2024 Kavli Prize awarded for research on face-selective brain areas – The Transmitter: Neuroscience News and Perspectives

Three pioneers in face-perception research have won the 2024 Kavli Prize in Neuroscience.

Nancy Kanwisher, professor of cognitive neuroscience at the Massachusetts Institute of Technology; Winrich Freiwald, professor of neurosciences and behavior at Rockefeller University; and Doris Tsao, professor of neurobiology at the University of California, Berkeley, will share the $1 million Kavli Prize for their discoveries of the regionsin both the human and monkey brainsresponsible for identifying and recognizing faces.

This is work thats very classic and very elegant, not only in face-processing and face-recognition work, but the impact its had on how we think about brain organization in general is huge, says Alexander Cohen, assistant professor of neurology at Harvard Medical School, who studies face recognition in autistic people.

The Norwegian Academy of Science and Letters awards the prize every two years.

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To get to the root of face processing, Kanwisher spent hours as a young researcher lying still in an MRI machine as images of faces and objects flashed before her. A spot in the bottom right of the cerebral cortex lit up when she and others looked at faces, according to functional MRI (fMRI) scans, she and her colleagues reported in a seminal 1997 paper. They called the region the fusiform face area.

This discovery offered some of the first concrete evidence that the brain specializes in sections, rather than working as a giant, adaptable generalist, Kanwisher says. This shows that for some mental functions, theres a very particular part of the brain that does just that and only that thing.

The discovery revolutionized how we thought about specialization of the brain, Cohen says.

Two other face-sensitive regionsthe occipital and superior temporal sulcus face areasprocess parts of the face, such as the eyes, nose and mouth, and changeable aspects, such as gaze direction, subsequent work showed.

But knowing that regions of the human brain selectively respond to a face cannot tell a researcher much about how or why this happens, Kanwisher says. Tsao and Freiwald built on Kanwishers findings by carrying out studies in macaque monkeys to answer questions that studies in people could not. They used fMRI to scan 10 of the animals while showing them pictures of human faces, macaque faces, hands, gadgets, fruits and vegetables, headless bodies and scrambled patterns.

The monkeys brains have six distinct face patches, thought to be analogous to the areas seen in people, Tsao and Freiwald reported in a 2008 study.

Individual cells in these face patch regions specialize in recognizing faces seen from different angleslooking up, down, tilted to the side, and in profile, for instanceaccording to electrophysiological recordings, suggesting these specialized modules work together across regions, the team discovered.

Specific neurons can even recognize the different components that go into forming a facefrom hair to pupils, Tsao and Freiwald found in additional work involving electrode recordings.

Thats when we got this picture that the face patches are really like this assembly line that are building this invariant representation of facial identity, Tsao says.

Two additional brain areas in macaques temporal lobe specifically respond to familiar faces and not unfamiliar ones, Freiwald and his colleagues later identified using fMRI.

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Tsao echoes her enthusiasm for the launchpad these findings have offered for future brain mapping. When we first started working on the face-patch system, people said its a total unicorn, Tsao says. That turned out to be completely wrong. It turns out that the face-patch system basically is a Rosetta Stone for all of the IT [inferior temporal] cortex. All of the IT cortex is organized in exactly the same way.

Understanding how we see faces can also be a tool for understanding more complex mental processes, such as memory and emotions, that are linked with social interactions, Freiwald says. Faces are the social stimulus for visual and social animals like us.

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AI model predicts human behavior from our poor decision-making – Big Think

Human beings behave irrationally or as an artificially intelligent robot might say, sub-optimally. Data, the emotionless yet affable android depicted in Star Trek: The Next Generation, regularly struggled to comprehend humans flawed decision-making. If he had been programmed with a new model devised by researchers at MIT and the University of Washington, he might have had an easier go of it.

In a paper published last month, Athul Paul Jacob, a Ph.D. student in AI at MIT, Dr. Jacob Andreas, his academic advisor, and Abhishek Gupta, an assistant professor in computer science and engineering at the University of Washington, described a new way to model an agents behavior. They then used their method to predict humans goals or actions.

Jacob, Andreas, and Gupta created what they termed a latent inference budget model. Its underlying breakthrough lies in inferring a human or machines computational constraints based on prior actions. These constraints result in sub-optimal choices. For example, a human constraint for decision decision-making is often time. When confronted with a difficult choice, we typically dont spend hours (or longer) gaming out every possible outcome. Instead, we make decisions quickly without taking the time to gather all the information available.

Models currently exist that account for irrational decision-making, but these only predict that errors will occur randomly. In reality, humans and machines screw up in more formulaic patterns. The latent inference budget model can quickly identify these patterns and then use them to forecast future behavior.

Across three tests, the researchers found that their new model generally outperforms the old models: It was as good or better at predicting a computer algorithms route when navigating a maze, a human chess players next move, and what a human speaker was trying to say from a quick utterance.

Jacob says that the research process made him realize how fundamental planning is to human behavior. Certain people are not inherently rational or irrational. Its just that some people take extra time to plan their actions while others take less.

At the end of the day, we saw that the depth of the planning, or how long someone thinks about the problem, is a really good proxy of how humans behave, he said in a statement.

Jacob envisions the model being used in futuristic robotic helpers or AI assistants.

If we know that a human is about to make a mistake, having seen how they have behaved before, the AI agent could step in and offer a better way to do it. Or the agent could adapt to the weaknesses that its human collaborators have, he said.

This is not scientists first attempt to develop tools that help AI predict human decision-making. Most researchers pursuing this goal envision positive futures. For example, we may someday see AI seamlessly coordinating their actions with ours, providing assistance in everyday tasks, boosting productivity at workplaces, and being our drinking buddies.

But there are more dystopian possibilities, too. AI models thoroughly designed to predict human behavior could also be used by bad actors to manipulate us. With enough data on how humans react to various stimuli, AI could be programmed to elicit responses that might not be in the targeted individuals best interest. Imagine if AI got really good at this. It would bring new urgency to the question of whether humans are agents with free will or simply automata reacting to external forces.

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Trajectories of brain and behaviour development in the womb, at birth and through infancy – Nature.com

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Trajectories of brain and behaviour development in the womb, at birth and through infancy - Nature.com

On TikTok, Goldendoodles Are People Trapped in Dog Bodies – The New York Times

He sits forlornly on a floating staircase, his body slightly slumped and his limbs in his lap, gazing out floor-to-ceiling windows into the summer foliage beyond. He seems to be contemplating something perhaps the meaning of life itself as the camera shifts around to the front to reveal his true condition. Hes not a man; hes a goldendoodle.

This video, taken by the dogs owner, Lawrence Skutelsky, is captioned Trying to find the zipper on my goldendoodle after this, and it has been viewed on TikTok more than 87 million times. Posted on May 24, it joined a pantheon of similar videos from other goldendoodle owners documenting the humanlike behavior of their pets and prompted a host of new additions to the genre.

Naturally, many viewers on TikTok are now joking that dogs particularly goldendoodles, a designer breed that is a cross between a golden retriever and a poodle may actually be people trapped in dog bodies.

Does anybody elses dog sit on them like a literal human child or is it just mine? Chloe Covington asked in a video she posted last year with her goldendoodle, Gemma, sitting upright on her lap. Others have shared clips of goldendoodles sitting on the stairs like Mr. Skutelskys dog or standing like a person.

Back in 2020, a woman named Molly Dolan, who lives in Charleston, S.C., posted a video of her goldendoodle walking upright on two hind legs across the entire street and it has been viewed about 6.5 million times to date.

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On TikTok, Goldendoodles Are People Trapped in Dog Bodies - The New York Times

ZkSync defends Sybil measures as Binance offers own ZK token airdrop – TradingView

Ethereum zero-knowledge layer-2 scaling platform zkSync has continued to defend criticism over the criteria for its zkSync (ZK) token airdrop, slated to launch on June 17.

In a frequently asked questions (FAQ) document updated on June 15, ZK Nation answered 15 questions explaining why some groups were eligible for the token while others werent.

One of its longer answers focused on its detection and prevention measures for Sybil attacks, which occur when one entity creates and uses a large number of wallets to farm an airdrop. This was a continuing pain point among airdrop claimants recently.

ZkSync reiterated it had used explicit Sybil detection in addition to a unique airdrop design to ensure the highest number of organic users were rewarded, but it also noted that this has led to some Sybil wallets being let through.

It explained some Sybils can employ sophisticated algorithmic strategies that are indistinguishable from real people.

They fund accounts from many distinct exchange addresses, never interact with each other, use randomized amounts, and use software to randomize daily patterns of human behavior, and even perform activities unique to the project (for example, using zkSync paymasters), it explained.

The majority of such bots are completely undetectable, even with the most advanced anti-Sybil methodology.

ZkSync claimed that being too aggressive with filtering could eliminate some Sybils but also might falsely flag many organic users, so it chose to reward organic users with high likelihood by using a combination of value scaling and multipliers.

Essentially, this assigned fewer eligibility points to wallets with low funding (a sign of Sybil behavior) but would give them a multiplying boost if there was onchain behavior that signaled human behavior.

ZkSync explained that Sybils typically creates many accounts but uses small amounts of crypto to fund each account to be capital efficient.

Introducing the ZK Token

Checker https://t.co/O2UonCvfzi

Announcement https://t.co/hjgI14PHoi

Docs https://t.co/taWBoCnfbc

Its time to put the ZK token into the hands of the community. Its your turn to govern ZKsyncs future. pic.twitter.com/VD3fZgH5bf

Real people, on the other hand, tend to concentrate most of their wealth in just a few accounts, making their balances much larger compared to bots, it explained.

There will be Sybils in every airdrop, it concluded. However, for every example of Sybil that can be identified, there are hundreds that were excluded.

Binance offers ZK listing and distribution amid ongoing concerns

It comes as crypto exchange Binance has offered its own ZK airdrop targeted at those not eligible for the official airdrop on June 17.

The exchange said it will offer 10.5 million ZK tokens to over 52,000 Binance users in light of the ongoing concerns from the community around ZK token distribution.

Eligible claim addresses need to have initiated at least 50 transactions on zkSync Era between February 2023 and March 2024, conducted transactions in at least seven months in that period, arent a centralized exchange, bridge or contract address and werent eligible for the official airdrop.

However, each Binance user will only be given 200 ZK each.

The exchange will also open the ZK token for trading from June 17, including trading pairs with Bitcoin (BTC), Tether (USDT) and First Digital USD (FDUSD).

The ZK token airdrop will launch on June 17. According to Whales Pro, the ZK token istrading in the pre-market for $0.36 at the time of writing.

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ZkSync defends Sybil measures as Binance offers own ZK token airdrop - TradingView

10 things only introverts find irritating, according to psychology – Hack Spirit

We all know those moments that make us want to retreat into our shells. But for introverts, its a whole different ball game.

Its not about disliking people or being antisocial. Its about how some situations can feel overwhelming or draining.

Simply put, introverts have a unique set of pet peeves that can feel like fingernails on a chalkboard. And psychology has plenty to say about it.

Here are 10 things only introverts find irritating.

Lets dive right in. If theres one thing that can make an introvert cringe, its small talk.

Now, its not that introverts dislike conversation. Quite the contrary, they thrive on deep, meaningful exchanges. The issue lies in the superficiality of small talk.

Small talk feels like a waste of energy for introverts. It drains them, without providing any substantial connection or new insights. Its like trying to swim in a puddle when youre used to the ocean.

Introverts process information more deeply than extroverts. They crave substance and depth, which small talk doesnt provide.

When you see your introverted friend at a party, skip the weather chit-chat and dive into something meaningful. Theyll appreciate it more than you know.

Heres another one for you: unexpected visitors.

Now, let me tell you a personal story. I remember this one time when I was deep into a book Id been looking forward to reading all week. Just as I was reaching the climax, the doorbell rang. Standing there was a friend whod thought theyd surprise me with an impromptu visit.

The thing is, surprise visits and introverts mix about as well as oil and water.

Introverts value their alone time. Its when we recharge, reflect, and relax. And unexpected interruptions? Theyre like pulling the plug on our battery charger.

Psychologists say this is because introverts have a lower threshold for stimulation. We prefer quiet, peaceful environments and need time to mentally prepare for social interactions.

If youre planning to drop by an introverts place, a heads-up will go a long way. Trust me on this one.

Ever heard the phrase all eyes on me? For introverts, its more like a nightmare than a dream.

Being the center of attention can feel like being under a microscope for introverts. They prefer to blend into the background, observing and listening rather than being the star of the show.

And heres an interesting spin: its not just a preference. Its actually wired into the brain. Neuroscientist Hans Eysenck found that introverts have higher levels of cortical arousal, meaning their brains are more active even at rest. This makes them more sensitive to external stimuli, like a room full of people focusing on them.

Networking events. Just hearing those words can make an introverts heart rate spike.

These events are typically designed around extroverted behaviors, with large crowds and constant social interaction. Its a lot of small talk, exchanging business cards, and trying to make an impression all things that can exhaust an introvert quickly.

Psychology explains that introverts tend to prefer one-on-one interactions and take time to process their thoughts before speaking. Networking events, with their fast-paced chatter and pressure to make immediate connections, can feel like a battlefield to an introvert.

If youre planning a networking event, consider incorporating some introvert-friendly features. Think quiet spaces for one-on-one conversations or structured networking activities. It might make all the difference for your introverted attendees.

Open offices, hailed for their ability to foster collaboration and communication, can be a real thorn in the side for introverts.

The constant buzz of activity, chatty coworkers, and lack of personal space can make it difficult for introverts to concentrate or feel comfortable. Its like trying to read a book in the middle of a busy market.

Psychological research indicates that introverts perform best in quiet, solitary environments where they can focus on their thoughts without external distractions.

While open offices may work for some, they arent the best fit for everyone. Offering quiet spaces or flexible work options can help ensure your introverted employees are at their most productive.

This ones a bit more emotional. One of the most frustrating things for an introvert is having their need for alone time misunderstood as rudeness or aloofness.

For introverts, alone time is not a luxury; its a necessity. Its how they recharge their mental and emotional batteries. Its their sanctuary, their retreat.

Psychology tells us that introverts gain energy from within, while social interactions can often deplete this energy. This is why they may seek solitude after a long day or prefer quiet nights in to big parties.

Its not that they dislike people or are being unsociable. Theyre simply taking care of their mental health and well-being in the best way they know how.

If an introvert in your life needs some alone time, dont take it personally. Just offer understanding and respect their need for solitude. Theyll appreciate it more than you can imagine.

I remember this one time I attended a music festival with some friends. The loud music, flashing lights, and throngs of people dancing and shouting it was all too much. I ended up leaving early and spending the rest of my night in a quiet park nearby.

This is a common scenario for many introverts. Overstimulating environments can be overwhelming and uncomfortable. The barrage of sights, sounds, and people can make it feel like their senses are under attack.

Psychology refers to this as sensory overload, which is more common in introverts due to their high sensitivity to external stimuli. It can lead to feelings of anxiety, irritability, and exhaustion.

When planning activities with an introvert, consider their comfort level with different environments. A quiet coffee shop might be a better meeting place than a bustling bar or busy street market.

Now, this might sound surprising given what weve discussed about introverts needing solitude. But hear me out.

While introverts do need their alone time to recharge, too much downtime can actually be a problem. Boredom is as draining for an introvert as overstimulation.

You see, introverts thrive on deep thought and reflection. They crave mental stimulation, just not the noisy, external kind. Long periods of inactivity, without anything to engage their minds, can lead to feelings of restlessness and unease.

Psychologists suggest that introverts are more prone to overthinking and rumination. So while they require quiet time to recharge, they also need meaningful activities or thought-provoking tasks to occupy their minds.

So yes, introverts need their space, but they also need a good book, a compelling project, or an intriguing puzzle to keep their minds active. Its all about balance.

Imagine this: youre in the middle of a deep thought or focused on a complex task, and suddenly, someone interrupts you. Its like being jolted out of your own headspace, right?

For introverts, this is particularly irritating. They value their quiet time to think and process information, and interruptions can feel like uninvited intrusions into their mental space.

From a psychological perspective, introverts require more time to shift their attention from one task to another. Therefore, sudden interruptions can be particularly disruptive for them.

So next time you need something from an introverted colleague or friend who seems engrossed in their work or thoughts, try to approach them gently or wait for a natural pause. Theyll likely appreciate your consideration.

If theres one thing that rankles an introvert more than anything else, its assumptions made about their personality.

Being labeled as shy, antisocial, or lonely simply because they process the world differently can be incredibly frustrating. Its not that theyre unsociable; they just socialize in a different way.

Psychology tells us that introversion is not a flaw or a defect. Its simply a different way of interacting with the world.

So, instead of making assumptions, take the time to understand and appreciate the introverts in your life for who they truly are. They might just surprise you.

As we thread through the complex tapestry of human behavior, its crucial to understand that introversion is not a quirk to be corrected, but a trait to be respected.

Carl Jung, one of the most influential figures in psychology, once said, The meeting of two personalities is like the contact of two chemical substances: if there is any reaction, both are transformed.

This beautifully captures the essence of respecting individual differences. Introverts may find certain situations irritating, not due to an inherent flaw, but simply because their internal world operates differently.

Whether youre an introvert feeling seen and understood, or an extrovert gaining a new perspective, remember this: our differences make us unique, and understanding them brings us closer together.

Embrace the quiet. It has its own music if you listen closely.

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AI-driven alerts improve patient care escalation and survival rates in hospitals – News-Medical.Net

Deploying and evaluating a machine learning intervention to improveclinical care and patient outcomes is a key step in moving clinical deterioration models from byte to bedside, according to a June 13 editorial in Critical Care Medicine that comments on a Mount Sinai study published in the same issue. The main study found that hospitalized patients were 43 percent more likely to have their care escalated and significantly less likely to die if their care team received AI-generated alerts signaling adverse changes in their health.

We wanted to see if quick alerts made by AI and machine learning, trained on many different types of patient data, could help reduce both how often patients need intensive care and their chances of dying in the hospital. Traditionally, we have relied on older manual methods such as the Modified Early Warning Score (MEWS) to predict clinical deterioration. However, our study shows automated machine learning algorithm scores that trigger evaluation by the provider can outperform these earlier methods in accurately predicting this decline. Importantly, it allows for earlier intervention, which could save more lives."

Matthew A. Levin, MD, lead study author, Professor of Anesthesiology, Perioperative and Pain Medicine, and Genetics and Genomic Sciences, at Icahn Mount Sinai, and Director of Clinical Data Science at The Mount Sinai Hospital

The non-randomized, prospective study looked at 2,740 adult patients who were admitted to four medical-surgical units at The Mount Sinai Hospital in New York. The patients were split into two groups: one that received real-time alerts based on the predicted likelihood of deterioration, sent directly to their nurses and physicians or a "rapid response team" of intensive care physicians, and another group where alerts were created but not sent. In the units where the alerts were suppressed, patients who met standard deterioration criteria received urgent interventions from the rapid response team.

Additional findings in the intervention group demonstrated that patients:

"Our research shows that real-time alerts using machine learning can substantially improve patient outcomes," says senior study author David L. Reich, MD, President of The Mount Sinai Hospital and Mount Sinai Queens, the Horace W. Goldsmith Professor of Anesthesiology, and Professor of Artificial Intelligence and Human Health at Icahn Mount Sinai. "These models are accurate and timely aids to clinical decision-making that help us bring the right team to the right patient at the right time. We think of these as 'augmented intelligence' tools that speed in-person clinical evaluations by our physicians and nurses and prompt the treatments that keep our patients safer. These are key steps toward the goal of becoming a learning health system."

The study was terminated early due to the COVID-19 pandemic. The algorithm has been deployed on all stepdown units within The Mount Sinai Hospital, using a simplified workflow. A stepdown unit is a specialized area in the hospital where patients who are stable but still require close monitoring and care are placed. It's a step between the intensive care unit (ICU) and a general hospital area, ensuring that patients receive the right level of attention as they recover.

A team of intensive care physicians visits the 15 patients with the highest prediction scores every day and makes treatment recommendations to the doctors and nurses caring for the patient. As the algorithm is continually retrained on larger numbers of patients over time, the assessments by the intensive care physicians serve as the gold standard of correctness, and the algorithm becomes more accurate through reinforcement learning.

In addition to this clinical deterioration algorithm, the researchers have developed and deployed 15 additional AI-based clinical decision support tools throughout the Mount Sinai Health System.

The Mount Sinai paper is titled "Real-Time Machine Learning Alerts to Prevent Escalation of Care: A Nonrandomized Clustered Pragmatic Clinical Trial." The remaining authors of the paper, all with Icahn Mount Sinai except where indicated, are Arash Kia, MD, MSc; Prem Timsina, PhD; Fu-yuan Cheng, MS; Kim-Anh-Nhi Nguyen, MS; Roopa Kohli-Seth, MD; Hung-Mo Lin, ScD (Yale University); Yuxia Ouyang, PhD; and Robert Freeman, RN, MSN, NE-BC.

Source:

Journal reference:

Levin, M. A., et al. (2024). Real-Time Machine Learning Alerts to Prevent Escalation of Care: A Nonrandomized Clustered Pragmatic Clinical Trial.Critical Care Medicine. doi.org/10.1097/CCM.0000000000006243.

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AI-driven alerts improve patient care escalation and survival rates in hospitals - News-Medical.Net

How Flow Cytometry Spurred Cell Biology – The Scientist

In the mid-twentieth century, Louis Kamentsky, an engineer at Columbia University at the time, searched for a convenient approach for differentiating cancerous and normal cells. He modified a cell counting device that arranged samples into a single-file line by mounting an oscilloscope to measure their absorption and scattering of light as the cells passed through a flow tube.1-4

Around the same time, Mack Fulwyler, an engineer working at Los Alamos National Laboratory, needed to separate particles, so he drew on existing techniques to create droplets to separate cells from a flow stream based upon charge that correlated to their volume.5,6 These approaches laid the foundation for flow cytometry, which is now a staple in biological research.

All of the methodology that existed before flow cytometry suddenly could be applied to the single cell, said Thomas Jovin, a biophysicist at the Max Plank Institute who developed advancements to the instruments in the 1970s as flow cytometry emerged as a major player in the research space.

Flow cytometry entered biomedical research in immunology and cancer labs out of initial interests in separating and counting cells in a mixed population, but groups also developed instruments purely to characterize cells.7,8 The flow cytometer and the flow sorter are not separate instruments, explained Jovin. The flow sorter requires that it be a flow cytometer at the same time because you have to make the same measurement. Its just that youre using it to process the cell after it has gone through the detection system. Today, instruments that both analyze and sort cells are referred to as flow sorters and those that do not are called flow analyzers.

Initially, flow measurements were based on fluorescent light emitted from dyes that researchers used to identify genetic material, but soon after, scientist also determined the cells size based on its light-scatter patterns.9, 10 These first instruments used lamps as their light source, but this soon changed. The lasers came along very quickly, Jovin said. They were important because you could focus a laser down to microns, whereas you cant do that with a large optical source like a lamp.

You can measure essentially anything in, on, or produced by a cell at a high rate of speed in a heterogeneous solution at a rapid rate.

Jonni Moore, University of Pennsylvania

Soon, researchers added more lasers to their instruments to expand the colors they could detect and developed methods to analyze and sort cells labeled with two fluorescent molecules.11,12 With the help of dichroic mirrors and bandpass filters that reflect and isolate, respectively, specific wavelengths of light to dedicated detectors, scientists could funnel the signal from multiple parameters to specific detectors to study more features of their samples.13

As the parameters that flow systems used expanded, data poured out of labs globally. You have a lot of signals that have been processed in real time, and you have to make decisions, in the case of the sorter, in real time, because otherwise your cells wont be there anymore, Jovin said. The only way to do that was by computation. Jovin and his team developed a computer-controlled flow cytometry instrument that facilitated the data analysis process.14

With the ability to rapidly assay and separate cells of interest from a mixed population based on multiple parameters, flow cytometry rivaled its predecessor, microscopy, in the study of cells. Jonni Moore, an immunologist and the director of the shared resource laboratory at the University of Pennsylvania, recalled using a flow cytometer for the first time after only having used a fluorescent microscope during graduate school. I thought I had died and gone to heaven, she said. According to Moore, classifying T lymphocytes on the microscope took several hours longer than the seconds it took her to analyze thousands of cells by flow cytometry. It really allowed me to ask a lot more questions in my research, Moore said.

While some research focused on the ability to analyze cell properties with flow systems, many groups used flow cytometry for its sorting capacity.15 However, as scientists developed new dyes, they could use flow cytometry to analyze more cellular parameters, such as mitochondrial activity and the quantity of particular receptors on cells.16-18

Flow cytometry analysis expanded into the clinical setting by helping streamline the quantification of CD4+ T cells during the human immunodeficiency virus (HIV) epidemic. Compared to microscopy, flow cytometry analysis was faster and more reliable.19, 20 Over the next 30 plus years, analytical cytometry exploded as we realized that we could measure virtually anything in, on, or produced by a cell, in multiple populations at the same time, Moore said.

Today, researchers still use flow cytometry to analyze a population of cells based on the presence of surface markers tagged with a fluorescent antibody or other probe. However, these analyzers can also use dyes and other techniques to investigate cellular functions, such as metabolism and protein secretion.21, 22 Researchers can assess cell proliferation and death with flow cytometry by measuring the dilution of dye or uptake of it.23, 24 While various individual methods exist that can measure the amount of protein or other mediators produced by cells or their activity, they require researchers to do them separately. The technology of flow cytometry, as it exists today, allows you to do all of that together, Moore said.

However, despite measuring an entire population of cells, flow cytometry is a single-cell technique. Because youve dissociated tissues and youve put these objects into kind of single file, youve lost where theyre seated next to one another, explained Lisa Nichols, the director of the flow cytometry facility at Stanford University. That level of spatial information requires microscopy. Nonetheless, flow cytometry produces high dimensional information on individual cells, and in contrast to other single cell techniques, does so more quickly on larger populations. Flow cytometry can actually go through and get you the results from millions of cells in a matter of minutes, Nichols said.

A high-throughput, single-cell method enables researchers to assess several cell parameters simultaneously with the help of lasers.

Scientists prepare samples as single cell suspensions and labels components of interest with fluorescent antibodies or other probes. The cytometer uses pumps to draw the sample through tubing to analyze it.

Using hydrodynamic focusing the instrument injects the sample into a fast-moving stream of fluid that funnels the sample single file through a narrow channel.

The channel leads to a point where the individual cells intersect with one or more lasers. The measured sample is deposited into a waste receptable after it passes this point.

As a cell begins to cross the laser beam, it scatters light. Light that mostly crosses the cell is detected as forward scatter and measures the cells size. Light that encounters obstacles in the cell changes direction and is detected by a side scatter detector, indicating the granularity of the cell. If the lasers excite fluorescent molecules in the cell, the emitted light is channeled through dichroic mirrors and bandpass filters to isolate specific wavelengths that meet detectors specific for those wavelengths.

Ashleigh Campsall

Fluorescent probes have come a long way since the 1960s. Researchers have added lasers and probes that recognize the violet and infrared range, as well as expanded probes into quantum dots, or inorganic nanocrystals.25-27 These additions greatly expanded the available colors for researchers to use, but introduced new challenges, as more color parameters increased the likelihood of overlapping spectra from these probes. As those overlaps increase, your ability to resolve very dim signals is compromised, said Nichols.

In traditional cytometers, to minimize overlapping signals from multiple fluorescent probes, the instrument doesnt use all of the light energy that a molecule emits. We take that whole spectrum, and we take a slice of it. And we measure that slice, said Timothy Bushnell, the flow cytometry core director at the University of Rochester. Mirrors and bandpass filters only permit a certain range of wavelengths to reach their detectors, which usually correspond to the peak emission spectra of commonly used probes.

While this method simplifies the problem of overlapping spectra in multiparameter experiments, it eliminates potentially valuable information. This prompted the development of spectral analyzers, which capture a fluorescent molecules full emission spectrum.28, 29 We now get the whole picture of what that spectrum looks like, Bushnell said.

Using single-labeled and unlabeled controls, the instrument accesses the entire spectrum of these samples to calculate the distinct emission spectra of each color from the mixed readout. The introduction of spectral flow cytometry enabled researchers to conduct multidimensional analyses. It lets you have more flexibility in what fluorochromes you use because youre not confined to this one detector, one fluorochrome phenomenon, Bushnell said. These advancements come in tandem with improved detector technology, such as swapping out current photomultiplier tubes for silica-based models that pick up longer wavelengths better.30

While flow cytometry enables a high dimensional analysis of individual cells within a population, researchers cannot see where their target of interest is within or on the cell. Our resolution is basically a dot on a plot, Bushnell said. This type of resolution traditionally had to be done with microscopy, but at the expense of time and quantity of cells analyzed. The introduction of imaging cytometry is changing that.31

Image flow cytometers capture an image of a cell as it flows through transit. We could combine the power of knowing where something is, so seeing where it is in the cell, with the statistics that flow can give you, Bushnell said.

Anything you can actually make into a particulate solution and put a fluorescent tag on, you can now measure.

Lisa Nichols, Stanford University

You are limited by the fact that it is flow, so these things are moving, Nichols said. Youre never going to get the resolution youre going to get with a microscope where its sitting still. Although not in the resolution possible with microscopy, the photographs provide additional information about where signal originates from within and on a sample.

Additionally, having been available for flow cytometry analyzers for more than a decade, this imaging capacity is becoming available for flow cytometry sorters.32 One setback in this application is the ability to take an image rapidly and interpret that image to make a decision for a falling samples fate. Things are moving so fast, you need to do one of two things, Nichols said. You either have to have a whole bunch of predetermined features that youre looking for that can be matched to each individual cell, or you have to have AI and computing technologies.

Not only will the rapid computing power of machine learning be necessary for quick sorting decisions, but as flow cytometry becomes increasingly multiparametric, researchers forgo the traditional bivariate plots for computational analyses already used in single-cell sequencing analyses.33-35 When you look at dot plots, two by twos, you only ever see the elephant foot. You can never see the whole elephant by doing that, said Moore. This opens the opportunity to explore and interpret data in completely new ways, possibly by introducing previously overlooked findings in datasets.

Beyond crunching the numbers in individual experiments, machine learning may offer the ability to account for variations between experiments, or batch effects. Even more broadly, these intelligent tools may be imperative for comparing and combining analyses between different institutions, confidently enabling collaborations.36

Flow cytometry is not restricted to cells. Anything you can actually make into a particulate solution and put a fluorescent tag on, you can now measure, said Nichols. With the help of microfluidic technology, instruments analyze everything from metal nanoparticles and microplastics to exosomes.37-40 These droplets have also paved the way for studying materials typically released from cells, including antibodies and other proteins and may soon be compatible with existing flow systems.41-43 Meanwhile, specially developed cytometers with the ability to more accurately measure the small scale of microparticles advance the research potential of this field.44, 45 All of these developments aim to push flow cytometry to its next limit.

References

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How Flow Cytometry Spurred Cell Biology - The Scientist

A new way to measure ageing and disease risk with the protein aggregation clock – EurekAlert

image:

Visualization of a protein aggregation clock

Credit: ill./: Nike Heinss / JGU

--JOINT PRESS RELEASE OF THE INSTITUTE OF MOLECULAR BIOLOGY (IMB) AND JOHANNES GUTENBERG UNIVERSITY MAINZ --

Could measuring protein clumps in our cells be a new way to find out our risk of getting age-related diseases? Professor Dorothee Dormann and Professor Edward Lemke of Johannes Gutenberg University Mainz (JGU), who are also adjunct directors at the Institute of Molecular Biology (IMB) in Mainz, propose the concept of a "protein aggregation clock" to measure ageing and health in a new perspective article published inNature Cell Biology.

As we age, the DNA and proteins that make up our bodies gradually undergo changes that cause our bodies to no longer work as well as before. This in turn makes us more prone to getting age-related diseases, such as cardiovascular disease, cancer, and Alzheimer's disease. One important change is that the proteins in our cells can sometimes become misfolded and clump together to form aggregates, so-called amyloids. Misfolding and aggregation can happen to any protein, but a specific group of proteins known as intrinsically disordered proteins (IDPs) are especially prone to forming amyloids. IDPs make up around 30 percent of the proteins in our cells and they are characterized by having no fixed structure. Instead, they are flexible and dynamic, flopping around like strands of cooked spaghetti.

While the molecular mechanisms are widely debated and an important aspect of basic research, scientists know that aggregates formed from IDPs tend to accumulate in many long-lived cells such as neurons or muscle cells as we age. Moreover, they can cause many age-related diseases, particularly neurodegenerative diseases such as Alzheimer's and Parkinson's disease. Thus, having many aggregates in a cell could be an indicator of how unhealthy the cell is or if a person is likely to develop an age-related disease soon. In their recently published article, Dormann and Lemke propose that IDP aggregation could be used as a biological "clock" to measure a person's health and age.

If developed further into a sensitive diagnostic test, a protein aggregation clock could be extremely useful. Firstly, doctors could use it to help diagnose age-related diseases at very early stages or identify people who are not yet sick but have a higher risk of developing disease as they age. This would allow them to be given preventative treatments before they develop severe disease. Secondly, scientists could use it to assess the effects of new experimental treatments to reduce protein aggregation in order to prevent or delay age-related diseases.

"In practice, we are still far away from a routine diagnostic test, and it is important that we improve our understanding of the fundamental mechanisms leading to IDP aggregation", said Dormann. "However, we want to stimulate thinking and research in the direction of studying protein aggregates to measure biological ageing processes," Lemke added. "We are optimistic that in the future we will be able to overcome the current challenges of reading a protein aggregation clock through more research on IDP dynamics and making further technological developments."

Although there are other "clocks" to measure ageing and health, most of them are based on nucleic acids like DNA. Dormann and Lemke think that a biological clock based on proteins would be a useful complement to these existing clocks, as proteins are among the most abundant molecules in cells and are crucial for all cellular functions. With the help of such a protein aggregation clock, they hope that scientists and doctors will be able to move one step closer towards helping people age healthily and preventing age-related diseases.

With their research, Dorothee Dormann and Edward Lemke contribute to the Center for Healthy Ageing (CHA), a virtual research center launched in 2021. The CHA brings together scientists in basic and clinical research from across Mainz who focus on ageing and age-related diseases. Their findings are to be used to promote healthy ageing and to find treatments that help prevent or cure age-related diseases.

Related links:

Contact: Professor Dr. Dorothee Dormann Molecular Cell Biology Institute of Molecular Physiology (IMP) Johannes Gutenberg University Mainz 55099 Mainz, GERMANY and Institute of Molecular Biology (IMB) 55128 Mainz, GERMANY phone: +49 6131 39-36206 e-mail: ddormann@uni-mainz.de https://www.blogs.uni-mainz.de/fb10-biologie-eng/about-the-faculty-of-biology/institutes/institute-of-molecular-physiology-imp/

Professor Dr. Edward Lemke Synthetic Biophysics Institute of Molecular Physiology (IMP) Johannes Gutenberg University Mainz 55099 Mainz, GERMANY and Institute of Molecular Biology (IMB) 55128 Mainz, GERMANY phone: +49 6131 39-36118 e-mail: edlemke@uni-mainz.de https://lemkelab.uni-mainz.de/

Read more:

Nature Cell Biology

Adding intrinsically disordered proteins to biological ageing clocks

23-May-2024

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.

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A new way to measure ageing and disease risk with the protein aggregation clock - EurekAlert