding the effect of force on the association kinetics of kinesin has important implications for intracellular transport, where the force-dependent detachment governs how kinesins interact with other kinesins and opposing dynein motors (Muller et al., 2008; Kunwar et al., 2011; Ohashi et al., 2018; Gicking et al., 2022) on vesicular cargoes.

Weaknesses:

The authors attribute the differences in the behaviour of kinesins when pulling against a DNA tether compared to an optical trap to the differences in the perpendicular forces. However, the compliance is also much different in these two experiments. The optical trap acts like a ~ linear spring with stiffness ~ 0.05 pN/nm. The dsDNA tether is an entropic spring, with negligible stiffness at low extensions and very high compliance once the tether is extended to its contour length (Fig. 1B). The effect of the compliance on the results should be addressed in the manuscript.

Compared to an optical trapping assay, the motors are also tethered closer to the microtubule in this geometry. In an optical trap assay, the bead could rotate when the kinesin is not bound. The authors should discuss how this tethering is expected to affect the kinesin reattachment and slipping. While likely outside the scope of this study, it would be interesting to compare the static tether used here with a dynamic tether like MAP7 or the CAP-GLY domain of p150glued.

In the single-molecule extension traces (Figure 1F-H; S3), the kinesin-2 traces often show jumps in position at the beginning of runs (e.g., the four runs from ~4-13 s in Fig. 1G). These jumps are not apparent in the kinesin-1 and -3 traces. What is the explanation? Is kinesin-2 binding accelerated by resisting loads more strongly than kinesin-1 and -3?

When comparing the durations of unloaded and stall events (Fig. 2), there is a potential for bias in the measurement, where very long unloaded runs cannot be observed due to the limited length of the microtubule (Thompson, Hoeprich, and Berger, 2013), while the duration of tethered runs is only limited by photobleaching. Was the possible censoring of the results addressed in the analysis?

The mathematical model is helpful in interpreting the data. To assess how the "slip" state contributes to the association kinetics, it would be helpful to compare the proposed model with a similar model with no slip state. Could the slips be explained by fast reattachments from the detached state?

Author response:

Reviewer 1 (Public review):

(1) Figure 1B shows the PREDICTED force-extension curve for DNA based on a worm-like chain model. Where is the experimental evidence for this curve? This issue is crucial because the F-E curve will decide how and when a catch-bond is induced (if at all it is) as the motor moves against the tensiometer. Unless this is actually measured by some other means, I find it hard to accept all the results based on Figure 1B.

The Worm-Like-Chain model for the elasticity of DNA was established by early work from the Bustamante lab (Smith et al., 1992)  and Marko and Siggia (Marko and Siggia, 1995), and was further validated and refined by the Block lab (Bouchiat et al., 1999; Wang et al., 1997). The 50 nm persistence length is the consensus value, and was shown to be independent of force and extension in Figure 3 of Bouchiat et al (Bouchiat et al., 1999). However, we would like to stress that for our conclusions, the precise details of the Force-Extension relationship of our dsDNA are immaterial. The key point is that the motor stretches the DNA and stalls when it reaches its stall force. Our claim of the catch-bond character of kinesin is based on the longer duration at stall compared to the run duration in the absence of load. Provided that the motor is indeed stalling because it has stretched out the DNA (which is strongly supported by the repeated stalling around the predicted extension corresponding to ~6 pN of force), then the stall duration depends on neither the precise value for the extension nor the precise value of the force at stall.

(2) The authors can correct me on this, but I believe that all the catch-bond studies using optical traps have exerted a load force that exceeds the actual force generated by the motor. For example, see Figure 2 in reference 42 (Kunwar et al). It is in this regime (load force > force from motor) that the dissociation rate is reduced (catch-bond is activated). Such a regime is never reached in the DNA tensiometer study because of the very construction of the experiment. I am very surprised that this point is overlooked in this manuscript. I am therefore not even sure that the present experiments even induce a catch-bond (in the sense reported for earlier papers).

It is true that Kunwar et al measured binding durations at super-stall loads and used that to conclude that dynein does act as a catch-bond (but kinesin does not) (Kunwar et al., 2011). However, we would like to correct the reviewer on this one. This approach of exerting super-stall forces and measuring binding durations is in fact less common than the approach of allowing the motor to walk up to stall and measuring the binding duration. This ‘fixed trap’ approach has been used to show catch-bond behavior of dynein (Leidel et al., 2012; Rai et al., 2013) and kinesin (Kuo et al., 2022; Pyrpassopoulos et al., 2020). For the non-processive motor Myosin I, a dynamic force clamp was used to keep the actin filament in place while the myosin generated a single step (Laakso et al., 2008). Because the motor generates the force, these are not superstall forces either.

(3) I appreciate the concerns about the Vertical force from the optical trap. But that leads to the following questions that have not at all been addressed in this paper:

(i) Why is the Vertical force only a problem for Kinesins, and not a problem for the dynein studies?

Actually, we do not claim that vertical force is not a problem for dynein; our data do not speak to this question. There is debate in the literature as to whether dynein has catch bond behavior in the traditional single-bead optical trap geometry - while some studies have measured dynein catch bond behavior (Kunwar et al., 2011; Leidel et al., 2012; Rai et al., 2013), others have found that dynein has slip-bond or ideal-bond behavior (Ezber et al., 2020; Nicholas et al., 2015; Rao et al., 2019). This discrepancy may relate to vertical forces, but not in an obvious way.

(ii) The authors state that "With this geometry, a kinesin motor pulls against the elastic force of a stretched DNA solely in a direction parallel to the microtubule". Is this really true? What matters is not just how the kinesin pulls the DNA, but also how the DNA pulls on the kinesin. In Figure 1A, what is the guarantee that the DNA is oriented only in the plane of the paper? In fact, the DNA could even be bending transiently in a manner that it pulls the kinesin motor UPWARDS (Vertical force). How are the authors sure that the reaction force between DNA and kinesin is oriented SOLELY along the microtubule?

We acknowledge that “solely” is an absolute term that is too strong to describe our geometry. We will soften this term in our revision to “nearly parallel to the microtubule”. In the Geometry Calculations section of Supplementary Methods, we calculate that if the motor and streptavidin are on the same protofilament, the vertical force will be <1% of the horizontal force. We also note that if the motor is on a different protofilament, there will be lateral forces and forces perpendicular to the microtubule surface, except they are oriented toward rather than away from the microtubule. The DNA can surely bend due to thermal forces, but because inertia plays a negligible role at the nanoscale (Howard, 2001; Purcell, 1977), any resulting upward forces will only be thermal forces, which the motor is already subjected to at all times.

(4) For this study to be really impactful and for some of the above concerns to be addressed, the data should also have included DNA tensiometer experiments with Dynein. I wonder why this was not done?

As much as we would love to fully characterize dynein here, this paper is about kinesin and it took a substantial effort. The dynein work merits a stand-alone paper.

While I do like several aspects of the paper, I do not believe that the conclusions are supported by the data presented in this paper for the reasons stated above.

The three key points the reviewer makes are the validity of the worm-like-chain model, the question of superstall loads, and the role of DNA bending in generating vertical forces. We hope that we have fully addressed these concerns in our responses above.

Reviewer #2 (Public review):

Major comments:

(1) The use of the term "catch bond" is misleading, as the authors do not really mean consistently a catch bond in the classical sense (i.e., a protein-protein interaction having a dissociation rate that decreases with load). Instead, what they mean is that after motor detachment (i.e., after a motor protein dissociating from a tubulin protein), there is a slip state during which the reattachment rate is higher as compared to a motor diffusing in solution. While this may indeed influence the dynamics of bidirectional cargo transport (e.g., during tug-of-war events), the used terms (detachment (with or without slip?), dissociation, rescue, ...) need to be better defined and the results discussed in the context of these definitions. It is very unsatisfactory at the moment, for example, that kinesin-3 is at first not classified as a catch bond, but later on (after tweaking the definitions) it is. In essence, the typical slip/catch bond nomenclature used for protein-protein interaction is not readily applicable for motors with slippage.

We appreciate the reviewer’s point and we will work to streamline and define terms in our revision.

(2) The authors define the stall duration as the time at full load, terminated by >60 nm slips/detachments. Isn't that a problem? Smaller slips are not detected/considered... but are also indicative of a motor dissociation event, i.e., the end of a stall. What is the distribution of the slip distances? If the slip distances follow an exponential decay, a large number of short slips are expected, and the presented data (neglecting those short slips) would be highly distorted.

The reviewer brings up a good point that there may be undetected slips. To address this question, we plotted the distribution of slip distances for kinesin-3, which by far had the most slip events. As the reviewer suggested, it is indeed an exponential distribution. Our preliminary analysis suggests that roughly 20% of events are missed due to this 60 nm cutoff. This will change our unloaded duration numbers slightly, but this will not alter our conclusions.\

(3) Along the same line: Why do the authors compare the stall duration (without including the time it took the motor to reach stall) to the unloaded single motor run durations? Shouldn't the times of the runs be included?

The elastic force of the DNA spring is variable as the motor steps up to stall, and so if we included the entire run duration then it would be difficult to specify what force we were comparing to unloaded. More importantly, if we assume that any stepping and detachment behavior is history independent, then it is mathematically proper to take any arbitrary starting point (such as when the motor reaches stall), start the clock there, and measure the distribution of detachments durations relative to that starting point.

More importantly, what we do in Fig. 3 is to separate out the ramps from the stalls and, using a statistical model, we compute a separate duration parameter (which is the inverse of the off-rate) for the ramp and the stall. What we find is that the relationship between ramp, stall, and unloaded durations is different for the three motors, which is interesting in itself.

(4) At many places, it appears too simple that for the biologically relevant processes, mainly/only the load-dependent off-rates of the motors matter. The stall forces and the kind of motor-cargo linkage (e.g., rigid vs. diffusive) do likely also matter. For example: "In the context of pulling a large cargo through the viscous cytoplasm or competing against dynein in a tug-of-war, these slip events enable the motor to maintain force generation and, hence, are distinct from true detachment events." I disagree. The kinesin force at reattachment (after slippage) is much smaller than at stall. What helps, however, is that due to the geometry of being held close to the microtubule (either by the DNA in the present case or by the cargo in vivo) the attachment rate is much higher. Note also that upon DNA relaxation, the motor is likely kept close to the microtubule surface, while, for example, when bound to a vesicle, the motor may diffuse away from the microtubule quickly (e.g., reference 20).

We appreciate the reviewer’s detailed thinking here, and we offer our perspective. As to the first point, we agree that the stall force is relevant and that the rigidity of the motor-cargo linkage will play a role. The goal of the sentence on pulling cargo that the reviewer highlights is to set up our analysis of slips, which we define as rearward displacements that don’t return to the baseline before force generation resumes. We agree that force after slippage is much smaller than at stall, and we plan to clarify that section of text. However, as shown in the model diagram in Fig. 5, we differentiate between the slip state (and recovery from this slip state) and the detached state (and reattachment from this detached state). This delineation is important because, as the reviewer points out, if we are measuring detachment and reattachment with our DNA tensiometer, then the geometry of a vesicle in a cell will be different and diffusion away from the microtubule or elastic recoil perpendicular to the microtubule will suppress this reattachment.

Our evidence for a slip state in which the motor maintains association with the microtubule comes from optical trapping work by Tokelis et al (Toleikis et al., 2020) and Sudhakar et al (Sudhakar et al., 2021). In particular, Sudhakar used small, high index Germanium microspheres that had a low drag coefficient. They showed that during ‘slip’ events, the relaxation time constant of the bead back to the center of the trap was nearly 10-fold slower than the trap response time, consistent with the motor exerting drag on the microtubule. (With larger beads, the drag of the bead swamps the motor-microtubule friction.) Another piece of support for the motor maintaining association during a slip is work by Ramaiya et al. who used birefringent microspheres to exert and measure rotational torque during kinesin stepping (Ramaiya et al., 2017). In most traces, when the motor returned to baseline following a stall, the torque was dissipated as well, consistent with a ‘detached’ state. However, a slip event is shown in S18a where the motor slips backward while maintaining torque. This is best explained by the motor slipping backward in a state where the heads are associated with the microtubule (at least sufficiently to resist rotational forces). Thus, we term the resumption after slip to be a rescue from the slip state rather than a reattachment from the detached state.

To finish the point, with the complex geometry of a vesicle, during slip events the motor remains associated with the microtubule and hence primed for recovery. This recovery rate is expected to be the same as for the DNA tensiometer. Following a detachment, however, we agree that there will likely be a higher probability of reattachment in the DNA tensiometer due to proximity effects, whereas with a vesicle any elastic recoil or ‘rolling’ will pull the detached motor away from the microtubule, suppressing reattachment. We plan to clarify these points in the text of the revision.

(5) Why were all motors linked to the neck-coil domain of kinesin-1? Couldn't it be that for normal function, the different coils matter? Autoinhibition can also be circumvented by consistently shortening the constructs.

We chose this dimerization approach to focus on how the mechoanochemical properties of kinesins vary between the three dominant transport families. We agree that in cells, autoinhibition of both kinesins and dynein likely play roles in regulating bidirectional transport, as will the activity of other regulatory proteins. The native coiled-coils may act as as ‘shock absorbers’ due to their compliance, or they might slow the motor reattachment rate due to the relatively large search volumes created by their long lengths (10s of nm). These are topics for future work. By using the neck-coil domain of kinesin-1 for all three motors, we eliminate any differences in autoinhibition or other regulation between the three kinesin families and focus solely on differences in the mechanochemistry of their motor domains.

(6) I am worried about the neutravidin on the microtubules, which may act as roadblocks (e.g. DOI: 10.1039/b803585g), slip termination sites (maybe without the neutravidin, the rescue rate would be much lower?), and potentially also DNA-interaction sites? At 8 nM neutravidin and the given level of biotinylation, what density of neutravidin do the authors expect on their microtubules? Can the authors rule out that the observed stall events are predominantly the result of a kinesin motor being stopped after a short slippage event at a neutravidin molecule?

We will address these points in our revision.

(7) Also, the unloaded runs should be performed on the same microtubules as in the DNA experiments, i.e., with neutravidin. Otherwise, I do not see how the values can be compared.

We will address this point in our revision.

(8) If, as stated, "a portion of kinesin-3 unloaded run durations were limited by the length of the microtubules, meaning the unloaded duration is a lower limit." corrections (such as Kaplan-Meier) should be applied, DOI: 10.1016/j.bpj.2017.09.024.

(9) Shouldn't Kaplan-Meier also be applied to the ramp durations ... as a ramp may also artificially end upon stall? Also, doesn't the comparison between ramp and stall duration have a problem, as each stall is preceded by a ramp ...and the (maximum) ramp times will depend on the speed of the motor? Kinesin-3 is the fastest motor and will reach stall much faster than kinesin-1. Isn't it obvious that the stall durations are longer than the ramp duration (as seen for all three motors in Figure 3)?

The reviewer rightly notes the many challenges in estimating the motor off-rates during ramps. To estimate ramp off-rates and as an independent approach to calculating the unloaded and stall durations, we developed a Markov model coupled with Bayesian inference methods to estimate a duration parameter (equivalent to the inverse of the off-rate) for the unloaded, ramp, and stall duration distributions. With the ramps, we have left censoring due to the difficulty in detecting the start of the ramps in the fluctuating baseline, and we have right censoring due to reaching stall (with different censoring of the ramp duration for the three motors due to their different speeds). The Markov model assumes a constant detachment probability and history independence, and thus is robust even in the face of left and right censoring (details in the Supplementary section). This approach is preferred over Kaplan-Meier because, although these non-parametric methods make no assumptions for the distribution, they require the user to know exactly where the start time is.

Regarding the potential underestimate of the kinesin-3 unloaded run duration due to finite microtubule lengths. The first point is that the unloaded duration data in Fig. 2C are quite linear up to 6 s and are well fit by the single-exponential fit (the points above 6s don’t affect the fit very much). The second point is that when we used our Markov model (which is robust against right censoring) to estimate the unloaded and stall durations, the results agreed with the single-exponential fits very well (Table S2). For instance, the single-exponential fit for the kinesin-3 unloaded duration was 2.74 s (2.33 – 3.17 s 95% CI) and the estimate from the Markov model was 2.76 (2.28 – 3.34 s 95% CI). Thus, we chose not to make any corrections due to finite microtubule lengths.

(10) It is not clear what is seen in Figure S6A: It looks like only single motors (green, w/o a DNA molecule) are walking ... Note: the influence of the attached DNA onto the stepping duration of a motor may depend on the DNA conformation (stretched and near to the microtubule (with neutravidin!) in the tethered case and spherically coiled in the untethered case).

In Figure S6A kymograph, the green traces are GFP-labeled kinesin-1 without DNA attached (which are in excess) and the red diagonal trace is a motor with DNA attached. There are also two faint horizontal red traces, which are labeled DNA diffusing by (smearing over a large area during a single frame). Panel S6B shows run durations of motors with DNA attached. We agree that the DNA conformation will differ if it is attached and stretched (more linear) versus simply being transported (random coil), but by its nature this control experiment is only addressing random coil DNA.

(11) Along this line: While the run time of kinesin-1 with DNA (1.4 s) is significantly shorter than the stall time (3.0 s), it is still larger than the unloaded run time (1.0 s). What do the authors think is the origin of this increase?

Our interpretation of the unloaded kinesin-DNA result is that the much slower diffusion constant of the DNA relative to the motor alone enables motors to transiently detach and rebind before the DNA cargo has diffused away, thus extending the run duration. In contrast, such detachment events for motors alone normally result in the motor diffusing away from the microtubule, terminating the run. This argument has been used to reconcile the longer single-motor run lengths in the gliding assay versus the bead assay (Block et al., 1990). Notably, this slower diffusion constant should not play a role in the DNA tensiometer geometry because if the motor transiently detaches, then it will be pulled backward by the elastic forces of the DNA and detected as a slip or detachment event. We will address this point in the revision.

(12) "The simplest prediction is that against the low loads experienced during ramps, the detachment rate should match the unloaded detachment rate." I disagree. I would already expect a slight increase.

Agreed. We will change this text to: “The prediction for a slip bond is that against the low loads experienced during ramps, the detachment rate should be equal to or faster than the unloaded detachment rate.”

(13) Isn't the model over-defined by fitting the values for the load-dependence of the strong-to-weak transition and fitting the load dependence into the transition to the slip state?

Essentially, yes, it is overdefined, but that is essentially by design and it is still very useful. Our goal here was to make as simple a model as possible that could account for the data and use it to compare model parameters for the different motor families. Ignoring the complexity of the slip and detached states, a model with a strong and weak state in the stepping cycle and a single transition out of the stepping cycle is the simplest formulation possible. And having rate constants (k_S-W and k_slip in our case) that vary exponentially with load makes thermodynamic sense for modeling mechanochemistry (Howard, 2001). Thus, we were pleasantly surprised that this bare-bones model could recapitulate the unloaded and stall durations for all three motors (Fig. 5C-E).

(14) "When kinesin-1 was tethered to a glass coverslip via a DNA linker and hydrodynamic forces were imposed on an associated microtubule, kinesin-1 dissociation rates were relatively insensitive to loads up to ~3 pN, inconsistent with slip-bond characteristics (37)." This statement appears not to be true. In reference 37, very similar to the geometry reported here, the microtubules were fixed on the surface, and the stepping of single kinesin motors attached to large beads (to which defined forces were applied by hydrodynamics) via long DNA linkers was studied. In fact, quite a number of statements made in the present manuscript have been made already in ref. 37 (see in particular sections 2.6 and 2.7), and the authors may consider putting their results better into this context in the Introduction and Discussion. It is also noteworthy to discuss that the (admittedly limited) data in ref. 37 does not indicate a "catch-bond" behavior but rather an insensitivity to force over a defined range of forces.

The reviewer misquoted our sentence. The actual wording of the sentence was: “When kinesin-1 was connected to micron-scale beads through a DNA linker and hydrodynamic forces parallel to the microtubule imposed, dissociation rates were relatively insensitive to loads up to ~3 pN, inconsistent with slip-bond characteristics (Urbanska et al., 2021).” The sentence the reviewer quoted was in a previous version that is available on BioRxiv and perhaps they were reading that version. Nonetheless, in the revision we will note in the Discussion that this behavior was indicative of an ideal bond (not a catch-bond), and we will also add a sentence in the Introduction highlighting this work.

Reviewer #3 (Public review):

The authors attribute the differences in the behaviour of kinesins when pulling against a DNA tether compared to an optical trap to the differences in the perpendicular forces. However, the compliance is also much different in these two experiments. The optical trap acts like a ~ linear spring with stiffness ~ 0.05 pN/nm. The dsDNA tether is an entropic spring, with negligible stiffness at low extensions and very high compliance once the tether is extended to its contour length (Fig. 1B). The effect of the compliance on the results should be addressed in the manuscript.

This is an interesting point. To address it, we calculated the predicted stiffness of the dsDNA by taking the slope of theoretical force-extension curve in Fig. 1B. Below 650 nm extension, the stiffness is <0.001 pN/nM; it reaches 0.01 pN/nM at 855 nm, and at 960 nm where the force is 6 pN the stiffness is roughly 0.2 pN/nm. That value is higher than the quoted 0.05 pN/nm trap stiffness, but for reference, at this stiffness, an 8 nm step leads to a 1.6 pN jump in force, which is reasonable. Importantly, the stiffness of kinesin motors has been estimated to be in the range of 0.3 pN (Coppin et al., 1996; Coppin et al., 1997). Granted, this stiffness is also nonlinear, but what this means is that even at stall, our dsDNA tether has a similar predicted compliance to the motor that is pulling on it. We will address this point in our revision.  

Compared to an optical trapping assay, the motors are also tethered closer to the microtubule in this geometry. In an optical trap assay, the bead could rotate when the kinesin is not bound. The authors should discuss how this tethering is expected to affect the kinesin reattachment and slipping. While likely outside the scope of this study, it would be interesting to compare the static tether used here with a dynamic tether like MAP7 or the CAP-GLY domain of p150glued.

Please see our response to Reviewer #2 Major Comment #4 above, which asks this same question in the context of intracellular cargo. We plan to address this in our revision. Regarding a dynamic tether, we agree that’s interesting – there are kinesins that have a second, non-canonical binding site that achieves this tethering (ncd and Cin8); p150glued likely does this naturally for dynein-dynactin-activator complexes; and we speculated in a review some years ago (Hancock, 2014) that during bidirectional transport kinesin and dynein may act as dynamic tethers for one another when not engaged, enhancing the activity of the opposing motor.

In the single-molecule extension traces (Figure 1F-H; S3), the kinesin-2 traces often show jumps in position at the beginning of runs (e.g., the four runs from ~4-13 s in Fig. 1G). These jumps are not apparent in the kinesin-1 and -3 traces. What is the explanation? Is kinesin-2 binding accelerated by resisting loads more strongly than kinesin-1 and -3?

Due to the compliance of the dsDNA, the 95% limits for the initial attachment position are +/- 290 nm (Fig. S2). Thus, some apparent ‘jumps’ from the detached state are expected. We will take a closer look at why there are jumps for kinesin-2 that aren’t apparent for kinesin-1 or -3.

When comparing the durations of unloaded and stall events (Fig. 2), there is a potential for bias in the measurement, where very long unloaded runs cannot be observed due to the limited length of the microtubule (Thompson, Hoeprich, and Berger, 2013), while the duration of tethered runs is only limited by photobleaching. Was the possible censoring of the results addressed in the analysis?

Yes. Please see response to Reviewer #2 points (8) and (9) above.

The mathematical model is helpful in interpreting the data. To assess how the "slip" state contributes to the association kinetics, it would be helpful to compare the proposed model with a similar model with no slip state. Could the slips be explained by fast reattachments from the detached state?

In the model, the slip state and the detached states are conceptually similar; they only differ in the sequence (slip to detached) and the transition rates into and out of them. The simple answer is: yes, the slips could be explained by fast reattachments from the detached state. In that case, the slip state and recovery could be called a “detached state with fast reattachment kinetics”. However, the key data for defining the kinetics of the slip and detached states is the distribution of Recovery times shown in Fig. 4D-F, which required a triple exponential to account for all of the data. If we simplified the model by eliminating the slip state and incorporating fast reattachment from a single detached state, then the distribution of Recovery times would be a single-exponential with a time constant equivalent to t₁, which would be a poor fit to the experimental distributions in Fig. 4D-F.

We appreciate the efforts and helpful suggestions of all three reviewers and the Editor.

References:

Block, S.M., L.S. Goldstein, and B.J. Schnapp. 1990. Bead movement by single kinesin molecules studied with optical tweezers. Nature. 348:348-352.

Bouchiat, C., M.D. Wang, J. Allemand, T. Strick, S.M. Block, and V. Croquette. 1999. Estimating the persistence length of a worm-like chain molecule from force-extension measurements. Biophys J. 76:409-413.

Coppin, C.M., J.T. Finer, J.A. Spudich, and R.D. Vale. 1996. Detection of sub-8-nm movements of kinesin by high-resolution optical-trap microscopy. Proc Natl Acad Sci U S A. 93:1913-1917.

Coppin, C.M., D.W. Pierce, L. Hsu, and R.D. Vale. 1997. The load dependence of kinesin's mechanical cycle. Proc Natl Acad Sci U S A. 94:8539-8544.

Ezber, Y., V. Belyy, S. Can, and A. Yildiz. 2020. Dynein Harnesses Active Fluctuations of Microtubules for Faster Movement. Nat Phys. 16:312-316.

Hancock, W.O. 2014. Bidirectional cargo transport: moving beyond tug of war. Nat Rev Mol Cell Biol. 15:615-628.

Howard, J. 2001. Mechanics of Motor Proteins and the Cytoskeleton. Sinauer Associates, Inc., Sunderland, MA. 367 pp.

Kunwar, A., S.K. Tripathy, J. Xu, M.K. Mattson, P. Anand, R. Sigua, M. Vershinin, R.J. McKenney, C.C. Yu, A. Mogilner, and S.P. Gross. 2011. Mechanical stochastic tug-of-war models cannot explain bidirectional lipid-droplet transport. Proc Natl Acad Sci U S A. 108:18960-18965.

Kuo, Y.W., M. Mahamdeh, Y. Tuna, and J. Howard. 2022. The force required to remove tubulin from the microtubule lattice by pulling on its alpha-tubulin C-terminal tail. Nature communications. 13:3651.

Laakso, J.M., J.H. Lewis, H. Shuman, and E.M. Ostap. 2008. Myosin I can act as a molecular force sensor. Science. 321:133-136.

Leidel, C., R.A. Longoria, F.M. Gutierrez, and G.T. Shubeita. 2012. Measuring molecular motor forces in vivo: implications for tug-of-war models of bidirectional transport. Biophys J. 103:492-500.

Marko, J.F., and E.D. Siggia. 1995. Stretching DNA. Macromolecules. 28:8759-8770.

Nicholas, M.P., F. Berger, L. Rao, S. Brenner, C. Cho, and A. Gennerich. 2015. Cytoplasmic dynein regulates its attachment to microtubules via nucleotide state-switched mechanosensing at multiple AAA domains. Proc Natl Acad Sci U S A. 112:6371-6376.

Purcell, E.M. 1977. Life at low Reynolds Number. Amer J. Phys. 45:3-11.

Pyrpassopoulos, S., H. Shuman, and E.M. Ostap. 2020. Modulation of Kinesin's Load-Bearing Capacity by Force Geometry and the Microtubule Track. Biophys J. 118:243-253.

Rai, A.K., A. Rai, A.J. Ramaiya, R. Jha, and R. Mallik. 2013. Molecular adaptations allow dynein to generate large collective forces inside cells. Cell. 152:172-182.

Ramaiya, A., B. Roy, M. Bugiel, and E. Schaffer. 2017. Kinesin rotates unidirectionally and generates torque while walking on microtubules. Proc Natl Acad Sci U S A. 114:10894-10899.

Rao, L., F. Berger, M.P. Nicholas, and A. Gennerich. 2019. Molecular mechanism of cytoplasmic dynein tension sensing. Nature communications. 10:3332.

Smith, S.B., L. Finzi, and C. Bustamante. 1992. Direct mechanical measurements of the elasticity of single DNA molecules by using magnetic beads. Science. 258:1122-1126.

Sudhakar, S., M.K. Abdosamadi, T.J. Jachowski, M. Bugiel, A. Jannasch, and E. Schaffer. 2021. Germanium nanospheres for ultraresolution picotensiometry of kinesin motors. Science. 371.

Toleikis, A., N.J. Carter, and R.A. Cross. 2020. Backstepping Mechanism of Kinesin-1. Biophys J. 119:1984-1994.

Urbanska, M., A. Ludecke, W.J. Walter, A.M. van Oijen, K.E. Duderstadt, and S. Diez. 2021. Highly-Parallel Microfluidics-Based Force Spectroscopy on Single Cytoskeletal Motors. Small. 17:e2007388.

Wang, M.D., H. Yin, R. Landick, J. Gelles, and S.M. Block. 1997. Stretching DNA with optical tweezers. Biophys J. 72:1335-1346.

Guide de décodage et d'optimisation du bulletin scolaire : Note de synthèse

Ce document propose une analyse approfondie des mécanismes du bulletin scolaire en Ontario, basée sur l'expertise pédagogique partagée lors du webinaire « Mieux comprendre le bulletin scolaire de votre enfant ».

Il vise à fournir aux parents et tuteurs les outils nécessaires pour interpréter les évaluations et soutenir efficacement le parcours académique de l'élève.

Résumé analytique

Le bulletin scolaire ne doit pas être perçu comme un simple classement, mais comme un outil de communication dynamique entre l'école et la famille.

Les points essentiels à retenir sont :

• Finalité pédagogique : Le bulletin mesure le progrès par rapport au curriculum provincial et non le potentiel intrinsèque ou la valeur de l'enfant.

• Indicateurs de réussite : Les habiletés d'apprentissage et les habitudes de travail (HH) sont souvent les prédicteurs les plus fiables des résultats académiques futurs.

• Approche constructive : La compréhension des verbes d'action dans les commentaires et l'identification des « prochaines étapes » sont cruciales pour la progression.

• Soutien ciblé : L'accompagnement à domicile doit privilégier la valorisation de l'effort et la régularité (10 minutes par année d'études) plutôt que la surcorrection.

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1. Structure et cycle des rapports scolaires

L'année scolaire est jalonnée de trois rapports distincts, chacun ayant une fonction spécifique dans le suivi de l'élève :

| Type de bulletin | Période | Contenu principal | | --- | --- | --- | | Bulletin de progrès | Automne (quelques mois après la rentrée) | Commentaires qualitatifs en français et mathématiques ; évaluation des habiletés d'apprentissage. | | Étape 1 | Hiver (en cours) | Notes détaillées (lettres ou pourcentages) et commentaires pour chaque sujet du curriculum. | | Étape 2 (Final) | Fin juin | Bilan de l'année complète avec notes finales et prochaines étapes pour l'année suivante. |

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2. Système de notation et interprétation des résultats

La notation varie selon le niveau scolaire, mais suit une logique de progression par rapport aux attentes du curriculum :

Niveaux de performance

• A (80 % - 100 %) : L'élève dépasse les attentes fixées par le curriculum.

• B (70 % - 79 %) : L'élève répond pleinement aux attentes. C'est un niveau de réussite solide et positif.

• C (60 % - 69 %) : L'élève approche des attentes ; des ajustements sont nécessaires pour consolider les acquis.

• D (50 % - 59 %) : L'élève est bien en dessous des attentes.

Cela constitue souvent un « drapeau rouge » nécessitant une intervention.

Les limites de la note

Il est impératif de comprendre que les lettres ou pourcentages ne mesurent pas :

• L'intelligence globale ou le quotient intellectuel.

• Le potentiel de réussite future.

• L'effort fourni spécifiquement à la maison.

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3. Habiletés d'apprentissage et habitudes de travail (HH)

Situées généralement en première page, les habiletés telles que l'organisation, l'autorégulation, l'esprit de collaboration et l'utilisation du français sont fondamentales.

• Corrélation avec les notes : Il existe un lien direct entre les HH et les résultats académiques.

Une baisse des habiletés (ex: désorganisation) précède souvent une baisse des notes.

• Indicateurs de comportement : Contrairement aux matières académiques, ces notes reflètent la manière dont l'élève apprend et interagit.

Par exemple, l'« utilisation du français » évalue la volonté de s'exprimer dans la langue, tandis que la « communication orale » évalue la compétence linguistique technique.

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4. Analyse des commentaires de l'enseignant

Les commentaires servent à expliciter la note et à tracer une feuille de route pour l'élève.

• Le choix des verbes : Un élève qui « maîtrise » une compétence est à un stade différent de celui qui « commence à » ou « continue de ».

Les parents doivent porter une attention particulière à ces nuances.

• Les prochaines étapes : C'est l'élément le plus critique du commentaire.

Il indique précisément ce que l'élève doit travailler pour passer au niveau supérieur (ex: passer d'un C+ à un B-).

• Communication orale : Ce domaine ne doit pas être confondu avec la personnalité (ex: timidité).

Il évalue la capacité à structurer des messages et à utiliser un vocabulaire approprié.

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5. Stratégies de soutien à domicile

Le rôle du parent est de soutenir, non d'enseigner à nouveau la matière.

Recommandations de gestion du temps

Le temps de travail à la maison devrait suivre la règle des 10 minutes par niveau scolaire :

• 1ère année : 10 minutes (lecture ou devoirs).

• 6ème année : 60 minutes.

• Note : Si aucun devoir n'est assigné, ce temps doit être consacré à la lecture ou à l'écoute de contenus en français (ex: Netflix en français pour les plus âgés).

Pratiques favorisantes

• Poser des questions ouvertes : Plutôt que de vérifier uniquement les réponses, interrogez l'enfant sur le contenu (« Pourquoi le personnage a-t-il fait cela ? »).

• Valoriser l'effort : Encourager le progrès quotidien plutôt que la perfection.

• Éviter la comparaison : Ne pas comparer les résultats avec la fratrie ou les pairs pour préserver l'estime de soi.

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6. Interventions spécialisées : Le PEI

Si un élève présente des difficultés persistantes (notes de niveau D), l'équipe école peut proposer un Plan d'enseignement individualisé (PEI).

• Adaptations : Changements dans les stratégies d'enseignement (temps supplémentaire, outils technologiques comme Google Reading & Write, diminution du nombre de questions) sans modifier le niveau du curriculum.

• Modifications : Changement du niveau de difficulté des attentes (ex: un élève en 4ème année travaillant sur le curriculum de mathématiques de 3ème année).

Cela nécessite le consentement formel des parents et s'appuie souvent sur des évaluations psychologiques ou éducationnelles.

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7. Communication efficace avec l'école

La collaboration avec l'enseignant titulaire et l'enseignant ressource est la clé du succès.

Voici des questions pertinentes pour une rencontre :

• Quelles sont les forces principales observées en classe ?

• Quelle est la priorité académique actuelle (ex: quel temps de verbe ou concept mathématique est étudié) ?

• Quelles sont les une ou deux stratégies prioritaires à appliquer à la maison ? (Il est déconseillé de tenter de suivre plus de deux objectifs simultanément).

Right ventricular hypertrophy / cor pulmonale Pulmonary embolus Ischaemic heart disease Rheumatic heart disease Congenital heart disease (e.g. atrial septal defect) Myocarditis Cardiomyopathy Lenègre-Lev disease: primary degenerative disease (fibrosis) of the conducting system

Deelnemer reageert niet meer

Aortic stenosis Ischaemic heart disease Hypertension Dilated cardiomyopathy Anterior MI Lenègre-Lev disease: primary degenerative disease (fibrosis) of the conducting system Hyperkalaemia Digoxin toxicity

me semblent mettre en évidence..

me semblent

me

les trois démarches ici exposées ne sont que..

me semble

j'attire

m'intéresse

je veux

J'entends

je désigne

J'aborde

Je propose

Inferior myocardial infarction AV-nodal blocking drugs (e.g. calcium-channel blockers, beta-blockers, digoxin) Idiopathic degeneration of the conducting system (Lenegre’s or Lev’s disease), causing true trifascicular block

Le Cerveau Attentif : Mécanismes, Défis et Maîtrise de l'Attention

Résumé Exécutif

Ce document de synthèse analyse les interventions de Jean-Philippe Lachaux, chercheur à l'Inserm et spécialiste des neurosciences cognitives, sur le fonctionnement de l'attention humaine.

Le constat central est que l'attention n'est pas une faculté éthérée, mais un processus biologique soumis à des contraintes physiques et chimiques précises.

L'attention agit comme un filtre indispensable pour un cerveau constamment saturé d'informations, déterminant ainsi notre perception de la réalité.

Le document détaille le modèle PIM (Perception, Intention, Manière d'agir), outil structurel de la concentration, et explore comment l'expertise transforme la perception en cibles spécifiques.

Il aborde également la "crise de l'attention" actuelle, exacerbée par les outils numériques qui exploitent les failles du circuit de la récompense.

Enfin, il propose le concept de "sens de l'équilibre attentionnel" et d'une "introspection informée" comme moyens de reprendre le contrôle sur notre vie mentale dans un environnement saturé de distractions.

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I. Nature et Fonction de l'Attention

L'attention n'est pas seulement une question de vigilance ; elle est le moteur qui définit notre expérience du monde seconde après seconde.

A. Un filtre contre la saturation

Le cerveau humain possède environ 86 à 100 milliards de neurones, mais il est paradoxalement très vite débordé.

L'attention effectue un travail de "nettoyage" pour éliminer les informations non pertinentes.

• L'aveuglement attentionnel : L'expérience du film avec le poivron démontre que lorsque l'attention est focalisée sur une tâche précise (suivre un gobelet), des éléments visuels pourtant évidents deviennent invisibles.

• La création de la réalité : Ce à quoi nous prêtons attention détermine notre vie mentale.

Mille personnes ayant des intentions différentes dans une même pièce vivront mille expériences distinctes.

B. L'incarnation biologique

L'attention est ancrée dans la matière biologique, ce qui impose deux réalités :

• L'inertie : La pensée est soumise aux lois de la physique, de la chimie et de la biologie.

Elle ne peut pas être instantanée ou infinie.

• L'introspection informée : Comprendre ces contraintes biologiques permet de "pacifier" notre relation à notre propre fonctionnement mental, en acceptant les limites de notre cerveau plutôt que de se juger "nul" ou "lent".

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II. Le Modèle PIM : La Structure de la Concentration

Lachaux propose de déconstruire l'image négative de la concentration (souvent associée à l'effort et à la crispation) pour la définir comme une adéquation parfaite entre le réglage cérébral et la tâche.

Les trois composantes du PIM

| Composante | Description | Exemple (le verre d'eau) | | --- | --- | --- | | P - Perception | La donnée sensorielle que l'on privilégie. | La position de l'eau par rapport au bord du verre. | | I - Intention | L'objectif précis à court terme. | Empêcher l'eau de se rapprocher du bord. | | M - Manière d'agir | Le contrôle moteur ou cognitif spécifique. | Ajuster finement les mouvements du poignet. |

La concentration est l'activation synchrone de ces trois éléments. Lorsqu'un individu applique le PIM, son cerveau n'engage que les ressources nécessaires, éliminant toute déperdition d'énergie.

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III. Expertise et Perceptions Spécialisées

L'entraînement permet de développer des "perceptions expertes", où l'attention se porte sur des cibles invisibles pour le néophyte.

• Patterns et Schémas : Un footballeur professionnel (ex: Sidney Govou) ne voit pas seulement des joueurs, mais des schémas tactiques et des "flèches" indiquant les trajectoires de drible créées par son cerveau.

• Le rôle de l'Insula : Cette structure cérébrale gère les sensations corporelles.

Les experts, comme la nageuse Mylène Lazare, apprennent à transformer une sensation négative (le stress) en une cible attentionnelle utile (une "boule de chaleur" énergisante).

• Apprentissage perceptif : On peut apprendre à "mieux voir" ou "mieux entendre", comme l'artisan qui détecte des informations cruciales dans le son de son marteau.

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IV. Les Failles du Système Attentionnel

Le système attentionnel humain présente des vulnérabilités que l'économie moderne exploite.

A. Le circuit de la récompense et la dopamine

Ce circuit mémorise les expériences plaisantes et nous pousse à les renouveler.

• Capture de l'attention par la valeur : Les stimuli associés à une gratification immédiate (sucre, réseaux sociaux, notifications) capturent l'attention de manière automatique.

• Récompenses non naturelles : Les applications numériques utilisent des récompenses intermittentes (type machine à sous) pour lesquelles le cerveau n'a pas développé de mécanisme de satiété au cours de l'évolution.

B. Le coût d'opportunité et la fatigue

• Le fardeau de la distraction : Savoir qu'une source de plaisir immédiat (smartphone) est disponible crée un "coût d'opportunité" qui rend la concentration sur une tâche ardue beaucoup plus fatigante.

• Vulnérabilité nocturne : Le soir, la fatigue affaiblit le cortex préfrontal (le régulateur) tout en rendant le circuit de la récompense plus sensible.

C'est ce qui explique la difficulté à arrêter le visionnage compulsif de vidéos ("autoplay") à 2h du matin.

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V. Stratégies de Reprise de Contrôle

Face à la saturation, plusieurs méthodes permettent de stabiliser l'attention.

A. Le sens de l'équilibre attentionnel

Inspiré de l'équilibre physique (comme sur une poutre), ce sens consiste à ressentir le moindre début de distraction pour ramener immédiatement l'attention vers sa cible.

Lachaux souligne le lien étroit entre le mouvement des yeux, la posture du corps et le déplacement de l'attention.

B. La méthode Feynman (L'intention précise)

Pour se concentrer sur un sujet complexe, Richard Feynman suggérait de transformer une intention vague ("apprendre mon cours") en intentions précises ("comprendre ces trois concepts"). Cela crée un "appel d'air" pour l'attention.

C. La "Mentalimentation"

Ce à quoi nous prêtons attention reconfigure nos cartes cognitives (dans l'hippocampe).

• Surreprésentation : Si nous consommons trop d'informations anxiogènes, ces concepts finissent par dominer notre vagabondage mental spontané, rendant notre vie intérieure plus sombre.

• Filtrage : Il est crucial de choisir ce que l'on "donne à manger" à son cerveau, car l'attention est la fourchette de l'esprit.

D. Applications Pédagogiques (ATOLE)

Le programme ATOLE vise à enseigner ces mécanismes aux enfants pour les aider à :

• Identifier leurs "micro-missions".

• Prendre conscience de leurs vulnérabilités face aux écrans.

• Développer une autonomie attentionnelle par le jeu et la compréhension des neurosciences.

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Citations Clés

"La distraction, du latin distraere, c'est déchirer.

C'est l'idée que l'esprit est déchiré entre deux choses."

"Une intention vague éparpille l'attention. L'attention s'évapore et se vaporise quand vous avez une intention vague."

"Un adulte, pour un enfant, est une prothèse de cortex préfrontal."

"L'attention choisit ce que l'on donne à manger à notre cerveau. Il faut soigner sa mentalimentation."

Test

Drugs: beta-blockers, calcium channel blockers, digoxin, amiodarone Increased vagal tone (e.g. athletes) Inferior MI Myocarditis Following cardiac surgery (mitral valve repair, Tetralogy of Fallot repair

Increased vagal tone Athletic training Inferior MI Mitral valve surgery Myocarditis (e.g. Lyme disease) Electrolyte disturbances (e.g. Hyperkalaemia) AV nodal blocking drugs (beta-blockers, calcium channel blockers, digoxin, amiodarone) May be a normal variant

PR interval > 200ms (five small squares)

eLife Assessment

The nematode C. elegans is an ideal model in which to achieve the ambitious goal of a genome-wide atlas of protein expression and localization. In this paper, the authors explore the utility of a new and efficient method for labeling proteins with fluorescent tags, evaluating its potential to be the basis for a larger, genome-wide effort that is likely to be very useful for the community. While the evidence for the method itself is solid, carrying out this project at a large scale will require significant additional feasibility studies.

Reviewer #1 (Public review):

Summary:

Eroglu and Hobert demonstrate that injecting CRISPR guides and repair constructs to target three genes at a time, tagging each with a different fluorescent protein, and selecting which gene to tag with which fluorophore based on genes' expression levels, can improve the efficiency of gene tagging.

Strengths:

This manuscript demonstrates that three genes can be targeted efficiently with three different fluorophores. It also presents some practical considerations, like using the fluorophore least complicated by agar/worm autofluorescence for genes with low expression levels, and cost calculations if the same methods were used on all genes.

Weaknesses:

Eroglu has demonstrated in a previous publication that single-stranded DNA injection can increase the efficiency of CRISPR in C. elegans while inserting two fluorescent proteins and a co-CRISPR marker into three loci. The current work is, therefore, an incremental advance. In general, I applaud the authors' willingness to think ahead to how whole proteome tagging might be accomplished, but I predict that the advance here will be one of many small advances that will get the field to that goal. The title vastly oversells the advance in my view, and the first sentence of the Discussion seems a more apt summary of the key advance here.

Some injections target genes on the same chromosome together, which will create unnecessary issues when doing necessary backcrossing, especially if the mutation rate is increased by CRISPR. Also, the need for backcrossing and perhaps sequencing made me wonder if injecting 3 together really is helpful vs targeting each gene separately, since only 5 worms need to be injected.

The limited utility of current blue fluorescent proteins makes me wonder if it's worth using at all at this stage, before there are better blue (or far red) fluorescent proteins.

Some literature reviews, particularly in the Introduction and Abstract, rely too much on recent examples from the authors' laboratory instead of presenting the state of the field. I'd like to have known what exactly has been done with simultaneous injection targeting multiple loci more thoroughly, comparing what has been accomplished to date by various laboratories' advances to date.

Reviewer #2 (Public review):

The manuscript by Eroglu and Hobert presents a set of strains each harboring up to three fluorescently tagged endogenous proteins. While there is technically nothing wrong with the method and the images are beautiful, we struggled to appreciate the advance of this work - who is this paper for?

As a technical method, the advance is minimal since the first author had already demonstrated that three mutations (fluorophore insertion and co-CRISPR marker) could be introduced simultaneously.

As a pilot for creating genome-scale resources, it is not clear whether three different fluorophores in one animal, while elegantly designed and implemented, will be desired by the broader community.

Finally, the interpretation of the patterns observed in the created lines is somewhat lacking. A Table with all the observations must be included. This can replace the descriptions of the observations with the different lines, which could be somewhat laborious for the reader, and are often wrong. There are numerous mistaken expectations of protein expression here, but two examples include:

(1) The expectation that ACDH-10 is enriched in the intestine and epidermal tissues (hypodermis)<br /> There are multiple paralogs of this protein (see WormPaths or WormFlux) that may share functions in different tissues. There is also no reason to assume that fatty acid metabolism does not occur in other tissues (including the germline). Finally, there are no published studies about this enzyme, so we really don't know for sure what it's doing.

(2) The expectation that HXK-1 is ubiquitously expressed<br /> Three paralogous enzymes are all associated with the same reaction, and we have shown that these three function redundantly in vivo, perhaps in different tissues (PMID: 40011787). Moreover, single-cell RNA-seq data (PMID: 38816550) also show enrichment of hxk-1 in gonadal sheath cells.

The table should have at least the following information: gene/protein name - Wormbase ID - TPM levels of single cell data assigned to tissues for L2, L4, and adult (all published) - tissues in which expression is observed in the lines presented by the authors.

Reviewer #3 (Public review):

Summary:

The authors argue that establishing the expression pattern and subcellular localisation of an animal's proteome will highlight many hypotheses for further study. To make this point and show feasibility, they developed a pipeline to knock in DNA encoding fluorescent tags into C. elegans genes.

Strengths:

The authors effectively make the points above. For example, they provide evidence of two populations of mitochondria in the C. elegans germline that differ qualitatively in the proteins they express. They also provide convincing evidence that labelling the whole proteome is an achievable goal with relatively limited resources and time.

Weaknesses:

Cell biology in C. elegans is challenging because of the small size of many of its cells, notably neurons. This can make establishing the sub-cellular localisation of a fluorescently tagged protein, or co-localizing it with another protein, tricky. The authors point out in their introduction that advances in light microscopy, such as diSPIM, STED, and ISM (a close relative of SIM), have increased the resolution of light microscopy. They also point out that recent advances in expansion microscopy can similarly help overcome the resolution limit.

(1) Have the authors investigated if the three fluorescent tags they use are appropriate for super-resolution microscopy of C. elegans, e.g., STED or SIM? Would Elektra be better than mTAGBFP2? How does mScarlet3-S2 compare to mScarlet 3?

(2) Have the authors investigated what tags could be used in expansion microscopy - that is, which retain antigenicity or even fluorescence after the protocol is applied? It may be useful to add different epitope tags to the knock-in cassettes for this purpose.

The paper is fine as it stands. The experiments above could add value to it and future-proof it, but are not essential. If the experiments are not attempted, the authors could refer to the points above in the discussion.

Author Response:

eLife Assessment

The nematode C. elegans is an ideal model in which to achieve the ambitious goal of a genome-wide atlas of protein expression and localization. In this paper, the authors explore the utility of a new and efficient method for labeling proteins with fluorescent tags, evaluating its potential to be the basis for a larger, genome-wide effort that is likely to be very useful for the community. While the evidence for the method itself is solid, carrying out this project at a large scale will require significant additional feasibility studies.

We appreciate the editor’s recognition that the evidence for our method is solid and that a genome-wide protein atlas in C. elegans would be highly valuable to the community. However, we respectfully disagree that significant additional feasibility studies are required. As comparison, the yeast proteome-wide GFP tagging project (Huh et al., Nature 2003) achieved ~75% coverage of ~6,000 proteins directly from an established protocol without any prior significant feasibility studies, at least to our knowledge. While the C. elegans genome is 3 times in size, we would argue that our tagging protocol may even be less labor intensive as it does not involve any cloning and the screening is visual, requiring no molecular biology skills. Reviewer 3 notes: “They also provide convincing evidence that labelling the whole proteome is an achievable goal with relatively limited resources and time.”

Our pilot study validates all key parameters for genome-wide scaling: editing efficiency at novel loci with untested reagents, viability of tagged worms, and detectability of multiple spectrally separated fluorophores across expression ranges. These address the core technical, biological, and practical challenges of large-scale endogenous tagging in a multicellular organism, leaving no fundamental barriers in our view.

The proposed cost and timeline align quite favorably with established large-scale consortium projects: e.g., ENCODE pilot analyzed 1% of the human genome at ~$55 million over 4 years; Mouse Knockout Consortium scaled to ~20,000 genes over 20 years (ongoing) with ~$100 million; Human Protein Atlas mapped ~87% of proteins with antibodies in fixed cells (through much more labor intensive methods) over 20+ years at >$100 million. With ~8% of C. elegans genes already tagged (WormTagDB), scaling our protocol to the proteome is feasible, potentially covering the genome in 5-6 years by a single lab or faster with distributed effort at a reagent cost of merely $2.2 million. The main barriers now are funding commitment and assembling collaborators, not further feasibility testing.

Public Reviews:

Reviewer #1 (Public review):

Summary:

Eroglu and Hobert demonstrate that injecting CRISPR guides and repair constructs to target three genes at a time, tagging each with a different fluorescent protein, and selecting which gene to tag with which fluorophore based on genes' expression levels, can improve the efficiency of gene tagging.

Strengths:

This manuscript demonstrates that three genes can be targeted efficiently with three different fluorophores. It also presents some practical considerations, like using the fluorophore least complicated by agar/worm autofluorescence for genes with low expression levels, and cost calculations if the same methods were used on all genes.

Weaknesses:

Eroglu has demonstrated in a previous publication that single-stranded DNA injection can increase the efficiency of CRISPR in C. elegans while inserting two fluorescent proteins and a co-CRISPR marker into three loci. The current work is, therefore, an incremental advance. In general, I applaud the authors' willingness to think ahead to how whole proteome tagging might be accomplished, but I predict that the advance here will be one of many small advances that will get the field to that goal.

Our manuscript indeed builds on prior multiplex editing (including our own co-CRISPR work), but the manuscript's primary contribution is not a novel technical breakthrough per se. Instead, our main goal was to pilot and strategize a feasible path to whole-proteome tagging in C. elegans and importantly test the following key parameters: (1) success rate of triple pools with prior untested reagents at novel targets; (2) utility of fluorophores across expression levels; (3) major effects on tagged protein function. In prior multiplexing, we used two targets which we already knew could be edited quite efficiently, with the 3rd target a point mutation with nearly 100% efficiency. Thus, it was not at all clear that picking 3 random genes and replacing the 3rd highly efficient locus with another less efficient large insertion would work or be sufficiently scalable for thousands of novel genes with unvalidated reagents at first pass.

The title vastly oversells the advance in my view, and the first sentence of the Discussion seems a more apt summary of the key advance here.

Some injections target genes on the same chromosome together, which will create unnecessary issues when doing necessary backcrossing, especially if the mutation rate is increased by CRISPR.

We disagree with the reviewer’s assessment of the need for backcrossing, for two reasons: (1) Prior studies have shown that off-target mutations are not a serious concern in C. elegans (reviewed in PMID: 26336798 and PMID: 24685391). For instance, WGS of strains after CRISPR/Cas9 found negligible off-target effects (PMID: 25249454, PMID: 30420468 – using similar RNP/ssDNA method and multiple guides; PMID: 23979577, PMID: 27650892 using other methods). Targeted sequencing studies have reported similar findings, using various CRISPR/Cas9 methods, with essentially no mutations at sites other than the intended target (PMID: 23995389; PMID: 23817069). (2) If the goal is to tag the entire genome, the introduction of backcrossing should not reasonably be a routine part of the initial tagging.

Lastly, if one wants to backcross at a later stage, the existence of tags on the same chromosome is actually an advantage because it permits selection for recombinants with wild-type chromosomes.

Also, the need for backcrossing and perhaps sequencing made me wonder if injecting 3 together really is helpful vs targeting each gene separately, since only 5 worms need to be injected.

Apart from our disagreement regarding backcrossing, we are puzzled by the reviewer’s comment that tagging each gene separately may not be considered helpful. Why would one do single tagging at a time, rather than triple tagging if the whole point of the paper is to demonstrate the scalability of tagging? Meaning, that one can shortcut tagging all genes by a factor of 3 through joint tagging? It is important to keep in mind that the rate limiting step for tagging the whole genome is the number of injections that can be done per day. Since there is no cloning to generate the repair templates/guides and all other reagents are commercially available and not sample specific, these can be prepared quite rapidly. Being able to isolate multiple lines (together or independently) from the same injection increases throughput 3-fold and in our view does not provide any disadvantages as individual tags can be isolated independently if desired.

Beyond the numerous technical advantages pooling provides (also lower cost and throughput for making injection mixes as well as imaging), our results show that it yields epistemic benefits as well: we would never have noted the subcellular pattern in Fig. 6B, C with different sets of mitochondria being marked by different mitochondrial proteins had we imaged them separately or even aligned to a pan-mitochondrial landmark. As we mentioned in the discussion, grouping proteins predicted to localize to the same compartment together can simultaneously test how uniform or differentiated such compartments are during the screen.

The limited utility of current blue fluorescent proteins makes me wonder if it's worth using at all at this stage, before there are better blue (or far red) fluorescent proteins.

We do not think that the utility of current BFPs is very limiting. The theoretical brightness of mTagBFP2 is comparable to that of EGFP (PMID: 30886412), which was useful for the bulk of currently tagged proteins. Due to modestly higher autofluorescence in the blue spectrum, the practical brightness is somewhat less ideal, but we have shown that many proteins are expressed high enough to be detected quite well with mTagBFP2 by eye at low magnification. We also note that many tags that are not visible by eye under a dissection scope become visible with long exposure cameras of widefield microscopes or modern confocal (GaAsP) detectors, so the list of genes detectable with mTagBFP2 is likely to be much higher. We routinely use mTagBFP2 to super-resolve subnuclear structures with endogenous tags (e.g., in the nucleolus), with some tags having lower annotated FPKMs than the genes tested here.

Some literature reviews, particularly in the Introduction and Abstract, rely too much on recent examples from the authors' laboratory instead of presenting the state of the field. I'd like to have known what exactly has been done with simultaneous injection targeting multiple loci more thoroughly, comparing what has been accomplished to date by various laboratories' advances to date.

We are not sure what the reviewer is referring to when bemoaning that the Abstract and Introduction are too focused on our paper and not presenting the state of the field. In the Abstract, we do not refer to any literature. In the Introduction, we cite 28 papers, 6 of those from our lab (4 of which providing examples of protein tags). We do not believe that this can be fairly called an unbalanced presentation of the state of the field.

This being said, we will gladly expand our Introduction to provide more background on co-CRISPRing. Labs have routinely used co-conversion (“coCRISPR”) markers for picking out their intended edits (e.g., point mutations or insertions), as it has been shown by multiple groups that a CRISPR/Cas9 edit at one locus correlates with efficiency at other simultaneous targets (PMID: 25161212). Generally, making point mutations with the Cas9/RNP protocol is highly efficient, especially at specific loci such as dpy-10. However, multiple FP-sized insertions have not been routinely attempted. We and only one other group have successfully attempted it using previously working targets and reagents (e.g., 28% in PMID: 26187122). Importantly, the efficiency of such multiple insertions has never been assessed at scale and using entirely untested reagents at novel sites – critical parameters to determine for a whole genome approach. So, we test here (1) the efficiency of triple insertions and (2) the chance of getting them with new and untested guides and reagents.

In our view, since we have to use some injection/coCRISPR marker anyway for those genes which are not expressed at dissecting-scope visible levels (likely most genes), using highly expressed intended targets as improvised markers in a pooled approach makes our approach much more efficient. It allows us to find the worms with the highest chance of yielding CRISPR insertions, which we can screen with higher power methods for the dimmer targets, while enabling us to co-isolate other intended targets. Insertions, being often heterozygous in F1, can be segregated independently if desired, or homozygosed together to facilitate maintenance then outcrossed individually by those interested in studying specific genes in more detail.

In the revised version of this manuscript, we will discuss some of these points in the first paragraph of the results section:

“In C. elegans, screening for novel CRISPR/Cas9-induced genomic edits is facilitated either by use of co-injection markers (i.e., plasmids that form extrachromosomal arrays) that yield phenotypes or fluorescence in progeny of successfully injected worms, or co-editing well characterized loci using established and highly efficient reagents which likewise yield visible phenotypes. In the latter approach, termed “co-CRISPR”, worms edited at the marker locus are most likely to also carry the intended edit (Arribere et al., 2014).”

“These attempts pooled reagents previously established to work efficiently and targeted genes that were known to yield functional fusion proteins when tagged. Thus, while in principle current methods could allow tagging of at least 3 independent loci in one injection if a co-CRISPR marker is omitted, it is not known to what extent such an approach could be generalized across the genome with previously unvalidated reagents (i.e., guides and repair template homology arms) at novel loci.”

Reviewer #2 (Public review):

The manuscript by Eroglu and Hobert presents a set of strains each harboring up to three fluorescently tagged endogenous proteins. While there is technically nothing wrong with the method and the images are beautiful, we struggled to appreciate the advance of this work - who is this paper for?

We consider this paper to have two purposes: (1) motivate the community to come together to consider such genome-wide tagging approach; (2) provide a reference point for funding agencies that such an aim is not unreasonable and will provide novel interesting insights.

As a technical method, the advance is minimal since the first author had already demonstrated that three mutations (fluorophore insertion and co-CRISPR marker) could be introduced simultaneously.

We agree that the basic principle is similar. However, it was not clear that triple pooling three novel large edits would work, given the numbers in our original paper or that it would be scalable.

The dpy-10 coCRISPR marker previously used is a highly efficient single site, with close to 100% hit rate. We also knew in the earlier study that the two pooled insertions already worked quite efficiently and did not disrupt the function of targeted proteins. Exchanging these plus dpy-10 for three novel tags was not guaranteed to succeed for many potential reasons, including both biological and technical. For instance, such a “marker free” approach necessitates that a significant number of targets in the genome should be expressed highly enough to be visible by fluorescence stereomicroscopy when tagged with current best fluorophores. The chance of disrupting gene function by tagging was also not explored in detail in C. elegans, nor whether one untested guide is generally sufficient. We think that establishing these parameters was meaningful and necessary for the goal of whole genome tagging. We have clarified some of these points in the text.

As a pilot for creating genome-scale resources, it is not clear whether three different fluorophores in one animal, while elegantly designed and implemented, will be desired by the broader community.

The usage of three different fluorophores is largely driven by the ability to co-inject and therefore cut injection effort by a factor of three. Moreover, having all three fluorophores together facilitates imaging and maintenance. Lastly, co-labeling has the potential to reveal unexpected patterns of co-localization or lack thereof (example: two mitochondrial proteins that we found to not have overlapping distribution). We clarified this point in the revised text in both the results and discussion.

Finally, the interpretation of the patterns observed in the created lines is somewhat lacking. A Table with all the observations must be included. This can replace the descriptions of the observations with the different lines, which could be somewhat laborious for the reader, and are often wrong. There are numerous mistaken expectations of protein expression here, but two examples include:

We are not convinced that expectations are mistaken. Below we respond to the reviewer’s specific examples and we are open to hear from the reviewer about additional cases.

(1) The expectation that ACDH-10 is enriched in the intestine and epidermal tissues (hypodermis).

There are multiple paralogs of this protein (see WormPaths or WormFlux) that may share functions in different tissues. There is also no reason to assume that fatty acid metabolism does not occur in other tissues (including the germline). Finally, there are no published studies about this enzyme, so we really don't know for sure what it's doing.

The expression of acdh-10 is annotated in multiple scRNA datasets as intestine and epidermal enriched (Packer et al 2019, highest intestine and hyp; Ghaddar et al 2023 intestine, sheath and BWM, and even oocyte). We did not mean to imply that fatty acid metabolism does not occur in the gonad, nor that a paralog of acdh-10 could not be performing the same function in tissues where acdh-10 is not expressed.

However, this raises an important question: why have different paralogs doing the same thing? Duplicate genes with the same function are generally not evolutionarily stable (PMID: 11073452, PMID: 24659815). That there are such striking tissue specific expression patterns of an essential or widely expressed protein class suggests that paralogs of the gene likely differ in some meaningful parameter that might align with tissue-specific functional needs or regulation. The reviewer’s statement that “there are no published studies about this enzyme, so we really don't know for sure what it's doing” is in fact an excellent demonstration of our point; finding out where the duplicates are expressed can provide a starting point to uncover potential differences between the paralogs. At the very least it can delineate to what degree paralogs diverge in their expression across the proteome and identify which such cases merit further study. In a more ideal scenario, prior information of protein function could indicate that the involved pathway requires tissue specific regulation.

(2) The expectation that HXK-1 is ubiquitously expressed.

Three paralogous enzymes are all associated with the same reaction, and we have shown that these three function redundantly in vivo, perhaps in different tissues (PMID: 40011787).

The cited paper (PMID: 40011787) does not show where they are expressed. We discussed redundancy/paralogs above in point 1, and in our view the same applies here. They may perform the same reaction but are likely to differ in some meaningful way, be it regulation or rate of activity, for them to be stably maintained as functional genes over evolution.

Moreover, single-cell RNA-seq data (PMID: 38816550) also show enrichment of hxk-1 in gonadal sheath cells.

We note that the Ghaddar et al. and CeNGEN/Taylor et al. datasets do not. The scRNA paper cited by the referee (PMID: 38816550) also shows enrichment in neurons and pharynx, which we did not note. In our view, these in fact further support our goals: often, transcript datasets alone (frequently used to infer tissue function) do not sufficiently predict protein expression. One can post hoc find an scRNA-seq dataset that aligns somewhat with our protein observations, but how does one know which to trust a priori? Disagreements between transcript datasets will ultimately require resolution at the protein level, in our view.

To clarify these points, we will add the following to the discussion section:

“We also noted unexpected cell type dependent distributions of proteins involved in broadly important metabolic processes such as ACDH-10, which was depleted from the germline compared to other tissues, and HXK-1, which was highly enriched in the gonadal sheath. Notably, for these as well as other cases, scRNA-seq datasets were not sufficient to deduce a priori the observed cell type specific differences at the protein level. Importantly, many genes encoding metabolic enzymes including acdh-10 and hxk-1 have paralogs that likely perform similar catalytic functions. Yet, duplicate genes with identical functions are generally not evolutionarily stable (Adler et al., 2014; Lynch and Conery, 2000); thus such genes are likely to differ in some meaningful parameter (e.g., regulation or activity) that might align with tissue-specific functional needs. Fully annotating the expression patterns of paralogs at the protein level could indicate which tissues require unique metabolic needs and indicate which paralogous genes have undergone sub- versus neo-functionalization. For those proteins that are less functionally understood, unexpected distributions might indicate which merit further study.”

The table should have at least the following information: gene/protein name - Wormbase ID - TPM levels of single cell data assigned to tissues for L2, L4, and adult (all published) - tissues in which expression is observed in the lines presented by the authors.

We will add this information to the table including annotated expression levels in young adults from various datasets (but not larval datasets as we did not image these). We note that each of these studies use different pipelines and report different metrics (scaled TPM/Z-score versus Seurat average expression versus TPM), so comparisons between them are not informative unless they are integrated and analyzed together.

Reviewer #3 (Public review):

Summary:

The authors argue that establishing the expression pattern and subcellular localisation of an animal's proteome will highlight many hypotheses for further study. To make this point and show feasibility, they developed a pipeline to knock in DNA encoding fluorescent tags into C. elegans genes.

Strengths:

The authors effectively make the points above. For example, they provide evidence of two populations of mitochondria in the C. elegans germline that differ qualitatively in the proteins they express. They also provide convincing evidence that labelling the whole proteome is an achievable goal with relatively limited resources and time.

We are grateful for the referee’s appreciation that whole proteome tagging is feasible.

Weaknesses:

Cell biology in C. elegans is challenging because of the small size of many of its cells, notably neurons. This can make establishing the sub-cellular localisation of a fluorescently tagged protein, or co-localizing it with another protein, tricky. The authors point out in their introduction that advances in light microscopy, such as diSPIM, STED, and ISM (a close relative of SIM), have increased the resolution of light microscopy. They also point out that recent advances in expansion microscopy can similarly help overcome the resolution limit.

(1) Have the authors investigated if the three fluorescent tags they use are appropriate for super-resolution microscopy of C. elegans, e.g., STED or SIM? Would Elektra be better than mTAGBFP2? How does mScarlet3-S2 compare to mScarlet 3?

All three tags work for ISM (i.e., Airyscan). We previously tried Electra (not for the genes tested here) but could not isolate positive tags. Given Electra is not that much brighter on paper than mTagBFP2 we did not pursue it further, though we recognize that these may simply have been unlucky injections. mScarlet3-S2 is quite a bit dimmer than mScarlet3 on paper – the advantage is that it has higher photostability. In our view, the limiting factor will be having FPs that are bright enough to screen, image and scale to the whole genome, so brightness will likely provide an advantage over photostability at this stage.

(2) Have the authors investigated what tags could be used in expansion microscopy - that is, which retain antigenicity or even fluorescence after the protocol is applied? It may be useful to add different epitope tags to the knock-in cassettes for this purpose.

mSG and mSc3 retain fluorescence after fixing with formaldehyde. We have not tested mTagBFP2 fluorescence in fixed worms. We agree that adding different epitope tags would be useful.

The paper is fine as it stands. The experiments above could add value to it and future-proof it, but are not essential. If the experiments are not attempted, the authors could refer to the points above in the discussion.

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