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black women central to queer movement in cuba
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www.welcomehps.com www.welcomehps.com
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(like hurting emails when messing with ledgers, etc.)
I don't know that I quite understand what this means.
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litgloss.buffalo.edu litgloss.buffalo.edu
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café
yadoorrrrrrrr :)
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new.oxfraud.com new.oxfraud.com
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itc
sp
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www.welcomehps.com www.welcomehps.com
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They are thinking and talking about the service we deliver with joy and positively with everyone they interact with and they are as excited as they can possibly get about real estate.
We should adjust this, it could be more concise & punchy. Maybe: "They proudly share their positive experience with our service and their excitement about real estate with others."
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Taking something that they viewed as a poorly performing stress and distraction and turning it into a joy that produces great returns year after year. Primarily being a firm they believe will always have their best interests at core.
We should rework this to something closer to: "Taking the complexity out of property ownership and transforming it into a smooth, rewarding experience that produces consistent returns year after year. All while knowing their best interests remain at the center of everything we do."
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ipfs.io ipfs.io
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💻.asus.🧊.♖-05xy k51qzi5uqu5djd3o0ovsrj50zh66awinzu4cw6bgc9heh0gtuzhu6zsl2z05xy
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IPFS infracons (InfraStructure Constellations)
infracons
Infrastructure Constellations
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www.americanyawp.com www.americanyawp.com
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e now have two great plants and many lesser works devoted to the production of atomic power. Employment during peak construction numbered 125,000 and over 65,000 individuals are even now engaged in operating the plants. Many have worked there for two and a half years. Few know what they have been producing. They see great quantities of material going in and they see nothing coming out of these plants, for the physical size of the explosive charge is exceedingly small. We have spent two billion dollars on the greatest scientific gamble in history — and won. But the greatest marvel is not the size of the enterprise, its secrecy, nor its cost, but the achievement of scientific brains in putting together infinitely complex pieces of knowledge held by
YOOOO
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mb was begun. With American and British scientists working together we entered the race of discovery against the Germans. The United States had available the large number of scientists of distinction in the many needed areas of knowledge. It had the tremendous industrial and financial resources necessary for the project and they could be devoted to it without undue impairment of other vital war work. In the United States the laboratory work and the production plants, on which a substantial start had already been made, would be out of reach of enemy bombing, while at that time Britain was exposed to constant air attack and was still threatened with the possibility of invasion. For these reasons Prime Minister Churchill and President Roosevelt agreed that
WhAT THE SIGMA
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re 1939, it was the accepted belief of scientists that it was theoretically possible to release atomic energy. But no one knew any practical method of doing it. By 1942, however, we knew that the Germans were working feverishly to find a way to add atomic energy to the other engines of war with which they hoped to enslave the world. But they failed. We may be grateful to Providence that the Germans got the V-1’s and V-2’s late and in limited quantities and even more grateful that they did not get the atomic b
6767676767676767
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Sixteen hours ago an American airplane dropped one bomb on Hiroshima and destroyed its usefulness to the enemy. That bomb had more power than 20,000 tons of TNT. It had more than two thousand times the blast power of the British “Grand Slam” which is the largest bomb ever yet used in the history of warfare. The Japanese began the war from the air at Pearl Harbor. They have been repaid many fold. And the end is not yet. With this bomb we have now added a new and revolutionary increase in destruction to supplement the growing power of our armed forces. In their present form these bombs are now in production and even more powerful forms are in development. It is an atomic bomb. It is a harnessing of the basic power of the universe. The force from which the s
CHEESE
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Successfully published under the key:
💻.asus.🧊.♖-05xy http://webui.ipfs.io.ipns.localhost:8080/#/files/💻/asus/🧊)
k51qzi5uqu5djd3o0ovsrj50zh66awinzu4cw6bgc9heh0gtuzhu6zsl2z05xy
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Local file Local file
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Als Zarathustra diese Worte gehört hatte, grüsste er den Heiligen undsprach: "Was hätte ich euch zu geben! Aber lasst mich schnell davon,dass ich euch Nichts nehme!
doesnt want to pop the holy guys bubble
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www.opensourceshakespeare.org www.opensourceshakespeare.org
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Romeo. Ah, Juliet, if the measure of thy joy Be heap'd like mine and that thy skill be more To blazon it, then sweeten with thy breath 1485This neighbour air, and let rich music's tongue Unfold the imagined happiness that both Receive in either by this dear encounter
Romeo says that if Juliet is as happy as he is, she should express her feelings and show how joyful their meeting makes them.
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Juliet. The clock struck nine when I did send the nurse; 1375In half an hour she promised to return. Perchance she cannot meet him: that's not so. O, she is lame! love's heralds should be thoughts, Which ten times faster glide than the sun's beams, Driving back shadows over louring hills: 1380Therefore do nimble-pinion'd doves draw love, And therefore hath the wind-swift Cupid wings. Now is the sun upon the highmost hill Of this day's journey, and from nine till twelve Is three long hours, yet she is not come. 1385Had she affections and warm youthful blood, She would be as swift in motion as a ball; My words would bandy her to my sweet love, And his to me: But old folks, many feign as they were dead; 1390Unwieldy, slow, heavy and pale as lead. O God, she comes! [Enter Nurse and PETER] O honey nurse, what news? Hast thou met with him? Send thy man away. 1395 Nurse. Peter, stay at the gate
The Nurse asks where she can find Romeo. Romeo jokingly replies that “young Romeo” will be older by the time she finds him and says he is the youngest Romeo, showing his playful and witty humor.
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Nurse. By my troth, it is well said; 'for himself to mar,' quoth a'? Gentlemen, can any of you tell me where I may find the young Romeo? Romeo. I can tell you; but young Romeo will be older when you have found him than he was when you sought him: 1275I am the youngest of that name, for fault of a wors
The Nurse asks where she can find Romeo. Romeo jokingly replies that “young Romeo” will be older by the time she finds him and says he is the youngest Romeo, showing his playful and witty humor.
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riar Laurence. The grey-eyed morn smiles on the frowning night, Chequering the eastern clouds with streaks of light, 1060And flecked darkness like a drunkard reels From forth day's path and Titan's fiery wheels: Now, ere the sun advance his burning eye, The day to cheer and night's dank dew to dry, I must up-fill this osier cage of ours 1065With baleful weeds and precious-juiced flowers. The earth that's nature's mother is her tomb; What is her burying grave that is her womb, And from her womb children of divers kind We sucking on her natural bosom find, 1070Many for many virtues excellent, None but for some and yet all different. O, mickle is the powerful grace that lies In herbs, plants, stones, and their true qualities: For nought so vile that on the earth doth live 1075But to the earth some special good doth give, Nor aught so good but strain'd from that fair use Revolts from true birth, stumbling on abuse: Virtue itself turns vice, being misapplied; And vice sometimes by action dignified. 1080Within the infant rind of this small flower Poison hath residence and medicine power: For this, being smelt, with that part cheers each part; Being tasted, slays all senses with the heart. Two such opposed kings encamp them still 1085In man as well as herbs, grace and rude will; And where the worser is predominant, Full soon the canker death eats up that plant.
Friar Laurence explains that nature has both good and bad qualities. Plants can heal or poison depending on how they are used. He compares this to humans, saying people also have both good and evil inside them.
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Juliet. Well, do not swear: although I joy in thee, I have no joy of this contract to-night: It is too rash, too unadvised, too sudden; Too like the lightning, which doth cease to be 970Ere one can say 'It lightens.' Sweet, good night! This bud of love, by summer's ripening breath, May prove a beauteous flower when next we meet. Good night, good night! as sweet repose and rest Come to thy heart as that within my breast!
Juliet loves Romeo but thinks their relationship is moving too fast. She wants their love to grow naturally and become stronger over time instead of rushing into promises.
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Mercutio. This cannot anger him: 'twould anger him To raise a spirit in his mistress' circle Of some strange nature, letting it there stand Till she had laid it and conjured it down; 825That were some spite: my invocation Is fair and honest, and in his mistress' name I conjure only but to raise up him
Here Mercutio jokes that he is not doing anything mean. He is just calling Romeo out by mentioning his girlfriend so Romeo will appear.
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www.biorxiv.org www.biorxiv.org
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The majority of conditions were evaluated through liquid cultures in microplate growth assays
In future work, it would be useful to collect brightfield/DIC microscopy data for these strains to examine the ratio of spherical to filamentous cells in these diverse environmental conditions.
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Of the 126 Y. lipolytica strains analyzed, 67 were newly sequenced in this study.
This is an invaluable expansion of genetic information! I think it would be neat to highlight the 67 newly sequenced strains in Figure 1 to emphasize your contributions.
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Eur2/Dairy strains
It's interesting to see that one of these grows relatively well in the presence of cycloheximide. It might be neat to dig into this strain more with additional phenotypic characterization and exploration of what's conferring this fitness.
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On a standardized test, there is only one right answer. Every other answer is wrong. But educators know when students are engaged in authentic and meaningful tasks, they can arrive at answers that are not entirely wrong or entirely right.
This is real teaching. we should be raising and educating students to think outside the box and to figure things out on their own. they should be independent, creative and should be able to stand up for themselves. There is never just 1 answer or 1 way to get to an answer and we should be allowing our students to explore that and let them think on their own.
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“Standardized tests don’t allow choice because it’s one-size-fits-all. Students may have the knowledge, but may not be able to show what they know and understand on the test. They can demonstrate that in PBA.”
I feel that this is 1 of the biggest issues with our school system is that it is used as a 1 size fits all system but that is not how our children learn. They are all different and learn in different ways and that is how we as educators should be teaching.
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“PBA allows students more choice in how they can show what hey’ve learned, and it allows differentiated instruction for different learning styles,”
This can help- students of all abilities learn the same contexts in the same environment. Being able to change things so your students can understand is what teaching is all about. It Should not be a 1 size fits all.
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This system of learning and assessment allows students to demonstrate knowledge and skill through critical-thinking, problem-solving, collaboration, and the application of knowledge to real-world situations. In other words, it helps students prepare for college, career, and life.
This is what we as a school system should be doing with our students. this will tell us what they know and give a better perspective of what our students need to learn and want to learn to make them successful students and in real-life.
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Standardized Testing is Still Failing Students Educators have long known that standardized tests are an inaccurate and unfair measure of student progress. There's a better way to assess students. By: Cindy Long, Senior Writer Published: March 30, 2023 Share Key Takeaways Standardized tests don’t accurately measure student learning and growth. Unlike standardized tests, performance-based assessment allows students to choose how they show learning. Performance-based assessment is equitable, accurate, and engaging for students and teachers. Break out your No. 2 pencil and answer this multiple choice question: How do standardized tests measure student learning? A. In a single snapshot. B. With biased test questions. C. Without determining learning growth. D. All of the above. If you didn’t answer “all of the above,” then: A. You haven’t been paying attention, or B. You work for a testing software company. Most of us know that standardized tests are inaccurate, inequitable, and often ineffective at gauging what students actually know. The good news is, there’s a better way: Performance-based assessment provides an essential piece of the puzzle in measuring student growth. What is Performance-Based Assessment (PBA)? This system of learning and assessment allows students to demonstrate knowledge and skill through critical-thinking, problem-solving, collaboration, and the application of knowledge to real-world situations. In other words, it helps students prepare for college, career, and life. PBA also allows educators to create more engaging instruction and address learning gaps by observing over time. And it helps them gather well-rounded information to better support their students’ success—a far cry from the “drill and kill” of state and federal standardized tests. PBA can mean asking students to compose a few sentences in an open-ended short response; develop a thorough analysis in an essay; conduct a laboratory investigation; curate a portfolio of student work; or complete an original research paper. Younger students may design experiments, write poems, or create art that demonstrate concepts. “PBA allows students more choice in how they can show what hey’ve learned, and it allows differentiated instruction for different learning styles,” says Molly Malinowski, a first-grade teacher at Lynch Elementary School, in the Winchester school district, in Massachusetts. “Standardized tests don’t allow choice because it’s one-size-fits-all. Students may have the knowledge, but may not be able to show what they know and understand on the test. They can demonstrate that in PBA.” “Performance-based assessment allows students more choice in how they can show what they’ve learned," says first-grade teacher Molly Malinowski. Built-in Differentiation One of Malinowski’s favorite math assessments focuses on addition, using numbers from 0 through 20. She introduces the concept and, with inquiry-based instruction, presents lessons and talks about strategies. As students pose questions or problems, the process ignites their curiosity. At the end of the unit, they have an “addition celebration.” She starts by building fluency and then asks students to share their problem-solving strategies with the class. “The best part is that they get to show their learning in a lot of different ways,” Malinowski says. “For this math standard, they make a video, a poster, a voice recording, a mini-play, or a piece of writing. Students have a voice in how they demonstrate their learning.” PBA allows students to demonstrate knowledge and skill through critical-thinking, problem-solving, collaboration, and the application of knowledge to real-world situations. In other words, it helps students prepare for college, career, and life. And when they share with the class, that helps reinforces everyone’s learning, she explains. None of this is possible in an individual test. “With this kind of instruction and assessment, we can … offer targeted support,” she says. “Some students will want to create their own piece of work, while others need more scaffolding, so I can really see who is learning what.” Each academic area in her school, from math to language arts to science and social studies, has a PBA. “We’ve been encouraged to take time to develop PBAs for our grade level, developing and tweaking them, and trying them out and making edits as we go,” she adds. Sequences, Not Snapshots Malinowski teaches in one of eight public school districts participating in the Massachusetts Consortium for Innovative Education Assessment (MCIEA). MCIEA is a partnership between these school districts and their local teachers unions, who are working together to create a fair and effective accountability system, offering a more dynamic picture of student quality and learning than a single standardized test. “The first objective of MCIEA is to measure student learning in a way that relies on teacher-created, classroom-embedded, performance assessments rather than externally created standardized assessments,” says MCIEA co-founder Jack Schneider. “The second objective is to measure school quality in a way that is more holistic, valid, and democratic than standardized tests.” In a science and sound assessment, Molly Malinowski’s students use what they learned to create instruments from recycled materials. Credit: Courtesy of Molly Malinowski The consortium’s framework goes beyond test scores and graduation and absentee rates, instead focusing on multiple measures of student engagement and achievement, as well as school environment. “It’s a more equitable system that doesn’t punish marginalized students,” Schneider explains. The current data used to measure student success, adds Schneider, closely correlates to race, income, and family educational attainment. It really only tells us about advantage and disadvantage outside school, not what schools are actually doing. “We want to capture all of the things that show student learning and achievement, not just this tortuously narrow vision that is embedded in the current system,” he says. “Where in the data is student engagement, their sense of belonging, performing arts, or development of civic competencies?” he asks. “There are massive gaps. So many of the current variables are just demographics in disguise.” On a standardized test, there is only one right answer. Every other answer is wrong. But educators know when students are engaged in authentic and meaningful tasks, they can arrive at answers that are not entirely wrong or entirely right. “We’d never give someone a standardized test to see if they can fly an airplane,” Schneider says. “PBA can show us much more effectively what a student knows that actually reflects the complexity of knowing and doing something.” Leveling the Playing the Field “PBA allows students to ask more questions and bounce ideas around, which reduces anxiety without reducing rigor,” says Alissa Holland. Credit: Jason Grow Alissa Holland is an instructional coach in the Milford Public Schools district, in Massachusetts, one of the districts participating in the MCIEA. “Standardized tests create test anxiety and some kids even have test phobia because they have just this one chance at getting it right,” says Holland, who works at Stacy Middle School. “PBA allows students to ask more questions and bounce ideas around, which reduces anxiety without reducing rigor." PBA also removes bias and creates more equity. For example, Holland recalls a state standardized test question about decomposition for eighth-grade science: “The question asked about grass clippings after mowing the lawn, and students got hung up on ‘grass clippings,’” she says. “Some had no idea what they were because they either lived in apartments and had no lawns, or they had lawns but didn’t mow them because they had landscapers.” A PBA on decomposition, on the other hand, would allow students to show their learning by demonstrating it with something they’re familiar with—grass clippings, an apple core, or leaves in the park—in a diagram, an essay or poem, or artwork. Students can show much more of their knowledge over time, in a form they choose, rather than on one day, on one test question, where only one answer is right, Holland explains. “Working on a PBA shows growth while inspiring a growth mindset,” Holland says. Her colleague Dan Cote, a social studies teacher in the same district, agrees. Nobody likes to regurgitate everything they know on a single test, he says. “The PBA process acknowledges that learning happens in different stages, where we can give feedback and build skills during the assessment,” Cote says. “It also increases engagement because students walk in the shoes of a geographer or historian, with tasks that mimic real world activities.” In Dan Cote’s social studies class, students demonstrate learning by studying artifacts like real-world archaeologists and explaining how they would lead an ancient civilization. Credit: Jason Grow Stronger Relationships with Students Standards and rubrics don’t always call for collaboration, and there’s certainly no teamwork on a test, but in PBA, students often work in groups that build critical social skills. When Cote’s students learn about earlier civilizations, they form teams of four and decide together what time period and landscape their civilization would inhabit. “They have tough decisions to make and problems to solve, like laws for farmers, how to respond to a natural disaster, what they should invest in as a civilization,” Cote explains. “Then each student writes their version of what happened, like a historian would—which demonstrates how easily bias occurs when the students read the other students’ varying versions of the same events.” Then the students create artifacts from their civilizations, and their classmates try to guess which civilization each student inhabited. At the end of every PBA, Cote debriefs with the class. “Students always say that working together was the best part,” he says. That’s the best part for the teachers, too, because it helps them build stronger relationships with students. “We gain so much more when we can hear their thoughts,” Cote says. “It’s not about a gotcha on a test score.” References See More See Less In this special NEA Today series, we examine the current state of student assessment, what's not working, and propose better ways of equitably and effectively supporting student learning. { let counter = 0; const id = 'div-gpt-ad-1582153075652-0' /** * Before calling googletag.display(), make sure that: * * - googletag has been defined and is ready * - the div we are calling can be found by the dom * */ const checkForPubAdsAndDiv = setInterval(function() { if (window.googletag && googletag.apiReady) { // Found everything. Commenting out debug in case we need it again. // console.dir('-----') // console.dir('adding to cmd: ' + id) // console.dir('checks: ' + counter) // console.dir('googletag.pubadsReady: ' + googletag.pubadsReady) // console.dir('googletag.pubads(): ' + googletag.pubads()) // console.dir('-----') googletag.cmd.push(function() { googletag.display('div-gpt-ad-1582153075652-0'); }); clearTimeout(checkForPubAdsAndDiv) } else { // Still waiting. counter++ if (counter === 120) { // About 30 seconds. // Commenting out debug in case we need it again. // console.dir('-----') // console.dir('gave up waiting on ' + id) // console.dir('window.googletag: ' + window.googletag) // console.dir('googletag.apiReady: ' + googletag.apiReady) // console.dir('div is found: ' + document.getElementById(id)) // console.dir('googletag.pubadsReady: ' + googletag.pubadsReady) // console.dir('googletag.pubads(): ' + googletag.pubads()) // console.dir('-----') clearTimeout(checkForPubAdsAndDiv) } } }, 250) } Get more from We're here to help you succeed in your career, advocate for public school students, and stay up to date on the latest education news. Sign up to stay informed. NEW nea.org email signup Contact Information First Name Last Name Zip Code Email Opt in to email updates from NEA (Optional) Your donation will be securely processed. Great public schools for every student
I don't feel that the standardized testing is beneficial for our students. We are teaching are students to take tests and not learn information. I have seen schools who spend the months prior to the testing working on teaching the kids how to take this test and what they need to do.
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drive.google.com drive.google.com
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ht distort the pheno
Machines are not neutral either. Factors such as camera exposure time, sensitivity, and recording methods also involve particular choices and positions.
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le skill of the virtuoso arti
Although the evaluation of a craftsman’s skill cannot be expressed with numbers in the same way as in science, there are still standards. For instance, in a workshop, an experienced craftsman teaches apprentices how smooth the stone should be polished and when the carving should stop. These standards are widely recognized within the craft community. In this sense, I wonder whether such shared consensus could also be considered a form of objectivity.
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n, rather than the assertion of unassailableauthorit
Objectivity is sometimes used to limit and supervise authority.
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menotime-playbook.timelessbiotech.com menotime-playbook.timelessbiotech.com
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Timeless Biotech is a small, focused company. We operate with minimal hierarchy and clear ownership of key areas. This page gives you an overview of who does what.
test
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www.biorxiv.org www.biorxiv.org
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These numbers are in the same range as our own
I'm curious how many of your higher confidence dynamic proteins overlap with dynamic proteins identified in previous studies, and if there's any enrichment of proteins belonging to specific clusters in Figure 8.
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We anticipate this dataset will be an important resource for cell cycle research in budding yeast.
This is a very valuable study and I'm excited to explore these data when they're publicly available!
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uj-wellbeing-workshop.netlify.app uj-wellbeing-workshop.netlify.app
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Each scale point represents an equal welfare increment. If violated, summing is invalid and interventions targeting different baselines become incomparable.
David Reinstein --- personally, this is the one I find least plauslible and most important.
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nterpersonal Comparability LSA = 7 ≈ LSB = 7 implies UA ≈ UB When two people report the same score, they experience similar welfare. Scale-use heterogeneity violates this assumption.
I don't think this one is necessary if we can (instead) assume that differences are equivalent. For example, if we assume that person A is actually experiencing higher welfare at all levels of reported score, but the differences between the scores are comparable, then compared to interventions for measured differences in well-being, that shouldn't matter.
I think it could also still be reliable if the distribution between the two populations is the same, even though we don't have specific inter-person comparability between any two compared individuals.
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equires four implicit assumptions
Give a linked source and citation for this.
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1 WELLBY = 1-point increase on a 0-10 life satisfaction scale × 1 person × 1 year W = Σi Σt LSit
Those are not clearly defined here, nor the indexing
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bafybeif26ootd53sc5vd2gctudzn7odohwsug54lm26ojfjzt743knxotq.ipfs.dweb.link bafybeif26ootd53sc5vd2gctudzn7odohwsug54lm26ojfjzt743knxotq.ipfs.dweb.link
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nmoer.pressbooks.pub nmoer.pressbooks.pub
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Each Works Cited entry has 9 components. You may not use each component in the reference; however, they all form a function to help the reader find the source you have cited. Note the punctuation after each element: Author. Title of Source. Title of Container, Other Contributors, Version, Number, Publisher, Publication date, Location.
format for work cited entry
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When citing electronic sources (such as articles from websites and databases), keep in mind that MLA, like all other style guides, was designed for books and journals (the paper versions!) Sometimes, making the entries for electronic sources feels like you are putting a square peg in a round hole. And, in some ways, you are. Many students wonder, why can’t I just link to the electronic source in the paper? Why Not Just Use Hyperlinks to Credit Sources? Hyperlinks are very useful for linking to information that will be read immediately. We all use hyperlinks in emails to link to videos, articles, and recipes. These are good uses of hyperlinks because, most likely, the information will still be there. And, you are probably linking to information that is free and available to the public. However, hyperlinks are not very useful for academic papers. Here are some reasons: Links change: The internet changes every day. Websites add and remove articles, on-line magazines and newspapers change their links. If there is only a link to a source and if that link changes, then the reader cannot find the source. Inaccessible Databases: Some of the information you will use will be from CNM databases. The readers of your article may not have access to the same database; therefore, a link is not sufficient. The reader needs to know pertinent information, such as the author’s name, title, etc., to be able to find the source.
Hyperlinks aren't always the best
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Giving credit where credit is due enhances your own credibility.
credibility works for all parties
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www.thesocietyofwilliamwallace.com www.thesocietyofwilliamwallace.com
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of his own accord,
The English believed he did it willingly, rather than getting exiled or betrayed.
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England exult ! thy Prince is peerless. Where thee he leadeth, follow fearless
Describes Wallace as fearless.
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William, wishing to save himself and his, hastened to flee by another road. But alas ! through the pride and burning envy of both, the noble Estates (communitas) of Scotland lay wretchedly overthrown throughout hill and dale, mountain and plain.
Portrays Wallace as selfish here, putting himself over his country and soldiers.
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(I have brought you to the ring, now dance if you can)"
This to me shows how defiant and confident Wallace was.
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Since this man was wandering and fugitive, he assembled about himself all those who were living in exile, and became something of a chief to them, and they grew into a large people.
The leader of many of the exiled in Scotland who wanted a revolution.
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Welsh William being made a noble, Straightway the Scots became ignoble. Treason and slaughter, arson and raid, By suff'ring and misery must be repaid.
The English saw that he wasn't from a noble family and immediately believed that Wallace was a criminal outlaw and needed to be stopped.
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an archer,
New information to me that he was seen as an archer, in Braveheart specifically and the other sources it isn't really touched upon. He also has a sword that is in a museum, so it is possible that he might have been a jack of all trades battle wise.
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turned towards Scotland; where at the Bridge of Stirling he was defeated by William Wallace, who, being at hand in order of battle (2), allowed so many of the English as he pleased to cross over the said bridge, and, at the right moment (3), attacked them, caused the bridge to be broken, where many of the English perished, with Hugh de Cressingham, the King's Treasurer; and it was said that the Scots caused him to be flayed, and in token of hatred made girths of his skin.
Based on this descriptor, he was clearly strategic and intelligent.
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William Wallace burnt all Northumberland
An invasion that hasn't been touched upon too much in my other sources. Shows in how vital Wallace was to Scotland, seen as the supreme leader by the English and he evidently WAS the English biggest fear.
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slew William de Heselrig at Lanark, the King's Sheriff of Clydesdale
Mentioned in the tertiary and secondary sources I found.
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Thomas Grey's Scalacronica
!
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readingandwritingyour.world readingandwritingyour.world
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Did you know that when you do a Google search you might get different results than the person sitting next to you? Google search results are heavily influenced by algorithms, keywords, advertisements, and even social biases.
excuse me?!?! how did I not know this?
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Brainstorm your various search terms
this is something so simple yet not something i have thought to do in the past with papers for other courses
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Quotation Marks – searches for the exact phrase
I didn't know you could do that...
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After reading “Why Historical Thinking is NOT about History,” use evidence from the article to discuss why it is important to carefully evaluate the credibility of a source. What could be some consequences of spreading misinformation?
It is important to carefully evaluate the credibility of a source because of the amount of misinformation out there. If said misinformation is spread, it can lead to several consequences, including people developing incorrect beliefs about historical events, reinforcing stereotypes, and spreading confusion about important topics. Overall, once misinformation spreads widely, it can be difficult to correct it because people will continue to believe and share it.
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Concept 1: Concept 2: Concept 3:
- How do teachers offer support in times of mental crisis?
- What do parents do in times of mental crisis?
- Are the students willing to reach out and get help?
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Therefore, we can build on your prior knowledge and add to your schema of research databases, search terms, and evaluating the credibility of sources.
Fire.
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only reality you know is digital
interesting
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www.americanyawp.com www.americanyawp.com
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What we mean by liberty is civil liberty, or liberty under law; and this means the guarantees of law that a man shall not be interfered with while using his own powers for his own welfare.
Men are not really free
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readingandwritingyour.world readingandwritingyour.world
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Starting with one of your sources, use notecards or sticky notes to write out ONE idea or major claim from your summary.
This doesn't seem organized even though it is a tool to organize ideas. This is hard to visual and must be done to see the true value.
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!!!
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menotime-playbook.timelessbiotech.com menotime-playbook.timelessbiotech.com
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If you click the button, you can switch between dark and light mode.
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nmoer.pressbooks.pub nmoer.pressbooks.pub
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Citing Indirect Sources If another source is cited within your source, it is called an “indirect source. When citing this, use “qtd. in” to indicate the source you actually consulted.
indirect sources
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If you need to cite multiple publications by different authors in the same sentence, you should list the multiple sources in alphabetical order by author and use a semicolon to separate them.
Sourcing multiple publications by different authors
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If you are using a website or other electronic source that does not have page numbers, use only the author’s name or title of the source in the in-text citation. Here are examples: If the source has page numbers: (Pauling 113). If the source does not have page numbers: (Pauling). If the source has page numbers: (“Bilingual Minds” 113). If the source does not have page numbers: (“Bilingual Minds”).
Sources with no page numbers
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When writing, make sure you inform the reader when you are using information from a source, whether that be direct quotations or paraphrasing information. And, it should be equally clear when you are expressing your own ideas.
Inform the reader when you're sourcing material
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If you follow MLA style and indicate your source both in your essay and in the Works Cited section, you will prevent the possibility of plagiarism
Plagiarism isn't cool
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In-text citations are used throughout your paper to credit your sources of information. In MLA style, the in-text citation in the body of the essay links to the Works Cited page at the en
In-Text Citations are important to source your content.
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readingandwritingyour.world readingandwritingyour.world
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as long as you have an Internet connection.
love this
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flexible mindset as a writer to experiment with certain techniques, rhetorical appeals, and ways of writing that you have carefully observed and annotated when you previously read.
continue to remind self of this even after this course. This will come in handy in future work projects and classes.
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, what is the most important chapter or section from this textbook, and why?
One of the most important sections of the textbook is the first chapter, which introduces all the processes. When I first started reading this OER, I wasn't sure what I was to expect, but all of these strategies for active reading have helped me actually understand and remember the text.
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applications of the same “recursive” processes.
I think it's important to reiterate these processes, as it helps us memorize them.
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UW-Madison
Test
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dl2.cuni.cz dl2.cuni.cz
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Nature – sometimes sears a Sapling
I think that the opening line of the poem is extremely interesting, as Dickinson starts off with a contradiction. Nature, who is personified, "sears", performs an act of violence in contrast to nurturing. It is as if Dickinson wants the reader to feel this force of violence, a Nature that doesn't protect her youngs, but she sometimes can harm them. This choice feels a little antithetical to the romanticized version of nature that the romantics held. It also suggests that harm and destrution might also be part of nature, of how things are.
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Mistake the Outside for the in
I think that this line feels very central of the poem's theme. Dickinson tries to convey the idea that us humans tend to misinterpret nature, or that our understanding and perception might tend to feel superficial, without really grapsing the depth what nature offers.
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We – who have the Souls –Die oftener – Not so vitally –
I think that this line encaptulates beautifully the general theme of the poem and Dickinson's main idea, which is that consciousness (having a soul) make us humans more volnurable at the end of the day, than nature. The line almost feels like a paradox, but I think that what Dickinson wants to convey with the closing line is that human life can endure more suffering.
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nmoer.pressbooks.pub nmoer.pressbooks.pub
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find an individual who knows about the assignment, your intended audience, and the purpose of the essay. This person is likely one of your peers
They can help your writing with grammar issues or help the writing to sum it up.
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he writer might decide that rearranging paragraphs will provide clarity and support for their argumen
people shouldnt be affraid to change their righting if its what can make their argument stronger.
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www.chronicle.com www.chronicle.com
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But the real Sword had nothing to do with this.
HOW is this legal?!
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unjournal.github.io unjournal.github.io
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html`<div style="background: #f8f9fa; padding: 1rem 1.25rem; border-left: 4px solid #3498db; margin-bottom: 1.5rem; font-size: 0.95em; line-height: 1.6;"> <strong>What these numbers represent:</strong> Simulated <strong>production cost per kilogram of cultured chicken</strong> (wet weight, unprocessed) in <strong>${targetYear}</strong>, based on ${stats.n.toLocaleString()} Monte Carlo simulations. This is the cost to produce meat in a bioreactor — not retail price, which would include processing, distribution, and margins. <br><br> <strong>Why it matters:</strong> If production costs reach <strong>~$10/kg</strong> (comparable to conventional chicken), cultured meat could compete at scale. If costs remain <strong>>$50/kg</strong>, the technology may remain niche. These thresholds inform whether animal welfare interventions should prioritize supporting this industry. </div>` RuntimeError: targetYear is not definedOJS Runtime Error (line 804, column 163) targetYear is not defined
How Can we fix this 'runtime error'.I think it was working before. The "target year" should be the "projection year" in the sidebar model parameters. The default year was 2036. #implement
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readingandwritingyour.world readingandwritingyour.world
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our goal is to make the conversation interesting enough that readers will want to get involved in it
I need to have confidence in this that someone else may be interested in the same things as me or that they have questioned the same things as me. Can I do this?
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Freire created “culture circles” which based the learning and practice of reading and writing on the issues that his students faced every day of their lives.
Love this so much! I wish I could see something like this now in my community to help the under represented people
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Freire’s focus in education was primarily with adult learners in Brazil, where masses of poor and under-represented workers were denied voting and other political rights because they were never taught to read and write
Keeping people uneducated in order to control that masses is such a common theme in so many different forms of media I have been exposed to recently. Even watching whats happening in the news today. WE MUST STRIVE TO BETTER OURSELVES IN ORDER TO HELP OTHERS AND THAT INCLUDES BECOMING MORE EDUCATED
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Meaningful research involves using the reading and writing strategies we’ve outlined earlier to investigate your own topics that can help you address issues that you and others like you experience, or even think about everyday.
How can I connect the topic to more than just myself and make it meaningful for my own curiosities as well as building the community around me.
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n other words, consider your audience, and what connects you and your curiosity, interests, and experience to a larger social issue or “motive” for change.
That makes a lot of sense.
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which means it will change through your research, reading and writing process as you gain new perspective from many sources—hence it is “working” or a “work in progress.”
Heck yeah!
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4. Draft your Inquiry Question using “How,” “Why,” “In what ways,” or “To what extent,” in a way that elicits a conversation in which you will be interested in participating.
To what extent are the schools willing to go to ensure safety during a mental crisis?
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3. Once you have your issue, consider your stance. What do you think about this issue? What is your initial opinion? This is your working thesis.
This issue is extremely important. It's still a struggle in schools today. There should be more support, and students should feel comfortable enough to share what they need.
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2. Once you have a Topic, narrow that down to an issue. An issue is anything that can be debated from multiple sides. For example, starting with the topic of Capitalism, and narrowing that down to the issue of homelessness in San Francisco.
When teachers and parents don't understand how to help a child during a mental health crisis, it can lead to a disastrous situation.
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Pre-writing Activity: Draft your Inquiry Question1.
What kind of support do teachers offer in a mental health crisis?
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1. What are some personal experiences you have that relate to larger social issues? 2. Why are these issues important to you? 3. Choose one of these issues to discuss: Why or how would your research of this issue represent an example of “intrinsic motivation” for you?
A personal experience I have that connects to a larger social issue is the mental health issues many people experienced after the COVID-19 pandemic. Many things changed in everyday life, especially for me. School moved online, and we were isolated. My family and I struggled a lot during this time. I also noticed that many of my classmates struggled with motivation and stress. These experiences showed me that mental health became a bigger issue for many people during and after the pandemic.
This issue is a priority to me because mental health affects how people function in their daily lives. After everything that happened during the pandemic, people were still trying to adjust back to normal life. Some people didn’t always have the support they needed, and that made it harder for them to cope. I think it’s important that mental health is taken seriously and that people have access to support and resources. Even now, I still struggle with the aftereffects of the pandemic.
I would research this topic since I have seen how mental health challenges affected people around me. Learning more about the topic could also help me better understand how to support others and myself.
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because the issue is real to you and your “intrinsic motivation” to research the issue is authentic.
!
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underactuated.mit.edu underactuated.mit.edu
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for a solution.
Once we obtain $$P(t) = S^{-1}(t)$$ it seems like we would want to compute the LQR gain matrix $$K(t) = R^{-1} B^\top S(t) = R^{-1} B^\top P^{-1}(t)$$, but we know that $$P^{-1}(t_f)$$ does not exist. Is this OK considering that our control input does not actually matter at time $$t_f$$ (since we have already reached the solution?)
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Drake provides a FiniteHorizonLinearQuadraticRegulator method
The FiniteHorizonLinearQuadraticRegulatorResult (Drake) shows that the optimal controller is given instead by $$u^* = u_0(t) - K(t) \left(x-x_0(t)\right) - k_0(t).$$
What is $$k_0(t)$$ and is there a way to, for example, ensure $$k_0(t) = 0$$? It seems odd that if $$x-x_0(t)$$ that your controller would not just output $$u^* = u_0(t)$$.
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www.coloradocollege.edu www.coloradocollege.edu
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Equity & Power
Last Gen ed at CC
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idlewords.com idlewords.com
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Despite the lavish production values, there's a strange sameness to everything. You're always in the same brown war zone.
Modern games and websites may have impressive visuals and high production budgets, but they often feel repetitive and lack originality. For example, COD has changed very little over the years. My main point is that high sales drive a focus on impressive visuals rather than creative innovation.
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katinamagazine.org katinamagazine.org
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But far from focusing only on the large publishers covered by DEAL, we’ve deliberately extended our agreements to cover the majority of publishers important to our authors, from the largest to the smallest, thereby leveling the playing field of support for OA publishing and ensuring that funds are available wherever our authors choose to publish.
I don't see that the playing field is levelled - if that were truly the case, and author wishing to publish with JMIR Publications would have to pay the exact same amount (or nothing) than an author wanting to publish with Wiley, Springer or Elsevier. This is not the case. Can the author give more details on the procurement process for publishing services?
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By contrast, TAs provide authors with the opportunity and means to publish their articles open access within their natural environment and without additional administrative burden.
There is an underlying assumption in this statement that assumes that "established" journals are the journals published by legacy publishers and researchers do not want to publish with pure open access journals. As an example, JMIR Publications journals are fully open access for over a quarter of a century and are very established. Authors want to publish here. But Project DEAL made a deal with the 3 biggest publishers and assumes that that this is where they want to publish
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phase out all reading fees from TAs, either at the outset or gradually over the course of one or more agreement cycles. We are already seeing this strategy materializing in the negotiations of several first movers, such as the Swedish Bibsam consortium, which is now actively negotiating agreements for publishing as a service
I agree with this - reading and publishing fees need to be disentangled. But what Bibsam is also doing is to preferentially make publishing agreements with pure open access publishers, rather than focussing on so-called "transformative" publishers.
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It's no wonder that a significant portion of the library community has come to view TAs as a mechanism designed to entrench the position of for-profit publishers.
That's exactly what it is: TAs are a mechanism designed to entrench the position of legacy subscription publishers.
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Since their introduction, TAs have enabled countries, consortia, and libraries worldwide to rapidly transition publications by their researchers to OA.
This is a very shortsighted view. Please name a single publisher who has actually fully transformed as a result of transformative agreements. Economists clearly see that "research institutions seem to be 'trapped' in transformative agreements. Instead of being a bridge towards a fully Open Access world, academia is stuck in the hybrid system. This endows the legacy (non-Open Access) publishing houses with substantial market power. It raises entry barriers, lowers competition, and increases costs for libraries and universities." (https://arxiv.org/abs/2409.20224)
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TAs shifted the scholarly publishing landscape by merging subscriptions and OA payments into a unified framework under the control of libraries and library consortia.
The statement suggests that TAs “shifted the scholarly publishing landscape.” In practice, most TAs repackage existing subscription spending rather than fundamentally restructuring publishing economics by opening up the publishing market. Repacking existing subscription spending overlooks that existing open access publishers are not even on the radar screen of librarians. TAs merge payment streams administratively, but do not necessarily transform the underlying market structure or cost model. Libraries may administer the agreements, but market control largely remains with dominant publishers. By linking OA payments to historical subscriptions, TAs structurally favor publishers that already have large subscription portfolios, strong negotiating positions with consortia and established “big deal” relationships.
Publishers that were already fully open access, and therefore had no subscription base to convert, are excluded from these agreements. As a result, TAs often reward publishers that transitioned slowly (or not at all) while disadvantaging early adopters of OA.
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Comparison of OA Article Share and Revenue Share, 2023.
The gap in revenue between OA and subscriptions is the reason why legacy publishers want to maintain their subscriptions and why TAs will cement a hybrid model where OA journals are created as garbage cans for rejected papers from subscription titles. A true reform to 100% open access can only happen through copyright reforms or funder/institutional mandates which outlaw locking away research results behind paywalls.
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the rationale for TAs lies in acknowledging the need to reorganize institutional investments in scholarly journal publishing in order to directly confront and dismantle the traditional subscription business model.
If you want a true reform, you need to cancel subscription journals and redirect funds to open access without subsidies for those who resisted OA for the longest time. TAs are sustaining legacy publishers that "promise" to transition to open access while neglecting to support authors who wish to publish with publishers that have already made that transition. This is not supporting open access; it is cementing existing oligopolies and locking libraries into hybrid or “conditional” models (like S2O). More importantly, it undermines the viability of fully open access publishers that made the transition decades ago or were born open access. TAs are a trap (https://arxiv.org/abs/2409.20224).
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Instead of forcing a behavioral change in authors, negotiating open access publishing options in the journals they value and trust brings open access to them, minimizing friction and maximizing engagement.
The author seems to think that authors only published in full open access journals because of mandates? To be clear: Full open access journals are not part of transformative agreements, because there is nothing to transform. Hence, from a perspective of an author whose favorite journal or publisher is fully open access, transformative agreements are doing exactly that: Forcing a behavior change to publish with legacy publishers where APCs are covered as part of the TA. JMIR Publications journals are ranked #1 in their field and researchers have to find alternative funding to publish here.
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uj-wellbeing-workshop.netlify.app uj-wellbeing-workshop.netlify.app
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Add questions and comments directly to the collaborative notes above, or submit them via the beliefs elicitation form.
Remove 'or submit them via...' Note that the "beliefs elicitation form" is doing something else. #adjust #implement (adjust this on all pages).
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decision problems that funders face when comparing interventions measured in different units (WELLBYs vs DALYs)
It's not just about 'comparing interventions measured in different units' #adjust #implement
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How funders currently navigate WELLBY vs DALY in cost-effectiveness analysis
Not just 'WELLBY vs DALY' ... --> How funders consider wellbeing and metrics based on self-reports in considering and comparing interventions.
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readingandwritingyour.world readingandwritingyour.world
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an Annotated Bibliography for each of your sources
This seems to make the process a bit easier.
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readingandwritingyour.world readingandwritingyour.world
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Creating your Healthy Information Ecosystem
I've never structured it that way.
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readingandwritingyour.world readingandwritingyour.world
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By contributing to Wikipedia, you can use your knowledge and research skills to make a real-world difference.
That's cool
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Did you know that you can help improve Wikipedia?
I did not know that
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readingandwritingyour.world readingandwritingyour.world
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Openness
Can I put aside my own opinions to open myself up to new perspectives in order have a full understanding of content?
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Critical Information Literacy
So important especially no with the amount of "Fake News" and opinions floating around as facts. Am I actively reading and using outside information to confirm information? Am I sharing credible information?
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Curiosity, Engagement:
Am I actually relating this to things outside of the reading in order to connect and have a deeper understanding, giving the text more meaning?
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because it is based on real life and real motivations to create change or solve a problem
This type of writing feels much more productive since we are challenging an issue and trying to make a difference.
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a more meaningful research process
This is more likely to stick with the student rather than the former, and it will be good practice to engage in a community you care about since that is what a lot of careers focus on
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pressbooks.library.torontomu.ca pressbooks.library.torontomu.ca
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She busied herself with following the aerial creations of the poets; and in the majestic and wondrous scenes which surrounded our Swiss home —the sublime shapes of the mountains, the changes of the seasons, tempest and calm, the silence of winter, and the life and turbulence of our Alpine summers—she found ample scope for admiration and delight. While my companion contemplated with a serious and satisfied spirit the magnificent appearances of things, I delighted in investigating their causes.
artistic and scientific
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platypus1917.org platypus1917.org
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assuming the rule over others, he had deprivedhimself of those peers in whose company he could have beenfree.
Freedom is innately relational. If everyone around you is subjugated to you, you are not able to exercise your complete freedom.
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The difference between this ancient concept of equalityand our notion that men are born or created equal and becomeunequal by virtue of social and political, that is man-made,institutions can hardly be over-emphasized. The equality of th~Greek polis, its isonomy, was an attribute of the polis and notof men, who received their equality by virtue of citizenship,not by virtue of birth.
!!!
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Suchan event, as Augustine emphasized, had occurred once butwould never occur again until the end of time. Secular historyin the Christian view remained bound within the cycles of an-tiquity - empires would rise and fall as in the past - except thatChristians, in the possession of an everlasting life, could breakthrough this cycle of everlasting change and must look withindifference upon the spectacles it offered.
This ties into her concept of Natality, very fundamental integration of St. Augustine's history to her own philosophy. This demonstrates a similarity with her thought with scholastics and the western canon more broadly, specifically on her conception on the object of free will.
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www.stonybrook.edu www.stonybrook.edu
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Remaking the American Patient: How Madison Avenue and Modern Medicine Turned Patients into Consumers
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stacks.stanford.edu stacks.stanford.edu
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Knowledge will forever govern ignorance:And a people who mean to be their own Governors, mustarm themselves with the power which knowledge gives.
!!!!
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The real question iswhether that information, once found, should be believed.
There is a lot of misinformation on the internet.
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. The Internet hasobliterated authority. You need no one’s permission to createa website. You need no papers signed to put up a YouTubevideo. You need no one’s stamp of approval to post a pictureon Instagram. You can Tweet to your heart’s content—someof you are doing so this very moment.
So true.
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Where would Our Virginia, Past and Present find backingfor a claim rejected out of hand by every reputable Civil Warhistorian we could think of?
Interesting.
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docs.google.com docs.google.com
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Song Of Love
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docdrop.org docdrop.org
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We need more road work
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This seems expensive...is there a cheaper alternative?
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This is great! Would love to see a live view camera so we can know beach conditions before packing the car and hauling to family to the beach. Full Support!
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Fully support! This gives another great option that is close to the roundabout. Would be nice to walk with my drink after dinner as I head to the symphony.
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socialsci.libretexts.org socialsci.libretexts.org
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Before the invention of writing, people conveyed virtually all knowledge through some combination of showing and telling. Elders recited tribal histories to attentive audiences.
this is probably how so much meaning was lost through wrong interpretations of things
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www.biorxiv.org www.biorxiv.org
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eLife Assessment
This study provides an important, comprehensive, large-scale dataset on transcription factor binding in Pseudomonas aeruginosa, along with analyses of its regulatory network, key virulence and metabolic regulators, and a pangenomic examination of transcription factors. Utilizing large-scale ChIP-seq and multi-omics integration, the research convincingly supports the hierarchical regulatory structures and offers insights into virulence mechanisms. This dataset, made available through an online database, should be an invaluable resource to the research community studying P. aeruginosa, a key pathogen at risk for hospital infections and development of antibiotic resistance.
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Reviewer #1 (Public review):
Summary:
In this work, Huang et al. revealed the complex regulatory functions and transcription network of 172 unknown transcriptional factors (TFs) in Pseudomonas aeruginosa PAO1. They have built a global TF-DNA binding landscape and elucidated binding preferences and functional roles of these TFs. More specifically, the authors established a hierarchical regulatory network and identified ternary regulatory motifs, and co-association modules. Since P. aeruginosa is a well known pathogen, the authors thus identified key TFs associated with virulence pathways (e.g., quorum sensing [QS], motility, biofilm formation), which could be potential drug targets for future development. The authors also explored the TF conservation and functional evolution through pan-genome and phylogenetic analyses. For the easy searching by other researchers, the authors developed a publicly accessible database (PATF_Net) integrating ChIP-seq and HT-SELEX data.
Strengths:
(1) The authors performed ChIP-seq analysis of 172 TFs (nearly half of the 373 predicted TFs in P. aeruginosa) and identified 81,009 significant binding peaks, representing one of the largest TF-DNA interaction studies in the field. Also, The integration of HT-SELEX, pan-genome, and phylogenetic analyses provided multi-dimensional insights into TF conservation and function.
(2) The authors provided informative analytical Framework for presenting the TFs, where a hierarchical network model based on the "hierarchy index (h)" classified TFs into top, middle, and bottom levels. They identified 13 ternary regulatory motifs and co-association clusters, which deepened our understanding of complex regulatory interactions.
(3) The PATF_Net database provides TF-target network visualization and data-sharing capabilities, offering practical utility for researchers especially for the P. aeruginosa field.
Weaknesses:
(1) There is very limited experimental validation for this study. Although 24 virulence-related master regulators (e.g., PA0815 regulating motility, biofilm, and QS) were identified, functional validation (e.g., gene knockout or phenotypic assays) is lacking, leaving some conclusions reliant on bioinformatic predictions. Another approach for validation is checking the mutations of these TFs from clinical strains of P. aeruginosa, where chronically adapted isolates often gain mutations in virulence regulators.
(2) ChIP-seq in bacteria may suffer from low-abundance TF signals and off-target effects. The functional implications of non-promoter binding peaks (e.g., coding regions) were not discussed.
(3) PATF_Net currently supports basic queries but lacks advanced tools (e.g., dynamic network modeling or cross-species comparisons). User experience and accessibility remain under-evaluated. But this could be improved in the future.
Achievement of Aims and Support for Conclusions
(1) The authors successfully mapped global P. aeruginosa TF binding sites, constructed hierarchical networks and co-association modules, and identified virulence-related TFs, fulfilling the primary objectives. The database and pan-genome analysis provide foundational resources for future studies.
(2) The hierarchical model aligns with known virulence mechanisms (e.g., LasR and ExsA at the bottom level directly regulating virulence genes). Co-association findings (e.g., PA2417 and PA2718 co-regulating pqsH) resonate with prior studies, though experimental confirmation of synergy is needed.
Impact on the Field and Utility of Data/Methods
(1) This study fills critical gaps in TF functional annotation in P. aeruginosa, offering new insights into pathogenicity mechanisms (e.g., antibiotic resistance, host adaptation). The hierarchical and co-association frameworks are transferable to other pathogens, advancing comparative studies of bacterial regulatory networks.
(2) PATF_Net enables rapid exploration of TF-target interactions, accelerating candidate regulator discovery.
Comments on revisions:
The authors have done a good job of revising their manuscript. The manuscript is now more concise and logical for readers.
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Reviewer #3 (Public review):
Summary:
The authors utilized ChIP-seq on strains containing tagged transcription factor (TF)-overexpression plasmids to identify binding sites for 172 transcription factors in P. aeruginosa. High-quality binding site data provides a rich resource for understanding regulation in this critical pathogen. These TFs were selected to fill gaps in prior studies measuring TF binding sites in P. aeruginosa. The authors further perform a structured analysis of the resulting transcriptional regulatory network, focusing on regulators of virulence and metabolism, in addition to performing a pangenomic analysis of the TFs. The resulting dataset has been made available through an online database. While the implemented approach to determining functional TF binding sites has limitations, the resulting dataset still has substantial value to P. aeruginosa research.
Strengths:
The generated TF binding site database fills an important gap in regulatory data in the key pathogen P. aeruginosa. Key analyses of this dataset presented include an analysis of TF interactions and regulators of virulence and metabolism, which should provide important context for future studies into these processes. Experimental validation has been included in the revised version. The online database containing this data is well organized and easy to access. As a data resource, this work should be of significant value to the infectious disease community.
Weaknesses:
Drawbacks of the study, which have been mitigated in a revised version, include 1) challenges interpreting binding site data obtained from TF overexpression due to unknown activity state of the TFs on the measured conditions (discussed by the authors), and 2) remaining challenges in the practical utilization of the TRN topological analysis.
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Author response:
The following is the authors’ response to the previous reviews
Public Reviews:
Reviewer #1 (Public review):
Summary:
In this work, Huang et al. revealed the complex regulatory functions and transcription network of 172 unknown transcriptional factors (TFs) in Pseudomonas aeruginosa PAO1. They have built a global TF-DNA binding landscape and elucidated binding preferences and functional roles of these TFs. More specifically, the authors established a hierarchical regulatory network and identified ternary regulatory motifs, and co-association modules. Since P. aeruginosa is a well known pathogen, the authors thus identified key TFs associated with virulence pathways (e.g., quorum sensing [QS], motility, biofilm formation), which could be potential drug targets for future development. The authors also explored the TF conservation and functional evolution through pan-genome and phylogenetic analyses. For the easy searching by other researchers, the authors developed a publicly accessible database (PATF_Net) integrating ChIP-seq and HT-SELEX data.
Strengths:
(1) The authors performed ChIP-seq analysis of 172 TFs (nearly half of the 373 predicted TFs in P. aeruginosa) and identified 81,009 significant binding peaks, representing one of the largest TF-DNA interaction studies in the field. Also, The integration of HT-SELEX, pan-genome, and phylogenetic analyses provided multi-dimensional insights into TF conservation and function.
(2) The authors provided informative analytical Framework for presenting the TFs, where a hierarchical network model based on the "hierarchy index (h)" classified TFs into top, middle, and bottom levels. They identified 13 ternary regulatory motifs and co-association clusters, which deepened our understanding of complex regulatory interactions.
(3) The PATF_Net database provides TF-target network visualization and data-sharing capabilities, offering practical utility for researchers especially for the P. aeruginosa field.
Thank you for your positive feedback!
Weaknesses:
(1) There is very limited experimental validation for this study. Although 24 virulence-related master regulators (e.g., PA0815 regulating motility, biofilm, and QS) were identified, functional validation (e.g., gene knockout or phenotypic assays) is lacking, leaving some conclusions reliant on bioinformatic predictions. Another approach for validation is checking the mutations of these TFs from clinical strains of P. aeruginosa, where chronically adapted isolates often gain mutations in virulence regulators.
Thank you for this valuable suggestion. We have performed the EMSA experiment to validate the binding result and also constructed the mutants for further functional validation. The details can be found in Figure S5.
(2) ChIP-seq in bacteria may suffer from low-abundance TF signals and off-target effects. The functional implications of non-promoter binding peaks (e.g., coding regions) were not discussed.
Thank you for this insightful comment regarding ChIP-seq data quality and non-promoter binding events. While we acknowledge that completely eliminating all non-specific binding signals is technically challenging in bacterial ChIP-seq experiments, we implemented stringent quality control measures including replicates, negative controls, and FDR cutoffs to minimize false positives.
Although the coding binding peaks represent a smaller fraction of total binding events, they are functionally significant rather than mere technical artifacts. Our previous work systematically demonstrated that bacterial TFs can bind to coding sequences and regulate gene expression through multiple mechanisms, including modulating cryptic promoter activity and antisense RNA transcription, hindering transcriptional elongation, and influencing translational efficiency[1]. We have now expanded the Discussion section to address these regulatory mechanisms.
(3) PATF_Net currently supports basic queries but lacks advanced tools (e.g., dynamic network modeling or cross-species comparisons). User experience and accessibility remain underevaluated. But this could be improved in the future.
Thank you for this constructive feedback on PATF_Net. We acknowledge that more advanced features would further enhance the platform’s utility. To enhance the utility of PA_TFNet, we have implemented two new features: (1) a virulence pathway browser that allows users to explore TF binding across curated gene sets for key virulence pathways (quorum sensing, secretion systems, biofilm, motility, etc.), and (2) a target gene search function that enables rapid identification of all TFs regulating any gene of interest by locus tag query.
Achievement of Aims and Support for Conclusions
(1) The authors successfully mapped global P. aeruginosa TF binding sites, constructed hierarchical networks and co-association modules, and identified virulence-related TFs, fulfilling the primary objectives. The database and pan-genome analysis provide foundational resources for future studies.
(2) The hierarchical model aligns with known virulence mechanisms (e.g., LasR and ExsA at the bottom level directly regulating virulence genes). Co-association findings (e.g., PA2417 and PA2718 co-regulating pqsH) resonate with prior studies, though experimental confirmation of synergy is needed.
Thank you for your positive feedback! We have added experimental validation in the Results section.
Impact on the Field and Utility of Data/Methods
(1) This study fills critical gaps in TF functional annotation in P. aeruginosa, offering new insights into pathogenicity mechanisms (e.g., antibiotic resistance, host adaptation). The hierarchical and co-association frameworks are transferable to other pathogens, advancing comparative studies of bacterial regulatory networks.
(2) PATF_Net enables rapid exploration of TF-target interactions, accelerating candidate regulator discovery.
Thank you for your positive feedback!
Reviewer #3 (Public review):
Summary:
The authors utilized ChIP-seq on strains containing tagged transcription factor (TF)-overexpression plasmids to identify binding sites for 172 transcription factors in P. aeruginosa. High-quality binding site data provides a rich resource for understanding regulation in this critical pathogen. These TFs were selected to fill gaps in prior studies measuring TF binding sites in P. aeruginosa. The authors further perform a structured analysis of the resulting transcriptional regulatory network, focusing on regulators of virulence and metabolism, in addition to performing a pangenomic analysis of the TFs. The resulting dataset has been made available through an online database. While the implemented approach to determining functional TF binding sites has limitations, the resulting dataset still has substantial value to P. aeruginosa research.
Strengths:
The generated TF binding site database fills an important gap in regulatory data in the key pathogen P. aeruginosa. Key analyses of this dataset presented include an analysis of TF interactions and regulators of virulence and metabolism, which should provide important context for future studies into these processes. The online database containing this data is well organized and easy to access. As a data resource, this work should be of significant value to the infectious disease community.
Thank you for your positive feedback!
Weaknesses:
Drawbacks of the study include 1) challenges interpreting binding site data obtained from TF overexpression due to unknown activity state of the TFs on the measured conditions, 2) limited practical value of the presented TRN topological analysis, and 3) lack of independent experimental validation of the proposed master regulators of virulence and metabolism.
We thank the reviewer for summarizing these key concerns. We acknowledge the limitations raised regarding TF overexpression, TRN topological analysis interpretation, and experimental validation. We provide detailed point-by-point responses to each of these concerns in our replies to the specific comments below, where we explain our rationale, the measures taken to address these limitations, and our plans for improvement.
Recommendations for the authors:
Reviewer #1 (Recommendations for the authors):
Future Directions for the authors to consider for next steps:
(1) Key TFs (e.g., PA1380, PA5428) should be validated via gene knock out experiments, fluorescent reporter assays, or animal models to confirm roles in virulence pathways.
Thank you for this important suggestion. We agree that experimental validation is essential to confirm their regulatory roles and biological functions.
Firstly, we selected a subset of key TFs, including PA0167, PA1380, PA0815, and PA3094, and performed Electrophoretic Mobility Shift Assays (EMSA) experiments to validate their direct binding to target promoters. These results confirmed the ChIP-seq-identified interactions and are now included as Figure S5A-F.
We also constructed a clean deletion mutant of PA1380 and PA 3094 (ΔPA1380 and ΔPA3094) and their complementary strains (ΔPA1380/p and ΔPA3094/p). We then performed RT-qPCR analysis to validate their regulatory effects on key target genes. We found that PA1380 positively regulate the expression of cupB1 and cupB3 genes (Figure S5F). While the CupB cluster was known not be as important as CupA cluster in the biofilm information, so we did not find significant difference in biofilm formation between WT and ΔPA1380. Additionally, we found TF PA3094 also positively regulate lecA expression, which were shown in Figure S5G.
We agree that comprehensive functional validation, including animal model studies, would further strengthen the biological significance of these findings. Such experiments are currently underway in our laboratory and will be the subject of follow-up studies.
We have revised the Results section and Method section to include these validation experiments and their implications. Please see Figure S5 and Lines 283-300.
“To experimentally validate the regulatory interactions identified by ChIP-seq, we performed biochemical and genetic analyses on selected TFs. First, we conducted Electrophoretic Mobility Shift Assays (EMSA) for four TFs, including PA0167, PA0815, PA1380, and PA3094, using DNA fragments containing their predicted binding sites from target gene promoters. These TFs showed specific binding to their cognate DNA sequences (Figure S5A-D), confirming the direct binding of the ChIP-seq-identified interactions.
To further validate the functional regulatory roles of these TFs, we constructed clean deletion mutants of PA1380 and PA3094 (ΔPA1380 and ΔPA3094) along with their complemented strains (ΔPA1380/p and ΔPA3094/p). RT-qPCR analysis revealed that PA1380 positively regulates the expression of cupB1 and cupB3 (Figure S5E), two genes within the CupB fimbrial cluster identified as ChIP-seq targets. Similarly, PA3094 was confirmed to positively regulate lecA expression (Figure S5F), which encodes a lectin involved in biofilm formation and host interactions[2]. Expression of these target genes was restored to wild-type (WT) levels in the complemented strains, validating the regulatory relationships predicted by ChIP-seq. These combined biochemical and genetic validations demonstrate the accuracy and biological relevance of our TF binding data.”
(2) Non-promoter binding events (e.g., coding regions) may regulate RNA stability, warranting integration with translatomics or epigenomics data.
Thank you for this suggestion. We have now expanded the Discussion section to address this comment. Please see Lines 478-482.
“Our analysis revealed that TF binding events occur within coding regions, which is consistent with our previous study demonstrating that bacterial TFs possess binding capabilities for coding regions and can regulate transcription through multiple mechanisms [1]. Besides, it may also regulate RNA stability, warranting integration with translatomics or epigenomics data.”
(3) Incorporate strain-specific TF data (e.g., clinical isolates) and dynamic visualization tools to broaden PATF_Net's applicability.
Thank you for this constructive suggestion. To enhance the utility of PA_TFNet, we have implemented two new features: (1) a virulence pathway browser that allows users to explore TF binding across curated gene sets for key virulence pathways (quorum sensing, secretion systems, biofilm, motility, etc.), and (2) a target gene search function that enables rapid identification of all TFs regulating any gene of interest by locus tag query. These features are now live on the database and described in the revised manuscript.
Regarding strain-specific TF data, we agree this would be valuable for understanding regulatory diversity in clinical isolates. However, such an expansion would require ChIP-seq profiling across multiple strains. The current dataset is based on the reference strain PAO1, which serves as the foundation for most P. aeruginosa research and allows direct comparison with existing genomic and functional studies. We have added a statement in the revised manuscript acknowledging this limitation and highlighting strain-specific TF analysis as an important future direction for the field. Please see Lines 372-390.
“The database offers multiple search modalities to facilitate data exploration: users can perform TF-centric searches to query binding sites, target genes, and regulatory networks for individual TFs, or utilize the target gene search function to identify all TFs that regulate any gene of interest by entering its locus tag. To connect regulatory data with biological function, we have implemented a virulence pathway browser that allows users to explore TF binding patterns across curated gene sets for major P. aeruginosa virulence pathways. Interactive visualization tools, including network graphs and binding profile plots, facilitate intuitive exploration of regulatory relationships. The primary purpose of PATF_Net is to store, search, and mine valuable information on P. aeruginosa TFs for researchers investigating P. aeruginosa infection. The current resource is based on the reference strain PAO1, which serves as the foundation for most P. aeruginosa molecular studies and allows direct integration with existing genomic annotations and functional data. However, P. aeruginosa exhibits substantial genomic diversity across clinical isolates, and strain-specific differences in TF binding patterns may contribute to phenotypic variation in virulence, antibiotic resistance, and host adaptation. Extension of this resource to include strain-specific regulatory maps from diverse clinical isolates would provide valuable insights into the regulatory basis and represents an important direction for future investigation.”
(4) Phylogenetic analysis highlights TF conservation in bacteria; future work could explore functional homology in other Gram-negative pathogens (e.g., E. coli).
Thank for this insightful suggestion. Our phylogenetic analysis revealed that P. aeruginosa TFs exhibit varying degrees of conservation across bacterial species, with some showing broad distribution across Gram-negative pathogens while others are lineage-specific.
We agree that exploring functional homology of orthologous TFs across species would be highly valuable. Such comparative studies could address whether conserved TFs regulate similar target genes and biological processes across species, or whether regulatory networks have been rewired during evolution. For example, comparative ChIP-seq analysis of P. aeruginosa TFs and their orthologs in Klebsiella pneumoniae or even Gram-positive pathogen like Bacillus cereus could reveal conserved regulatory modules governing universal virulence or metabolic strategies versus species-specific adaptations. This represents an important direction for future investigation and would be facilitated by the comprehensive TF binding dataset we provide here. We have expanded the Discussion section to highlight this future direction. Please see Lines 539-550.
“While our phylogenetic analysis reveals varying degrees of TF conservation across bacterial species, the functional implications of this conservation remain to be fully explored. Many P. aeruginosa TFs have clear orthologs in both Gram-negative (e.g., Klebsiella pneumoniae) and Gram-positive pathogens (e.g., Bacillus cereus), yet whether these orthologs regulate similar target genes and biological processes is largely unknown. Future comparative ChIP-seq profiling of orthologous TFs could reveal the extent to which regulatory network architecture is conserved versus rewired during bacterial evolution, potentially identifying core regulatory modules governing universal bacterial strategies versus species-specific innovations. Such cross-species comparisons would enhance our understanding of regulatory network evolution and enable functional prediction in less well-characterized pathogens based on homology to experimentally validated P. aeruginosa regulators.”
Reviewer #3 (Recommendations for the authors):
Major comments
- Limitations of the ChIP-seq approach: With overexpression plasmids as an approach to TRN elucidation, there are always a set of concerns. First, TF expression is not enough to ensure regulatory activity - metabolite effects must be such that the TF is active which requires growing the cells in activating conditions. Second, the presence of a binding event does not mean that the binding has a regulatory effect - the authors are clearly aware of this as they specify binding sites in promoter regions, which should be helpful, but they also mention the possibility of regulatory binding events in coding regions. These issues should be listed as weaknesses of the approach in the Discussion.
Thank you for these important suggestions. We agree that these limitations should be explicitly discussed. We have now added a dedicated paragraph in the Discussion section addressing these concerns. Please see Lines 492-501.
“However, several limitations of the ChIP-seq approach should be acknowledged. Firstly, TF overexpression ensures sufficient protein levels for ChIP-seq signal detection but does not guarantee that all TFs are in their active conformational states, as many bacterial TFs require allosteric activation by metabolites, cofactors, or post-translational modifications. The cells under standard laboratory conditions which may not activate all TFs to their maximal regulatory states, potentially leading to underestimation of condition-specific binding peaks. Secondly, while we observed TF binding at thousands of genomic sites, binding per se does not equate to functional regulation, as chromatin context, cofactor availability, and competitive binding all influence regulatory outcomes.”
- Lack of independent validation: The study seems to lack substantial independent validation of either the functional nature of the binding sites as well as the proposed physiological regulatory role of the TFs. For example, for the 103 identified TF motifs, do any of these agree with existing motifs in motif databases that may be homologous to P. aeruginosa TFs? The authors claim to have discovered master regulators of virulence and associated core regulatory clusters - but there does not seem to be any independent validation of the proposed associations. The authors selected the TF targets to cover TFs that had not yet been characterized; however, it would have been nice to have some overlap with previous studies so that consistency and data quality could be assessed.
Thank you for raising these critical points about validation.
As for motif validation, we compared the existing motifs in the RegPrecise database[3] and we found that the motif of PA3587 show significant similarity to homologous TFs in Pseudomonadaceae. We have added the related description in the Results section. Please see Figure S3B and Lines 228-231.
As for the validation of master regulators, we have performed EMSA experiments for validating the binding events and constructed the mutants for function validation. We have added the related contents in Results section. Please see Figure S5 and Lines 283-300.
We have discussed the overlap between our results and previous studies in the Discussion section. Please see Lines 530-538.
“PA0797 is known to regulate the pqs system and pyocyanin production[4]. In the present study, it was also found to bind to the pqsH promoter region and its motif was visualised. PA5428 was found to bind to the promoter regions of aceA and glcB genes[5], which was also demonstrated in our ChIP-seq results. PA4381 (CloR) was found to be associated with polymyxin resistance in a previous study[6] and to be possibly related to ROS resistance in the present study. Furthermore, PA5032 plays a putative role in biofilm regulation and also forms an operon with PA5033, an HP associated with biofilm formation[7].”
- Uncertain value of TRN topology analysis: The relationship between ternary motifs and pathogenicity of P. aeruginosa, and why the authors argue these results motivated TF-targeting drugs (the topic of the last paragraph of the Discussion), are unclear to me. The authors allude to possible connections between pathogenicity, growth, and drug resistance, but I don't see concrete examples here of related TF interactions that clearly represent these relationships. The sections "Hierarchical networks of TFs based on pairwise interactions" and "Ternary regulatory motifs show flexible relationships among TFs in P. aeruginosa" seem to not say much in terms of results that are actionable or possible to validate. A topological graph is constructed based on observed TF-TF connections in measured binding sites - however, it's unclear if any of these connections are physiologically meaningful. Line 178 - Why would there be any connection between the structural family of TF and its location in the proposed TRN hierarchy?
Thank you for this valuable comment on TRN topology analysis. It is hard to quantify precisely how much this resource will accelerate P. aeruginosa research or drug development, but we believe providing this foundational network architecture has inherent value for the community, which is valued for enabling hypothesis generation even before comprehensive functional validation. We would like to clarify our perspective on these findings and have added the discussion in the revised manuscript to better describe their nature and value. Please see Lines 517-528.
“Additionally, although the TRN analysis revealed organizational patterns in P. aeruginosa regulatory network, the functional significance these topological features, including their specific contributions to pathogenicity, metabolic adaptation, and antibiotic resistance remains to be experimentally determined in the future work. The hierarchical structure and regulatory motifs we identified represent objective network properties derived from our binding data, but translating these structural observations into mechanistic understanding will require condition-specific functional studies, genetic validation, and phenotypic characterization. Our analysis provided a systematic framework and generating testable hypotheses rather than definitive functional conclusions. Nevertheless, these network-level organizational principles provided value to the community as a foundational reference, similar to other regulatory network maps[8] that were useful even before comprehensive validation.”
- Identification of "master" regulators: Line 527 on virulence regulators: "We first generated gene lists associated with nine pathways" - is this not somewhat circular, i.e. using gene lists generated from (I assume) co-regulated gene sets to identify regulators of those gene lists? I can't tell from the cited reference (80), which is their own prior review article, what the original source of these gene lists was. Somewhat related to this point - Line 32: 24 "master regulators" - if there are that many, is it still considered a master regulator? Line 270: This term "master regulator" would seem to require some quantitative justification. Identifying 24 (a large number of) "master" regulators of virulence would seem to dilute the implied power of the term.
We apologize for the lack of clarity regarding the virulence pathway gene lists, and we have provided complete gene lists for virulence-related pathways, which were compiled from functional annotations, in our online PA_TFNet database.
Additionally, we appreciate your concern about the use of “master” regulator. The usage is based on previous studies[9,10], and the master regulator is commonly known in the development of multicellular organisms as a subset of TFs that control the expression of multiple downstream genes and govern lineage commitment or key biological processes. We employed the term "master regulator" in an analogous manner to specify a class of functionally crucial TFs that participate in a pathway or biological event by regulating multiple downstream genes statistically enriched in that pathway. In line with this definition, we identified TFs whose targets were significantly enriched in genes associated with specific virulence pathways (hypergeometric test, P < 0.05).
We understand the concern that identifying 24 master regulators might seem to dilute the term. However, we would like to clarify that each of these 24 TFs is a "master regulator" with respect to specific virulence pathways based on statistical criteria, not necessarily a global master regulator of multiple pathways of P. aeruginosa. We have revised the Method section. Please see Lines 604-612.
- Line 234: "Genome-wide synergistic co-association of TFs in P. aeruginosa." This section was an interesting analysis. As I mention above, the weakness of an overexpression approach is not knowing whether the TF is active on the examined conditions. By looking at shared binding peaks across overexpression of different TFs, it should indeed be possible to glean some regulatory connections across TFs. Furthermore, the authors discuss specific examples that appear physiologically reasonable, which is appreciated.
We thank the reviewer for this positive assessment of our co-association analysis. We agree with the limitation of the overexpression approach, which have been discussed in the Discussion section. We are pleased that the reviewer found the approach and specific examples valuable.
Minor comments
- Line 35 - "high-throughput systematic evolution of ligands by exponential enrichment" - no idea what this means. Is this related to the web-based database, or why is it mentioned in the same sentence?
We apologize for the unclear presentation. To clarify: “High-throughput systematic evolution of ligands by exponential enrichment” (HT-SELEX) is an in vitro technique for determining TF DNA-binding motifs, which our group previously applied to a subset of P. aeruginosa TFs in a prior publication[11]. In the current study, we performed ChIP-seq for 172 TFs, which represent the majority of TFs not covered by the previous HT-SELEX study. Together, these two complementary approaches (HT-SELEX for in vitro binding motifs, ChIP-seq for in vivo genomic binding sites) provide near-complete coverage of the P. aeruginosa TF repertoire. Both datasets are integrated into our PA_TFNet database.
Due to space constraints in the abstract, we could not provide detailed explanation of HT-SELEX, but we have now improved the clarity in the Introduction to better explain the relationship between our previous HT-SELEX work and the current ChIP-seq study, and why both are mentioned together in the context of the database. Please see Lines 99-105.
- Line 193 - Only 9 auto-regulating TFs seems like a low number, given the frequency of negative auto-regulation in other organisms like E. coli. Could the authors comment on their expectations based on well-curated TRNs?
Thank you for this comment. We agree that 9 auto-regulating TFs is lower than might be expected based on E. coli, where auto-regulation is more prevalent. This likely reflects technical limitations of ChIP-seq approach that our detection was limited to standard growth conditions rather than the diverse physiological states where auto-regulation often occurs. Therefore, the 9 TFs we report represent a high-confidence subset, and the true frequency of auto-regulation in P. aeruginosa likely is higher. We added the content in the revised manuscript. Please see Lines 193-196.
“This number likely represents a conservative estimate, as experiments may not optimally capture auto-regulatory events that depend on native expression levels or specific physiological conditions.”
- Line 230 - "This conservation suggests that TFs within the same cluster co-regulate similar sets of genes." - Why would clustering of TF binding site motifs need to be done to make this assessment? Couldn't the shared set of regulated genes be identified directly from the binding site data? Computing TF binding site motifs has obvious value, but I am struggling to understand the point of clustering the motifs. Is there some implied evolutionary or physiological connection here? No specific physiological roles or hypotheses are discussed in this section.
Thank you for this important question. We agree that shared target genes can be identified directly from ChIP-seq binding data, which we also analyzed (co-association analysis). The motif clustering analysis serves a complementary and distinct purpose that provides information not directly obtainable from overlapped targets alone. Specifically, target overlap is inherently condition dependent, and motif clustering captures this intrinsic binding specificity, which reflects the structural similarity of DBDs, evolutionary relationships, and potential for functional redundancy or cooperativity under specific conditions. We have revised the related content in the manuscript, and please see Lines 236-242.
“Clustering of TF binding motifs identified groups of TFs with similar intrinsic DNA-binding specificities. As expected, many clusters contained TFs from the same DBD families, reflecting evolutionary conservation and potential functional redundancy or competitive binding at shared regulatory elements. Notably, the clustering also uncovered associations between TFs from different DBD families, suggesting convergent evolution of binding specificity or novel regulatory interactions that warrant further investigation.”
- Line 284 - should "metabolomic" be "metabolic"? I didn't see metabolomic data
Yes, we have revised. Please see Line 311.
- Several of the figures are too small (e.g. Fig S4A) or complex (Fig 2A) to see clearly or glean information from.
Thank you for this comment. We acknowledge that Figure 2A and Figure S4A contain dense information due to the comprehensive nature of the regulatory network and the large number of TFs analyzed. We believe these overview figures serve an important purpose in conveying the scale and organization of the regulatory network, while the tables (Table S6 for Fig. S4A and Table S3 for Fig. 2A) provide the granular data needed for specific inquiries. We have also made the figures available in higher resolution and increased font sizes where possible without compromising the overall layout.
- I don't understand the organization of the "Ternary regulatory motifs" in Supplementary Data File 4 - A table of contents explaining the tabs and columns would be welcome (for this as well as other supplementary files, some of which are more straightforward than others).
Thank you for this suggestion. We have now revised all supplementary data files to include header and necessary annotations in the first row. Specifically for Supplementary Data File 4, the three columns (Top, Middle, Bottom) represent the left, middle, and right node, respectively, in each ternary regulatory motif.
- I would have expected genomic locations of TF binding sites would have been one of the Supplementary Tables, to increase the accessibility of the data. However, the data is made available through their website, https://jiadhuang0417.shinyapps.io/PATF_Net/, which was easy to access and download the full dataset, so this is a minor issue.
Thank for accessing our PA_TFNet database and for the positive feedback on data accessibility. We agree that providing genomic locations of TF binding sites is crucial. These data are fully available and downloadable through the web interface, which allows flexible searching, filtering, and batch download of binding sites. We felt that the interactive and database format provides more functionality than static supplementary tables (e.g., dynamic filtering by TF, genomic region, or binding strength), given the large scale of this dataset.
References
(1) Hua, C., Huang, J., Wang, T., Sun, Y., Liu, J., Huang, L. et al. Bacterial Transcription Factors Bind to Coding Regions and Regulate Internal Cryptic Promoters. Mbio 13, e0164322 (2022).
(2) Chemani, C., Imberty, A., de Bentzmann, S., Pierre, M., Wimmerová, M., Guery, B. P. et al. Role of LecA and LecB lectins in Pseudomonas aeruginosa-induced lung injury and effect of carbohydrate ligands. Infect Immun 77, 2065-2075 (2009).
(3) Novichkov, P. S., Kazakov, A. E., Ravcheev, D. A., Leyn, S. A., Kovaleva, G. Y., Sutormin, R. A. et al. RegPrecise 3.0–a resource for genome-scale exploration of transcriptional regulation in bacteria. Bmc Genomics 14, 745 (2013).
(4) Cui, G. Y., Zhang, Y. X., Xu, X. J., Liu, Y. Y., Li, Z., Wu, M. et al. PmiR senses 2-methylisocitrate levels to regulate bacterial virulence in Pseudomonas aeruginosa. Sci Adv 8 (2022).
(5) Hwang, W., Yong, J. H., Min, K. B., Lee, K.-M., Pascoe, B., Sheppard, S. K. et al. Genome-wide association study of signature genetic alterations among pseudomonas aeruginosa cystic fibrosis isolates. Plos Pathog 17, e1009681 (2021).
(6) Gutu, A. D., Sgambati, N., Strasbourger, P., Brannon, M. K., Jacobs, M. A., Haugen, E. et al. Polymyxin resistance of Pseudomonas aeruginosa phoQ mutants is dependent on additional two-component regulatory systems. Antimicrob Agents Chemother 57, 2204-2215 (2013).
(7) Zhang, L., Fritsch, M., Hammond, L., Landreville, R., Slatculescu, C., Colavita, A. et al. Identification of genes involved in Pseudomonas aeruginosa biofilm-specific resistance to antibiotics. PLoS One 8, e61625 (2013).
(8) Galan-Vasquez, E., Luna, B. & Martinez-Antonio, A. The Regulatory Network of Pseudomonas aeruginosa. Microb Inform Exp 1, 3 (2011).
(9) Fan, L. G., Wang, T. T., Hua, C. F., Sun, W. J., Li, X. Y., Grunwald, L. et al. A compendium of DNA-binding specificities of transcription factors in Pseudomonas syringae. Nat Commun 11 (2020).
(10) Chan, S. S.-K. & Kyba, M. What is a master regulator? Journal of stem cell research & therapy 3, 114 (2013).
(11) Wang, T. T., Sun, W. J., Fan, L. G., Hua, C. F., Wu, N., Fan, S. R. et al. An atlas of the binding specificities of transcription factors in Pseudomonas aeruginosa directs prediction of novel regulators in virulence. Elife 10 (2021).
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eLife Assessment
This useful study characterizes the evolution of medial prefrontal cortex activity during the learning of an odor-based choice task. The evidence provided is solid, providing quantification of functional classes of cells over the course of learning using the longitudinal calcium recordings in prefrontal cortex, and quantification of prefrontal sequences. However, the experimental design appears to provide limited evidence to support strong conclusions regarding the functional relevance of neural sequences. The study will be of interest to neuroscientists investigating learning and decision-making processes.
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Reviewer #1 (Public review):
This study presents a useful finding about development of task representations in mouse medial prefrontal cortex using 1-photon calcium recordings in an olfactory-guided spatial memory task. A key strength of the study is the use of longitudinal recordings allowing identification of task-related activity that emerges after learning. The study also reports existence of neuronal sequences during learning and their replay at reward locations. The evidence provided is solid, providing quantification of functional classes of cells over the course of learning using the longitudinal calcium recordings in prefrontal cortex, and quantification of prefrontal sequences.
(1) The authors continue to state that task phase selective cells (non-splitter) cells can be considered as "cross-condition generalization" and interpret them as "potential building blocks of schemas". However, cross-condition generalization requires demonstration of cross-condition generalization performance (CCGP) of neural decoders across task conditions, which is not shown here.
(2) The authors note that correlations on short time scales are not similar between sampling and reward phase, acknowledging that these two represent different behavioral states in a cued-memory task, and that the manuscript should more clearly distinguish replay with "pure sequences". However, while the last line in the abstract states that "sub-second neural sequences in the mPFC are more likely involved in behavioral outcomes rather than planning future actions", references are made throughout the manuscript to preplay/replay sequences, including results primarily for non-cued spatial memory tasks, in which there is no cued sampling phase. For example, lines 259-263 state "During odor sampling phase, no such significant replay was observed..." and "... sequence clusters showed small but significant bias to preplay in the sampling phase". If the authors want to distinguish between replay and "pure" sequences, then the terminology "replay" and "preplay" should not be used here.
Further, large parts of the Discussion are devoted to comparison to hippocampal ripple-associated replay. Lines 355-356 in Discussion state that "the suggestion that mPFC sequences may also support planning [Tang et al., 2021] could not be confirmed by our work as sequences in the odor sampling phase were absent". It should be clarified that this is a comparison between what the authors term "pure sequences" in the sampling phase of an odor-cued task, and internally generated sequences during hippocampal ripples in a non-cued spatial memory task, so this is not a like-for-like comparison.
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Author response:
The following is the authors’ response to the previous reviews
Public Reviews:
Reviewer #1 (Public review):
There are a few remaining issues:
(1) The manuscript quantifies changes over learning in prefrontal goal-selective cells (equated to "splitter" place cells in hippocampus) and task-phase selective cells (similar to non-splitter place cells that are not goal modulated). A subset of these task cells remain stable throughout learning, and are equated to schema representations in the study. In the memory literature, schemas are generally described as relational networks of abstract and generalized information, that enable adapting to novel context and inference by enabling retrieval of related information from previous contexts. The task-phase selective cells that stay stable throughout learning clearly will have a role in organizing task representations, but to this reviewer, denoting them as forming a schema is an unwarranted interpretation. By this definition, hippocampal non-splitter place cells that emerge early in learning and are stable over days would also form a schema. Therefore, schema notation cannot just be based on stability, it requires further evidence of abstraction such as cross-condition generalization.
We agree with the reviewer that task phase selective cells (“non-splitter cells”) alone do not fulfill the “relationality” criterion of schemas. We found only few of them, and so we cannot really say something about how they covary. We, however, would like to stress that our finding that task phase selective cells have stable firing field comparing learned (task) and habituation (no-task) conditions can be considered as “cross-condition generalization.” We have further specified our discussion of schemas with a particular emphasis on a potential interpretation of the generalizing task phase cells as “potential building blocks of schemas.”
(2) The quantification of prefrontal replay sequences during reward is useful, but it is still unconvincing that the distinction between existence of sequences in the odor sampling phase and reward phase is not trivially expected based on prior literature. This is odor guided task, not a spatial exploration task with no cues, and it is very well-established (as noted in citations in the previous review) that during odor sampling, animals' will sniff in an exploratory stage, resulting in strong beta and respiratory rhythms in prefrontal cortex. Not having LFP recordings in this task does not preclude considering prior literature that clearly shows that odor sampling results in a unique internal state network state, when animals are retrieving the odor-associated goal, vastly different from a reward sampling phase. The authors argue that this is not trivial since they see some sequences during sampling, although they also argue the opposite in response to a question from Reviewer 2 about shuffling controls for sequences, that 'not' seeing these sequences in the sampling phase is an internal control. The bigger issue here is equating these sequences during sampling to replay/ preplay or reactivation sequences similar to the reward phase, since the prefrontal network dynamics are engaged in odor-driven retrieval of associated goals during sampling, as has been shown in previous studies.
We agree with the reviewer that sampling and reward phase represent two very different behavioral states. Nevertheless, correlations on short time scales could be similar, which we show is not the case and therefore we do not consider this result trivial. Regarding the interpretation of sequences, we apologize that we have not been sufficiently clear on distinguishing replay with pure sequences. While we find such sequences in the sampling phase (indicative of fast temporal correlation structure beyond cofiring quantified in Figure 3) they are NOT pre/replaying any task related information. Otherwise, our results are fully in line with previous literature on oscillations that we have included in the previous round of revisions. We added a similar explanation at multiple instances in the Results and Discussion section.
Reviewer #2 (Public review):
Comments on revisions:
Further changes are needed to improve the description of the methods and the discussion needs to be extended to contrast the results with previously published results of the group. Some control figures would also be needed to quantitatively demonstrate, across the entire dataset, that sequence detection did not identify random events as sequences, even if the detection method was designed to exclude such sequences. For example, showing that sequences are not detected in randomised data with the current method would better convince readers of the method's validity.
We have added control quantifications from time randomized sequences which produce a much lower amount of detected sequences. See response below.
Although differences in the classification scheme relative to the Muysers et al. (2025) paper have been explained, the similarity (perhaps equivalence of results) is not sufficiently acknowledged - e.g., at the beginning of the discussion.
We have added a paragraph at the beginning of the Discussion on how our results align with the Muysers et al. 2025 paper.
Although the control of spurious sequences may have been built into the method, this is not sufficiently explained in the method. It is also not clear what kind of randomization was performed. Importantly, I do not see a quantification that shows that the detected sequences are significantly better than the sequence quality measure on randomized events. Or that randomized data do not lead to sequence clusters.
In response to this question, we have added the requested shuffling control (Supplement 1B to Figure 4). In the shuffled data the amount of detected recurring sequence clusters is only about half of those in the original data. The amount of bursts assigned to clusters in the shuffled data only remains 46% of the originally assigned bursts on average, clearly indicating that the detected sequences in the non-randomized data cannot be explained without assuming stable temporal order.
Some clusters, however, are still detected in randomized data, which, however, is expected if participation of cells is heterogeneous with some highly active cells occurring in more than half of the bursts. Then random sequences spuriously occur above chance level representing the clusters of random order of few highly active cells. In line with this interpretation, we see that
(1) Bursts that were removed after shuffling have exactly 0 high-firing cells
(2) Clusters derived from shuffled sequence have a less sparse contribution of high firing cells, i.e., high firing cells contribute to significantly more clusters in randomized data than in nonrandomized data.
The difference in the distribution of high firing cells further indicates that sequences obtained with and without randomization are of different quality.
The spurious (false positive) clusters detected after randomization nevertheless may have a physiological meaning as they identify rate coactivation patterns that were also picked up by analysis in Figure 3.
Also, it is still not clear how the number of clusters was established. I understand that the previously published paper may have covered these questions; these should be explained here as well.
The Methods sections states “The [cluster merging] procedure was repeated until no pair [of clusters] satisfied the merging criterion.”
Also, the sequence similarity description is still confusing in the method; please correct this sentence "Only the l neurons active in both sequences of a pair were taken into account."
We do not see what is wrong with this sentence. To avoid confusion.” we have replaced lower case l with upper case L as sequence length.
Reviewer #3 (Public review):
One comment is that the threshold for extracting burst events (0.5 standard deviations, presumably above the mean) seems lower than what one usually sees as a threshold for population burst detection, and the authors show (in Supplementary Fig 1) that this means bursts cover ~20-40% of the data. However, it is potentially a strength of this work that their results are found by using this more permissive threshold.
We have added further specifications following the Reviewer’s suggestion and now mention that the threshold is permissive and “capturing large amount cofiring structure.”
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This is not a comment upon the ordinary use of the word ‘free’; that use may or may not coincide with the Free Will Defender's. What God thought good, on this view, was the existence of creatures whose activity is not causally determined—who, like he himself, are centres of creative activity. The freedom of such creatures will no doubt be limited by causal laws and antecedent conditions. They will not be free to do just anything; even if I am free, I am not free to run a mile in two minutes. Of course my freedom is also enhanced by causal laws; it is only by virtue of such laws that I am free to build a house or walk on the surface of the earth. But if I am free with respect to an action A, then causal laws and antecedent conditions determine neither that I take A nor that I refrain.
God created free will beings with limits. This means there are limits to what we can do, i.e.) we can not run a mile in a minute and we must find virtue in doing what is good in life
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eLife Assessment
The authors make an important contribution to comparative functional genomics by developing a semi-automated computational pipeline that integrates classification and marker-based cluster annotation to identify orthologous cell types. Using a single-cell RNA-seq dataset of induced pluripotent stem cells and derived embryonic bodies from four primate species: humans, orangutans, cynomolgus macaques, and rhesus macaques, the authors provide convincing evidence that cell type-specific marker genes are substantially less transferable across species than broadly expressed genes, with transferability declining as phylogenetic distance increases. This study establishes a key framework and reference dataset for comparative single-cell analyses and encourages more rigorous evaluation of marker gene transferability across species.
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Reviewer #1 (Public review):
Summary:
Jocher, Janssen et al examine the robustness of comparative functional genomics studies in primates that make use of induced pluripotent stem cell-derived cells. Comparative studies in primates, especially amongst the great apes, are generally hindered by the very limited availability of samples, and iPSCs, which can be maintained in the laboratory indefinitely and defined into other cell types, have emerged as promising model systems because they allow the generation of data from tissues and cells that would otherwise would be unobservable.
Undirected differentation of iPSCs into many cell types at once, using a method known as embryoid body differentiation, requires researchers to manually assign all cell types in the dataset so they can be correctly analysed. Typically, this is done using marker genes associated with a specific cell type. These are defined a priori, and have historically tended to be characterised in mice and human and then employed to annotate other species. Jocher, Janssen et al ask if the marker genes and features used to define a given cell type in one species are suitable for use in a second species, and then quantify the degree of usefulness of these markers. They find that genes that are informative and cell type specific in a given species are less valuable for cell type identification in other species, and that this value, or transferability, drops off as the evolutionary distance between species increases.
This paper will help guide future comparative studies of gene expression in primates (and more broadly) as well as add to the growing literature on the broader challenges of selecting powerful and reliable marker genes for use in single cell transcriptomics.
Strengths:
Marker gene selection and cell type annotation is challenging problem in scRNA studies, and successful classification of cells often requires manual expert input. This can be hard to reproduce across studies, as despite general agreement on the identity of many cell types, different methods for identifying marker genes will return different sets of genes. The rise of comparative functional genomics complicates this even further, as a robust marker gene in one species need not always be as useful in a different taxon. The finding that so many marker genes have poor transferability is striking, and by interrogating the assumption of transferability in a thorough and systematic fashion, this paper reminds us of the importance of systematically validating analytical choices. The focus on identifying how transferability varies across different types of marker genes (especially when comparing TFs to lncRNAs), and on exploring different methods to identify marker genes, also suggests additional criteria by which future researchers could select robust marker genes in their own data.
The paper is built on a substantial amount of clearly reported and thoroughly considered data, including EBs and cells from four different primate species - humans, orangutans, and two macaque species. The authors go to great lengths to ensure the EBs are as comparable as possible across species, and take similar care with their computational analyses, always erring on the side of drawing conservative conclusions that are robustly supported by their data over more tenuously supported ones that could be impacted by data processing artefacts such as differences in mappability etc. For example, I like the approach of using liftoff to robustly identify genes in non-human species that can be mapped to and compared across species confidently, rather than relying on the likely incomplete annotation of the non-human primate genomes. The authors also provide an interactive data visualisation website that allows users to explore the dataset in depth, examine expression patterns of their own favourite marker genes and perform the same kinds of analyses on their own data if desired, facilitating consistency between comparative primate studies.
Weaknesses and recommendations:
(1) Embryoid body generation is known to be highly variable from one replicate to the next for both technical and biological reasons, and the authors do their best to account for this, both by their testing of different ways of generating EBs, and by including multiple technical replicates/clones per species. However, there is still some variability that could be worth exploring in more depth. For example, the orangutan seems to have differentiated preferentially towards cardiac mesoderm whereas the other species seemed to prefer ectoderm fates, as shown in Figure 2C. Likewise, Supplementary Figure 2C suggests significant unbalance in the contributions across replicates within a species, which is not surprising given the nature of EBs, while Supplementary Figure 6 suggests that despite including three different clones from a single rhesus macaque, most of the data came from a single clone. The manuscript would be strengthened by a more thorough exploration of the intra-species patterns of variability, especially for the taxa with multiple biological replicates, and how they impact the number of cell types detected across taxa etc.
The same holds for the temporal aspect of the data, which is not really discussed in depth despite being a strength of the design. Instead, days 8 and 16 are analysed jointly, without much attention being paid to the possible differences between them. Are EBs at day 16 more variable between species than at day 8? Is day 8 too soon to do these kinds of analyses? Are markers for earlier developmental progenitors better/more transferable than those for more derived cell types?
(2) Closely tied to the point above, by necessity the authors collapse their data into seven fairly coarse cell types, and then examine the performance of canonical marker genes (as well as those discovered de novo) across the species. But some of the clusters they use are somewhat broad, and so it is worth asking whether the lack of specificity exhibited by some marker genes and driving their conclusions is driven by inter-species heterogeneity within a given cluster.
Comments on revisions:
I think the authors have addressed my previous comments to my satisfaction, and I thank them for the changes they have made, it's good to see that the manuscript is just as sound as it seemed the first time around.
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Author response:
The following is the authors’ response to the original reviews.
Most importantly, in accordance with questions raised by Reviewer 1, we now include a detailed comparison of the cell type frequencies between the two examined time points as well as comparison of the pseudotimes along those lineages. This is detailed in the new section “Many cell types are shared between day 8 and day 16 EBs” and illustrated in Supplementary Figure 6c and Supplementary Figures 7-8.
Besides this new chapter and its accompanying methods part, we mainly edited the language and to clarify methods and assumptions according to the Reviewer suggestions.
The main concern of Reviewer 2 was our use of the liftoff gene annotation. We explained our reasoning for this choice extensively in our public response to the Reviewer, but did not incorporate this into our manuscript because even though this is an important subject it is not within the main scope of our paper.
Public Reviews:
Reviewer #1 (Public review):
Summary:
Jocher, Janssen, et al examine the robustness of comparative functional genomics studies in primates that make use of induced pluripotent stem cell-derived cells. Comparative studies in primates, especially amongst the great apes, are generally hindered by the very limited availability of samples, and iPSCs, which can be maintained in the laboratory indefinitely and defined into other cell types, have emerged as promising model systems because they allow the generation of data from tissues and cells that would otherwise be unobservable.
Undirected differentiation of iPSCs into many cell types at once, using a method known as embryoid body differentiation, requires researchers to manually assign all cell types in the dataset so they can be correctly analysed. Typically, this is done using marker genes associated with a specific cell type. These are defined a priori, and have historically tended to be characterised in mice and humans and then employed to annotate other species. Jocher, Janssen, et al ask if the marker genes and features used to define a given cell type in one species are suitable for use in a second species, and then quantify the degree of usefulness of these markers. They find that genes that are informative and cell type specific in a given species are less valuable for cell type identification in other species, and that this value, or transferability, drops off as the evolutionary distance between species increases.
This paper will help guide future comparative studies of gene expression in primates (and more broadly) as well as add to the growing literature on the broader challenges of selecting powerful and reliable marker genes for use in single-cell transcriptomics.
Strengths:
Marker gene selection and cell type annotation is a challenging problem in scRNA studies, and successful classification of cells often requires manual expert input. This can be hard to reproduce across studies, as, despite general agreement on the identity of many cell types, different methods for identifying marker genes will return different sets of genes. The rise of comparative functional genomics complicates this even further, as a robust marker gene in one species need not always be as useful in a different taxon. The finding that so many marker genes have poor transferability is striking, and by interrogating the assumption of transferability in a thorough and systematic fashion, this paper reminds us of the importance of systematically validating analytical choices. The focus on identifying how transferability varies across different types of marker genes (especially when comparing TFs to lncRNAs), and on exploring different methods to identify marker genes, also suggests additional criteria by which future researchers could select robust marker genes in their own data.
The paper is built on a substantial amount of clearly reported and thoroughly considered data, including EBs and cells from four different primate species - humans, orangutans, and two macaque species. The authors go to great lengths to ensure the EBs are as comparable as possible across species, and take similar care with their computational analyses, always erring on the side of drawing conservative conclusions that are robustly supported by their data over more tenuously supported ones that could be impacted by data processing artefacts such as differences in mappability, etc. For example, I like the approach of using liftoff to robustly identify genes in non-human species that can be mapped to and compared across species confidently, rather than relying on the likely incomplete annotation of the non-human primate genomes. The authors also provide an interactive data visualisation website that allows users to explore the dataset in depth, examine expression patterns of their own favourite marker genes and perform the same kinds of analyses on their own data if desired, facilitating consistency between comparative primate studies.
We thank the Reviewer for their kind assessment of our work.
Weaknesses and recommendations:
(1) Embryoid body generation is known to be highly variable from one replicate to the next for both technical and biological reasons, and the authors do their best to account for this, both by their testing of different ways of generating EBs, and by including multiple technical replicates/clones per species. However, there is still some variability that could be worth exploring in more depth. For example, the orangutan seems to have differentiated preferentially towards cardiac mesoderm whereas the other species seemed to prefer ectoderm fates, as shown in Figure 2C. Likewise, Supplementary Figure 2C suggests a significant unbalance in the contributions across replicates within a species, which is not surprising given the nature of EBs, while Supplementary Figure 6 suggests that despite including three different clones from a single rhesus macaque, most of the data came from a single clone. The manuscript would be strengthened by a more thorough exploration of the intra-species patterns of variability, especially for the taxa with multiple biological replicates, and how they impact the number of cell types detected across taxa, etc.
You are absolutely correct in pointing out that the large clonal variability in cell type composition is a challenge for our analysis. We also noted the odd behavior of the orangutan EBs, and their underrepresentation of ectoderm. There are many possible sources for these variable differentiation propensities: clone, sample origin (in this case urine) and individual. However, unfortunately for the orangutan, we have only one individual and one sample origin and thus cannot say whether this germ layer preference says something about the species or is due to our specific sample. Because of this high variability from multiple sources, getting enough cell types with an appreciable overlap between species was limiting to analyses. In order to be able to derive meaningful conclusions from intra-species analyses and the impact of different sources of variation on cell type propensity, we would need to sequence many more EBs with an experimental design that balances possible sources of variation. This would go beyond the scope of this study.
Instead, here we control for intra-species variation in our analyses as much as possible: For the analysis of cell type specificity and conservation the comparison is relative for the different specificity degrees (Figure 3C). For the analysis of marker gene conservation, we explicitly take intra-species variation into account (Figure 4D).
The same holds for the temporal aspect of the data, which is not really discussed in depth despite being a strength of the design. Instead, days 8 and 16 are analysed jointly, without much attention being paid to the possible differences between them.
Concerning the temporal aspect, indeed we knowingly omitted to include an explicit comparison of day 8 and day 16 EBs, because we felt that it was not directly relevant to our main message. Our pseudotime analysis showed that the differences of the two time points were indeed a matter of degree and not so much of quality. All major lineages were already present at day 8 and even though day 8 cells had on average earlier pseudotimes, there was a large overlap in the pseudotime distributions between the two sampling time points (Author response image 1). That is why we decided to analyse the data together.
Are EBs at day 16 more variable between species than at day 8? Is day 8 too soon to do these kinds of analyses?
When we started the experiment, we simply did not know what to expect. We were worried that cell types at day 8 might be too transient, but longer culture can also introduce biases. That is why we wanted to look at two time points, however as mentioned above the differences are in degree.
Concerning the cell type composition: yes, day 16 EBs are more heterogeneous than day 8 EBs. Firstly, older EBs have more distinguishable cell types and hence even if all EBs had identical composition, the sampling variance would be higher given that we sampled a similar number of cells from both time points. Secondly, in order to grow EBs for a longer time, we moved them from floating to attached culture on day 8 and it is unclear how much variance is added by this extra handling step.
Are markers for earlier developmental progenitors better/more transferable than those for more derived cell types?
We did not see any differences in the marker conservation between early and late cell types, but we have too little data to say whether this carries biological meaning.
Author response image 1.
Pseudotime analysis for a differentiation trajectory towards neurons. Single cells were first aggregated into metacells per species using SEACells (Persad et al. 2023). Pluripotent and ectoderm metacells were then integrated across all four species using Harmony and a combined pseudotime was inferred with Slingshot (Street et al. 2018), specifying iPSCs as the starting cluster. Here, lineage 3 is shown, illustrating a differentiation towards neurons. (A) PHATE embedding colored by pseudotime (Moon et al. 2019). (B) PHATE embedding colored by celltype. (C) Pseudotime distribution across the sampling timepoints (day 8 and day 16) in different species.
(2) Closely tied to the point above, by necessity the authors collapse their data into seven fairly coarse cell types and then examine the performance of canonical marker genes (as well as those discovered de novo) across the species. However some of the clusters they use are somewhat broad, and so it is worth asking whether the lack of specificity exhibited by some marker genes and driving their conclusions is driven by inter-species heterogeneity within a given cluster.
Author response image 2.
UMAP visualization for the Harmony-integrated dataset across all four species for the seven shared cell types, colored by cell type identity (A) and species (B).
Good point, if we understand correctly, the concern is that in our relatively broadly defined cell types, species are not well mixed and that this in turn is partly responsible for marker gene divergence. This problem is indeed difficult to address, because most approaches to evaluate this require integration across species which might lead to questionable results (see our Discussion).
Nevertheless, we attempted an integration across all four species. To this end, we subset the cells for the 7 cell types that we found in all four species and visualized cell types and species in the UMAPs above (Author response image 2).
We see that cardiac fibroblasts appear poorly integrated in the UMAP, but they still have very transferable marker genes across species. We quantified integration quality using the cell-specific mixing score (cms) (Lütge et al. 2021) and indeed found that the proportion of well integrated cells is lowest for cardiac fibroblasts (Author response image 3A). On the other end of the cms spectrum, neural crest cells appear to have the best integration across species, but their marker transferability between species is rather worse than for cardiac fibroblasts (Supplementary Figure 9). Cell-type wise calculated rank-biased overlap scores that we use for marker gene conservation show the same trends (Author response image 3B) as the F1 scores for marker gene transferability. Hence, given our current dataset we do not see any indication that the low marker gene conservation is a result of too broadly defined cell types.
Author response image 3.
(A) Evaluation of species mixing per cell type in the Harmony-integrated dataset, quantified by the fraction of cells with an adjusted cell-specific mixing score (cms) above 0.05. (B) Summary of rank-biased overlap (RBO) scores per cell type to assess concordance of marker gene rankings for all species pairs.
Reviewer #2 (Public review):
Summary:
The authors present an important study on identifying and comparing orthologous cell types across multiple species. This manuscript focuses on characterizing cell types in embryoid bodies (EBs) derived from induced pluripotent stem cells (iPSCs) of four primate species, humans, orangutans, cynomolgus macaques, and rhesus macaques, providing valuable insights into cross-species comparisons.
Strengths:
To achieve this, the authors developed a semi-automated computational pipeline that integrates classification and marker-based cluster annotation to identify orthologous cell types across primates. This study makes a significant contribution to the field by advancing cross-species cell type identification.
We thank the reviewer for their positive and thoughtful feedback.
Weaknesses:
However, several critical points need to be addressed.
(1) Use of Liftoff for GTF Annotation
The authors used Liftoff to generate GTF files for Pongo abelii, Macaca fascicularis, and Macaca mulatta by transferring the hg38 annotation to the corresponding primate genomes. However, it is unclear why they did not use species-specific GTF files, as all these genomes have existing annotations. Why did the authors choose not to follow this approach?
As Reviewer 1 also points out, also we have observed that the annotation of non-human primates often has truncated 3’UTRs. This is especially problematic for 3’ UMI transcriptome data as the ones in the 10x dataset that we present here. To illustrate this we compared the Liftoff annotation derived from Gencode v32, that we also used throughout our manuscript to the Ensembl gene annotation Macaca_fascicularis_6.0.111. We used transcriptomes from human and cynomolgus iPSC bulk RNAseq (Kliesmete et al. 2024) using the Prime-seq protocol (Janjic et al. 2022) which is very similar to 10x in that it also uses 3’ UMIs. On average using Liftoff produces higher counts than the Ensembl annotation (Author response image 4A). Moreover, when comparing across species, using Ensembl for the macaque leads to an asymmetry in differentially expressed genes, with apparently many more up-regulated genes in humans. In contrast, when we use the Liftoff annotation, we detect fewer DE-genes and a similar number of genes is up-regulated in macaques as in humans (Author response image 4B). We think that the many more DE-genes are artifacts due to mismatched annotation in human and cynomolgus macaques. We illustrate this for the case of the transcription factor SALL4 in Author response image 4C, D. The Ensembl annotation reports 2 transcripts, while Liftoff from Gencode v32 suggests 5 transcripts, one of which has a longer 3’UTR. This longer transcript is also supported by Nanopore data from macaque iPSCs. The truncation of the 3’UTR in this case leads to underestimation of the expression of SALL4 in macaques and hence SALL4 is detected as up-regulated in humans (DESeq2: LFC= 1.34, p-adj<2e-9). In contrast, when using the Liftoff annotation SALL4 does not appear to be DE between humans and macaques (LFC=0.33, p.adj=0.20).
Author response image 4.
(A) UMI-counts/ gene for the same cynomolgus macaque iPSC samples. On the x-axis the gtf file from Ensembl Macaca_fascicularis_6.0.111 was used to count and on the y-axis we used our filtered Liftoff annotation that transferred the human gene models from Gencode v32. (B) The # of DE-genes between human and cynomolgus iPSCs detected with DESeq2. In Liftoff, we counted human samples using Gencode v32 and compared it to the Liftoff annotation of the same human gene models to macFas6. In Ensembl, we use Gencode v32 for the human and Ensembl Macaca_fascicularis_6.0.111 for the Macaque. For both comparisons we subset the genes to only contain one-to-one orthologs as annotated in biomart. Up and down regulation is relative to human expression. C) Read counts for one example gene SALL4. Here we used in addition to the Liftoff and Ensembl annotation also transcripts derived from Nanopore cDNA sequencing of cynomolgus iPSCs. D) Gene models for SALL4 in the space of MacFas6 and a coverage for iPSC-Prime-seq bulk RNA-sequencing.
(2) Transcript Filtering and Potential Biases
The authors excluded transcripts with partial mapping (<50%), low sequence identity (<50%), or excessive length differences (>100 bp and >2× length ratio). Such filtering may introduce biases in read alignment. Did the authors evaluate the impact of these filtering choices on alignment rates?
We excluded those transcripts from analysis in both species, because they present a convolution of sequence-annotation differences and expression. The focus in our study is on regulatory evolution and we knowingly omit marker differences that are due to a marker being mutated away, we will make this clearer in the text of a revised version.
(3) Data Integration with Harmony
The methods section does not specify the parameters used for data integration with Harmony. Including these details would clarify how cross-species integration was performed.
We want to stress that none of our conservation and marker gene analyses relies on cross-species integration. We only used the Harmony integrated data for visualisation in Figure 1 and the rough germ-layer check up in Supplementary Figure S3. We will add a better description in the revised version.
Reference
Janjic, Aleksandar, Lucas E. Wange, Johannes W. Bagnoli, Johanna Geuder, Phong Nguyen, Daniel Richter, Beate Vieth, et al. 2022. “Prime-Seq, Efficient and Powerful Bulk RNA Sequencing.” Genome Biology 23 (1): 88.
Kliesmete, Zane, Peter Orchard, Victor Yan Kin Lee, Johanna Geuder, Simon M. Krauß, Mari Ohnuki, Jessica Jocher, Beate Vieth, Wolfgang Enard, and Ines Hellmann. 2024. “Evidence for Compensatory Evolution within Pleiotropic Regulatory Elements.” Genome Research 34 (10): 1528–39.
Lütge, Almut, Joanna Zyprych-Walczak, Urszula Brykczynska Kunzmann, Helena L. Crowell, Daniela Calini, Dheeraj Malhotra, Charlotte Soneson, and Mark D. Robinson. 2021. “CellMixS: Quantifying and Visualizing Batch Effects in Single-Cell RNA-Seq Data.” Life Science Alliance 4 (6): e202001004.
Moon, Kevin R., David van Dijk, Zheng Wang, Scott Gigante, Daniel B. Burkhardt, William S. Chen, Kristina Yim, et al. 2019. “Visualizing Structure and Transitions in High-Dimensional Biological Data.” Nature Biotechnology 37 (12): 1482–92.
Persad, Sitara, Zi-Ning Choo, Christine Dien, Noor Sohail, Ignas Masilionis, Ronan Chaligné, Tal Nawy, et al. 2023. “SEACells Infers Transcriptional and Epigenomic Cellular States from Single-Cell Genomics Data.” Nature Biotechnology 41 (12): 1746–57.
Street, Kelly, Davide Risso, Russell B. Fletcher, Diya Das, John Ngai, Nir Yosef, Elizabeth Purdom, and Sandrine Dudoit. 2018. “Slingshot: Cell Lineage and Pseudotime Inference for Single-Cell Transcriptomics.” BMC Genomics 19 (1): 477.
Recommendations for the authors:
Reviewer #1 (Recommendations for the authors):
(1) Figure 1B: the orangutan tubulin stain looks a bit unusual - just confirming that this is indeed the right image the authors want to include here.
We agree, this unfortunately also reflects the findings from the scRNA-seq analysis in that we found hardly any cells that we would classify as proper neurons.
(2) Typo on line 90: 'loosing' should be 'losing'.
Fixed
(3) Line 118: why do the authors believe that using singleR will give better results than MetaNeighbour? This certainly seems supported by the data in S4 and S5, but the reasoning is not clear.
We think that this might depend on the signal to noise ratio, which is a property specific to each dataset. Here we just wanted to state that our approach seems to work better for our developmental data, but we didn’t test out other data and thus cannot generalize.
(4) Figure 2B: there are some coloured lines on the first filled black bar from the left - do they mean anything? I couldn't work it out from looking at the figure.
Indeed this is a bit misleading the colors on the left represent the species identity: this was to illustrate the mixing of the of species for each cell type: The legend reads now: “Each line represents a cell which are colored by their species of origin on the left and by their current cell type assignment during the annotation procedure on the right.”
(5) Figure 3: I did not understand how the seven bins of the cell type specificity metric were derived until much later - it is just the number of cell types in which a gene is expressed, yes? Might be worth making this clearer earlier in the text.
We made this more explicit in the legend. “Boxplot of expression conservation of genes according to the number of different cell types in which a gene is expressed in humans (cell type specificity).”
(6) It would be great to provide a bit more thorough documentation for the shiny app, so it can serve as a stand-alone resource and not require going back and forth with the paper to make sure one knows what one is doing at every point.
Agree, this would be a good idea. We are on it.
(7) Line 477: I think this is unclear - the authors retain over 11000 cells per species but then set the maximum number of cells in a cluster for pairwise comparison to 250... which is a lot fewer. What happens to all the other cells? This probably needs some rewriting to clarify it.
We did this to minimize the power differences due to cell numbers and thus make the results more comparable across species. We added this explanation to the methods section for Marker gene detection.
Reviewer #2 (Recommendations for the authors):
How was the clustering resolution (0.1) determined?
This resolution was only used for the initial rough check up of the germ layers as reported in Figure 1 and Supplementary Figures S3. We chose this resolution because it yielded roughly the same number of clusters as the number of cell types that we got from classification with the Rhodes et al data.
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I’m focused on supporting student and faculty publishing, which takes various forms.
Does this include mental health?
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eLife Assessment
Varani et al present important findings regarding the role of distinct cerebellothalamic connections in motor learning and performance. The evidence supporting the main claims is convincing, with multiple replications, validation of their techniques, and appropriate controls. The work will be of broad interest to neuroscientists interested in central mechanisms of motor learning and control, as well as thalamic physiology.
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Reviewer #2 (Public review):
Summary:
This study examines the contribution of cerebello-thalamic pathways to motor skill learning and consolidation in an accelerating rotarod task. The authors use chemogenetic silencing to manipulate activity of cerebellar nuclei neurons projecting to two thalamic subregions that target motor cortex and striatum. By silencing these pathways during different phases of task acquisition (during task vs after task), the authors report valuable finding of the involvement of these cerebellar pathways in learning and consolidation.
Strengths:
The experiments are well-executed. The authors perform multiple controls and careful analysis to solidly rule out any gross motor deficits caused by their cerebellar nuclei manipulation. The finding that cerebellar projections to the thalamus are required for learning and execution of the accelerating rotarod task adds to a growing body of literature on the interactions between the cerebellum, motor cortex, and basal ganglia during motor learning. The finding that silencing the cerebellar nuclei after task impairs consolidation of the learned skill is interesting.
Revision comment:
The revised manuscript is improved in clarity and methodological detail. An important addition is the retrograde labeling data showing a degree of anatomical segregation between CN->CL and CN->VAL pathways that strengthens their reported different functional roles. I still think that potential effects on motor execution when cerebellar nuclei are silenced during task performance may complicate interpretations specifically related to learning. However, the evidence supporting a role of the cerebellar nuclei in off-line consolidation is convincing.
Overall, the study outlines a multifaceted role of the cerebellum in motor learning, consolidation, and execution. The demonstration that cerebellar projections to distinct forebrain structures contribute to these processes is significant.
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Reviewer #3 (Public review):
Summary:
Varani et al present important findings regarding the role of distinct cerebellothalamic connections in motor learning and performance. Their key findings are that: 1) cerebellothalamic connections are important for learning motor skills, 2) cerebellar efferents specifically to the central lateral (CL) thalamus are important for short-term learning, 3) cerebellar efferents specifically to the ventral anterior lateral (VAL) complex are important for offline consolidation of learned skills, and 4) that once a skill is acquired, cerebellothalamic connections become important for online task performance. The authors went to great lengths to separate effects on motor performance from learning, for the most part successfully. While one could argue about some of the specifics, there is little doubt that the CN-CL and CN-VAL pathways play distinct roles in motor learning and performance. An important next step will be to dissect the downstream mechanisms by which these cerebellothalamic pathways mediate motor learning and adaptation.
Strengths:
(1) The dissociation between on-line learning through CN-CL and offline consolidation through CN-VAL is convincing.
(2) The ability to tease learning apart from performance using their titrated chemogenetic approach is impressive. In particular, their use of multiple motor assays to demonstrate preserved motor function and balance is an important control.
(3) The evidence supporting the main claims is convincing, with multiple replications of the findings and appropriate controls.
(4) The retrograde tracing experiments (Supplementary Figure 5) demonstrate convincingly that the CN-VAL and CN-CL projections are almost entirely segregated,
Weaknesses:
(1) Despite the care the authors took to demonstrate that their chemogenetic approach does not impair online performance, there is (as they acknowledge in the Discussion) impaired rotarod performance at fixed higher speeds in Supplementary Figure 4f for CN-VAL projections, suggesting that there could be subtle changes in motor performance below the level of detection of their assays. There is also a trend in the same direction that did not pass significance for CN-CL at higher speeds, suggesting that part of the effects could be related to subtle deficits in performance.
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Author response:
The following is the authors’ response to the original reviews.
eLife Assessment
This study provides evidence that cerebellar projections to the thalamus are required for learning and execution of motor skills in the accelerating rotarod task. This important study adds to a growing body of literature on the interactions between the cerebellum, motor cortex, and basal ganglia during motor learning. The data presentation is generally sound, especially the main observations, with some limitations in describing the statistical methods and a lack of support for two separate cerebello-thalamic pathways, which is incomplete in supporting the overall claim.
We completed the MS by adding a double retrograde labelling study showing that the two pathways have limited overlap and by addressing the other concerns.
Public Reviews:
Reviewer #1 (Public review):
This is an interesting manuscript tackling the issue of whether subcircuits of the cerebellum are differentially involved in processes of motor performance, learning, or learning consolidation. The authors focus on cerebellar outputs to the ventrolateral thalamus (VL) and to the centrolateral thalamus (CL), since these thalamic nuclei project to the motor cortex and striatum respectively, and thus might be expected to participate in diverse components of motor control and learning. In mice challenged with an accelerating rotarod, the investigators reduce cerebellar output either broadly, or in projection-specific populations, with CNO targeting DREADD-expressing neurons. They first establish that there are not major control deficits with the treatment regime, finding no differences in basic locomotor behavior, grid test, and fixed-speed rotarod. This is interpreted to allow them to differentiate control from learning, and their inter-relationships. These manipulations are coupled with chronic electrophysiological recordings targeted to the cerebellar nuclei (CN) to control for the efficacy of the CNO manipulation. I found the manuscript intriguing, offering much food for thought, and am confident that it will influence further work on motor learning consolidation. The issue of motor consolidation supported by the cerebellum is timely and interesting, and the claims are novel. There are some limitations to the data presentation and claims, highlighted below, which, if amended, would improve the manuscript.
We thank the reviewer for the positive comments and insightful critics.
(1) Statistical analyses: There is too little information provided about how the Deming regressions, mean points, slopes, and intercepts were compared across conditions. This is important since in the heart of the study when the effects of inactivating CL- vs VL- projecting neurons are being compared to control performance, these statistical methods become paramount. Details of these comparisons and their assumptions should be added to the Methods section. As it stands I barely see information about these tests, and only in the figure legends. I would also like the authors to describe whether there is a criterion for significance in a given correlation to be then compared to another. If I have a weak correlation for a regression model that is non-significant, I would not want to 'compare' that regression to another one since it is already a weak model. The authors should comment on the inclusion criteria for using statistics on regression models.
We thank the reviewer for pointing out this weakness of description. The description of the Methods has thus been expanded and better justified in the “Quantification and statistical analysis” section.
We agree with the reviewer that comparison between Deming regressions would be fragile due to the weakness of these regression in treatment groups (while they are quite robust for control groups) and they are not included in the MS, although Deming regression coefficients with their confidence intervals are now provided for all groups in the statistical tables. As now more clearly explained in the Methods, the comparisons between groups are based on the distribution of residuals around regressions of the control regression lines. If we understand correctly the reviewer’s request, the control groups are all included.
(2) The introduction makes the claim that the cerebellar feedback to the forebrain and cortex are functionally segregated. I interpreted this to mean that the cerebellar output neurons are known to project to either VL or CL exclusively (i.e. they do not collateralize). I was unaware of this knowledge and could find no support for the claim in the references provided (Proville 2014; Hintzer 2018; Bosan 2013). Either I am confused as to the authors' meaning or the claim is inaccurate. This point is broader however than some confusion about citation.
The references are not cited in the context of collaterals from the DCN but for the output channels of the basal ganglia and cerebellum: “They [basal ganglia and cerebellum] send projections back to the cortex via anatomically and functionally segregated channels, which are relayed by predominantly non-overlapping thalamic regions (Bostan, Dum et al. 2013, Proville, Spolidoro et al. 2014, Hintzen, Pelzer et al. 2018).” Indeed, the thalamic compartments targeted by the basal ganglia and cerebellum are distinct, and in the Proville 2014, we showed some functional segregation of the cerebello-cortical projections (whisker vs orofacial ascending projections). Hintzen et al. have indeed performed an extensive review indicating the limited overlap between cerebellar- and basal ganglia-recipient territories. The sentence has been corrected to clarify what the “They” referred to.
The study assumes that the CN-CL population and CN-VL population are distinct cells, but to my knowledge, this has not been established. It is difficult to make sense of the data if they are entirely the same populations, unless projection topography differs, but in any event, it is critical to clarify this point: are these different cell types from the nuclei? how has that been rigorously established?; is there overlap? No overlap? Etc. Results should be interpreted in light of the level of this knowledge of the anatomy in the mouse or rat.
There is indeed a paragraph devoted to the discussion of this point (last part of the section “A specific impact on learning of CL-projecting CN neurons.”). Briefly, we actually know from the literature that there is a degree of collateralization (CN neurons projecting to both VAL and CL, see refs cited above), but as the reviewer says, it does not seem logically possible that the exact same population would have different effects, which are very distinct during the first learning days. The only possible explanation is the CN-CL and CN-VAL infections recruit somewhat different populations of neurons. We have now added more experiments to support our finding using retrograde infections using two rAAV viruses expressing red and green fluorescent reporter. These experiments confirm the limited overlap of the two populations of interest obtained by retrograde infection. We feel thus confident that while some CN neurons may project to both structures, retrograde infection strategies thus appear to differentially infect CN populations.
(3) It is commendable that the authors perform electrophysiology to validate DREADD/CNO. So many investigators don't bother and I really appreciate these data. Would the authors please show the 'wash' in Figure 1a, so that we can see the recovery of the spiking hash after CNO is cleared from the system? This would provide confidence that the signal is not disappearing for reasons of electrode instability or tissue damage/ other.
The recordings were not extended to the wash period, but examination of the firing rate before CNO on successive days did not evidence major changes in the population firing rate (this is now shown in a new supplementary figure 6).
(4) I don't think that the "Learning" and "Maintenance" terminology is very helpful and in fact may sow confusion. I would recommend that the authors use a day range " Days 1-3 vs 4-7" or similar, to refer to these epochs. The terminology chosen begs for careful validation, definitions, etc, and seems like it is unlikely uniform across all animals, thus it seems more appropriate to just report it straight, defining the epochs by day. Such original terminology could still be used in the Discussion, with appropriate caveats.
Since reference to these time windows is repeatedly used in the text we have shifted to “Early” and “Late” phase terminology.
(5) Minor, but, on the top of page 14 in the Results, the text states, "Suggesting the presence of a 'critical period' in the consolidation of the task." I think this is a non-standard use of 'critical period' and should be removed. If kept, the authors must define what they mean specifically and provide sufficient additional analyses to support the idea. As it stands, the point will sow confusion.
This has been corrected to: “suggesting the cerebellar contribution to the consolidation of the task is critical early in the learning process and cannot be easily reinstated later”
Reviewer #2 (Public review):
Summary:
This study examines the contribution of cerebello-thalamic pathways to motor skill learning and consolidation in an accelerating rotarod task. The authors use chemogenetic silencing to manipulate the activity of cerebellar nuclei neurons projecting to two thalamic subregions that target the motor cortex and striatum. By silencing these pathways during different phases of task acquisition (during the task vs after the task), the authors report valuable findings of the involvement of these cerebellar pathways in learning and consolidation.
Strengths:
The experiments are well-executed. The authors perform multiple controls and careful analysis to solidly rule out any gross motor deficits caused by their cerebellar nuclei manipulation. The finding that cerebellar projections to the thalamus are required for learning and execution of the accelerating rotarod task adds to a growing body of literature on the interactions between the cerebellum, motor cortex, and basal ganglia during motor learning. The finding that silencing the cerebellar nuclei after a task impairs the consolidation of the learned skill is interesting.
We thank the reviewer for the positive comments and insightful critics below.
Weaknesses:
While the controls for a lack of gross motor deficit are solid, the data seem to show some motor execution deficit when cerebellar nuclei are silenced during task performance. This deficit could potentially impact learning when cerebellar nuclei are silenced during task acquisition.
One of our key controls are the tests of the treatment on fixed speed rotarod, which provides the closest conditions to the ones found in the accelerating rotarod (the main difference between the protocols being the slow steady acceleration of rod rotation in the accelerating version). Indeed, small but measurable deficits are found at the highest speed in the fixed speed rotarod in the CN-VAL group, while there was no measurable effect on the CN-CL group, which actually shows lower performances from the second day of learning; we believe this supports our claim that the CN-CL inhibition impacted more the learning process than the motor coordination. In contrast, the CN-VAL group only showed significantly lower performance on day 4 consistent with intact learning abilities. Yet, under CNO, CN-VAL mice could stay for more than a minute and half at 20rpm, while in average they fell from the accelerating rotarod as soon as the rotarod reached the speed of ~19rpm (130s). Overall, we focused our argument on the first days of learning where the differences between the groups are more pronounced. We clarified the discussion (section “A specific impact on learning of CL-projecting CN neurons.”)
Separately, I find the support for two separate cerebello-thalamic pathways incomplete. The data presented do not clearly show the two pathways are anatomically parallel. The difference in behavioral deficits caused by manipulating these pathways also appears subtle.
There is indeed a paragraph devoted to the discussion of this point (last part of the section “A specific impact on learning of CL-projecting CN neurons.”). Briefly, we actually know from the literature that there is a degree of collateralization (CN neurons projecting to both VAL and CL, see refs cited above), but it does not seem logically possible that the exact same population would have different effects, which are very distinct during the first learning days. The only possible explanation is the CN-CL and CN-VAL infections recruit somewhat different populations of neurons. We have now added more experiments to support our finding using retrograde infections using two rAAV viruses expressing red and green fluorescent reporter. These experiments confirm the limited overlap of the two populations of interest obtained by retrograde infection. We feel thus confident that while some CN neurons may project to both structures, retrograde infection strategies thus appear to differentially infect CN populations.
While we agree that after 3-4 days of learning the difference between the groups becomes elusive, we respectfully disagree with the reviewer that in the early stages these differences are negligible.
Reviewer #3 (Public review):
Summary:
Varani et al present important findings regarding the role of distinct cerebellothalamic connections in motor learning and performance. Their key findings are that:
(1) Cerebellothalamic connections are important for learning motor skills
(2) Cerebellar efferents specifically to the central lateral (CL) thalamus are important for shortterm learning
(3) Cerebellar efferents specifically to the ventral anterior lateral (VAL) complex are important for offline consolidation of learned skills, and
(4) That once a skill is acquired, cerebellothalamic connections become important for online task performance.
The authors went to great lengths to separate effects on motor performance from learning, for the most part successfully. While one could argue about some of the specifics, there is little doubt that the CN-CL and CN-VAL pathways play distinct roles in motor learning and performance. An important next step will be to dissect the downstream mechanisms by which these cerebellothalamic pathways mediate motor learning and adaptation.
Strengths:
(1) The dissociation between online learning through CN-CL and offline consolidation through CN-VAL is convincing.
(2) The ability to tease learning apart from performance using their titrated chemogenetic approach is impressive. In particular, their use of multiple motor assays to demonstrate preserved motor function and balance is an important control.
(3) The evidence supporting the main claims is convincing, with multiple replications of the findings and appropriate controls.
We thank the reviewer for the positive comments and insightful critics below.
Weaknesses:
(1) Despite the care the authors took to demonstrate that their chemogenetic approach does not impair online performance, there is a trend towards impaired rotarod performance at higher speeds in Supplementary Figure 4f, suggesting that there could be subtle changes in motor performance below the level of detection of their assays.
This is now better acknowledged in the discussion in the section “A specific impact on learning of CL-projecting CN neurons.” However, we want to underline that the strongest deficit in learning is found in animals with CN->CL inhibition which latency to fall saturates at about 100s on the rotarod; this indicates that mice fall as soon as the accelerating rotarod speed reaches about 16rpm. In fixed speed rotarod, the inhibition of CN->CL neurons shows not even a trend of difference at 15rpm with control mice, and the animals run 2 minutes without falling at this speed. This makes us confident that the CN->CL pathway interfers more with the learning than with the actual locomotor function on the rotarod.
(2) There is likely some overlap between CN neurons projecting to VAL and CL, somewhat limiting the specificity of their conclusions.
This issue is treated in the discussion. (see also replies to reviewers 1 and 2 above). We added experiments with simultaneous retro-AAV infections in CL and VAL and the data are presented in Supplementary Figure 5. We found that retrograde infection targeted different populations of CN neurons; although collaterals in both CL and VAL may be present for (some of) these two populations of neurons, they are likely strongly biased toward one or the other thalamic regions, explaining the differential retrograde labelling in the CN. We hope these experiments will answer the reviewer’ s concern.
Recommendations for the authors:
Reviewer #2 (Recommendations for the authors):
(1) Multiple studies have reported on the effect of cerebellar nuclei (CN) manipulation on locomotion. Here the authors perform several controls and careful analysis to rule out gross motor deficits caused by DREADD-mediated CN silencing. As the authors point out in the discussion, part of the difference from prior studies could be the mild degree of inhibition here. However, it is possible that the CN inhibition here induces a subtle motor deficit and the accelerating rotarod task is challenging and more readily reveals this motor deficit, rather than a deficit in motor learning per se. Two pieces of data seem to suggest this:
(a) under CN inhibition during the task (Figure 1i), mice could never achieve the level of performance as mice under CN inhibition after the task, even after several days of training, which suggests the CN inhibition is interfering with task performance;
(b) in highly trained mice (after learning), applying the CN inhibition impaired performance to a similar extend as mice in Figure 1i (Figure 4).
Can the authors rule out the possibility that CN inhibition during the task is impairing motor execution rather than motor learning?
We do not rule out a contribution of impaired motor coordination at the highest speed (last paragraph of the section “A specific impact on learning of CL-projecting CN neurons.”). Indeed, most of our argument in favor of deficit in learning is primarily in the first days (Early phase), particularly for the CN->CL CNO group (Fig 3h). A crucial control in our work is the use of fixed speed rotarod, where no deficit is observed. The difference between the fixed and accelerating rotarod is rather minimal since the acceleration of the rotarod is rather small (0.12rpm/s for speed up to >20 rpm).
Interpreting the effect of treatment reversal is challenging. If the only effect of CNO was a motor deficit, the animals who learned under CNO should rapidly regain higher performance under saline, which is not observed. When switching from CNO to Saline after 7 days of training, it is difficult to disentangle which part is due to a crude motor deficit (which would not show in fixed speed rotarod), and which part is due to an unability to resume motor learning after the task has been (mis-)consolidated.
(2) The separation of the cerebellar pathways to the intralaminar thalamus (IL) and ventral thalamus (VAL) is not clear to me. It is not clear the CN neurons projecting to these nuclei are distinct. In addition, although IL projects to the striatum and VAL does not, both IL and VAL project to motor cortex. It is unclear to what extent these pathways can be separated. The argument for distinct pathways (as laid out in the discussion) is the distinct behavior deficits when manipulating these two pathways, but this difference seems subtle (point 3).
We now clarify that CN populations are different help to retrograde labelling experiments (new Suppl Fig 5). A discussion on the differences in IL and VAL projections is now discussed in the last paragraph of the section “A specific impact on learning of CL-projecting CN neurons.” Briefly, we argue that the despite some overlap of their targets, the profiles of the CL and VAL differ substantially.
(3) The pattern of behavioral deficits induced by CN->CL and CN->VAL neurons appear similar in Figure 3b-c and e-f. I have difficulty seeing how these data lead to the differences in the regression fits in panels 3g-k, which seem to show distinct patterns of performance change within and across sessions. One notable difference in Figure 3b-c and e-f seems to be that CN->VAL CNO treated mice exhibit lower performance on the very first trial for most days. Somehow, this pattern is present even after the CNO treatment is switched to saline (Figure 3f). I wonder if this data point is driving the difference. One control analysis the authors could do is to exclude the 1st trial and test if the effects are preserved.
Since the learning is cumulative and involves varying degree of consolidation it is indeed difficult to substantiate the difference from the average performance: a performance on day 3 may be limited by slow learning and perfect consolidation or good learning and imperfect consolidation. That is why we designed an analysis which takes into account the observed relationships between initial performance, within session gain of performance and acrosssession carry-over of this gain of performance (Fig 2). This analysis focuses on the first days of learning, before the performance plateau is reached in the CNO groups. While a clear deficit in consolidation is observed with full CN inhibition, this is not the case for the CN→CL CNO groups, despite their weaker performance after 3 days, similar to that seen with full CN inhibition. In contrast, normal learning is observed in the CN→VAL CNO group during these three days. The consolidation deficit in the CN→VAL CNO group is more subtle than in the CN CNO group and is indeed largely driven by the first data point. This is consistent with the idea that CN→VAL inhibition only partially impairs consolidation (compared to full CN inhibition), leaving some “savings” that allow rapid reacquisition.
(4) The quantification of locomotion in Figure S2 needs more information. What is linear movement? What is sigma? What is the alternation coefficient? These are not defined in the legends or the Methods as far as I can tell. Related to point 1 above, the authors should provide some analysis of the stride length and hindlimb to forelimb distance as measures of locomotion execution.
These measures were taken from Simon J Neurosci 2004 24(8):1987-1995 which is now cited and their description is now provided in the Methods.
Minor:
(5) To help readers follow the logic of experimental design, please explain why CNO was switched to saline after day 4 in Figures 1j, 3c, and f. Specifically, is the saline manipulation meant to test something as opposed to applying CNO throughout the entire course of the behavioral test?
Since we had no difference between the groups at the end of the Early phase, we decided to test whether the skill consolidated under CNO remained available when the CNO was removed (and it indeed was). This is now more clearly stated in the Results.
(6) I have difficulty understanding what is plotted in Figure 4b and d. The legend says the change in performance is calculated the same way as in Figure 2a, so the changes are presumably the regression slopes. But how are the regression slopes calculated for daily start (1st trial) and daily end (last trial)?
Skill level at the beginning and end of each trial correspond to the values of the regression line for abscissae values of trial 1 and trial 7 (green points). This has been added to the figure legend.
(7) Do CN-CL and CN-VAL neurons also project to other brain regions besides the thalamus? Might these pathways also contribute to learning and consolidation of the accelerating rotarod task? Please discuss.
This is now discussed in more detail in the last paragraph of the section “A specific impact on learning of CL-projecting CN neurons.”
Reviewer #3 (Recommendations for the authors):
(1) Please check the anatomic evidence for the strict dichotomy between intralaminar (specifically central lateral nucleus) nuclei projecting to the striatum and the ventral-anteriorlateral (VAL) complex projecting to the cortex. For example, while the Chen et al paper shows that there are cerebellar-intralaminar-striatal projections, it does not exclude intralaminar cortex projections, which have at least been demonstrated in rats. Similarly, VAL has projections to striatum (see, e.g., Smith et al, "The thalamostriatal system in normal and diseased states", Frontiers in Systems Neuroscience, 2014). It may be that some of these projections are stronger, but I don't think it's true that these pathways are as well-separated as the authors suggest. I also don't think this changes the fundamental conclusions but is important for potential mechanisms by which differential learning could occur and necessitate modification of Figure 5.
We have toned down the interpretation of CL and VAL relaying specifically to different brain structures and mostly put forward the duality of the pathways. The connections with the cortex are now discussed at the end of the section “A specific impact on learning of CL-projecting CN neurons.”
(2) Please provide more details on the spike sorting. By what metrics were single units declared to be well-separated? How many units were identified under each condition? What was the distribution of firing rates with and without CNO treatment? Are the units shown in panel 1f from before and after CNO as in panel E or are just 2 examples of isolated units? The units by themselves are not very helpful to the reader. Showing sample auto and/or crosscorrelograms for units recorded on the same electrode would be more helpful to show how well-isolated the units are.
Single units were considered well-isolated based on quantitative quality metrics computed after MountainSort 4 spike sorting (Phyton 3.8). Units were required to have a signal-to-noise ratio (SNR) greater than 5, inter-spike interval (ISI) violations less than 1%, an amplitude cutoff below 0.1, a presence ratio above 0.9, a firing rate greater than 0.1 Hz, and at least 50 detected spikes. In addition, units were assessed for temporal stability across the recording using autocorrelograms and presence over the recording, ensuring there were no prolonged periods of total inactivity. Units meeting these criteria were deemed well-separated and reliable for further analysis. This has been added to the Methods.
Cell numbers are provided with the statistics in the supplementary table for fig panel 1g. Panels are from the same unit before and after CNO. Example of auto- crosscorr- are provided in the new Supplementary Figure 6.
(3) Panel 2g - "firing rate modulation" is unclear. I think the authors are showing the mean firing rate with DREADD+CNO treatment divided by the mean firing rate in the pre-CNO condition for the same group (I couldn't find that in the Methods, my apologies if I missed it)? However, firing rate modulation to me means variability in firing rate within a recording. Perhaps "relative firing rate" or "% pre-CNO firing rate" would be clearer?
The definition has been added to the Method and the axis has been changed to ‘Change in FR induced by SAL/CNO’
(4) Figure 3f - why does consolidation appear to be impaired after the transition from CNO to saline between sessions, when in panel 1j suppressing the CN does not have a similar effect once CNO is switched to saline? Could this be driven by a small number of mice? Since a central conclusion of the paper is that CN-VAL connections are uniquely important for posttraining consolidation, this discrepancy is important to explain - if the results post-saline are spurious, how do we know that the results post-CNO aren't also spurious? Panels similar to Figure 4b and d showing all the data from the last/first trial of each session I think would be convincing.
Our results overall indicate that the overnight consolidation of the improvement in performance seem only effective in the early phase (as pointed out on the summary figure 5). We do not believe then that the saline results are spurious.
It can be seen indeed in the control groups of the figure 1; to make this more visible, we plot in Author response image 1 the difference between trial 7 and trial 1 the next day. An overnight drop in performance becomes visible in the late phase.
Author response image 1.
The decrement on the first trial in the first 3 days is visible for the majority of the mice. The plot asked by the reviewer is represented in the Author response image 2.
Author response image 2.
Minor points:
(5) In panel 1a, the solid yellow line obscures a lot of the image and I don't think adds anything.
We assume this was referring to a line on fig1d, which has been removed.
(6) Panel 2a - color selection could present problems for those with red-green color blindness.
This has been fixed.
(7) Supplementary Figure 3 - what are the arrows and arrowheads indicating?
These have been removed.
(8) In the Discussion: "Studies of cerebellar synaptic plasticity provide clearly support the involvement of cerebellum in rotarod learning..." Delete the word "provide"
This has been fixed
(9) "This indicates that either the distinct functional roles of VAL-projecting or CLprojecting." The second "of" should be "or", I think.
This has been fixed.
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Establishing sustainable economic development pathways
To edit.
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“My brothers, sisters, uncles, neighbors, streets, the bread ovens, schools, children going to schools ...we miss all of that, everything in Syria is precious to us” she says, with tears hovering in her eyes (Firpo). She also exposes the terrible living conditions there: “[W]e didn’t run away, Syria has become uninhabitable. Not even animals could live there. No power, no running water, no safety, and no security. You don’t know who to fight...even when you lock yourself away, you’re not safe...I was most scared of seeing my children die right in front of me” (Firpo).
This whole quote expresses how in Syria things are serious. They are asking for help, in need of support. The Syrian refugee says "I was most scared of seeing my children die right in front of me", this is putting an idea on how bad the conditions and what is happening out there.
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According to Goleman, what differentiates effective leaders from ineffective ones becomes their ability to control their own emotions and understand other people’s emotions, their internal motivation, and their social skills (Goleman, 2004).
What sets apart of successful leadership to incompetent leadership is emotional intelligence and empathy.
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eLife Assessment
In this valuable study, the authors report on an innovative chemostat propagation system to reduce eukaryotic viruses while retaining phages in mixtures used for FVTs (fecal virome transplant). The authors hypothesized that chemostat-propagated viromes could modulate the gut microbiota and reduce necrotizing enterocolitis (NEC) lesions while avoiding potential side effects, such as earlier onset of diarrhea. Although no effect on NEC could be demonstrated, the revised document addressed the other concerns and is much improved from its original version. The study is convincing in that it integrates in vitro fermentation, high-resolution metagenomics, immunogenicity assays, and in vivo validation, demonstrating the potential of FVT using eukaryotic-free virome-based therapeutics.
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Reviewer #1 (Public review):
Summary:
Fecal virome transfer (FVT) has the potential to take advantage of microbiome associated phages to treat diseases such as NEC. However, FVT is also associated with toxicity due to the presence of eukaryotic viruses in the mixture, which are difficult to filter out. The authors use a chemostat propagation system to reduce the presence of eukaryotic viruses (these become lost over time during culture). They show in pig models of NEC that chemostat propagation reduce the incidence of diarrhea induced by FVTs.
Strengths:
The authors report an innovative yet simple approach that has the potential to be useful for future applications. Most of the experiments are easy to follow and are performed well.
Weaknesses:
The biggest weakness is that the authors show that their technique addresses safety, but they are unable to demonstrate that they retain efficacy in their NEC model. This could be due to technical issues or perhaps the efficacy of FVT reported in the literature is not robust.
During the revision, the authors have acknowledged these limitations and added clarifications where necessary.
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Reviewer #2 (Public review):
The authors hypothesized that chemostat propagated viromes could modulate the GM and reduce NEC lesions while avoiding potential side effects, such as the earlier onset of diarrhea. This is interesting.
Major revision
(1) As authors said, the aim of the research is 'We hypothesized that chemostat propagated viromes could modulate the GM and reduce NEC lesions while avoiding potentialside effects, such as earlier onset of diarrhea'.
(a) For the efficacy, in Fig 5, there are no significance in stomach pathology and enterocolitis between groups, even between the control group and the experimental groups, is it because of the low incidence of NEC? This may affect the statistical power of the conclusions. And how can you draw the conclusion that chemostat can reduce NEC lesions?
(b) Lack of gross view pictures of animal tissues or any other pathological pictures is not convincing.
(c) For the safety, such as body weight development, FVT had no statistical significance with control, CVT and CVT-MO, so how can you draw the conclusion that chemostat can avoiding potentialside effects?
(d) The evidence to prove the decrease of eukaryotic viruses are not enough and quantitative.
(2) Fig 3F,
(a) How can a medium have 'the baseline viral content' ?
(b) Statistical significance of relative abundance of specific eukaryotic viral contigs between different times is unkown.
(c) Some of listed eukaryotic viruses, their hosts are not pigs, piglets or even human, so what's the meaning if these eukaryotic viruses decreased?
(3) In this study, pH 6.5 was selected as the pH value for chemostat cultivation, but considering the different adaptability of different bacteria to pH, it is recommended to further explore the effect of pH on bacteria and virus groups. In particular, it was optimized to maintain the growth of beneficial bacteria such as Lactobacillaceae and Bacteroides in order to improve the effect of chemostat cultivation.
(4) In some charts, the annotation of error lines, statistical significance markers (even 'ns' should be marked), etc., should be more standardized and clearer. And in your results section, the combination of pictures is messy, thus maybe you should do some recombination.
Comments on revisions:
(1) At the design level, the study posited "reduction of necrotizing enterocolitis (NEC)" as the primary hypothesis and endpoint. Yet neither of the two in-vivo experiments demonstrated any NEC-protective signal; Experiment 2 even showed a trend toward more severe gastric lesions. Although delayed onset of diarrhea can be listed as a secondary endpoint, its clinical significance is limited. The work remains a safety proof-of-concept and falls short of efficacy validation, yielding insufficient scientific value for publication.
(2) The manuscript postulates a link between the loss of Lactobacillaceae phages and the absence of NEC protection, but no reverse verification (e.g., re-introducing these phages or optimizing culture to retain them) was performed within the study.
(3) Culturing intestinal microbiota ex vivo is inherently challenging, owing to oxygen sensitivity, pH drift, nutrient depletion, and other factors. This study not only failed to demonstrate stable congruence between the cultured community and the original fecal inoculum, but also documented a marked loss of Lactobacillaceae and a 75 % drop in viral diversity. In the absence of any NEC-protective efficacy, the authors likewise provide no functional validation of phage viability (lysis assays, MOI determination, etc.). Consequently, the data are inadequate to support expectations of therapeutic benefit in vivo.
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Reviewer #3 (Public review):
This study investigated the in vitro amplification of donor fecal virus using chemostat culturing technology, aiming to reduce eukaryotic virus load while preserving bacteriophage community diversity, thereby optimizing the safety and efficacy of FVT. The research employed a preterm pig model to evaluate the effects of chemostat-propagated viromes (CVT) in preventing necrotizing enterocolitis (NEC) and mitigating adverse effects such as diarrhea.
Strengths:
(1) Enhanced Safety Profile:<br /> Chemostat cultivation effectively reduced eukaryotic virus load, thereby minimizing the potential infection risks associated with virome transplantation and offering a safer virome preparation method for clinical applications.
(2) Process Reproducibility:<br /> The chemostat system achieved stable amplification of bacteriophage communities (Bray-Curtis similarity >70%), mitigating the impact of donor fecal variability on therapeutic efficacy.
Comments on revision:
The authors have satisfactorily addressed all comments and concerns raised during the review process. The revised manuscript is clear, complete, and meets the standards of the journal.
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Author response:
The following is the authors’ response to the original reviews.
Public Reviews:
Reviewer #1 (Public review):
Summary:
Fecal virome transfer (FVT) has the potential to take advantage of microbiome associated phages to treat diseases such as NEC. However, FVT is also associated with toxicity due to the presence of eukaryotic viruses in the mixture, which are difficult to filter out. The authors use a chemostat propagation system to reduce the presence of eukaryotic viruses (these become lost over time during culture). They show in pig models of NEC that chemostat propagation reduce the incidence of diarrhea induced by FVTs.
Strengths:
The authors report an innovative yet simple approach that has the potential to be useful for future applications. Most of the experiments are easy to follow and performed well.
Weaknesses:
The biggest weakness is that the authors show that their technique addresses safety, but they are unable to demonstrate that they retain efficacy in their NEC model. This could be due to technical issues or perhaps the efficacy of FVT reported in the literature is not robust. If they cannot demonstrate efficacy of the chemostat propagated virome mixture, the value of the study is compromised.
We appreciate the reviewer’s assessment and fully acknowledge that our inability to demonstrate NEC protection by FVT is a limitation to the study. If technical issues cover the variability in disease phenotype in our animal model, which is of a spontaneous nature, then yes we fully agree. Issues with FVT preparation are however unlikely, as this is performed per protocol. The effect of FVT on NEC has hitherto only been demonstrated by our research group in two individual studies using separate donor fecal material, so it is indeed too early to speculate about robustness in FVT response. We have briefly mentioned this in the results (lines 563-565) and discussion (lines 777-779), but agree that it needs further elaboration. We have now revised the discussion and conclusion to better emphasize the extent and consequences of this limitation (lines 793-797 + lines 817-818). Importantly, we show that inclusion of specific nutrients, such as milk oligosaccharides, impacts the resulting propagated fecal-derived virome. One can argue that this is not surprising, but it has nevertheless not been shown before – and it opens up possibilities for future “tailor-made” fecal-derived viromes with predictable profiles and effects.
Even though we do not demonstrate an effect of the chemostat-propagated virome, we still believe that the study provides valuable insights as a proof-of-concept. Specifically, we demonstrate that in vitro chemostat propagation can significantly modulate the safety profile of FVT, while still driving changes in the microbiome, e.g., by decreasing C. perfringens.
The above issue is especially concerning because the chemostat propagation selected for bacteria that may not necessarily be the ones that harbor the beneficial phages. Without an understanding of exactly how FVT works, is it possible to make any conclusion about the usefulness of the chemostat approach?
The chemostat work was based on the idea that if we culture a fecal inoculum under suitable conditions, then the phageome would propagate alongside and allow for a scalable production method for standardized donor-independent FVT. We are cognizant that the chemostat end-culture diverged quite markedly from the fecal inoculum. In reality, such divergence is unavoidable when performing in vitro simulation of intestinal growth conditions. On the positive side, we showed that we could drive an expansion of Bacteroides spp. by supplementing the media with human milk oligosaccharides. We have previously shown that Bacteroides spp. engraft FMT recipients that are in turn protected from NEC. However, there is much room for refinement of the chemostat culture condition; i.e. to preserve the rich repertoire of lactobacilli from the inoculum e.g. by means of lowering the pH. Moreover, the loss of viral diversity in the chemostat end-culture also needs to be addressed, potentially by lowering the chemostat dilution-rate to allow the time for phage propagation. Based on these insights, we will in the near future invest heavily in improving the chemostat procedure to end up with a propagated fecal virome with better resemblance to the fecal inoculum.
Finally, can the authors rule out that their observations in THP-1 cells are driven by LPS or some other bacterial product in the media?
We thank the reviewer for raising this point. To minimize the influence of bacterial contaminants such as LPS or other small bacterial products, we implemented several steps during sample preparation. Specifically, we performed ultrafiltration using a 300 kDa molecular weight cut-off, which should remove small molecules, including LPS, bacterial metabolites, and other potential soluble immunomodulators. Hereafter, all viral preparations underwent endotoxin removal procedures prior to cell exposure. These precautions reduce the likelihood that our observed effects in THP-1 cells are attributable to bacterial products rather than viral components. This is explained in the referenced article (20), but we have now added the clarification to the Methods section of the revised manuscript (lines 222 and 227). The immune expression profile differs markedly between the viral preparations and the E. coli control, e.g. IFNG, TLR3, TLR8, making it highly likely that viral epitopes are the major drivers of the viral preparations with less impact by any potential bacterial epitope contaminant. This is now mentioned in the results section (line 541-543):
Reviewer #2 (Public review):
Major revision
(1) As authors state that the aim of the research is 'We hypothesized that chemostat propagated viromes could modulate the GM and reduce NEC lesions while avoiding potential side effects, such as earlier onset of diarrhea'.
(a) For the efficacy, in Fig 5, there are no significance in stomach pathology and enterocolitis between groups, even between control group and experimental groups, is it because of the low incidence of NEC? This may affect the statistical power of the conclusions. Therefore, it is unclear how one can draw the conclusion that chemostat can reduce NEC lesions?
Thank you for highlighting this important point. We fully agree and would like to clarify that it is not our intention to conclude that chemostat propagation reduces NEC lesions under the experimental settings within this paper. Rather, this was our initial hypothesis, which could not be confirmed. The unexpectedly low incidence of NEC across groups in Piglet Experiment 1 did not allow for a clear conclusion, but the second Piglet Experiment 2 failed to show a NEC-reducing effect. We have stated this important point in the following sections:
- Abstract (line 42-44): “However, these signatures were lost in recipients of chemostat-propagated viromes, and only minor microbiome effects and no NEC prevention were observed.”
- Results (line 699): “This highlights that while chemostat propagation effectively mitigates virus-associated diarrhea, the method needs further optimization to targt NEC.”
- Discussion (lines 773–775): “However, the MO-propagated chemostat virome did not increase Bacteroides or Parabacteroides spp. in the recipient’s gut, nor did it provide NEC protection.”
- We have rephrased this to emphasize the importance of Experiment 2.
- To avoid any potential misinterpretation, we have rephrased line 598 to reflect that we observed “a difference in the clinical side effect pattern” rather than implying efficacy.
- Furthermore, we have updated the summary title for Figure 8 (line 704) to clearly state: “MO-propagated virome modestly exacerbates gastric injury and fails to improve NEC.”
- Also, we have added the following section to the discussion (lines 793-797): “However, we acknowledge that the absence of demonstrated NEC prevention by the native donor virome is a significant limitation to conclusions regarding efficacy. Without a protective baseline, we cannot assess whether the virome efficacy was lost during chemostat propagation. Consequently, we cannot confirm or dismiss the hypothesis that chemostats can preserve a phage community capable of preventing NEC.”
- Lastly, we have updated the conclusion (lines 817-818): “However, as neither the chemostat-propagated viromes nor the native donor virome demonstrated NEC prevention, the efficacy of the chemostat approach remains inconclusive.”
- These changes should clarify that while the study demonstrates improved safety via reduced diarrhea, NEC efficacy was not obtained.
(b) More convincing pathology images would be helpful.
Since we did not observe a protective effect against NEC with either of the treatments, we opted not to include pathology images. However, extensive examples can be found in the cited paper (reference 37), which describes our NEC scoring methodology in the Methods section (lines 268-271): https://doi.org/10.1016/j.yexmp.2024.104936.
(c) For the safety, such as body weight development, FVT had no statistical significance difference from control, CVT, and CVT-MO, so how can you drawn the conclusion that chemostat can avoid potential side effects?
We appreciate the reviewer’s observation. To clarify, we do not claim that chemostat propagation completely avoids all potential side effects, but rather that it mitigates them. As shown in Fig. 5G, FVT recipients exhibited significantly reduced body weight gain compared to controls, CVT, and CVT-MO specifically on day 4, but not on day 5. This transient effect suggests that side effects such as reduced growth and early-onset diarrhea are delayed, not entirely prevented, by chemostat propagation. This is stated in the results section in lines 593-595. We also believe that this is consistent with the paper title and the conclusion that the chemostat process minimizes the adverse effects associated with native FVT (line 813).
(d) There is lack of evidence to convince the reader that there is a decrease of eukaryotic viruses. More quantitative data here would be useful.
Apart from the fact that it is impossible for eukaryotic viruses to shed in a system devoid of eukaryotic cells, and that the chemostat runs continuously exchanges the culture, thereby diluting any substance incapable of propagation, we agree that quantitative data to demonstrate a reduction of eukaryotic virus load is lacking.
However, in this case we believe the relative viral abundance data are almost as convincing. To make this even clearer, we have produced new graphs showing 1) the eukaryotic viral abundance relative to total viral abundance and 2) observed eukaryotic viral species, both after medium subtraction. Eukaryotic viral relative abundances decrease from around 0.4% to approach zero already in the batch phase, and similarly number of eukaryotic viral species decrease from around 10 in the fecal inoculum to zero midway through the chemostat phase. These new graphs are now part of Supplementary figure S3 B-C. Moreover, an error in the eukaryotic viral heatmaps presented in Figure 3F now means that the relative abundance of each sample (column) now sums up to 100%. Please also notice from the lower heatmap (where the virome signature of the medium is subtracted) that no eukaryotic viruses are identified from the sequencing data of the samples from the chemostat from 50 hours and onwards.
However, for future experiments we will consider adding a known quantity of a marker virus to the inoculum and monitoring its concentration (e.g., by qPCR) throughout the culture process. Importantly, if the resulting virome is meant for in vivo testing, this marker virus should be inert to the receiving organism.
(2) Questions regarding Fig 3F,
(a) How can the medium have 'the baseline viral content' ?
As we have previously seen persistent eukaryotic viral signals in metagenomics sequencing data from chemostat experiments, we sampled and sequenced the culture medium. As is seen from Figure 3F, this only concerns Dicistroviridae, as the patterns of the remaining eukaryotic viral signals before and after medium subtraction are virtually similar. For some reason, a component of the culture medium contains a genetic signal from this entity. Since all culture components are sterilized, it is most likely genomic traces that are then continuously supplied with the medium and appears in all culture samples. As it is unlikely to derive from intact viruses, the in vivo implications are deemed minimal.
(b) What is the statistical significance of relative abundance of specific eukaryotic viruses?
The same as any statistical comparison on single OTU level in a nucleotide sequencing dataset. As commented above, it does not prove a quantitative depletion of eukaryotic virus throughout the chemostat process but given the context a reduction in relative abundance supports the notion that eukaryotic viruses are indeed depleted when the culture medium is exchanged. The relevant question to us is: What is the magnitude of depletion? Which is particularly relevant since the clinical data indicates a delay and not a prevention of side effects after transplantation. Hence, as proposed above, the use of a marker virus would provide us with that answer.
(c) The hosts for some of the listed eukaryotic viruses are neither pigs or human, as such the significance of a decrease in these viruses to humans is unclear.
Dicistroviridae is not present in the inoculum and shows up only when medium is added. Picobirnavirus and Astrovirus are relevant mammalian intestinal viruses, whereas Smacoviridae is less well described (dois: 10.3389/fvets.2020.615293 and 10.3390/v8020042). Genomoviridae as a fungal virus indeed appears to be less relevant in the case of the mammalian intestine. Indeed, at any given time point in any given individual, be it a pig or a human, it would carry with it several viral species that are incapable of infecting it, most likely transiting after being ingested with food, or in the case of pigs through rummaging. It is no secret that we have been searching for a causative agent responsible for the clinical side effect patterns related with FVT, but there seems to be no consistent viral agent that is overabundant in diarrheal piglets. Hence, in this study, we are mostly interested in the proof-of-concept for overall eukaryotic virus reduction through chemostat propagation, and we believe we have presented data in support of this.
(3) In this study, pH 6.5 was selected as the pH value for chemostat cultivation, but considering the different adaptability of different bacteria to pH, it is recommended to further explore the effect of pH on bacteria and virus groups. In particular, it was optimized to maintain the growth of beneficial bacteria such as Lactobacillaceae and Bacteroides in order to improve the effect of chemostat cultivation.
We agree that pH is a key parameter in shaping microbial communities during chemostat cultivation. As noted, we selected pH 6.5 to balance physiological relevance and bacterial viability, but we acknowledge that this pH may not be optimal for supporting the growth of certain potentially beneficial taxa such as Lactobacillaceae. We explicitly address this in the discussion (lines 736–741), where we state that the selected pH may have limited engraftment and that future studies should investigate pH optimization to better support bacterial groups and improve the overall effectiveness of the cultivation system.
(4) Please improve the quality of the images, charts, error bars and statistical significance markers throughout and mark the n's. used in each experiment.
We have carefully reviewed all figures and could not identify any general image quality issues. If some specific images or panels appear unclear or problematic, we would appreciate it if the reviewer could point them out so we can address them directly.
Regarding sample sizes, the number of animals (n) is indicated in Fig. 5A and its legend, as well as in Fig. 8A. We have now also added this information to the legend of Fig. 8 for clarity.
To improve the clarity of statistical findings, we have added asterisks to denote significance in panels 6A, 6F, and 7A, as requested.
To improve the clarity of Fig. 3B, we have added a dashed line to separate LAC and LAC-MO.
Reviewer #3 (Public review):
Major revisions
This study investigated the in vitro amplification of donor fecal virus using chemostat culturing technology, aiming to reduce eukaryotic virus load while preserving bacteriophage community diversity, thereby optimizing the safety and efficacy of FVT. The research employed a preterm pig model to evaluate the effects of chemostat-propagated viromes (CVT) in preventing necrotizing enterocolitis (NEC) and mitigating adverse effects such as diarrhea.
Strengths:
Enhanced Safety Profile: Chemostat cultivation effectively reduced eukaryotic virus load, thereby minimizing the potential infection risks associated with virome transplantation and offering a safer virome preparation method for clinical applications.
Process Reproducibility: The chemostat system achieved stable amplification of bacteriophage communities (Bray-Curtis similarity >70%), mitigating the impact of donor fecal variability on therapeutic efficacy.
Weaknesses:
Loss of Phage Functionality: The chemostat cultivation resulted in a reduction in phage diversity (e.g., the loss of Lactobacillaceae phages), which may compromise their protective effects against NEC (potentially linked to the immunomodulatory functions of Lactobacilli). The authors should explicitly address this limitation in the discussion section, particularly if additional experiments cannot be conducted to resolve it within the current study.
We appreciate the reviewer’s concern and agree that the loss of phage diversity during chemostat cultivation, especially phages targeting Lactobacillaceae, is an important limitation with potential implications for NEC protection.
We already described the depletion of Lactobacillaceae in the chemostat and its implications in the discussion (lines 742-751 + 787-793), along with our plans to address this in future work by adjusting culture pH. However, we acknowledge that the significance of losing phage diversity deserves more explicit attention. Accordingly, we have expanded the discussion to highlight the possible consequences of this loss and its impact on phage functionality (see lines 758–762), as suggested by the reviewer.
Limitations in Experimental Design: The low incidence of NEC lesions in the control group reduced the statistical power of the study. This limitation undermines the ability to conclusively evaluate the efficacy and safety of the chemostat-propagated virome as a novel intervention for NEC. Future studies should optimize experimental conditions (e.g., using a more NEC-susceptible model or diet) to ensure adequate disease incidence for robust statistical comparisons.
We agree that the low NEC incidence in Experiment 1 limited the statistical power to evaluate efficacy. To address this, we designed Experiment 2 using a more NEC-inducing diet (formula 2), which resulted in a higher level of baseline lesions. This allowed for a more conclusive assessment, demonstrating that the MO-propagated chemostat virome did not provide NEC protection when using the donor feces and culture conditions applied in this experiment.
We acknowledge that this was too unclear in the original manuscript. Please see the response to the first comment by Reviewer 2, where we have highlighted several revisions to improve clarity.
However, we do believe the data are robust enough to conclude that the level of diarrhea — and thereby safety — was improved in the piglet model, which is why we chose to focus on this aspect in the paper’s title.
Recommendations for the authors:
Reviewer #3 (Recommendations for the authors):
The manuscript presents a well-structured study investigating the feasibility of using chemostat-based culturing of the fecal virome to reduce the transfer of eukaryotic viruses during fecal virome transfer (FVT). Utilizing both in vitro fermentation systems and a preterm piglet model, the authors explore whether this method could be a safer and equally effective alternative to raw FVT for treating neonatal intestinal diseases, such as necrotizing enterocolitis (NEC). This study introduces a novel mitigation strategy for FVT through chemostat fermentation. However, a significant revision is recommended before the manuscript can be considered for publication.
Major Changes:
- A central aim of the study was to assess whether chemostat-cultured viromes maintain protective effects against NEC. However, this key outcome remains "unresolved" due to the low incidence of NEC in the control group. The discussion should address this limitation.
We fully acknowledge this limitation and agree that our study cannot conclude whether the NEC effect of FVT was maintained without demonstrating an effect of this native virome. Please see our response to a similar concern raised by Reviewer 1, where we describe the revisions made to the discussion (lines 793-797) and conclusion (lines 817-818).
- The section on viral particle enrichment should be expanded and discussed in more detail. It would be beneficial to examine its efficiency in separating bacteria from viral-like particles (VLPs) compared to findings from previously reported studies. The authors should clarify the rationale behind the selected dose of VLPs used in the experiments and their role in virus engraftment results.
We selected the virome isolation method based on previous experiments within our lab, demonstrating efficient separation of bacteria and virus particles, using a 0.45 um filter syringe. Filtrates were quality assessed by fluorescence microscopy, showing absence of intact bacteria. Using a diverse mock virus community, we also showed a high degree of preservation of infective viruses in the FVT following the isolation procedures. We have now expanded the description of the separation method in the results section with a reference to this work (lines 188-190). We did however choose to increase the molecular weight cut off (MWCO) to enhance the exclusion of non-viral components.
We acknowledge that the rationale and importance of the VLP dose was lacking in the discussion. This has now been added (line 758-762).
- The viral richness of chemostat viromes was significantly lower than that of native feces. The authors should discuss how this may impact microbiome and virome outcomes.
We have included this point in the new section about VLP dose in the discussion. Please see lines 758-762.
- The immune response was assessed through THP-1 cells and a limited piglet cytokine panel. These may not fully represent the intestinal epithelial or mucosal immune responses. Thus, authors should acknowledge these limitations in the discussion section.
Thank you for the comment. The limitation of using THP-1 cells as an in vitro model is already acknowledged in the results section (line 545): “Since fecal-derived eukaryotic viruses mainly infect intestinal cells, an
in vivo stimulation may reveal a different response pattern. ”
The limited panel of porcine cytokines was not intended as a comprehensive assessment of the mucosal immune response, but rather as supportive data for NEC-associated inflammation, as we have previously demonstrated (reference 37: https://doi.org/10.1016/j.yexmp.2024.104936). To obtain a comprehensive view of the immune response, a few days after diarrhoea onset, we additionally performed RNA-Seq analyses of the intestinal lymph node.
- While the manuscript is comprehensive, it is also lengthy and text-heavy. Some sections could be condensed for clarity.
The manuscript has been through multiple revisions by authors. While it is indeed lengthy, we have removed non-essential information and redundancies and now feel that the balance between data, text, figures, and supplementary information is acceptable.
- Several figures (e.g., Figs. 1-5) contain significant data but need clearer summaries in their captions.
We appreciate the suggestion and have revised the captions for Figs. 1-8 to provide clearer, more informative summaries of the data they present.
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eLife Assessment
This important study combines microfluidic experiments with mathematical modeling to elucidate the reciprocal interplay between flow dynamics and biofilm growth and detachment. Using Pseudomonas aeruginosa as a model organism, the authors identify several key regimes and stages of biofilm development. Overall, the comparison between experimental observations of biofilm behavior under varying flow conditions and corresponding theoretical predictions forms a compelling understanding of the processes involved in biofilm dynamics. The results will be of interest to researchers studying biofilms and their technological and biological applications.
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Reviewer #1 (Public review):
Summary:
The paper investigates the interplay between fluid flow and biofilm development using Pseudomonas aeruginosa PAO1 in microfluidic channels. By combining experimental observations with mathematical modeling, the study identifies the significant impact of nutrient limitation and hydrodynamic forces on biofilm growth and detachment. The authors demonstrate that nutrient limitation drives the longitudinal distribution of biomass, while flow-induced detachment influences the maximum clogging and temporal dynamics. The study highlights that pressure buildup plays a critical role in biofilm detachment, leading to cyclic episodes of sloughing and regrowth. A stochastic model is used to describe the detachment process, capturing the apparent randomness of sloughing events. The findings offer insights into biofilm behavior during clogging and fouling, potentially relevant to infections, environmental processes, and engineering applications.
Strengths:
This paper demonstrates a strong integration of experimental work and mathematical modeling, providing a comprehensive understanding of biofilm dynamics in a straight microfluidic channel. The simplicity of the microchannel geometry allows for accurate modeling, and the findings have the potential to be applied to more complex geometries. The detailed analysis of nutrient limitation and its impact on biofilm growth offers valuable insights into the conditions that drive biofilm formation. The model effectively describes biofilm development across different stages, capturing both initial growth and cyclic detachment processes. While cyclic pressure buildup has been studied previously, the incorporation of a stochastic model to describe detachment events is a novel and significant contribution, capturing the complexity and randomness of biofilm behavior. Finally, the investigation of pressure buildup and its role in cyclic detachment and regrowth enhances our understanding of the mechanical forces at play, making the findings applicable to a wide range of technological and clinical contexts.
Weaknesses:
The study achieves its primary objective of combining experiments and modeling to elucidate the coupling between flow, biofilm growth, and detachment in a confined microfluidic channel. In the revised manuscript, the authors have clarified several methodological choices and underlying assumptions. The points below are best viewed not as weaknesses, but as aspects that define the scope of the approach.
• Biofilm porosity and permeability. The authors now discuss biofilm porosity and provide a clear rationale for neglecting permeability effects in their system, arguing that flow around dense biofilm structures dominates over flow through the matrix. While this assumption appears reasonable for the conditions explored, permeability effects are not explicitly modeled and could become relevant in less compact or more heterogeneous biofilms.
• Characterization of the EPS matrix. The role of the extracellular matrix is convincingly addressed using polysaccharide‑deficient mutants, which provides a strong and causal link between EPS composition and mechanical stability. At the same time, the absence of complementary biochemical or imaging‑based characterization means that spatial or temporal variations in EPS distribution are not directly resolved, limiting the level of structural details.
• Three‑dimensional interpretation of biofilm development. The authors clarify that three‑dimensional information is primarily obtained from pressure‑based measurements, with two‑dimensional imaging serving as a validation tool. This approach is coherent and supported by scaling arguments and reproducibility across experiments.
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Author response:
The following is the authors’ response to the original reviews.
We sincerely thank the reviewer for the thorough and constructive evaluation of our manuscript. We greatly appreciate the recognition of our work's strengths, particularly the integration of experiments and mathematical modeling, the stochastic framework for describing sloughing events, and the insights into pressure-driven detachment dynamics.
We have carefully considered each point raised and provide detailed responses below. In response to the reviewer's comments, we have revised the Methods section to better clarify our approach to three-dimensional assessment. We believe these revisions have improved the clarity of the manuscript.
Below, we address each of the specific concerns raised by the reviewer:
Public Reviews:
Reviewer #1 (Public review):
Weaknesses:<br /> The study achieves its primary goal of integrating experiments and modeling to understand the coupling between flow and biofilm growth and detachment in a microfluidic channel, but it should have highlighted the weaknesses of the methods. I list the ones that, in my opinion, are the main ones:
The study does not consider biofilm porosity, which could significantly affect the flow and forces exerted on the biofilm. Porosity could impact the boundary conditions, such as the no-slip condition, which should be validated experimentally.
Porosity is indeed a key component of biofilm structures, resulting from the polymeric nature of the EPS matrix, mechanical forces, and biological processes such as cell death or predation. When considering flow-biofilm interactions, this porosity may allow fluid flow through the biofilm, with reported permeability values spanning an extremely broad range from 1015 to 10-7 m2 (Kurz et al., 2023).
However, we argue that biofilm permeability is not the primary driver in our system:
(1) In microscopy visualization, our biofilms form dense structures where flow around the biofilm through narrow channels dominates over flow through the porous biofilm matrix.
(2) We performed microrheology experiments in these biofilms by imaging the Brownian motion of nanoparticles in the biofilm. Their trajectories indicate that, in our conditions, the viscoelastic flow of the biofilm itself largely dominates over the flow of culture medium through the biofilm matrix.
(3) We argue that the extreme variability in reported permeability values (spanning several orders of magnitude, Kurz et al., 2023) reflects not only differences in experimental systems, but also fundamental challenges in defining and measuring permeability for viscoelastoplastic biofilms (the biofilm itself is actually flowing). Given this uncertainty, incorporating permeability into our model would introduce parameters that cannot be reliably constrained from literature or independently measured in our setup. Our approach (i.e. treating the biofilm as impermeable and focusing on flow obstruction) avoids this parametrization complexity while successfully capturing the observed dynamics.
(4) Our model successfully predicts the observed scaling laws (φmax ∝ Q1/2, Fig. 7f) and hydraulic resistance dynamics (Fig. 3) without invoking permeability, suggesting that flow obstruction rather than flow penetration is the dominant mechanism.
Reference: Kurz, D. L.; Secchi, E.; Stocker, R.; Jimenez-Martinez, J. Morphogenesis of biofilms in porous media and control on hydrodynamics. Environ. Sci. Technol. 2023, 57 (14), 5666−5677.
The research suggests EPS development as a stage in biofilm growth but does not probe it using lectin staining. This makes it impossible to accurately assess the role of EPS in biofilm development and detachment processes.
We respectfully disagree that lectin staining is necessary to assess the role of EPS in our system, and we argue that our approach using genetic mutants is superior for the following reasons. Lectin staining has significant limitations. While widely used, lectin staining (e.g., concanavalin A) is non-specific (binding not only to EPS polysaccharides but also to bacterial cell surfaces) and is non-quantitative. It can confirm the presence of polysaccharides but cannot establish causal relationships between specific EPS components and mechanical properties or detachment dynamics. We performed preliminary experiments with ConA-rhodamine (data not shown), which showed widespread presence of polysaccharides. However, this provided limited insight beyond confirming EPS production, which is well-established for P. aeruginosa PAO1 biofilms. We employed a more rigorous genetic approach to directly assess the role of EPS composition. We used Δpel and Δpsl mutants (strains lacking key exopolysaccharides that are the primary structural components of the PAO1 matrix). Our results demonstrate that both mutants show significantly reduced maximum clogging compared to wild-type. The Δpsl mutant is particularly affected, with near-complete detachment at certain flow rates. These differences directly link EPS composition to mechanical stability and detachment dynamics. This genetic approach provides causal, quantitative evidence for the role of specific EPS components in biofilm development and detachment, information that lectin staining cannot provide. We believe this addresses the reviewer's concern more rigorously than lectin staining would.
While the force and flow are three-dimensional, the images are taken in two dimensions. The paper does not clearly explain how the 2D images are extrapolated to make 3D assessments, which could lead to inaccuracies.
We thank the reviewer for this important observation. We would like to clarify our methodological approach. Our primary three-dimensional measurement is the hydraulic resistance R(t), obtained from pressure drop measurements across the biofilm-containing channel section. This pressure-based measurement inherently captures the three-dimensional flow obstruction caused by the biofilm. We then employ a geometric model (uniform biofilm layer on all channel walls) to convert R(t) into volume fraction φ(t).
The two-dimensional fluorescence imaging serves to validate this model-based approach rather than being the basis for three-dimensional extrapolation. The uniform layer assumption is supported by three independent lines of evidence: (i) the excellent quantitative agreement between predicted and measured scaling laws (φmax ∝ Q1/2, Fig. 7f), obtained without adjustable parameters; (ii) the high reproducibility of φmax values across different flow rates and replicates; and (iii) the strong correlation between model-derived φ(t) from pressure measurements and integrated fluorescence intensity (Fig. 3b-d).
We have added clarifying text in the Methods section (subsection "Data analysis for the calculation of the hydraulic resistance and volume fraction") to better explain this approach and emphasize that pressure measurements provide the three-dimensional information, with the geometric model serving as the link to volume fraction.
Although the findings are tested using polysaccharide-deficient mutants, the results could have been analyzed in greater detail. A more thorough analysis would help to better understand the role of matrix composition on the stochastic model of detachment.
We thank the reviewer for this suggestion. Our mutant analysis demonstrates that Δpsl and Δpel strains have significantly reduced φmax and altered detachment dynamics compared to wild-type (Fig. 8), directly linking EPS composition to mechanical stability as predicted by our model. A rigorous quantitative connection between matrix composition and the stochastic parameters (interevent times, jump amplitudes) would require: (i) substantially more sloughing events for statistical power, (ii) independent mechanical characterization of each mutant, and (iii) a mechanistic model linking EPS composition to detachment parameters. We are currently developing microrheology approaches to characterize mutant mechanical properties, which could enable such refinement in future work.
However, this represents a substantial study beyond the scope of the current manuscript, which establishes the self-sustained sloughing-regrowth cycle and its stochastic nature. The mutant results serve their intended purpose: demonstrating that EPS composition affects detachment, consistent with our model's framework.
Reviewer #2 (Public review):
This manuscript develops well-controlled microfluidic experiments and mathematical modelling to resolve how the temporal development of P. aeruginosa biofilms is shaped by ambient flow. The experiment considers a simple rectangular channel on which a constant flow rate is applied and UV LEDs are used to confine the biofilm to a relatively small length of device. While there is often considerable geometrical complexity in confined environments and feedback between biofilm/flow (e.g. in porous media), these simplified conditions are much more amenable to analysis. A non-dimensional mathematical model that considers nutrient transport, biofilm growth and detachment is developed and used to interpret experimental data. Regimes with both gradual detachment and catastrophic sloughing are considered. The concentration of nutrients in the media is altered to resolve the effect of nutrient limitation. In addition, the role of a couple of major polysaccharide EPS components are explored with mutants, which leads results in line with previous studies.
There has been a vast amount of experimental and modelling work done on biofilms, but relatively rarely are the two linked together so tightly as in this paper. Predictions on influence of the non-dimensional Damkohler number on the longitudinal distribution of biofilm and functional dependence of flow on the maximum amount of biofilm (𝜙max) are demonstrated. The study reconfirms a number of previous works that showed the gradual detachment rate of biofilms scales with the square root of the shear stress. More challenging are the rapid biofilm detachment events where a large amount of biofilm is detached at once. These events occur are identified experimentally using an automated analysis pipeline and are fitted with probability distributions. The time between detachment events was fitted with a Gamma distribution and the amplitude of the detachment events was fitted with a log-normal distribution, however, it is not clear how good these fits are. Experimental data was then used as an input for a stochastic differential equation, but the output of this model is compared only qualitatively to that of the experiments. Overall, this paper does an admirable job of developing a well-constrained experiments and a tightly integrated mathematical framework through which to interpret them. However, the new insights this provides the underlying physical/biological mechanisms are relatively limited.
We thank the reviewer for the thorough evaluation of our work and for highlighting the tight integration between experiments and modeling. We appreciate the constructive feedback regarding the goodness-of-fit for the probability distributions.
To address the concern that "it is not clear how good these fits are," we have added quantile-quantile (Q-Q) plots for the Gamma distribution fits of inter-event times to the Supplementary Materials (Supplementary Figure S20). These plots demonstrate that the sample quantiles track the theoretical Gamma quantiles across all flow rates (0.2, 2, and 20 μL/min), indicating that the Gamma distribution provides a reasonable approximation of the overall distributional behavior. For detachment amplitudes, we selected the lognormal distribution based on the observed high skewness and kurtosis in the data, which are characteristic signatures of lognormal processes.
Formal goodness-of-fit tests (chi-square, Kolmogorov-Smirnov) yielded mixed results across datasets, passing for some while failing for others. This variability reflects inherent noise from measurements, discrete temporal sampling, automated detection thresholds, and intrinsic biological variability. Importantly, our goal is to capture essential distributional characteristics for input into the stochastic model, not to achieve perfect statistical fit across all individual datasets. The Q-Q plots confirm that these distributions provide reasonable approximations, and the qualitative agreement between model predictions and experimental observations validates this modeling approach. We have revised the Methods section to clarify this rationale.
We respectfully disagree that “new insights this provides the underlying physical/biological mechanisms are relatively limited.” Beyond confirming previous findings (e.g., scaling for gradual detachment), we believe our work provides several novel mechanistic insights. First, the Pe/Da criterion enables quantitative prediction of nutrient limitation regimes, allowing systematic decoupling of nutrient effects from other phenomena in biofilm studies. Second, we demonstrate that pressure, not shear, drives sloughing detachment events, a mechanism overlooked in previous studies where the notion of “shear-induced detachment” clearly dominates. Third, we show that sloughing-regrowth cycles occur even in single channels, establishing pressure-driven fluctuations as a signature of confined biofilm growth, independent of geometric complexity. Finally, the stochastic description of sloughing demonstrates that, while instantaneous biofilm states are irreproducible, the underlying randomness is predictable, therefore addressing a fundamental challenge in biofilm research.
Recommendations For The Authors:
Reviewer #1 (Recommendations For The Authors):
(1) In the abstract, I suggest clarifying the term "bacteria development." It is unclear if it refers to bacterial growth, biofilm formation, or biofilm detachment. The concept is expressed more clearly at the end of the Introduction.
We have modified the entire abstract to make it clearer. The abstract now explicitly establishes the key processes - growth ('nutrients necessary for growth', 'growing bacteria obstruct flow paths') and detachment ('mechanical stresses that cause detachment', 'flow-induced detachment', 'sloughing') - before using 'bacterial development' as a collective term to refer to these coupled spatiotemporal dynamics. We believe the abstract is now clear as written.
(2) Findings from Sanfilippo et al. (2019) were slightly questioned by Padron et al. (PNAS, 2023), who discovered that H2O2 transport is responsible for fro operon upregulation.
Thanks for the clarification, which is indeed significant. The new sentence now reads: Pseudomonas aeruginosa has been found to regulate the fro operon in response to flow-modulated H2O2 concentrations (Sanfilippo et al. 2019, Padron et al. 2023).
(3) Additionally, Kurz et al. (2022) account for pressure buildup as the mechanism controlling sloughing.
We respectfully disagree and note that Kurz et al. (2022) identify shear stress, not pressure buildup, as the primary mechanism controlling sloughing. Besides the title, key sentences include “opening was driven by a physical process and specifically by the shear forces associated with flow through the biofilm”, “The opening of the PFPs is driven by flow-induced shear stress, which increases as a PFP becomes narrower due to microbial growth, causing biofilm compression and rupture.” While pressure differences are measured as indicators of system state and do contribute to normal compression stresses, their mechanistic explanation emphasizes that narrowing PFPs experience increased shear rates that eventually exceed the biofilm's yield stress, triggering viscoplastic deformation and detachment. The pressure buildup is a hydraulic consequence of narrowing rather than the direct cause of sloughing. In contrast, our work demonstrates that in confined geometries, pressure differences generate tangential stresses at the biofilm-solid interface that directly drive detachment.
(4) The flow control strategy represented in Fig. 1 is not explained and should be detailed in the Methods section.
The methods section reads as follows. Inoculation and flow experiments BHI suspensions were adjusted at optical density at OD640nm= 0.2 (108 CFU/mL) and inoculated inside the microchannels from the outlet, up to approximately ¾ of the channel length in order to keep a clean inlet. The system was let at room temperature (25°C) for 3h under static conditions. Flow experiments were then performed at 0.02, 0.2, 2, 20 and 200 μL/min constant flow rates for 72h in the microchannels at room temperature. For the experiments at 0.2, 2, 20 and 200 μL/min, the fluidic system was based on a sterile culture medium reservoir pressurized by a pressure controller (Fluigent FlowEZ) and connected with a flow rate controller (Fluigent Flow unit). The flow rate was maintained constant by using a controller with a feedback loop adjusting the pressure in the liquid reservoir. The reservoir was connected to the chip using Tygon tubing (Saint Gobain Life Sciences Tygon™ ND 100-80) of 0.52 mm internal diameter and 1.52 mm external diameter, along with PEEK tubing (Cytiva Akta pure) with 0.25 mm inner diameter adapters for flow rate controller. The waste container was also pressurized by another independent pressure controller to reduce air bubble formation in the inlet part. For the experiments at 0.02 μL/min, we used an Harvard Phd2000 syringe pump for the flow.
(5) Including images of the actual biofilms formed in a portion of the channel would aid in understanding the analysis presented in Fig. 2.
Images are introduced later on (eg Figure 5). There is also supplementary material showing videos.
(6) The boundary conditions used to calculate the stress in the developed model should be discussed. The authors should specify why biofilm porosity is neglected.
We have added a detailed discussion in the supplementary (Section I.2).
(7) In the first section of the Results, the authors hypothesize that heterogeneity in biofilm development could be due to oxygen limitation. However, given the high oxygen permeability of PDMS, this hypothesis is later denied by their data. It would be prudent to avoid this hypothesis initially to streamline the presentation. Additionally, the authors should specify how oxygen levels at the inlet and outlet are measured.
We appreciate this comment and agree that streamlining would simplify the presentation. However, after careful consideration, we have chosen to retain the oxygen limitation hypothesis for the following reasons: (1) oxygen limitation is a frequently invoked mechanism in biofilm systems and deserves explicit consideration, (2) it is not immediately obvious that oxygen remains non-limiting in larger microchannels where transverse gradients could develop, and (3) systematically eliminating this plausible alternative hypothesis strengthens our mechanistic conclusion that BHI drives the observed heterogeneity. Regarding oxygen measurements: we did not directly measure dissolved oxygen concentrations. Our approach is only indirect.
(8) What is the standard deviation of the doubling time measured at different flows (page 9)?
We have indicated the standard deviation in the text. Note that the graph shows the SEM.
(9) What is the "zone of interest" in the channel mentioned on page 9?
We have added the following sentence to clarify: To further understand this effect, let us consider the mass balance of biofilm in the zone of interest -- the zone where biofilm grows in between the two UVC irradiation zones -- in the channel.
(10) Minor and major detachment events should be classified based on a defined threshold or criteria, and their frequency should be measured.
We appreciate the reviewer's concern about quantitative rigor. However, we respectfully disagree that imposing arbitrary thresholds to classify 'minor' vs. 'major' events would improve our analysis. Detachment events in our system span a continuum of magnitudes, and any threshold would be artificial and potentially misleading. Our quantitative characterization of detachment dynamics is provided through the statistical analysis of interevent times, which we show follow a gamma distribution. This stochastic framework captures the full spectrum of detachment behavior without requiring arbitrary binning. The terms 'minor' and 'major' in our manuscript are used qualitatively to illustrate the range of observed phenomena, not as formal classifications.
(11) Have the authors identified a reason for the peaks in the volume fraction in the Δpsl mutants at the highest flow rate?
The biofilm thickness following these sloughing events is below our detection limit, consistent with a residual layer of cells. However, these cells grow, leading to a time window where the fraction is measurable, before a new detachment event occurs. Our understanding is that the psl mutant forms a weaker matrix with a much lower threshold for sloughing.
(12) The fit of the probability density function for the relative density function does not match the data well. The authors should comment on this.
We have added quantile-quantile (Q-Q) plots for the Gamma distribution fits of inter-event times to the Supplementary Materials (Supplementary Figure S20). These plots demonstrate that the sample quantiles track the theoretical Gamma quantiles across all flow rates (0.2, 2, and 20 μL/min), indicating that the Gamma distribution provides a reasonable approximation of the overall distributional behavior. For detachment amplitudes, we selected the lognormal distribution based on the observed high skewness and kurtosis in the data, which are characteristic signatures of lognormal processes. Formal goodness-of-fit tests (chi-square, Kolmogorov-Smirnov) yielded mixed results across datasets, passing for some while failing for others. This variability reflects inherent noise from measurements, discrete temporal sampling, automated detection thresholds, and intrinsic biological variability. Importantly, our goal is to capture essential distributional characteristics for input into the stochastic model, not to achieve perfect statistical fit across all individual datasets. The Q-Q plots confirm that these distributions provide reasonable approximations, and the qualitative agreement between model predictions and experimental observations validates this modeling approach. We have revised the Methods section to clarify this rationale.
(13) Additionally, the simulated fraction appears very flat, with limited detachments compared to experiments. Why?
The model captures the essential dynamics of growth-detachment cycles, including the characteristic timescales and volume fraction ranges. Some event-to-event variability in the experimental data likely reflects biological stochasticity not captured by our current approach—for example, variations in local biofilm mechanical properties or matrix composition that affect the precise stress at which sloughing occurs. While incorporating such biological variability as a stochastic parameter would improve detailed agreement, it would require extensive additional characterization beyond the scope of this study. The current model successfully reproduces the key qualitative and semi-quantitative features of the system.
(14) The methods section should include a more detailed explanation of how the model was validated against experimental data.
Model validation was performed by comparing predicted biofilm volume fraction time series and sloughing event statistics against experimental observations across multiple flow rates. The model reproduces the characteristic growth-sloughing cycles, timescales, and steady-state volume fractions without additional parameter fitting beyond the experimentally measured distributions.
(15) It would be useful to include information on the reproducibility of the experiments and any variations observed between replicates.
Experiments were performed in N=3 biological replicates. Individual time series for all replicates are shown in Supplementary Figures, demonstrating consistent behavior across replicates.
(16) A discussion of the limitations of the study, particularly regarding the assumptions made in the modeling and their potential impact on the results, would strengthen the paper.
We have added a discussion on why we chose to neglect the porosity of the biofilm, and strengthened parts on the uniform biofilm layer assumption.
Reviewer #2 (Recommendations For The Authors):
Page 2: "A vast" —> "The vast"
Changed.
The text and line widths on many of the figures are far too small. I printed it out at normal size, but had to look at a PDF and magnify to actually see what the graphs are showing. Fig. 9c is particularly illegible.
Changed.
Fig. 1 caption "photonic" —> "optical"?
Changed
Can you spell out the actual mathematical definition of 𝜙 on page 5 when it is introduced? Currently it just says the "cross section volume fraction of the biofilm", but that seems potentially ambiguous. It is valid to say that this is "fraction of the cross section occupied by the biofilm"?
Changed
Bottom of page 5: can you state the physical interpretation of the assumption that M is bounded between 0 and 1. i.e. that growth is larger than detachment?
There is a comment on that in the paper. It reads “In assuming that M ∈ ]0, 1] and eliminating cases where M > 1, we have not considered situations of systematic detachment 𝜙equ = 0 for any value of the concentration, since this is not a situation that we encountered experimentally.” This comes just after presenting the expression on the only non-trivial steady-state, as it becomes easier to explain the consequences of the initial choice at this point.
Currently the choice of detachment initially used in the model is a bit confusing. You say that you are going to assume a (1-𝜙)-1 model for simplicity (bottom of page 5), but then later you find that the (1-𝜙)3/4 model is more accurate (page 16). Since the latter has already been confirmed in numerous other studies, why not start with that one from the beginning?
We thank the reviewer for this important question, which highlights an area where our presentation could be clearer. We did not find that the (1-φ)-3/4 model is "more accurate." Rather, we deliberately chose the (1-φ)-1 scaling because it captures pressure-induced detachment, which we hypothesized would dominate in confined flows where biofilms clog a large portion of the channel. The (1-φ)-3/4 scaling, widely used in previous studies, describes shear stress at the biofilm/fluid interface and was developed primarily for reactor systems where pressure effects are negligible. Our analysis on page 16 validates this choice by demonstrating that pressure stress indeed exceeds shear stress when volume fraction is large, which corresponds to late Stage I and all of Stage II precisely where our model is applied. The excellent quantitative agreement between predicted and measured φmax values across flow rates (Fig. 7f, Table 1) further supports the (1-φ)-1 scaling. We recognize that our initial presentation may have suggested the (1-φ)-1 choice was merely for "simplicity." We have revised this section to emphasize that this scaling was chosen specifically to capture pressure-driven detachment in confined geometries, with the physical justification provided by the stress analysis that follows. We have also clarified our ideas on page 16 to express clearly that (1-φ)-3/4 is never used. We could alternatively use a multi-modal detachment function combining both scalings, but the data do not require this additional complexity.
In general, the models you derived in this study could be better contrasted with that from previous works. e.g. can you compare your Eqn (4) with the steady-state solutions obtained by other previous studies? Is this consistent with previous works or different? (aside from framing the biofilm thickness in terms of 𝜙)
We are currently working on a paper dedicated to modeling biofilm development in confined flows, which will do a better job at comparing approaches.
Top of page 6 - you assume K* = 0.1 - Does this assume that cells grow at half the rate in 0.1X BHI as they do in 1X BHI? Has this been confirmed experimentally or is this just a guess?
This was estimated rather than measured directly. Model predictions were a lot more sensitive to the Damköhler number, than to the value of K.
"radial" is used widely in this paper, but you are using a square geometry. Is "transverse" a better choice?
Yes it clearly is. It’s been changed.
Fig 3. Are panels (a) and (b) showing different bioreps of the same condition? If so, please spell that out in the caption.
There was an error here in the caption of fig a. This has been changed. The correspondence is between a and c, and these are exactly the same, not bioreps.
In multiple places it noted that the change in hydraulic resistance is correlated with the "change in biofilm colonization." Why not demonstrate this directly using a cross correlation analysis? How is the latter connected to the 𝜙 parameter? (e.g. is this d(𝜙)/dt?)
We thank the reviewer for this suggestion. To clarify: φ(t) represents the volume fraction of biofilm in the channel. We measure this in two independent ways: (1) φ(t) from hydraulic resistance (black line in Fig. 3) i.e. calculated from pressure measurements using φ = 1 - √(R₀/R(t)), assuming uniform layer growth (see Methods section "Data analysis for the calculation of hydraulic resistance and volume fraction") and (2) φ(t) from fluorescence (green squares in Fig. 3) i.e. estimated from integrated GFP intensity or image segmentation of the glass/liquid interface. The reviewer is correct that we should quantify this relationship directly. We have now added correlation analysis between these two independent measurements of φ (new Supplementary Figure S21). The analysis shows strong positive correlation, with r-values ranged from 0.68 to 0.77 across all flow rates. This validates two key aspects of our approach: (1) the uniform layer assumption used to convert R(t) to φ(t) is reasonable, and (2) the pressure-based measurements accurately capture the dynamics visible in fluorescence imaging, including both growth phases and sloughing events. The strong agreement is particularly notable given that these measurements probe different aspects of the biofilm: hydraulic resistance is sensitive to the three-dimensional obstruction of flow, while fluorescence captures primarily the biofilm attached to the glass surface within our focal plane. Their correlation supports the model assumptions. We have revised the manuscript to clarify this relationship and present the correlation analysis.
Top of page 9 - a doubling time of 110 mins is reported in liquid culture - is this in shaken or static conditions? Can you provide some data on how this was calculated? (e.g. on a plate reader?) Do you think your measurements in the microfluidics could be affected by attachment/detachment of cells, rather than being solely driven by division. It is curious that your apparent growth rate varies by a factor of two across the different flow rates and there is not a monotonic dependency. Both attachment and detachment would depend on the flow rate (with some non-trivial dependencies).e.g. https://www.pnas.org/doi/10.1073/pnas.2307718120 https://doi.org/10.1016/j.bpj.2010.11.078
Given that your doubling time in the microfluidics is sole based on changes in cell number (rather than directly tracking cell divisions) it seems possible your results here are measuring the combined effect of growth, attachment and detachment, rather than just growth.
We agree with those comments regarding the doubling time measurement. We have added a description of how we performed the doubling time measurement in the Methods section.
Page 9 - you discuss the role of EPS here, but the effect of EPS is not demonstrated here and this is muddled with a discussion about the non-linearity of the putative dependency. Maybe this would be on a firmer footing if you save the discussion of EPS for the section on the Psl and Pel mutants?
Changed.
Middle of page 9: Please define what "smooth detachment" means and contrast it with catastrophic sloughing. Also, please define what you mean by "flow, seeding, and erosion" detachment are and how these three things differ from one another.
We have clearly defined each term in the revised version.
The results from wavelet scalograms seem to be underutilised and not well described. Can you clearly say what time series this analyses has been calculated on the caption? e.g. hydraulic resistance? Other than simply pointing out the "blue stripes", what can be gained from this analyses that could not be obtained with another method? It would be great if the basic features of this plot could more fully discussed (e.g. is the curved envelope at the bottom caused by edge effects?)
We have improved the text, captions and method section following the reviewer’s comment.
Fig. 5 a and b - please list the time at which each of these images were taken. Do these have the same dt between the two sets of images?
Yes the dt is the same (30 minutes). It’s been indicated in the caption.
Fig. 6: you have significant 2D variation in the biofilm width along the length of the channel. The relative contribution of pressure and shear based detachment will be different at different positions along the length. However, this variation is ignored in your model. Can you please comment on this in our manuscript and how it might affect the interpretation of your results? e.g. would the longitudinally averaged description yield the same result as one that takes the geometry into account (on average)?
Our model indeed assumes longitudinally averaged properties. A more detailed spatially resolved model would be valuable for capturing heterogeneities and will be explored in future work.
Bottom of page 11: you say standard deviations are in the range of 10-3. How does this jibe with the error bars on the middle flow rate in Fig. 7e?
This extremely low standard deviation only applies to the maximum value of 𝜙 and is a completely different measurement from the whisker boxes presented in fig7e.
Fig. 7: You are calculating the "Fraction" here. Is this "𝜙"? If so, can you put that on the y-axis instead? You calculate the volume fraction two different ways e.g. with hydraulic resistance and with imaging. Is only one of these shown in (e)? Is the same powerlaw dependence shown in (f) conserved when the other measurement of the "fraction" is used? Can you include both in Fig. 7e?
We have modified the axis and indicated 𝜙.
(e) is calculated only from hydraulic resistance. This is the most precise measurement to evaluate 𝜙 quantitatively.
Related to the previous comment: Some of the estimates of 𝜙max in Table 1 are obtained by fitting the model to integrated fluorescence data (Fig. 2b), while others are estimated from measurements of the hydraulic resistance. The former yields non-unique sets of parameters. Can the biofilm fraction instead actually be estimated directly from fluorescent imaging by segmenting biofilm and directly calculating how much of the cross section is occupied by cells on average across the length? This seems like a more direct measure of this quantity. Given there are multiple ways of estimating the same parameter, it would be better consistency checking to make sure that different methods actually yield the same result.
We have now added in Fig S21 a direct comparison of these two measurement methods. These are strongly correlated. Microscopy is more direct but only provides 2D pictures. Hydraulic resistance provides a 3D measurement, but relies on a model of biofilm distribution. Both are imperfect, but correlate well. In particular, we see that the 2D measurement does capture sloughing.
You cite a large number of supplemental figures (e.g. Fig. S21 on page 12), but the figures in your SI only go up to 11.
We have revised references to supplementary figures.
Bottom of page 11: Your data from liquid culture suggests that your psl mutant grows at half the rate of WT cells. Is that consistent with your microfluidic data (e.g. Fig. 8)? If not, might this be a sign that your growth rate analyses from the microfluidics might be affected by attachment/detachment? (see comment above) Psl cells should detach much more easily.
The approach taken to measure doubling times in the microfluidic system does not rely on the macroscopic measurements presented in figure 8, but rather on the approach presented in fig 4. These measurements require specific imaging (different magnification and time stepping) and we did not perform such experiments for the mutants.
In analyses of sloughing, you fit the times between the jumps and the relative amplitude. Are these two random variables correlated with one another? Might that influence your results? Your methods say that "jumps were identified through through the selection of local maxima" of the derivative. Do you to say "minima" here? Did you keep all local maxima/minima or did you have a threshold?
These are two random variables, not correlated with another. This is an assumption, and it would be interesting to analyze whether these are correlated. To perform this analysis, we believe that we would first need to acquire even more data and more replications to improve the statistical analysis.
Yes, it was minima (in the code we make everything positive, hence the confusion).
Yes, there is a threshold on the value of the jump itself. This value is extremely low and essentially filters out noise.
Fig. 9 - can you make it clearer in the caption what timeseries you are analysing here? I understand from the methods this that is the "volume fraction." The data/fits are difficult to see in Fig. 9 b and impossible to see in Fig. 9c because the green bars get in the way of the other two data sets. Can this visualisation be improved? It is not clear to me how good of a job the Gamma and log-normal fits are actually doing.
We have clarified that histograms are calculated from all experiments/replicates.
We have slightly modified the graph to make it clearer. This comparison is intrinsically hard, partly because it compares discrete data with continuous PDFs.
Aside from noting the results from the stochastic sloughing model are 'strikingly similar to experimental data', which seems to be based on a qualitative analysis of the lines in Fig. 7 d, e, and f. However, experimental data is not plotted in the same graph nor is the experimental data that we should be comparing this to cited in the text/caption.
We have added a note in the caption to indicate which figure it can be compared to.
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newhampshirebulletin.com newhampshirebulletin.com
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PFAS
Air and water pollutant
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cohenjer.github.io cohenjer.github.io
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python package spyrit
Une de plus en bonus ;)
@article{Abascal_2025, title = {{{SPyRiT}} 3.0: An Open Source Package for Single-Pixel Imaging Based on Deep Learning}, shorttitle = {{{SPyRiT}} 3.0}, author = {Abascal, J. and Baudier, T. and Phan, R. and Repetti, A. and Ducros, N.}, year = 2025, month = jun, journal = {Optics Express}, volume = {33}, number = {13}, pages = {27988--28005}, publisher = {Optica Publishing Group}, issn = {1094-4087}, doi = {10.1364/OE.559227}, urldate = {2025-07-14}, abstract = {Single-pixel imaging is able to acquire an image from a few point measurements thanks to dedicated reconstruction algorithms. In recent years, reconstruction approaches based on deep learning have outperformed most alternatives. However, computational experiments and data-driven methods have become difficult, if not impossible, to reproduce. The development of tools enabling reproducibility and benchmarking is therefore now essential. This paper describes SPyRiT, an open-source PyTorch-based toolbox capable of handling various simulation configurations and reconstruction methods based on deep learning. In particular, SPyRiT implements both existing and new supervised and plug-and-play methods, including post-processing and iterative strategies. Our reconstruction results demonstrate that supervised methods trained on simulated data can be successfully applied to experimental data when the signal-to-noise ratio of the measurements is higher or equal to that of the training phase. On the other hand, the hyperparameter of the plug-and-play methods can be tuned to manage lower signal-to-noise ratios. Among the supervised methods, DC-Net is found to be robust to deviations in the noise level, achieving similar results to plug-and-play methods without hyperparameter selection, while offering low memory requirements and short reconstruction times. The modularity of SPyRiT enables the rigorous benchmarking of reconstructions based on deep learning in single-pixel imaging, as well as in related fields such as ghost imaging. Thanks to its modularity and versatility, SPyRiT is suitable for further studies beyond this work and could also benefit other modalities in the field of computational optics.}, langid = {english}, keywords = {Computational imaging,Deep learning,Fluorescence lifetime imaging,Ghost imaging,Magnetic resonance imaging,Single pixel imaging}, file = {C:\Users\ducros\Zotero\storage\DZKXQLJL\Abascal et al. - 2025 - SPyRiT 3.0 an open source package for single-pixel imaging based on deep learning.pdf} }
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todo ask Nicolas better ref
Plutot celle-ci :
@article{BenetiMartins_2023, title = {{{OpenSpyrit}}: An Ecosystem for Open Single-Pixel Hyperspectral Imaging}, shorttitle = {{{OpenSpyrit}}}, author = {Beneti Martins, Guilherme and {Mahieu-Williame}, Laurent and Baudier, Thomas and Ducros, Nicolas}, year = 2023, month = may, journal = {Optics Express}, volume = {31}, number = {10}, pages = {15599}, issn = {1094-4087}, doi = {10.1364/OE.483937}, urldate = {2023-08-28}, abstract = {This paper describes OpenSpyrit, an open access and open source ecosystem for reproducible research in hyperspectral single-pixel imaging, composed of SPAS (a Python single-pixel acquisition software), SPYRIT (a Python single-pixel reconstruction toolkit) and SPIHIM (a single-pixel hyperspectral image collection). The proposed OpenSpyrit ecosystem responds to the need for reproducibility and benchmarking in single-pixel imaging by providing open data and open software. The SPIHIM collection, which is the first open-access FAIR dataset for hyperspectral single-pixel imaging, currently includes 140 raw measurements acquired using SPAS and the corresponding hypercubes reconstructed using SPYRIT. The hypercubes are reconstructed by both inverse Hadamard transformation of the raw data and using the denoised completion network (DC-Net), a data-driven reconstruction algorithm. The hypercubes obtained by inverse Hadamard transformation have a native size of 64\,\texttimes\,64\,\texttimes\,2048 for a spectral resolution of 2.3 nm and a spatial resolution that is comprised between 182.4 \textmu m and 15.2 \textmu m depending on the digital zoom. The hypercubes obtained using the DC-Net are reconstructed at an increased resolution of 128\,\texttimes\,128\,\texttimes\,2048. The OpenSpyrit ecosystem should constitute a reference to support benchmarking for future developments in single-pixel imaging.}, langid = {english}, file = {C\:\Users\ducros\Zotero\storage\NDYHKKKJ\Beneti Martins et al. - 2023 - OpenSpyrit an ecosystem for open single-pixel hyp.pdf;C\:\Users\ducros\Zotero\storage\PW824TZX\Beneti Martins et al. - 2023 - OpenSpyrit an ecosystem for open single-pixel hyperspectral imaging.pdf} }
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TODO ref Sloane 1978 cf article demander à Nicolas
See [Harwit_1979, section 3.5.4]
@book{Harwit_1979, title = {Hadamard {{Transform Optics}}}, author = {Harwit, Martin and Sloane, Neil J. A.}, year = 1979, publisher = {Academic Press}, isbn = {978-0-12-330050-8 0-12-330050-9} }
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www.jstor.org www.jstor.org
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. A disasters impact on childrenvaries based on their prior exposure totraumatic events, socioeconomic factors, age,gender, personality traits, cognitive skills,and relationships with their parents andfamilies
Page 10, disasters effects are affected by previous experiences.
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mutabit.com mutabit.com
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"Nunca he visto a gente pasar por alto la magnitud de lo que está sucedientdo tan gravemente como lo hacen ahora" Nicholas Negroponte. Predijo que el internet no haría nada menos que traer la paz mundial al derribar las fronteras nacionales.
Faltaría agregar el momento en la cual fue hecha la captura
Buena práctica de sacar la cita textual fuera de la imagen.
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Se inicia con la pregunta de ¿qué pasa si un medio pone en circulación ideas nuevas? y de cómo esto ha ocurrido desde hace mucho tiempo con varios de los inventos que fueron creados con el próposito de la paz mundial pero se enfatiza de que esto nunca se logró. Lo que llega a evidenciar que entre más ideas existas, habrían más ideas con las qque poder estar de acuerdo o no a nivel personal.
A esta idea, es pertinente especificar la marca del tiempo.
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Se inicia con la pregunta de ¿qué pasa si un medio pone en circulación ideas nuevas?
En realidad se inicia con la anécdota de Marga y su blog de comidas.
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chem.libretexts.org chem.libretexts.org
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uj-wellbeing-workshop.netlify.app uj-wellbeing-workshop.netlify.app
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discussion. SEGMENT 1 ~11:00 AM ET 25 min Stakeholder Problem Statement & Pivotal Questions Stakeholders present their WELLBY/DALY challenges (~10 min each), then we introduce key PQs for belief elicitation (~5 min) Speakers: Peter Hickman (Coefficient Giving), Matt Lerner (Founders Pledge) Upcoming
Here or somewhere early in the workshop, we should have the opportunity for participants to provide feedback about whether the Pivotal questions are clear and useful, and which ones are more important to their work and to the ~welfare of humanity.
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uj-wellbeing-workshop.netlify.app uj-wellbeing-workshop.netlify.app
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If the effectiveness of some programs have already been measured in terms of WELLBYs, while others are measured in terms of DALYs, what method or what "mapping structure or approach" should we use to compare and convert between them?
It might be too many questions on conversion here if the workshop's not focusing on conversion. We might want to move some of these more detailed questions to a second outlinked page.
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These are some of the key operationalized questions from our Wellbeing Pivotal Questions project. We want to elicit expert and stakeholder beliefs—before, during, and after reviewing the evidence and key arguments—to see how views evolve and where consensus exists. (All questions are optional.)
These have Metaculus versions. We probably want to link them here, but we also don't want to overwhelm people.
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📋 Full question specifications: For more detail, context, and the complete set of operationalized questions, see the canonical Wellbeing PQ formulations on Coda →
We link to these, but they might be a bit overwhelming for session participants - perhaps put a disclaimer here.
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k51qzi5uqu5dm9g6q2l275rmato8ce47dz8cn4di3nglvgpjqd93p2rubxv5t3.ipns.localhost:8080 k51qzi5uqu5dm9g6q2l275rmato8ce47dz8cn4di3nglvgpjqd93p2rubxv5t3.ipns.localhost:8080
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💻/asus/🧊/♖/indy
http://webui.ipfs.io.ipns.localhost:8080/#/files/%F0%9F%92%BB/asus/%F0%9F%A7%8A/%E2%99%96
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stylo.ecrituresnumeriques.ca stylo.ecrituresnumeriques.cauntitled1
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untitled
Ici il manque un titre
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Local file Local file
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by unscientific men
aorse than sceince
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Ridiculing the claim thatlanguage could serve as an accurate proxy for race, the Court retortedthat “history has witnessed the adoption of the English tongue by mil-lions of Negroes, whose descendants can never be classified racially withthe descendants of white persons notwithstanding both may speak a com-mon root language.
thwy do all this and stil..
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www.google.com www.google.com
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popups2.lib.uliege.be popups2.lib.uliege.be
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Ceci est une note de page Je fais de la mise en page
et je fais des citations
J'ajoute un lien
Et une image :
- Une liste numérotée
- une liste à puce
Et je mentionne @jdumont83
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stylo.ecrituresnumeriques.ca stylo.ecrituresnumeriques.ca
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2025
Attention, la date sur la page web indique que la publication a eu lieu de 13 février 2025. Or, dans la référence écrite originale, la date mentionnée était le 05 mars 2024.
J'ignore s'il y a eu des mises à jour entre temps qui ont pu causé un changement de date dans la page. En tous les cas, j'ai privilégié la date du 13 février 2025 pour que les informations du site et de la bibliographie soient homogènes.
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theconversation.com theconversation.com
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Il s’agit du multitasking
Il s'agit du premier comportement présenté comme nouveau en conséquence de l'hyperconnexion.
Dans ce paragraphe, l'auteur met en lumière les conséquence négatives : perte de concentration, perte d'efficacité et diminution de l'engagement dans le travail au profit des loisirs. Mais ces arguments ne sont appuyés ni par des faits ni par des données empiriques.
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