Women are more reluctant than men to ask for deadline extensions

Women are less likely than men to ask for more time to complete projects with adjustable deadlines at work or school, new research finds.

Compared to men, women were more concerned that they would be burdening others by asking for an extension, and that they would be seen as incompetent, the study showed.

Prior research has shown that women feel more time stress than men do, and feeling uncomfortable about asking for more time to complete projects may be one important reason why, said Grant Donnelly, co-author of the study and assistant professor of marketing at The Ohio State University’s Fisher College of Business.

“Women understandably feel like they have too many things to do and not enough time to do them. We found that not asking for more time to complete tasks undermines women’s well-being and also their performance,” Donnelly said.

“But we also found a possible solution: Women were as likely to ask for deadline extensions as men when organizations had formal policies on making deadline extension requests.”

Donnelly conducted the research with Ashley Whillans, Jaewon Yoon and Aurora Turek of the Harvard Business School. It was published today (Nov. 1, 2021) in the journal Proceedings of the National Academy of Sciences.

The research involved nine studies with more than 5,000 participants, including online panels of working adults and undergraduate students.

Donnelly said that for him, one of the most compelling of the nine studies was one conducted in his own class.

He assigned a discussion paper that was worth 20% of the grade to 103 students in an undergraduate business course. All students were given one week to submit the paper, but were told they could email Donnelly to request an extension without penalty.

Male students were more than twice as likely as female students to request an extension for the assignment (15% of female vs. 36% of male students).

Not asking for an extension could hurt students, the findings showed. A teaching assistant who rated the papers gave better scores to those who had asked for an extension. (The assistant did not know who wrote the papers and whether they asked for extensions, or the purpose of the study.)

“What we found is that when students requested an extension, they made good use of that time and performed better on the task,” he said. “Women may hurt themselves by not requesting additional time.”

Several other of the nine studies by the researchers involving working adults showed that women’s focus on other people and their needs played a big role in why they were uncomfortable asking for deadline extensions.

In these studies, participants imagined they were assigned to submit a proposal for an upcoming event that was due the next day, but needed more time. In the scenario, they could ask for an extension from their supervisor.

Participants were asked a variety of questions about how asking for an extension might affect themselves and their team, and how it might affect how they were viewed by others.

Results showed that women believed they would be seen as less competent if they asked for an extension. But that wasn’t the main reason that women were reluctant to request more time.

“It was their concern about burdening their team and manager with more work that most strongly predicted women’s discomfort with asking for more time on adjustable deadlines,” Donnelly said.

“Perceived burden and emotions like shame, embarrassment and guilt explained why women experienced more discomfort with asking for extensions than men did.”

And these feelings have real-life implications. Consistent with prior research, women in this study reported feeling more time-pressed and experienced more burnout than men.

But the good news from the findings is that organizations can level the playing field – resulting in women and men asking for more time on projects at nearly the same rate – by creating a formal way to request deadline extensions.

In one study, the researchers analyzed data from an online university that had a formal policy for extension requests – all students were entitled to four 24-hour extensions per semester, which could be requested using an online form.

In this case, women were as likely to submit at least one request during the semester studied as were men (24% of women vs. 25% of men). That finding was replicated in another of the nine studies.

Donnelly said he believes companies and other organizations should create formal avenues for requesting deadline extensions.

“It’s a structural issue. When organizations have formal policies about deadlines, it creates the opportunity for men and women to have equal experiences for requesting additional time,” he said.

“And we found evidence that allowing deadline extensions, when possible, can result in better work. That’s helpful for employers and employees.”

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Spiders’ Web Secrets Unraveled

Johns Hopkins University researchers discovered precisely how spiders build webs by using night vision and artificial intelligence to track and record every movement of all eight legs as spiders worked in the dark.

Their creation of a web-building playbook or algorithm brings new understanding of how creatures with brains a fraction of the size of a human’s are able to create structures of such elegance, complexity and geometric precision. The findings, now available online, are set to publish in the November issue of Current Biology.

“I first got interested in this topic while I was out birding with my son. After seeing a spectacular web I thought, ‘if you went to a zoo and saw a chimpanzee building this you’d think that’s one amazing and impressive chimpanzee.’ Well this is even more amazing because a spider’s brain is so tiny and I was frustrated that we didn’t know more about how this remarkable behavior occurs,” said senior author Andrew Gordus, a Johns Hopkins behavioral biologist. “Now we’ve defined the entire choreography for web building, which has never been done for any animal architecture at this fine of a resolution.”

Web-weaving spiders that build blindly using only the sense of touch, have fascinated humans for centuries. Not all spiders build webs but those that do are among a subset of animal species known for their architectural creations, like nest-building birds and puffer fish that create elaborate sand circles when mating.

The first step to understanding how the relatively small brains of these animal architects support their high-level construction projects, is to systematically document and analyze the behaviors and motor skills involved, which until now has never been done, mainly because of the challenges of capturing and recording the actions, Gordus said.

Here his team studied a hackled orb weaver, a spider native to the western United States that’s small enough to sit comfortably on a fingertip. To observe the spiders during their nighttime web-building work, the lab designed an arena with infrared cameras and infrared lights. With that set-up they monitored and recorded six spiders every night as they constructed webs. They tracked the millions of individual leg actions with machine vision software designed specifically to detect limb movement.

“Even if you video record it, that’s a lot of legs to track, over a long time, across many individuals,” said lead author Abel Corver, a graduate student studying web-making and neurophysiology. “It’s just too much to go through every frame and annotate the leg points by hand so we trained machine vision software to detect the posture of the spider, frame by frame, so we could document everything the legs do to build an entire web.”

They found that web-making behaviors are quite similar across spiders, so much so that the researchers were able to predict the part of a web a spider was working on just from seeing the position of a leg.

“Even if the final structure is a little different, the rules they use to build the web are the same,” Gordus said. “They’re all using the same rules, which confirms the rules are encoded in their brains. Now we want to know how those rules are encoded at the level of neurons.”

Future work for the lab includes experiments with mind-altering drugs to determine which circuits in the spider’s brain are responsible for the various stages of web-building.

“The spider is fascinating,” Corver said, “because here you have an animal with a brain built on the same fundamental building blocks as our own, and this work could give us hints on how we can understand larger brain systems, including humans, and I think that’s very exciting.

Authors also include Nicholas Wilkerson, a former Hopkins undergraduate and current graduate student at Atlantic Veterinary College, and Jeremy Miller, a graduate student at Johns Hopkins.

The work was supported by the National Science Foundation Graduate Research Fellowship Program and National Institutes of Health grant R35GM124883.

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Adolescents’ Recreational Screen Time Doubled During Pandemic, Affecting Mental Health

Many parents fretted over their children’s screen use during the pandemic with good reason, according to a new study in JAMA Pediatrics. UC San Francisco-led researchers found that 12- to 13-year-old children in the United States doubled their non-school-related screen time to 7.7 hours a day in May 2020, compared to 3.8 hours a day before the pandemic. The study also found that children of color and those from lower-income families logged more hours on screens than their white, wealthier peers.

The study found the most common recreational activities were watching or streaming movies, videos and television, followed by gaming.

Spending more time on screens has mental health effects, including more depression and anxiety, said Jason Nagata, MD, lead author on the JAMA Pediatrics study and UCSF assistant professor of pediatrics.  “As screen time increased, so did adolescents’ worry and stress, while their coping abilities declined,” Nagata said. “Though social media and video chat can foster social connection and support, we found that most of the adolescents’ screen use during the pandemic didn’t serve this purpose.”

Screen time lends itself to more sedentary time and less physical activity, snacking while distracted, eating in the absence of hunger, and greater exposure to food advertising.

JASON NAGATA, MD, UCSF ASSISTANT PROFESSOR OF PEDIATRICS

Excessive screen use in adolescents also is associated with weight gain and binge eating, Nagata noted: “Screen time lends itself to more sedentary time and less physical activity, snacking while distracted, eating in the absence of hunger, and greater exposure to food advertising.”

Research conducted before the pandemic found screen time differed by race and income, and the current study saw those trends persist.

“We generally found higher screen time in Black and Latino/a adolescents and in those from lower-income households,” Nagata said. “This may be due to structural and systemic factors, such as lack of financial resources to do other kinds of activities or lack of access to safe outdoor spaces.”

Screen time amounts were self-reported by 5,412 adolescents ages 12-13 years who are taking part in the Adolescent Brain Cognitive Development (ABCD) longitudinal study. The ABCD study is following nearly 12,000 preadolescents into their adolescent years, from 2016 to 2026.

Authors: UCSF co-authors are Jason Nagata, MD; Kirsten Bibbins-Domingo, PhD, MD; Chloe Cattle, BS; and Puja Iyer, BA. Additional authors and affiliations can be found in the paper.

Funding: The study was funded in part by the National Institutes of Health (grant #K08HL159350). Dr. Nagata also was funded by a Career Development Award (CDA34760281) by the American Heart Association.

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An Early Warning System for Malaria Can Give Local Officials Time to Save Lives

A Duke University-led initiative to predict and prevent malaria outbreaks in the Amazon has received a $3.4 million grant from the National Institute of Allergy and Infectious Diseases (NIAID).

The grant will support the research team’s efforts to develop new and more reliable methods to forecast where and when a malaria outbreak will occur, weeks or even months in advance, and identify which intervention strategy will best control its spread.

Since 2010, Amazon-basin countries have experienced a 600% increase in malaria cases, the most rapid rise in confirmed cases in any region worldwide, yet international aid to fund malaria control programs there has plummeted.

A key part of the Duke-led, NIAID-funded research will be adapting a Malaria Early Warning System (MEWS) the research team has developed and successfully tested in Peru so that it can be used in the Brazilian and Ecuadorian Amazon, too.

The system uses statistical models to predict the probability of a malaria outbreak at sites across a region, based on analysis of satellite-generated data on local temperatures, precipitation, land use, human population density, extent of forest cover, and other factors that can promote disease transmission.

The system can also identify which intervention strategies will best control malaria’s spread under local conditions at the time of the outbreak.

In Peru, MEWS has demonstrated greater than 90% sensitivity and specificity in predicting outbreaks up to 12 weeks in advance across small regions, said William Pan, associate professor of global environmental health, who leads the initiative.

“That’s a huge improvement over conventional surveillance used for decision-making, which relies on confirmed-case data that can be four weeks old by the time it reaches public health agencies,” Pan said. “MEWS gives local officials time to respond proactively rather than reactively.”

In addition to supporting the team’s work to adapt MEWS for use in malaria-prone regions of Ecuador and Brazil, the NIAID grant will enable Pan and his colleagues to investigate how interactions between human communities clustered along many international borders in Amazonia contribute to large-scale patterns of malaria transmission.

Locals cross these borders regularly to buy and sell goods, seek medical care or other services, attend events, or visit friends and family on the other side, Pan explained. Their movements can help malaria spread across national jurisdictions and complicate efforts to track and control its transmission. The new research aims to identify which control strategies will work best in these trans-governmental social networks.

“Malaria remains a major problem in Latin America, yet it is the only region of the world where investments from global malaria donors are declining,” Pan said. “Given the relatively strong health infrastructure there compared to other malaria endemic regions of the world, we have a real opportunity to eliminate malaria from the western hemisphere and the MEWS system is one step towards that shared goal. Our vision is not just a technical fix, but a bottom-up approach that engages stakeholders from the community to national and international levels.”

Duke’s partners in the initiative are Johns Hopkins University; Universidad Peruana Cayetano-Heredia; Pontificia Universidad Católica del Perú; Universidad San Francisco de Quito; Universidad Federal Minas Gerais; the Oswaldo Cruz Foundation; Peru’s Ministry of Health; and Ecuador’s Ministry of Health.

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Key to resilient energy-efficient AI/machine learning may reside in human brain

A clearer understanding of how a type of brain cell known as astrocytes function and can be emulated in the physics of hardware devices, may result in artificial intelligence (AI) and machine learning that autonomously self-repairs and consumes much less energy than the technologies currently do, according to a team of Penn State researchers.

Astrocytes are named for their star shape and are a type of glial cell, which are support cells for neurons in the brain. They play a crucial role in brain functions such as memory, learning, self-repair and synchronization.

“This project stemmed from recent observations in computational neuroscience, as there has been a lot of effort and understanding of how the brain works and people are trying to revise the model of simplistic neuron-synapse connections,” said Abhronil Sengupta, assistant professor of electrical engineering and computer science. “It turns out there is a third component in the brain, the astrocytes, which constitutes a significant section of the cells in the brain, but its role in machine learning and neuroscience has kind of been overlooked.”

At the same time, the AI and machine learning fields are experiencing a boom. According to the analytics firm Burning Glass Technologies, demand for AI and machine learning skills is expected to increase by a compound growth rate of 71% by 2025. However, AI and machine learning faces a challenge as the use of these technologies increase — they use a lot of energy.

“An often-underestimated issue of AI and machine learning is the amount of power consumption of these systems,” Sengupta said. “A few years back, for instance, IBM tried to simulate the brain activity of a cat, and in doing so ended up consuming around a few megawatts of power. And if we were to just extend this number to simulate brain activity of a human being on the best possible supercomputer we have today, the power consumption would be even higher than megawatts.”

All this power usage is due to the complex dance of switches, semiconductors and other mechanical and electrical processes that happens in computer processing, which greatly increases when the processes are as complex as what AI and machine learning demand. A potential solution is neuromorphic computing, which is computing that mimics brain functions. Neuromorphic computing is of interest to researchers because the human brain has evolved to use much less energy for its processes than do a computer, so mimicking those functions would make AI and machine learning a more energy-efficient process.

Another brain function that holds potential for neuromorphic computing is how the brain can self-repair damaged neurons and synapses.

“Studying astrocytes for the type of self-repair and synchronization functionalities they can enable in neuromorphic computing is really in its infancy. There’s a lot of potential opportunities with these kinds of components.”

Abhronil Sengupta, assistant professor of electrical engineering and computer science

“Astrocytes play a very crucial role in self-repairing the brain,” Sengupta said. “When we try to come up with these new device structures, we try to form a prototype artificial neuromorphic hardware, these are characterized by a lot of hardware-level faults. So perhaps we can draw insights from computational neuroscience based on how astrocyte glial cells are causing self-repair in the brain and use those concepts to possibly cause self-repair of neuromorphic hardware to repair these faults.”

Sengupta’s lab primarily works with spintronic devices, a form of electronics that process information via spinning electrons. The researchers examine the devices‘ magnetic structures and how to make them neuromorphic by mimicking various neural synaptic functions of the brain in the intrinsic physics of the devices.

This research was part of a study published in January in Frontiers in Neuroscience. That research, in turn, resulted in the study recently published in the same journal.

“When we started working on the aspects of self-repair in the previous study, we realized that astrocytes also contribute to temporal information binding,” Sengupta said.

Temporal information binding is how the brain can make sense of relations between separate events happening at separate times, and making sense of these events as a sequence, which is an important function of AI and machine learning.

“It turns out that the magnetic structures we were working with in the prior study can be synchronized together through various coupling mechanisms, and we wanted to explore how you can have these synchronized magnetic devices mimic astrocyte-induced phase coupling, going beyond prior work on solely neuro-synaptic devices,” Sengupta said. “We want the intrinsic physics of the devices to mimic the astrocyte phase coupling that you have in the brain.”

To better understand how this might be achieved, the researchers developed neuroscience models, including those of astrocytes, to understand what aspects of astrocyte functions would be most relevant for their research. They also developed theoretical modeling of the potential spintronic devices.

“We needed to understand the device physics and that involved a lot of theoretical modeling of the devices, and then we looked into how we could develop an end-to-end, cross-disciplinary modeling framework including everything from neuroscience models to algorithms to device physics,” Sengupta said.

“AI and machine learning is revolutionizing the world around us every day, you see it from your smartphones recognizing pictures of your friends and family, to machine learning’s huge impact on medical diagnosis for different kinds of diseases.”

Abhronil Sengupta, assistant professor of electrical engineering and computer science

Creating such energy-efficient and fault-resilient “astromorphic computing” could open the door for more sophisticated AI and machine learning work to be done on power-constrained devices such as smartphones.

“AI and machine learning is revolutionizing the world around us every day, you see it from your smartphones recognizing pictures of your friends and family, to machine learning’s huge impact on medical diagnosis for different kinds of diseases,” Sengupta said. “At the same time, studying astrocytes for the type of self-repair and synchronization functionalities they can enable in neuromorphic computing is really in its infancy. There’s a lot of potential opportunities with these kinds of components.”

Along with Sengupta, researchers in the first paper released in January, “On the Self-Repair Role of Astrocytes in STDP Enabled Unsupervised SNNs,” include Mehul Rastogi, former research intern in the Neuromorphic Computing Lab; Sen Lu, graduate research assistant in computer science; and Nafiul Islam, graduate research assistant in electrical engineering. Along with Sengupta, researchers in the paper released in October, “Emulation of Astrocyte Induced Neural Phase Synchrony in Spin-Orbit Torque Oscillator Neurons,” include Umang Garg, who was a research intern at Penn State during the study, and Kezhou Yang, doctoral candidate in material science.

The National Science Foundation supported this work through the Early Concept Grant for Exploratory Research program which is specifically targeted for interdisciplinary high-risk, high-payoff projects with a transformative scope.

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Astronomers suggest radiation, not supernovae, drives superwinds in some galaxies

When astronomers observe superwinds traveling at extremely high speeds from super star clusters, or “starbursts,” they previously assumed the winds were driven by supernovae, the explosions of stars.

This was the case for a starburst called Mrk 71 in a nearby galaxy. Astronomers had observed incredibly fast superwinds—traveling at about 1% of the speed of light—emanating from the cluster, and classic reasoning suggested the blasts from many supernovae drive the gas to such a high rate of speed.

But University of Michigan astronomers think supernovae aren’t the reason: the cluster is too young to have supernovae. They suspect a different mechanism is behind the superwind.

By studying the wind and starburst properties, the astronomers established that ultraviolet radiation from the compact starburst itself drove the superwind. Their findings, published in the journal Astrophysical Journal Letters, may help explain one chapter of the universe’s beginnings.

Just after the Big Bang, the universe was very dense and opaque, says lead author and graduate student Lena Komarova. The universe was so densely packed with particles, no light could pass through them.

“But when the first stars formed in the first galaxies, they produced lots of ultraviolet light. And this essentially evaporates the gas in the universe,” Komarova said. “It’s a process similar to when you have a fog in the morning that you can’t see through—but then the sunshine comes and hits the fog, it starts breaking up into smaller droplets, and you start seeing the light pass.”

In this analogy, neutral hydrogen atoms, which make up 92% of the cosmos, are the “fog” in the universe. But as light started shining out from the first stars forming in the universe, ultraviolet light from these stars began breaking up the hydrogen particles.

“The universe essentially becomes transparent and this happens at so-called cosmic dawn when the first stars appear,” Komarova said. “And so that’s what we’re trying to figure out: How do you get this UV light that’s energetic enough to evaporate the universe, to get out of the galaxies, without it all being absorbed by hydrogen?”

Komarova and Sally Oey, U-M professor of astronomy and senior author of the paper, think the answer lies in the superwinds that they found are generated by the radiation of these compact starburst galaxies. The radiation—ultraviolet light—”evaporates” hydrogen atoms, which are composed of a single proton and a single electron, by stripping off the electrons, ionizing them.

“Only UV light is capable of doing this, because the light has to be above a certain threshold energy,” Oey said. “Once the hydrogen is ionized, it becomes transparent because it can’t capture more UV photons.”

The U-M astronomers came up with the hypothesis of a radiation-driven wind to explain Mrk 71, a starburst region within the galaxy NGC 2366. By examining the spectrum of this region, Komarova and Oey were able to study the gas velocity structure, and found a smooth wind that originated at the brightest Mrk 71 super star cluster.

“We found that even if you had supernovae, there still wouldn’t be enough energy to accelerate the gas to the speeds that we observe,” Komarova said. “We compared the force of stellar light on the gas to the force of gravity, and we found that the radiation is much stronger than gravity—so it can, in fact, push the gas out without gravity bringing it back in. This is what we call a radiation-driven wind.”

The acceleration itself happens when intense light irradiates dense blobs of hydrogen gas from one direction, pushing the gas along, similar to how exploding gas forces a bullet out of a gun. The blobs must be too dense to be evaporated by the ultraviolet radiation. But the light also escapes through spaces between the dense blobs of hydrogen, and blasts blobs farther out from the star cluster.

“The reason why this is linked to the very high velocities is that in order for the blobs to get accelerated to such high speeds, they need to be constantly trapping these UV rays, even at large distances from the star cluster,” Oey said.

What the researchers then propose is this process clears pathways for ultraviolet light to pass between clumps of hydrogen gas.

“So, that UV light can in fact leave its cluster where it was born and go out into the rest of the universe to evaporate it,” Komarova said. “This is putting in another piece of the puzzle of evaporation of the universe and provides a specific physical mechanism of how you do it.”

The researchers drew their conclusion using the Hubble Space Telescope and archive data gathered at the Gemini-North Observatory in Hawaii.

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Scientists identify the cause of Alzheimer’s progression in the brain

For the first time, researchers have used human data to quantify the speed of different processes that lead to Alzheimer’s disease and found that it develops in a very different way than previously thought. Their results could have important implications for the development of potential treatments.

This research shows the value of working with human data instead of imperfect animal models

Tuomas Knowles

The international team, led by the University of Cambridge, found that instead of starting from a single point in the brain and initiating a chain reaction which leads to the death of brain cells, Alzheimer’s disease reaches different regions of the brain early. How quickly the disease kills cells in these regions, through the production of toxic protein clusters, limits how quickly the disease progresses overall.

The researchers used post-mortem brain samples from Alzheimer’s patients, as well as PET scans from living patients, who ranged from those with mild cognitive impairment to those with late-stage Alzheimer’s disease, to track the aggregation of tau, one of two key proteins implicated in the condition.

In Alzheimer’s disease, tau and another protein called amyloid-beta build up into tangles and plaques – known collectively as aggregates – causing brain cells to die and the brain to shrink. This results in memory loss, personality changes and difficulty carrying out daily functions.

By combining five different datasets and applying them to the same mathematical model, the researchers observed that the mechanism controlling the rate of progression in Alzheimer’s disease is the replication of aggregates in individual regions of the brain, and not the spread of aggregates from one region to another.

The results, reported in the journal Science Advances, open up new ways of understanding the progress of Alzheimer’s and other neurodegenerative diseases, and new ways that future treatments might be developed.

For many years, the processes within the brain which result in Alzheimer’s disease have been described using terms like ‘cascade’ and ‘chain reaction’. It is a difficult disease to study, since it develops over decades, and a definitive diagnosis can only be given after examining samples of brain tissue after death.

For years, researchers have relied largely on animal models to study the disease. Results from mice suggested that Alzheimer’s disease spreads quickly, as the toxic protein clusters colonise different parts of the brain.

“The thinking had been that Alzheimer’s develops in a way that’s similar to many cancers: the aggregates form in one region and then spread through the brain,” said Dr Georg Meisl from Cambridge’s Yusuf Hamied Department of Chemistry, the paper’s first author. “But instead, we found that when Alzheimer’s starts there are already aggregates in multiple regions of the brain, and so trying to stop the spread between regions will do little to slow the disease.”

This is the first time that human data has been used to track which processes control the development of Alzheimer’s disease over time. It was made possible in part by the chemical kinetics approach developed at Cambridge over the last decade which allows the processes of aggregation and spread in the brain to be modelled, as well as advances in PET scanning and improvements in the sensitivity of other brain measurements.

“This research shows the value of working with human data instead of imperfect animal models,” said co-senior author Professor Tuomas Knowles, also from the Department of Chemistry. “It’s exciting to see the progress in this field – fifteen years ago, the basic molecular mechanisms were determined for simple systems in a test tube by us and others; but now we’re able to study this process at the molecular level in real patients, which is an important step to one day developing treatments.”

The researchers found that the replication of tau aggregates is surprisingly slow – taking up to five years. “Neurons are surprisingly good at stopping aggregates from forming, but we need to find ways to make them even better if we’re going to develop an effective treatment,” said co-senior author Professor Sir David Klenerman, from the UK Dementia Research Institute at the University of Cambridge. “It’s fascinating how biology has evolved to stop the aggregation of proteins.”

The researchers say their methodology could be used to help the development of treatments for Alzheimer’s disease, which affects an estimated 44 million people worldwide, by targeting the most important processes that occur when humans develop the disease. In addition, the methodology could be applied to other neurodegenerative diseases, such as Parkinson’s disease.

“The key discovery is that stopping the replication of aggregates rather than their propagation is going to be more effective at the stages of the disease that we studied,” said Knowles.

The researchers are now planning to look at the earlier processes in the development of the disease, and extend the studies to other diseases such as Frontal temporal dementia, traumatic brain injury and progressive supranuclear palsy where tau aggregates are also formed during disease.

The study is a collaboration between researchers at the UK Dementia Research Institute, the University of Cambridge and Harvard Medical School. Funding is acknowledged from Sidney Sussex College Cambridge, the European Research Council, the Royal Society, JPB Foundation, the Rainwater Foundation, the NIH, and the NIHR Cambridge Biomedical Research Centre which supports the Cambridge Brain Bank.

Reference:
Georg Meisl et al. ‘In vivo rate-determining steps of tau seed accumulation in Alzheimer’s disease.’ Science Advances (2021). DOI: 10.1126/sciadv.abh1448

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