MIT scientists find a way to rejuvenate the immune system as we age

 

As people get older, the immune system often becomes less effective. Populations of T cells shrink, and the remaining cells may respond more slowly to germs. That slowdown can leave older adults more vulnerable to many kinds of infections.

To address this age related decline, scientists from MIT and the Broad Institute developed a method to temporarily reprogram liver cells in a way that strengthens T cell performance. The goal is to make up for the reduced output of the thymus, the organ where T cells normally mature.

In the study, the team used mRNA to deliver three important factors that support T cell survival. With this approach, they were able to rejuvenate the immune systems of mice. Older mice that received the treatment produced larger and more varied T cell populations after vaccination, and they also showed improved responses to cancer immunotherapy.

The researchers say that if this strategy can be adapted for patients, it could help people stay healthier as they age.

"If we can restore something essential like the immune system, hopefully we can help people stay free of disease for a longer span of their life," says Feng Zhang, the James and Patricia Poitras Professor of Neuroscience at MIT, who has joint appointments in the departments of Brain and Cognitive Sciences and Biological Engineering.

Zhang is also an investigator at the McGovern Institute for Brain Research at MIT, a core institute member at the Broad Institute of MIT and Harvard, and an investigator in the Howard Hughes Medical Institute. He is the senior author of the new study. Former MIT postdoc Mirco Friedrich is the lead author of the paper, which was published in Nature.

The Thymus and Why T Cells Decline With Age

The thymus is a small organ located in front of the heart, and it is essential for building a healthy supply of T cells. Inside the thymus, immature T cells go through a checkpoint process that helps create a diverse set of T cells. The thymus also releases cytokines and growth factors that help T cells survive.

But beginning in early adulthood, the thymus starts to shrink. This process is called thymic involution, and it reduces the body's ability to produce new T cells. By about age 75, the thymus is essentially nonfunctional.

"As we get older, the immune system begins to decline. We wanted to think about how can we maintain this kind of immune protection for a longer period of time, and that's what led us to think about what we can do to boost immunity," Friedrich says.

Earlier efforts to rejuvenate the immune system have often focused on sending T cell growth factors through the bloodstream, but that approach can cause harmful side effects. Other researchers are investigating whether transplanted stem cells could help regrow functional thymus tissue.

A Temporary Liver Factory Powered by mRNA

The MIT team chose a different strategy. They asked whether the body could be prompted to create a temporary "factory" that produces the same T cell stimulating signals typically made by the thymus.

"Our approach is more of a synthetic approach," Zhang says. "We're engineering the body to mimic thymic factor secretion."

They selected the liver for the job for several reasons. The liver can produce large amounts of protein even in old age. It is also easier to deliver mRNA to the liver than to many other organs. In addition, all circulating blood flows through the liver, including T cells, making it a practical place to release immune supporting signals into the bloodstream.

To build this factory, the researchers picked three immune cues involved in T cell maturation. They encoded these factors into mRNA and packaged the sequences into lipid nanoparticles. After injection into the bloodstream, the nanoparticles collect in the liver. Hepatocytes take up the mRNA and begin making the proteins encoded by it.

The three factors delivered were DLL1, FLT-3, and IL-7. These signals help immature progenitor T cells develop into fully differentiated T cells.

Vaccine and Cancer Immunotherapy Benefits in Older Mice

Experiments in mice showed multiple positive outcomes. In one test, the researchers injected the mRNA particles into 18 month old mice, roughly comparable to humans in their 50s. Because mRNA does not last long in the body, the team gave repeated doses over four weeks to keep the liver producing the factors consistently.

After the treatment, T cell populations increased substantially in both size and function.

The team then examined whether the approach improved vaccine responses. They vaccinated mice with ovalbumin, a protein found in egg whites that is often used to study immune reactions to a specific antigen. In 18 month old mice that received the mRNA treatment before vaccination, the number of cytotoxic T cells targeting ovalbumin doubled compared with untreated mice of the same age.

The researchers also found that the mRNA method could strengthen responses to cancer immunotherapy. They treated 18 month old mice with the mRNA, implanted tumors, and then gave the mice a checkpoint inhibitor drug. This drug targets PD-L1 and is intended to release the immune system's brakes so T cells can attack tumor cells more effectively.

Mice that received both the checkpoint inhibitor and the mRNA treatment had much higher survival rates and lived longer than mice that received the checkpoint inhibitor drug without the mRNA treatment.

The researchers determined that all three factors were required for the immune improvement. No single factor could reproduce the full effect. Next, the team plans to test the approach in additional animal models and search for other signaling factors that might further strengthen immune function. They also want to investigate how the treatment influences other immune cells, including B cells.

Other authors of the paper include Julie Pham, Jiakun Tian, Hongyu Chen, Jiahao Huang, Niklas Kehl, Sophia Liu, Blake Lash, Fei Chen, Xiao Wang, and Rhiannon Macrae.

The research was funded in part by the Howard Hughes Medical Institute, the K. Lisa Yang Brain-Body Center at MIT, Broad Institute Programmable Therapeutics Gift Donors, the Pershing Square Foundation, the Phillips family, J. and P. Poitras, and an EMBO Postdoctoral Fellowship.

Journal Reference:

1. Mirco J. Friedrich, Julie Pham, Jiakun Tian, Hongyu Chen, Jiahao Huang, Niklas Kehl, Sophia Liu, Blake Lash, Fei Chen, Xiao Wang, Rhiannon K. Macrae, Feng Zhang. Transient hepatic reconstitution of trophic factors enhances aged immunity. Nature, 2025; DOI: 10.1038/s41586-025-09873-4 

Courtesy:
Massachusetts Institute of Technology. "MIT scientists find a way to rejuvenate the immune system as we age." ScienceDaily. ScienceDaily, 29 December 2025. <www.sciencedaily.com/releases/2025/12/251227082718.htm>. 

 

 

 

 

The brain has a hidden language and scientists just found it

 

Scientists have developed a protein that can record the chemical messages brain cells receive, rather than focusing only on the signals they send out. These incoming signals are created when neurons release glutamate, a neurotransmitter that plays a vital role in brain communication. Although glutamate is essential for processes like learning and memory, its activity has been extremely difficult to measure because the signals are faint and happen very quickly.

This new tool makes it possible to detect those subtle chemical messages as they arrive, giving researchers access to a part of brain communication that has long been hidden.

Being able to observe incoming signals allows scientists to study how neurons process information. Each brain cell receives thousands of inputs, and how it combines those signals determines whether it produces an output. This process is thought to underlie decisions, thoughts, and memories, and studying it directly could help explain how the brain performs complex computations.

The advance also opens new paths for disease research. Problems with glutamate signaling have been linked to conditions such as Alzheimer's disease, schizophrenia, autism, epilepsy, and others. By measuring these signals more precisely, researchers may be able to identify the biological roots of these disorders.

Drug development could also benefit. Pharmaceutical companies can use these sensors to see how experimental treatments affect real synaptic activity, which may help speed up the search for more effective therapies.

Introducing a powerful glutamate sensor

The protein was engineered by researchers at the Allen Institute and HHMI's Janelia Research Campus. Known as iGluSnFR4 (pronounced 'glue sniffer'), it acts as a molecular "glutamate indicator." Its sensitivity allows it to detect even the weakest incoming signals exchanged between neurons.

By revealing when and where glutamate is released, iGluSnFR4 provides a new way to interpret the complex patterns of brain activity that support learning, memory, and emotion. It gives scientists the ability to watch neurons communicate inside the brain in real time. The findings were recently published in Nature Methods and could significantly change how neural activity is measured and analyzed in neuroscience research.

How brain cells communicate

To understand the impact of this advance, it helps to look at how neurons interact. The brain contains billions of neurons that communicate by sending electrical signals along branch-like structures called axons. When an electrical signal reaches the end of an axon, it cannot cross the small gap to the next neuron, which is known as a synapse.

Instead, the signal triggers the release of neurotransmitters into the synapse. Glutamate is the most common of these chemical messengers and plays a key role in memory, learning, and emotion. When glutamate reaches the next neuron, it can cause that cell to fire, continuing the chain of communication.

From fragments to the full conversation

This process can be compared to falling dominos, but it is far more complex. Each neuron receives input from thousands of others, and only certain combinations and patterns of activity will trigger the receiving neuron to fire. With this new protein sensor, scientists can now identify which patterns of incoming activity lead to that response.

Until now, observing these incoming signals in living brain tissue was nearly impossible. Previous technologies were too slow or lacked the sensitivity needed to measure activity at individual synapses. As a result, researchers could only see pieces of the communication process rather than the full exchange. This new approach allows them to capture the entire conversation.

Making sense of neural connections

"It's like reading a book with all the words scrambled and not understanding the order of the words or how they're arranged," said Kaspar Podgorski, Ph.D., a lead author of the study and senior scientist at the Allen Institute. "I feel like what we're doing here is adding the connections between those neurons and by doing that, we now understand the order of the words on the pages, and what they mean."

Before protein sensors like iGluSnFR4 were available, researchers could only measure outgoing signals from neurons. This left a major gap in understanding, since the incoming signals were too fast and too faint to detect.

"Neuroscientists have pretty good ways of measuring structural connections between neurons, and in separate experiments, we can measure what some of the neurons in the brain are saying, but we haven't been good at combining these two kinds of information. It's hard to measure what neurons are saying to which other neurons," Podgorski said. "What we have invented here is a way of measuring information that comes into neurons from different sources, and that's been a critical part missing from neuroscience research."

Collaboration behind the breakthrough

"The success of iGluSnFR4 stems from our close collaboration started at HHMI's Janelia Research Campus between the GENIE Project team and Kaspar's lab. That research has extended to the phenomenal in vivo characterization work done by the Allen Institute's Neural Dynamics group," said Jeremy Hasseman, Ph.D., a scientist with HHMI's Janelia Research Campus. "This was a great example of collaboration across labs and institutes to enable new discoveries in neuroscience."

A new window into brain function

This discovery overcomes a major limitation in modern neuroscience by making it possible to directly observe how neurons receive information. With iGluSnFR4 now available to researchers through Addgene, scientists have a powerful new tool to explore brain function in greater detail. As this technology spreads, it may help reveal answers to some of the brain's most enduring questions.

Journal Reference:

1. Abhi Aggarwal, Adrian Negrean, Yang Chen, Rishyashring Iyer, Daniel Reep, Anyi Liu, Anirudh Palutla, Michael E. Xie, Bryan J. MacLennan, Kenta M. Hagihara, Lucas W. Kinsey, Julianna L. Sun, Pantong Yao, Jihong Zheng, Arthur Tsang, Getahun Tsegaye, Yonghai Zhang, Ronak H. Patel, Benjamin J. Arthur, Julien Hiblot, Philipp Leippe, Miroslaw Tarnawski, Jonathan S. Marvin, Jason D. Vevea, Srinivas C. Turaga, Alison G. Tebo, Matteo Carandini, L. Federico Rossi, David Kleinfeld, Arthur Konnerth, Karel Svoboda, Glenn C. Turner, Jeremy P. Hasseman, Kaspar Podgorski. Glutamate indicators with increased sensitivity and tailored deactivation rates. Nature Methods, 2025; DOI: 10.1038/s41592-025-02965-z 

Courtesy:

Allen Institute. "The brain has a hidden language and scientists just found it." ScienceDaily. ScienceDaily, 29 December 2025. <www.sciencedaily.com/releases/2025/12/251225235950.htm>.

 

 

 

 

 

 

Ramanujan’s 100-year-old pi formula is still revealing the Universe

 

Most people first encounter the irrational number π (pi) -- commonly approximated as 3.14 and extending infinitely without repeating -- during school lessons about circles. In recent decades, advances in computing have pushed this familiar constant far beyond the classroom, with powerful supercomputers now calculating pi to trillions of decimal places.

Researchers have now uncovered an unexpected twist. Physicists at the Centre for High Energy Physics (CHEP), Indian Institute of Science (IISc) report that mathematical formulas developed a century ago to compute pi are closely linked to some of today's most important ideas in fundamental physics. These connections appear in theoretical descriptions of percolation, fluid turbulence, and even certain features of black holes.

Ramanujan's Remarkable Pi Formulae

In 1914, shortly before leaving Madras for Cambridge, renowned Indian mathematician Srinivasa Ramanujan published a paper presenting 17 different formulas for calculating pi. These expressions were strikingly efficient, allowing pi to be computed much faster than existing techniques of the time. Despite containing only a small number of mathematical terms, the formulas produced an impressive number of accurate digits.

Their impact has endured. Ramanujan's methods became foundational to modern mathematical and computational approaches for calculating pi, including those used by today's most advanced machines. "Scientists have computed pi up to 200 trillion digits using an algorithm called the Chudnovsky algorithm," says Aninda Sinha, Professor at CHEP and senior author of the study. "These algorithms are actually based on Ramanujan's work."

A Deeper Question Behind the Mathematics

For Sinha and Faizan Bhat, the study's first author and a former IISc PhD student, the mystery went beyond computational efficiency. They asked why such powerful formulas should exist in the first place. Rather than treating them as purely abstract results, the team searched for an explanation rooted in physics.

"We wanted to see whether the starting point of his formulae fit naturally into some physics," says Sinha. "In other words, is there a physical world where Ramanujan's mathematics appears on its own?"

Where Pi Meets Scale Invariance and Physics Extremes

Their investigation led them to a broad family of theories known as conformal field theories, and more specifically to logarithmic conformal field theories. These theories describe systems that exhibit scale invariance symmetry -- meaning they look the same regardless of how closely they are examined, similar to fractals.

A familiar physical example appears at the critical point of water, defined by a precise temperature and pressure at which liquid water and water vapor become indistinguishable. At this point, water displays scale invariance symmetry, and its behavior can be captured using conformal field theory. Similar critical behavior arises in percolation (how substances spread through a material), during the onset of turbulence in fluids, and in certain theoretical treatments of black holes. These phenomena fall within the domain of logarithmic conformal field theories.

Using Ramanujan's Structure to Solve Physics Problems

The researchers discovered that the mathematical framework at the heart of Ramanujan's pi formulas also appears in the equations underlying these logarithmic conformal field theories. By exploiting this shared structure, they were able to compute key quantities within the theories more efficiently. Such calculations could ultimately improve scientists' understanding of complex processes like turbulence and percolation.

The approach mirrors Ramanujan's own method of starting from a compact mathematical expression and rapidly arriving at precise results for pi. "[In] any piece of beautiful mathematics, you almost always find that there is a physical system which actually mirrors the mathematics," says Bhat. "Ramanujan's motivation might have been very mathematical, but without his knowledge, he was also studying black holes, turbulence, percolation, all sorts of things."

A Century-Old Insight With Modern Impact

The findings reveal that Ramanujan's formulas, developed more than 100 years ago, offer a previously hidden advantage for making modern high-energy physics calculations faster and more manageable. Beyond their practical value, the researchers say the work highlights the extraordinary reach of Ramanujan's ideas.

"We were simply fascinated by the way a genius working in early 20th century India, with almost no contact with modern physics, anticipated structures that are now central to our understanding of the universe," says Sinha.

Journal Reference:

1. Faizan Bhat, Aninda Sinha. Ramanujan’s 1/π Series and Conformal Field Theories. Physical Review Letters, 2025; 135 (23) DOI: 10.1103/c38g-fd2v 

Courtesy: Indian Institute of Science (IISc). "Ramanujan’s 100-year-old pi formula is still revealing the Universe." ScienceDaily. ScienceDaily, 16 December 2025. <www.sciencedaily.com/releases/2025/12/251216081949.htm>. 

 

 

 

A flesh-eating fly once eradicated is moving back toward the U.S.

When the New World screwworm last spread across the United States, it caused widespread damage to livestock and took decades to eliminate. That history is now driving a new effort by researchers at the University of California Riverside, who are working to stop the parasitic fly before it can reestablish itself.

Despite its name, the New World screwworm is not a worm. It is the larval, or maggot, stage of a metallic-looking blowfly known as Cochliomyia hominivorax. Most blowflies are harmless and play an important role by breaking down dead animals. This species is different because it feeds on living tissue.

"Not all blowflies are this species. We don't have to be afraid of all flies," said Amy Murillo, UCR assistant professor of entomology and principal investigator of the project. "But this particular species isn't one we want here."

Monitoring California for Early Warning Signs

Backed by $507,000 from the California Department of Food and Agriculture, UCR entomologists are launching a statewide monitoring program to detect any early signs of the fly's return. The screwworm lays its eggs in open wounds on warm-blooded animals, including humans. Once the eggs hatch, the maggots burrow into flesh in a corkscrew motion, which is how the insect got its name.

The New World screwworm was once common across California and much of the southern United States. About 60 years ago, it was successfully wiped out using a large-scale program that released millions of sterile male flies. Because female screwworms mate only once, the strategy caused the population to collapse. That effort pushed the species south to Panama, where the U.S. Department of Agriculture has maintained a protective barrier ever since.

A Growing Threat to the North

In recent years, the screwworm has started appearing again in parts of Central America and southern Mexico. Experts believe the resurgence is linked to the movement of infested animals, often transported by people who unknowingly help the pest spread.

"It hasn't been found in California yet, but it's within 70 miles of the Texas border," Murillo said. "We need to be prepared."

Traps, Lures, and Early Detection

Murillo is working with Alec Gerry, a UCR veterinary entomology professor and CE Specialist, to deploy traps across California. These traps use a lure developed by the USDA that mimics the smell of rotting flesh. While many blowfly species are attracted to it, the lure is also effective at drawing in the New World screwworm. Researchers will regularly check the traps for any sign that the invasive fly has crossed into the state.

The project also includes an outreach effort aimed at veterinarians, livestock handlers, and entomologists. These groups are the most likely to encounter screwworm infestations early, and catching an outbreak quickly is key to stopping it from spreading.

Why Livestock Face the Greatest Risk

Screwworms pose a serious threat to farm animals, especially those with common injuries from barbed wire, birthing, or procedures such as dehorning. Without treatment, infestations can quickly worsen as flies lay more eggs, enlarging wounds and sometimes leading to death.

California's dairy and cattle industries are particularly vulnerable. "Most people think of citrus or avocados as being our top exports, but it's actually dairy that leads our agricultural economy," Murillo said.

Public Awareness as a Line of Defense

Even though the fly has not been detected in California, researchers say public awareness is an important part of prevention. "Not all blowflies are harmful, and many are beneficial," Murillo said. "But if you notice something unusual on your pet or livestock, reach out to a vet. Don't ignore it."

If an outbreak were to happen again, Murillo said the same sterile insect technique used in the past would still be the most effective tool for stopping it.

Rare but Possible Human Infections

Although screwworms primarily target animals, humans can also be affected under certain conditions, particularly when open wounds go untreated. Infections have been documented in people who traveled to regions where the fly is active. Even so, livestock remain the primary concern.

"They need an opening in the flesh, and it doesn't have to be large. They don't make wounds, but they do exploit them," Murillo said.

Staying Alert Without Panic

Murillo emphasized that the goal is preparedness, not fear.

"You don't have to worry that they're going to start eating your flesh," Murillo said. "But we do hope that this project will help people to be more vigilant in recognizing and preventing screwworm infestations in animals should they return to California."

Story Source:

Materials provided by University of California - Riverside. Note: Content may be edited for style and length.

 

Courtesy:

University of California - Riverside. "A flesh-eating fly once eradicated is moving back toward the U.S.." ScienceDaily. ScienceDaily, 18 December 2025. <www.sciencedaily.com/releases/2025/12/251217082501.htm>.  

AI detects cancer but it’s also reading who you are

 

At a glance:

• A new study shows that artificial intelligence systems used to diagnose cancer from pathology slides do not perform equally for all patients, with accuracy varying across different demographic groups.
• Researchers pinpointed three key reasons behind this bias and created a new approach that significantly reduced these differences.
• The results emphasize why medical AI must be routinely evaluated for bias to help ensure fair and reliable cancer care for everyone.

Pathology and the Foundations of Cancer Diagnosis

For decades, pathology has been essential to how doctors diagnose and treat cancer. A pathologist studies an extremely thin slice of human tissue under a microscope, searching for visual signs that reveal whether cancer is present and, if so, what type and stage it has reached.

To a trained specialist, examining a pink, swirling tissue sample dotted with purple cells is like grading a test without a name on it -- the slide contains vital information about the disease, but it offers no clues about who the patient is.

When AI Sees More Than Expected

That assumption does not fully apply to artificial intelligence systems now entering pathology labs. A new study led by researchers at Harvard Medical School shows that pathology AI models can infer demographic details directly from tissue slides. This unexpected ability can introduce bias into cancer diagnosis across different patient groups.

After evaluating several widely used AI models designed to identify cancer, the researchers found that these systems did not perform equally for all patients. Diagnostic accuracy varied based on patients' self-reported race, gender, and age. The team also uncovered several reasons why these disparities occur.

To address the issue, the researchers developed a framework called FAIR-Path, which significantly reduced bias in the tested models.

"Reading demographics from a pathology slide is thought of as a 'mission impossible' for a human pathologist, so the bias in pathology AI was a surprise to us," said senior author Kun-Hsing Yu, associate professor of biomedical informatics in the Blavatnik Institute at HMS and HMS assistant professor of pathology at Brigham and Women's Hospital.

Yu emphasized that recognizing and correcting bias in medical AI is critical, since it can directly influence diagnostic accuracy and patient outcomes. The success of FAIR-Path suggests that improving fairness in cancer pathology AI, and possibly other medical AI tools, may not require major changes to existing systems.

The work, which was supported in part by federal funding, is described Dec. 16 in Cell Reports Medicine.

Putting Cancer AI to the Test

Yu and his colleagues examined bias in four commonly used pathology AI models currently being developed for cancer diagnosis. These deep-learning systems were trained on large collections of labeled pathology slides, allowing them to learn biological patterns and apply that knowledge to new samples.

The team evaluated the models using a large, multi-institutional dataset that included pathology slides from 20 different types of cancer.

Across all four models, performance gaps consistently emerged. The AI systems were less accurate for certain demographic groups defined by race, gender, and age. For example, the models struggled to distinguish lung cancer subtypes in African American patients and in male patients. They also showed reduced accuracy when classifying breast cancer subtypes in younger patients. In addition, the models had difficulty detecting breast, renal, thyroid, and stomach cancers in some demographic groups. Overall, these disparities appeared in roughly 29 percent of the diagnostic tasks analyzed.

According to Yu, these errors arise because the AI systems extract demographic information from the tissue images -- and then rely on patterns linked to those demographics when making diagnostic decisions.

The findings were unexpected. "Because we would expect pathology evaluation to be objective," Yu said. "When evaluating images, we don't necessarily need to know a patient's demographics to make a diagnosis."

This led the researchers to ask a key question: Why was pathology AI failing to meet the same standard of objectivity?

Why Bias Appears in Pathology AI

The team identified three main contributors to the bias.

First, training data are often uneven. Tissue samples are easier to obtain from some demographic groups than others, resulting in imbalanced datasets. This makes it harder for AI models to accurately diagnose cancers in groups that are underrepresented, including some populations defined by race, age, or gender.

However, Yu noted that "the problem turned out to be much deeper than that." In several cases, the models performed worse for certain demographic groups even when sample sizes were similar.

Further analysis pointed to differences in disease incidence. Some cancers occur more frequently in specific populations, allowing AI models to become especially accurate for those groups. As a result, the same models may struggle to diagnose cancers in populations where those diseases are less common.

The researchers also found that AI models can detect subtle molecular differences across demographic groups. For example, the systems may identify mutations in cancer driver genes and use them as shortcuts to classify cancer type -- which can reduce accuracy in populations where those mutations are less prevalent.

"We found that because AI is so powerful, it can differentiate many obscure biological signals that cannot be detected by standard human evaluation," Yu said.

Over time, this can cause AI models to focus on signals tied more closely to demographics than to the disease itself, weakening diagnostic performance across diverse patient groups.

Taken together, Yu said, these findings show that bias in pathology AI is influenced not only by the quality and balance of training data, but also by the way the models are trained to interpret what they see.

A New Approach to Reducing Bias

After identifying the sources of bias, the researchers set out to correct them.

They developed FAIR-Path, a framework based on an existing machine-learning method known as contrastive learning. This approach modifies AI training so that models focus more strongly on critical distinctions, such as differences between cancer types, while reducing attention to less relevant differences, including demographic characteristics.

When FAIR-Path was applied to the tested models, diagnostic disparities dropped by about 88 percent.

"We show that by making this small adjustment, the models can learn robust features that make them more generalizable and fairer across different populations," Yu said.

The result is encouraging, he added, because it suggests that meaningful reductions in bias are possible even without perfectly balanced or fully representative training datasets.

Looking ahead, Yu and his team are working with institutions worldwide to study pathology AI bias in regions with different demographics, clinical practices, and laboratory settings. They are also exploring how FAIR-Path could be adapted for situations with limited data. Another area of interest is understanding how AI-driven bias contributes to broader disparities in health care and patient outcomes.

Ultimately, Yu said, the goal is to develop pathology AI systems that support human experts by delivering fast, accurate, and fair diagnoses for all patients.

"I think there's hope that if we are more aware of and careful about how we design AI systems, we can build models that perform well in every population," he said.

Authorship, funding, disclosures

Additional authors on the study include Shih-Yen Lin, Pei-Chen Tsai, Fang-Yi Su, Chun-Yen Chen, Fuchen Li, Junhan Zhao, Yuk Yeung Ho, Tsung-Lu Michael Lee, Elizabeth Healey, Po-Jen Lin, Ting-Wan Kao, Dmytro Vremenko, Thomas Roetzer-Pejrimovsky, Lynette Sholl, Deborah Dillon, Nancy U. Lin, David Meredith, Keith L. Ligon, Ying-Chun Lo, Nipon Chaisuriya, David J. Cook, Adelheid Woehrer, Jeffrey Meyerhardt, Shuji Ogino, MacLean P. Nasrallah, Jeffrey A. Golden, Sabina Signoretti, and Jung-Hsien Chiang.

Funding was provided by the National Institute of General Medical Sciences and the National Heart, Lung, and Blood Institute at the National Institutes of Health (grants R35GM142879, R01HL174679), the Department of Defense (Peer Reviewed Cancer Research Program Career Development Award HT9425-231-0523), the American Cancer Society (Research Scholar Grant RSG-24-1253761-01-ESED), a Google Research Scholar Award, a Harvard Medical School Dean's Innovation Award, the National Science and Technology Council of Taiwan (grants NSTC 113-2917-I-006-009, 112-2634-F-006-003, 113-2321-B-006-023, 114-2917-I-006-016), and a doctoral student scholarship from the Xin Miao Education Foundation.

Ligon was a consultant of Travera, Bristol Myers Squibb, Servier, IntegraGen, L.E.K. Consulting, and Blaze Bioscience; received equity from Travera; and has research funding from Bristol Myers Squibb and Lilly. Vremenko is a cofounder and shareholder of Vectorly.

The authors prepared the initial manuscript and used ChatGPT to edit selected sections to improve readability. After using this tool, the authors reviewed and edited the content as needed and take full responsibility for the content of the published article.

Journal Reference:

1. Shih-Yen Lin, Pei-Chen Tsai, Fang-Yi Su, Chun-Yen Chen, Fuchen Li, Junhan Zhao, Yuk Yeung Ho, Tsung-Lu Michael Lee, Elizabeth Healey, Po-Jen Lin, Ting-Wan Kao, Dmytro Vremenko, Thomas Roetzer-Pejrimovsky, Lynette Sholl, Deborah Dillon, Nancy U. Lin, David Meredith, Keith L. Ligon, Ying-Chun Lo, Nipon Chaisuriya, David J. Cook, Adelheid Woehrer, Jeffrey Meyerhardt, Shuji Ogino, MacLean P. Nasrallah, Jeffrey A. Golden, Sabina Signoretti, Jung-Hsien Chiang, Kun-Hsing Yu. Contrastive learning enhances fairness in pathology artificial intelligence systems. Cell Reports Medicine, 2025; 6 (12): 102527 DOI: 10.1016/j.xcrm.2025.102527 

Courtesy:

Harvard Medical School. "AI detects cancer but it’s also reading who you are." ScienceDaily. ScienceDaily, 17 December 2025. <www.sciencedaily.com/releases/2025/12/251217231230.htm>. 

 

 

 

 

 

 

A hidden T cell switch could make cancer immunotherapy work for more people

Over the past ten years, T cell immunotherapy has emerged as one of the most promising developments in cancer treatment. These therapies work by training a patient's own immune system to detect and destroy dangerous cells. Despite their success, scientists have struggled to fully explain how these treatments function at a molecular level. This lack of understanding has slowed progress, especially since T cell therapies work well for only a small number of cancer types and fail in most others, for reasons that have remained unclear. Gaining insight into their modus operandi could help make these therapies effective for far more patients.

Scientists at The Rockefeller University have now uncovered crucial details about the T cell receptor (TCR), a protein complex embedded in the cell membrane that plays a central role in T cell therapies. Using cryo-EM, researchers from the Laboratory of Molecular Electron Microscopy studied the receptor in a biochemical setting designed to closely resemble its native milieu. They discovered that the TCR behaves like a jack-in-the-box, staying compact until it encounters an antigen or another suspicious particle, at which point it rapidly opens. This behavior contradicts what earlier cryo-EM studies of the receptor had shown.

The findings, published in Nature Communications, could help researchers improve and expand the use of T cell immunotherapies.

"This new fundamental understanding of how the signaling system works may help re-engineer that next generation of treatments," says first author Ryan Notti, an instructor in clinical investigation in Walz's lab and a special fellow in the Department of Medicine at Memorial Sloan Kettering Cancer Center, where he treats patients with sarcomas, or cancers that arise in soft tissue or bone.

"The T cell receptor is really the basis of virtually all oncological immunotherapies, so it's remarkable that we use the system but really have had no idea how it actually works -- and that's where basic science steps in," says Walz, a world expert in cryo-EM imaging. "This is some of the most important work to ever come out of my lab."

How T Cells Detect Threats

Walz's lab focuses on producing detailed images of macromolecular complexes, especially proteins found in cell membranes that help cells communicate with their surroundings. The TCR is one such complex. Made up of multiple proteins, it enables T cells to recognize antigens displayed by human leukocyte antigen (HLA) complexes on other cells. This recognition process is what T cell therapies rely on to mobilize the immune system against cancer.

Although scientists have known the individual parts of the TCR for many years, the earliest steps that trigger its activation have remained elusive. Notti, who works as both a physician and a researcher, found this gap especially troubling because many of his sarcoma patients were not benefiting from T cell immunotherapies.

"Determining that would help us understand how the information gets from outside the cell, where those antigens are being presented by HLAs, to the inside of the cell, where signaling turns on the T cell," he says.

Notti earned his Ph.D. in structural microbiology at Rockefeller before moving into oncology, and he suggested to Walz that they investigate this unanswered question together.

Rebuilding the TCR's Natural Environment

Walz's team is known for creating custom membrane environments that closely mimic the natural surroundings of membrane proteins. "We can change the biochemical composition, the thickness of the membrane, the tension and curvature, the size -- all kinds of parameters that we know have an influence on the embedded protein," Walz says.

For this study, the researchers set out to observe the TCR in conditions that closely resemble those inside a living cell. They placed the receptor into a nanodisc, a tiny disc-shaped section of membrane held in solution by a scaffold protein wrapped around its edge. Assembling the full receptor was difficult, and "getting all eight of these proteins properly assembled into the nanodisc was challenging," Notti says.

Previous structural studies of the TCR had relied on detergent, which often strips away the surrounding membrane. Walz notes that this was the first time the receptor complex had been restored to a membrane environment for detailed imaging.

Seeing the Receptor Switch On

Once the TCR was embedded in the nanodisc, the researchers used cryo-EM to visualize it. The images showed that the receptor remains closed and compact when inactive. When it encounters an antigen-presenting molecule, however, the structure opens and extends outward, resembling a wide-reaching motion.

The result surprised the team. "The data that were available when we began this research depicted this complex as being open and extended in its dormant state," Notti explains. "As far as anyone knew, the T cell receptor didn't undergo any conformational changes when binding to these antigens. But we found that it does, springing open like a sort of jack-in-the-box."

The researchers believe two factors made this discovery possible. First, they carefully recreated the TCR's in vivo membrane environment using the right lipid mixture. Second, they reinserted the receptor into a membrane using nanodiscs before conducting cryo-EM imaging. They found that an intact membrane keeps the receptor in a closed position until activation occurs. In earlier studies, detergent may have removed this restraint, allowing the receptor to open prematurely.

"It was important that we used a lipid mixture that resembled that of the native T cell membrane," says Walz. "If we had just used a model lipid, we wouldn't have seen this closed dormant state either."

Implications for Cancer Therapies and Vaccines

The team believes their findings could help improve treatments that rely on T cell receptors. "Re-engineering the next generation of immunotherapies tops the charts in terms of unmet clinical needs," Notti says. "For example, adoptive T cell therapies are being used successfully to treat certain very rare sarcomas, so one could imagine using our insights to re-engineer the sensitivity of those receptors by tuning their activation threshold."

Walz also sees potential applications beyond cancer therapy. "This information may be used for vaccine design as well," he adds. "People in the field can now use our structures to see refined details about the interactions between different antigens presented by HLA and T cell receptors. Those different modes of interaction might have some implication for how the receptor functions -- and ways to optimize it."

Journal Reference:

1. Ryan Q. Notti, Fei Yi, Søren Heissel, Martin W. Bush, Zaki Molvi, Pujita Das, Henrik Molina, Christopher A. Klebanoff, Thomas Walz. The resting and ligand-bound states of the membrane-embedded human T-cell receptor–CD3 complex. Nature Communications, 2025; 16 (1) DOI: 10.1038/s41467-025-66939-7 

Courtesy: Rockefeller University. "A hidden T cell switch could make cancer immunotherapy work for more people." ScienceDaily. ScienceDaily, 18 December 2025. <www.sciencedaily.com/releases/2025/12/251218074429.htm>. 

Scientists find brain cell switch that could reverse obesity’s effects

Fatty diets and obesity affect the structure and function of astrocytes¹, the star-shaped brain cells located in the striatum, a brain region involved in the perception of pleasure generated by food consumption. What is even more surprising is that by manipulating these astrocytes in vivo in mice can influence metabolism and correct certain cognitive changes associated with obesity (ability to relearn a task, for example). These results, described by scientists from the CNRS² and the Université Paris Cité, were recently published in the journal Nature Communication.

These discoveries reinforce the idea that astrocytes (long neglected in favour of neurons) play a key role in brain function. They also demonstrate, for the first time, the ability of astrocytes to restore cognitive function in the context of obesity, opening up new avenues of research to identify their exact role in energy metabolism.

These conclusions were reached using a combination of ex vivo and in vivo approaches in rodents, including chemogenetic techniques³, brain imaging, locomotion tests, cognitive behaviour and measuring the body's energy metabolism.

Notes

1. Unlike neurons, astrocytes (nervous system cells) do not generate electrical activity, which has made them less easy to study in the past. However, thanks to improvements in observation techniques, we now know that their close cooperation with neurons is essential to the proper functioning of the nervous system.
2. Reporting to l'Unité de biologie fonctionnelle et adaptative (CNRS/Université Paris Cité). Scientists from l'Institut de biologie Paris-Seine (CNRS/Inserm/Sorbonne Université) were also involved.
3. Calcium is an essential chemical element for astrocyte function, enabling synaptic activity to be modulated. The chemogenetic technique employed was based on the use of a virus, to express, in a targeted manner in the astrocytes, a protein that could modulate calcium flow in the cell, rather like a switch. The scientists were thus able to study the effect of these calcium flows on the activity of the astrocytes and surrounding neurons.

Journal Reference:

1. Enrica Montalban, Anthony Ansoult, Daniela Herrera Moro Chao, Cuong Pham, Clara Franco, Andrea Contini, Julien Castel, Rim Hassouna, Marene H. Hardonk, Anna Petitbon, Ewout Foppen, Giuseppe Gangarossa, Pierre Trifilieff, Dongdong Li, Serge Luquet, Claire Martin. Striatal astrocytes modulate behavioral flexibility and whole-body metabolism in mice. Nature Communications, 2025; 16 (1) DOI: 10.1038/s41467-025-60968-y 

Courtesy:

CNRS. "Scientists find brain cell switch that could reverse obesity’s effects." ScienceDaily. ScienceDaily, 8 August 2025. <www.sciencedaily.com/releases/2025/08/250807233048.htm>. 

 

 

Scientists just found a tiny molecule that could change how we lose weight

The obesity rate has more than doubled in the last 30 years, affecting more than one billion people worldwide. This prevalent condition is also linked to other metabolic disorders, including type 2 diabetes, cardiovascular diseases, chronic kidney disease, and cancers. Current treatment options include lifestyle interventions, bariatric surgery, and GLP-1 drugs like Ozempic or Wegovy, but many patients struggle to access or complete these treatments or to maintain their weight loss afterwards.

Salk Institute scientists are looking for a new treatment strategy in microproteins, an understudied class of molecules found throughout the body that play roles in both health and disease. In a new study, the researchers screened thousands of fat cell genes using CRISPR gene editing to find dozens of genes that likely code for microproteins -- one of which they confirmed -- that regulate either fat cell proliferation or lipid accumulation.

The findings, published in Proceedings of the National Academy of Sciences on August 7, 2025, identify new microproteins that could potentially ser

ve as drug targets to treat obesity and other metabolic disorders. The study also showcases the value of CRISPR screening in future microprotein discovery.

"CRISPR screening is extremely effective at finding important factors in obesity and metabolism that could become therapeutic targets," says senior author Alan Saghatelian, a professor and holder of the Dr. Frederik Paulsen Chair at Salk. "These new screening technologies are allowing us to reveal a whole new level of biological regulation driven by microproteins. The more we screen, the more disease-associated microproteins we find, and the more potential targets we have for future drug development."

Current obesity and metabolic disorder therapeutics

When our energy consumption exceeds our energy expenditure, fat cells can grow in both size and number. Fat cells store the excess energy in the form of fatty molecules called lipids. But while some excess storage is manageable, too much can cause fat deposits to accumulate around the body -- leading to whole-body inflammation and organ dysfunction.

Many factors regulate this complex energy storage system. The problem is, how do we find them all, and how do we filter for factors that may make good therapeutic candidates?

This has been a longstanding question for Salk scientists. In fact, Salk Professor Ronald Evans has been working on it for decades. Evans is an expert on PPAR gamma, a key regulator of fat cell development and a potent target for treating diabetes. Several drugs have been developed to target PPAR gamma to treat obesity, but they resulted in side effects like weight gain and bone loss. An ideal PPAR gamma-based obesity therapeutic has yet to hit the market.

When PPAR gamma drugs fell short, GLP-1 drugs entered the scene. GLP-1 is a peptide small enough to be considered a microprotein, and it serves as a blood sugar and appetite regulator. But, like PPAR gamma, GLP-1 drugs have their own shortcomings, such as muscle loss and nausea. Nonetheless, the popularity of GLP-1 drugs demonstrates a promising future for microprotein drugs in the obesity therapeutic space.

 

Saghatelian's team is now searching for the next microprotein therapeutic with new genetic tools that bring microproteins out of the "dark." For many years, long stretches of the genome have been considered "junk" and thus left unexplored. But recent technological advances have allowed scientists to look at these dark sections and find a hidden world of microproteins -- in turn, expanding protein libraries by 10 to 30 percent.

In particular, the Salk team is using innovative CRISPR screening to scour the "dark" for possible microproteins. This approach is enabling the simultaneous discovery of thousands of potential microproteins involved in lipid storage and fat cell biology, accelerating the search for the next PPAR gamma or GLP-1 drug.

How CRISPR screening accelerates the search for microproteins

CRISPR screens work by cutting out genes of interest in cells and observing whether the cell thrives or dies without them. From these results, scientists can determine the importance and function of specific genes. In this case, the Salk team was interested in genes that may code for microproteins involved in fat cell differentiation or proliferation.

"We wanted to know if there was anything we had been missing in all these years of research into the body's metabolic processes," says first author Victor Pai, a postdoctoral researcher in Saghatelian's lab. "And CRISPR allows us to pick out interesting and functional genes that specifically impact lipid accumulation and fat cell development."

This latest research follows up on a prior study from Saghatelian's lab. The previous study identified thousands of potential microproteins by analyzing microprotein-coding RNA strands derived from mouse fat tissues. These microprotein-coding RNA strands were filed away to await investigation into their functions.

The new study first expanded this collection to include additional microproteins identified from a pre-fat cell model. Notably, this new model captures the differentiation process from pre-fat cell to a fully mature fat cell. Next, the researchers screened the cell model with CRISPR to determine how many of these potential microproteins were involved in fat cell differentiation or proliferation.

"We're not the first to screen for microproteins with CRISPR," adds Pai, "but we're the first to look for microproteins involved in fat cell proliferation. This is a huge step for metabolism and obesity research."

Microproteins of interest and next steps

Using their mouse model and CRISPR screening approach, the team identified microproteins that may be involved in fat cell biology. They then narrowed the pool even further with another experiment to create a shortlist of 38 potential microproteins involved in lipid droplet formation -- which indicates increasing fat storage -- during fat cell differentiation.

At this point, the shortlisted microproteins were all still "potential" microproteins. This is because the genetic screening finds genes that may code for microproteins, rather than finding the microproteins themselves. While this approach is a helpful workaround to finding microproteins that are otherwise so small they elude capture, it also means that the screened microproteins require further testing to confirm whether they are functional.

And that's what the Salk team did next. They picked several of the shortlisted microproteins to test and were able to verify one. Pai hypothesizes this new microprotein, called Adipocyte-smORF-1183, influences lipid droplet formation in fat cells (also known as adipocytes).

Verification of Adipocyte-smORF-1183 is an exciting step toward identifying more microproteins involved in lipid accumulation and fat cell regulation in obesity. It also verifies that CRISPR is an effective tool for finding microproteins involved in fat cell biology, obesity, and metabolism.

"That's the goal of research, right?" says Saghatelian. "You keep going. It's a constant process of improvement as we establish better technology and better workflows to enhance discovery and, eventually, therapeutic outcomes down the line."

Next, the researchers will repeat the study with human fat cells. They also hope their success inspires others to use CRISPR screenings to continue bringing microproteins out from the dark -- like Adipocyte-smORF-1183, which until now, was considered an unimportant bit of "junk" DNA.

Further validation or screening of new cell libraries will expand the list of potential drug candidates, setting the stage for the new-and-improved obesity and metabolic disorder therapeutics of the future.

Other authors include Hazel Shan, Cynthia Donaldson, Joan Vaughan, Eduardo V. De Souza, Carolyn O'Connor, and Michelle Liem of Salk; and Antonio Pinto and Jolene Diedrich of Scripps Research Institute.

The work was supported by the National Institutes of Health (F32 DK132927, RC2 DK129961, R01 DK106210, R01 GM102491, RF1 AG086547, NCI Cancer Center P30 014195, S10- OD023689, and S10-OD034268), Ferring Foundation, Clayton Foundation, and Larry and Carol Greenfield Technology Fund.

Journal Reference:

1. Victor J. Pai, Huanqi Shan, Cynthia J. Donaldson, Joan M. Vaughan, Eduardo V. De Souza, Carolyn O’Connor, Michelle Liem, Antonio F. M. Pinto, Jolene Diedrich, Alan Saghatelian. CRISPR–Cas9 screening reveals microproteins regulating adipocyte proliferation and lipid metabolism. Proceedings of the National Academy of Sciences, 2025; 122 (32) DOI: 10.1073/pnas.2506534122 

Courtesy:

Salk Institute. "Scientists just found a tiny molecule that could change how we lose weight." ScienceDaily. ScienceDaily, 10 August 2025. <www.sciencedaily.com/releases/2025/08/250809100924.htm>. 

 

 

 

The parasite that turns off your body’s pain alarm and sneaks in

New research, published in The Journal of Immunology, discovered that a parasitic worm suppresses neurons in the skin to evade detection. The researchers suggest that the worm likely evolved this mechanism to enhance its own survival, and that the discovery of the molecules responsible for the suppression could aid in the development of new painkillers.

Schistosomiasis is a parasitic infection caused by helminths, a type of worm. Infection occurs during contact with infested water through activities like swimming, washing clothes, and fishing, when larvae penetrate the skin. Surprisingly, the worm often evades detection by the immune system, unlike other bacteria or parasites that typically cause pain, itching, or rashes.

In this new study, researchers from Tulane School of Medicine aimed to find out why the parasitic worm Schistosoma mansoni doesn't cause pain or itching when it penetrates the skin. Their findings show that S. mansoni causes a reduction in the activity of TRPV1+, a protein that sends signals the brain interprets as heat, pain, or itching. As part of pain-sensing in sensory neurons, TRPV1+ regulates immune responses in many scenarios such as infection, allergy, cancer, autoimmunity, and even hair growth.

The researchers found that S. mansoni produces molecules that suppress TRPV1+ to block signals from being sent to the brain, allowing S. mansoni to infect the skin largely undetected. It is likely S. mansoni evolved the molecules that block TRPV1+ to enhance its survival.

"If we identify and isolate the molecules used by helminths to block TRPV1+ activation, it may present a novel alternative to current opioid-based treatments for reducing pain," said Dr. De'Broski R. Herbert, Professor of Immunology at Tulane School of Medicine, who led the study. "The molecules that block TRPV1+ could also be developed into therapeutics that reduce disease severity for individuals suffering from painful inflammatory conditions."

The study also found that TRPV1+ is necessary for initiating host protection against S. mansoni. TRPV1+ activation leads to the rapid mobilization of immune cells, including gd T cells, monocytes, and neutrophils, that induce inflammation. This inflammation plays a crucial role in host resistance to the larval entry into the skin. These findings highlight the importance of neurons that sense pain and itching in successful immune responses

"Identifying the molecules in S. mansoni that block TRPV1+ could inform preventive treatments for schistosomiasis. We envision a topical agent which activates TRPV1+ to prevent infection from contaminated water for individuals at risk of acquiring S. mansoni," said Dr. Herbert.

In this study, mice were infected with S. mansoi and evaluated for their sensitivity to pain as well as the role of TRPV1+ in preventing infection. Researchers next plan to identify the nature of the secreted or surface-associated helminth molecules that are responsible for blocking TRPV1+ activity and specific gd T cell subsets that are responsible for immune responses. The researchers also seek to further understand the neurons that helminths have evolved to suppress.

Journal Reference:

1. Juan M Inclan-Rico, Adriana Stephenson, Camila M Napuri, Heather L Rossi, Li-Yin Hung, Christopher F Pastore, Wenqin Luo, De’Broski R Herbert. TRPV1 neurons promote cutaneous immunity against Schistosoma mansoni. The Journal of Immunology, 7 August 2025 DOI: 10.1093/jimmun/vkaf141 

Courtesy:

American Association of Immunologists Inc. "The parasite that turns off your body’s pain alarm and sneaks in." ScienceDaily. ScienceDaily, 12 August 2025. <www.sciencedaily.com/releases/2025/08/250811104224.htm>. 

 

 

Researchers grow 400+ brain cell types—a leap for Alzheimer’s and Parkinson’s research

Nerve cells are not just nerve cells. Depending on how finely we distinguish, there are several hundred to several thousand different types of nerve cell in the human brain according to the latest calculations. These cell types vary in their function, in the number and length of their cellular appendages, and in their interconnections. They emit different neurotransmitters into our synapses and, depending on the region of the brain - for example, the cerebral cortex or the midbrain - different cell types are active.

When scientists produced nerve cells from stem cells in Petri dishes for their experiments in the past, it was not possible to take their vast diversity into account. Until now, researchers had only developed procedures for growing a few dozen different types of nerve cell in vitro. They achieved this using genetic engineering or by adding signalling molecules to activate particular cellular signalling pathways. However, they never got close to achieving the diversity of hundreds or thousands of different nerve cell types that actually exists.

"Neurons derived from stem cells are frequently used to study diseases. But up to now, researchers have often ignored which precise types of neuron they are working with," says Barbara Treutlein, Professor at the Department of Biosystems Science and Engineering at ETH Zurich in Basel. However, this is not the best approach to such work. "If we want to develop cell culture models for diseases and disorders such as Alzheimer's, Parkinson's and depression, we need to take the specific type of nerve cell involved into consideration."

Systematic screening was the key to success

Treutlein and her team have now successfully produced over 400 different types of nerve cell. In doing so, the scientists have paved the way for more precise basic neurological research with cell culture experiments.

The ETH researchers achieved this by working with a culture of human induced pluripotent stem cells that had been generated from blood cells. In these cells, they used genetic engineering to activate certain neuronal regulator genes and treated the cells with various morphogens, a special class of signalling molecules. Treutlein and her team took a systematic approach, using seven morphogens in different combinations and concentrations in their screening experiments. This resulted in almost 200 different sets of experimental conditions.

Morphogens

Morphogens are messengers that are known from research into embryonic development. They are not distributed uniformly within an embryo but occur in a variety of concentrations forming spatial patterns. In this way, they define the position of cells within the embryo, for example whether a cell is near the body axis or in the back, abdomen, head or torso. Accordingly, morphogens help to determine what grows where in the embryo.

The researchers used various analyses to prove that they had produced over 400 different types of nerve cell in their experiment. They examined the RNA (and therefore genetic activity) at the level of individual cells, as well as the external appearance of cells and their function: for example, which type of cell appendage they had in which quantities and which electric nerve impulses they emitted.

The researchers then compared their data with information from databases of neurons from the human brain. By doing this, they were able to identify the types of nerve cell that had been created, such as those found in the peripheral nervous system or brain cells and the part of the brain they come from, whether they perceive pain, cold or movement, and so on.

In-vitro neurons for active ingredient research

Treutlein clarifies that they are still a long way off producing all types of nerve cell that exist in vitro. Nonetheless, the researchers now have access to a much larger number of different cell types than they had before.

They would like to use in-vitro nerve cells to develop cell culture models for studying serious neurological conditions, including schizophrenia, Alzheimer's, Parkinson's, epilepsy, sleep disorders and multiple sclerosis. Cell culture models of this kind are also of great interest in pharmaceutical research for testing the effects of new active compounds in cell cultures without animal testing, with the ultimate aim of one day being able to cure these conditions.

In the future, the cells could also be used for cell replacement therapy, which involves replacing sick or dead nerve cells in the brain with new human cells.

But there is a challenge to overcome before this can happen: the researchers often produced a mixture of multiple different types of nerve cell in their experiments. They are now working to optimise their method so that each experimental condition only produces one specific cell type. They already have some initial ideas as to how this might be achieved.

Journal Reference:

1. Hsiu-Chuan Lin, Jasper Janssens, Benedikt Eisinger, Philipp Hornauer, Ann-Sophie Kroell, Malgorzata Santel, Maria Pascual-Garcia, Ryoko Okamoto, Kyriaki Karava, Zhisong He, Marthe Priouret, Manuel Schr&ouml;ter, J. Gray Camp, Barbara Treutlein. Human neuron subtype programming via single-cell transcriptome-coupled patterning screens. Science, 2025; 389 (6756) DOI: 10.1126/science.adn6121 

Courtesy:
ETH Zurich. "Researchers grow 400+ brain cell types—a leap for Alzheimer’s and Parkinson’s research." ScienceDaily. ScienceDaily, 12 July 2025. <www.sciencedaily.com/releases/2025/07/250711224316.htm>. 

 

Hormone therapy supercharges tirzepatide, unleashing major weight loss after menopause

Using tirzepatide and menopause hormone therapy at the same time leads to increased weight loss in postmenopausal women with overweight or obesity compared to use of tirzepatide treatment alone, according to a study presented at ENDO 2025, the Endocrine Society's annual meeting in San Francisco, Calif.

"These data are the first to show the combined use of tirzepatide and menopause hormone therapy significantly increases treatment effectiveness in postmenopausal women," said Regina Castaneda, M.D., research fellow for the Division of Endocrinology at the Mayo Clinic in Jacksonville, Fla. "Previous studies of the medication semaglutide found similar results. Achieving these outcomes with a second obesity medication may indicate a broader efficacy trend for pairing these two classes of medications."

Menopause-related hormonal changes often result in increased abdominal fat, decreased muscle mass and altered energy expenditure that leads to weight gain and puts millions of women at risk for developing heart disease and other serious health issues.

To confirm the hypothesis that concurrent menopause hormone therapy enhances the effectiveness of tirzepatide for weight loss in postmenopausal women, researchers conducted a real-world study using the electronic medical records of 120 postmenopausal women over a median duration of 18 months. The study included two cohorts: 40 women using menopause hormone therapy concurrently with tirzepatide and 80 women using tirzepatide alone.

The results showed superior total body weight loss percentage for women using tirzepatide plus menopause hormone therapy (17%) compared to those using tirzepatide alone (14%). In addition, a higher percentage of menopause hormone therapy users (45%) also achieved at least 20% total body weight loss, compared to 18% of menopause hormone therapy non-users.

"The information garnered through this new study provides important insights to develop more effective and personalized weight management interventions to reduce a postmenopausal woman's risk of overweight and obesity-related health complications," said Maria Daniela Hurtado Andrade, M.D., Ph.D., assistant professor of medicine and consultant for the Division of Endocrinology at the Mayo Clinic. "This study underscores the urgent need for further research to better understand how obesity medications and menopause hormone therapy work together. Gaining this knowledge could greatly improve the health and well-being of millions of postmenopausal women. It also points to the need for better strategies to make these treatments more accessible and available to those who need them."

This research was funded by the National Institutes of Health Bridging Interdisciplinary Careers in Women's Health Research Grant and the Mayo Clinic Center for Women's Health Research.

Citation:

The Endocrine Society. "Hormone therapy supercharges tirzepatide, unleashing major weight loss after menopause." ScienceDaily. ScienceDaily, 13 July 2025. <www.sciencedaily.com/releases/2025/07/250713031441.htm>. 

 

Not just diabetes: How slightly high blood sugar wrecks men’s sexual health

Metabolic health factors, including small increases in blood sugar, are the main drivers of change in the reproductive systems and sexual functioning of aging men, according to a study presented at ENDO 2025, the Endocrine Society's annual meeting in San Francisco, Calif.

"Although age and testosterone levels have long been considered an impetus for men's declining sexual health, our research indicates that these changes more closely correlate with modest increases in blood sugar and other metabolic changes," said Michael Zitzmann, M.D., Ph.D., professor and doctor of medicine at University Hospital in Muenster, Germany. "This means that men can take steps to preserve or revive their reproductive health with lifestyle choices and appropriate medical interventions."

These conclusions follow a long-term study of healthy men (without diabetes mellitus, heart disease and/or cancer) aged 18-85 that began in 2014 with 200 participants and concluded in 2020 with 117 participants. Researchers studied progressive changes in participants' semen and hormonal profiles, erectile functioning and metabolic health (BMI and blood sugar levels marked by the HbA1c test).

Findings indicated that over time hormone levels and semen parameters stayed largely within normal ranges. However, sperm movement and erectile function declined in men with minimally elevated blood sugar levels that were below the 6.5% HbA1c diabetes threshold. The study also found that while testosterone levels did not have a direct impact on erectile function, they did correlate with participants' libido assessment.

"We're hopeful that the information gleaned from this study will help doctors and their patients formulate effective male sexual health maintenance plans," Zitzmann added. "We now know that it's in our power to retain sexual and reproductive well-being in men, even as they age."

This research was conducted as part of the FAME 2.0 study.

Citation:

The Endocrine Society. "Not just diabetes: How slightly high blood sugar wrecks men’s sexual health." ScienceDaily. ScienceDaily, 13 July 2025. <www.sciencedaily.com/releases/2025/07/250713031439.htm>. 

 

AI sees what doctors miss: Fatty liver disease hidden in chest x-rays

 

Fatty liver disease, caused by the accumulation of fat in the liver, is estimated to affect one in four people worldwide. If left untreated, it can lead to serious complications, such as cirrhosis and liver cancer, making it crucial to detect early and initiate treatment.

Currently, standard tests for diagnosing fatty liver disease include ultrasounds, CTs, and MRIs, which require costly specialized equipment and facilities. In contrast, chest X-rays are performed more frequently, are relatively inexpensive, and involve low radiation exposure. Although this test is primarily used to examine the condition of the lungs and heart, it also captures part of the liver, making it possible to detect signs of fatty liver disease. However, the relationship between chest X-rays and fatty liver disease has rarely been a subject of in-depth study.

Therefore, a research group led by Associate Professor Sawako Uchida-Kobayashi and Associate Professor Daiju Ueda at Osaka Metropolitan University's Graduate School of Medicine developed an AI model that can detect the presence of fatty liver disease from chest X-ray images.

In this retrospective study, a total of 6,599 chest X-ray images containing data from 4,414 patients were used to develop an AI model utilizing controlled attenuation parameter (CAP) scores. The AI model was verified to be highly accurate, with the area under the receiver operating characteristic curve (AUC) ranging from 0.82 to 0.83.

"The development of diagnostic methods using easily obtainable and inexpensive chest X-rays has the potential to improve fatty liver detection. We hope it can be put into practical use in the future," stated Professor Uchida-Kobayashi.

 

Journal Reference:

1. Daiju Ueda, Sawako Uchida-Kobayashi, Akira Yamamoto, Shannon L. Walston, Hiroyuki Motoyama, Hideki Fujii, Toshio Watanabe, Yukio Miki, Norifumi Kawada. Performance of a Chest Radiograph&amp;#8211;based Deep Learning Model for Detecting Hepatic Steatosis. Radiology: Cardiothoracic Imaging, 2025; 7 (3) DOI: 10.1148/ryct.240402 

Courtesy:

Osaka Metropolitan University. "AI sees what doctors miss: Fatty liver disease hidden in chest x-rays." ScienceDaily. ScienceDaily, 27 June 2025. <www.sciencedaily.com/releases/2025/06/250627021845.htm>.

 

 

 

Scientists warn of bat virus just one mutation from infecting humans

 

A group of MERS-related bat viruses could mutate to infect humans. One type, HKU5, is especially concerning due to its ability to bind to ACE2 receptors in animals—and potentially humans next. Credit: Shutterstock

A group of bat viruses closely related to the deadly Middle East respiratory syndrome coronavirus (MERS-CoV) could be one small mutation away from being capable of spilling over into human populations and potentially causing the next pandemic.

A recent study published in the journal Nature Communicationsexamined an understudied group of coronaviruses known as merbecoviruses -- the same viral subgenus that includes MERS-CoV -- to better understand how they infect host cells. The research team, which included scientists at Washington State University, the California Institute of Technology and the University of North Carolina, found that while most merbecoviruses appear unlikely to pose a direct threat to people, one subgroup known as HKU5 possesses concerning traits.

"Merbecoviruses - and HKU5 viruses in particular - really hadn't been looked at much, but our study shows how these viruses infect cells," said Michael Letko, a virologist at WSU's College of Veterinary Medicine who helped to spearhead the study. "What we also found is HKU5 viruses may be only a small step away from being able to spill over into humans."

During the past two decades, scientists have cataloged the genetic sequences of thousands of viruses in wild animals, but, in most cases, little is known about whether these viruses pose a threat to humans. Letko's lab in WSU's Paul G. Allen School for Global Health focuses on closing that gap and identifying potentially dangerous viruses.

For their most recent study, Letko's team targeted merbecoviruses, which have received limited attention apart from MERS-CoV, a zoonotic coronavirus first noted in 2012 that is transmitted from dromedary camels to humans. It causes severe respiratory disease and has a mortality rate of approximately 34%.

Like other coronaviruses, merbecovirusesrely on a spike protein to bind to receptors and invade host cells. Letko's team used virus-like particles containing only the portion of the spike responsible for binding to receptors and tested their ability to infect cells in the lab. While most merbecoviruses appear unlikely to be able to infect humans, HKU5 viruses - which have been found across Asia, Europe, Africa and the Middle East - were shown to use a host receptor known as ACE2, the same used by the more well-known SARS-CoV-2 virus that causes COVID-19. One small difference: HKU5 viruses, for now, can only use the ACE2 gene in bats, but do not use the human version nearly as well.

Examining HKU5 viruses found in Asia where their natural host is the Japanese house bat (Pipistrellus abramus), the researchers demonstrated some mutations in the spike protein that may allow the viruses to bind to ACE2 receptors in other species, including humans. Researchers on another study that came out earlier this year analyzed one HKU5 virus in China that has already been documented to have jumped into minks, showing there is potential for these viruses to cross species-barriers.

"These viruses are so closely related to MERS, so we have to be concerned if they ever infect humans," Letko said. "While there's no evidence they've crossed into people yet, the potential is there -- and that makes them worth watching."

The team also used artificial intelligence to explore the viruses. WSU postdoctoral researcher Victoria Jefferson used a program called AlphaFold 3 to model how the HKU5 spike protein binds to ACE2 at the molecular level, which could help provide a better understanding of how antibodies might block the infection or how the virus could mutate.

Up until this point, such structural analysis required months of lab work and specialized equipment. With AlphaFold, Jefferson generated accurate predictions in minutes. The results matched those recently documented by a research team that used traditional approaches.

Letko noted the study and its methods could be used for future research projects and aid in the development of new vaccines and treatments.

The research was funded through a research project grant from the National Institutes of Health. Jefferson's work was supported by an NIH T32 training grant.

Journal Reference:

1. Nicholas J. Catanzaro, Ziyan Wu, Chengcheng Fan, Victoria Jefferson, Anfal Abdelgadir, Alexandra Sch&auml;fer, Boyd L. Yount, Pamela J. Bjorkman, Ralph Baric, Michael Letko. ACE2 from Pipistrellus abramus bats is a receptor for HKU5 coronaviruses. Nature Communications, 2025; 16 (1) DOI: 10.1038/s41467-025-60286-3 

Courtesy: 

Washington State University. "Scientists warn of bat virus just one mutation from infecting humans." ScienceDaily. ScienceDaily, 12 June 2025. <www.sciencedaily.com/releases/2025/06/250612081312.htm>. 

 

 

The common blood test that predicts how fast Alzheimer’s hits

Insulin resistance detected by routine triglyceride-glucose (TyG) index can flag people with early Alzheimer's who are four times more likely to present rapid cognitive decline, according to new research presented at the European Academy of Neurology (EAN) Congress 2025.¹

Neurologists at the University of Brescia reviewed records for 315 non-diabetic patients with cognitive deficits, including 200 with biologically confirmed Alzheimer's disease. All subjects underwent an assessment of insulin resistance using the TyG index and a clinical follow-up of 3 years. When patients were divided according to TyG index, those in the highest third of the Mild Cognitive Impairment AD subgroup deteriorated far more quickly than their lower-TyG peers, losing >2.5 points on the Mini Mental State Examination per year (hazard ratio 4.08, 95% CI 1.06-15.73). No such link appeared in the non-AD cohort.

"Once mild cognitive impairment is diagnosed, families always ask how fast it will progress," said lead investigator Dr. Bianca Gumina. "Our data show that a simple metabolic marker available in every hospital laboratory can help identify more vulnerable subjects who may be suitable candidates for targeted therapy or specific intervention strategies."

While insulin resistance has been linked to the onset of Alzheimer's disease, its role in how quickly the condition progresses has received less attention. This study aimed to fill that gap by focusing on its impact during the prodromal mild cognitive impairment (MCI) stage, when patients follow highly variable trajectories. The researchers used the TyG index, which offers a low-cost, routinely available surrogate for insulin resistance, to explore whether metabolic dysfunction could help predict the pace of cognitive decline after diagnosis.

In AD specifically, insulin resistance is believed to impair neuronal glucose uptake, promote amyloid accumulation, disrupt the blood-brain barrier, and fuel inflammation - pathways that are less relevant or differently regulated in other neurodegenerative diseases.

"We were surprised to see the effect only in the Alzheimer's spectrum and not in other neurodegenerative diseases," Dr. Gumina noted. "It suggests a disease-specific vulnerability to metabolic stress during the prodromal window, when interventions may still change the trajectory."

The researchers at University of Brescia, led by Professor Padovani and Professor Pilotto, found that high TyG was also associated with blood-brain barrier disruption and cardiovascular risk factors, yet it showed no interaction with the APOE ε4 genotype, indicating that metabolic and genetic risks may act through distinct pathways.²

Identifying high-TyG patients could refine enrolment for anti-amyloid or anti-tau trials and prompt earlier lifestyle or pharmacological measures to improve insulin sensitivity. The researchers are currently investigating whether TyG levels also track with neuroimaging biomarkers to aid earlier detection and stratification.

"If targeting metabolism can delay progression, we will have a readily modifiable target that works alongside emerging disease-modifying drugs," concluded Dr. Gumina.

References:

1. Gumina B., Galli A., Tolassi C. et al. The Triglyceride-Glucose Index as Predictor of Cognitive Decline in Alzheimer's Spectrum Disorders. Presented at the European Academy of Neurology (EAN) Congress 2025; 23 June 2025; Helsinki, Finland.
2. Padovani A., Galli A., Bazzoli E., et al. (2025). The role of insulin resistance and APOE genotype on blood-brain barrier integrity in Alzheimer's disease. Alzheimer's & Dementia. Advance online publication. https://doi.org/10.1002/alz.14556

Courtesy:

Beyond. "The common blood test that predicts how fast Alzheimer’s hits." ScienceDaily. ScienceDaily, 22 June 2025. <www.sciencedaily.com/releases/2025/06/250622224303.htm>. 

 

 

Artificial intelligence isn’t hurting workers—It might be helping

As artificial intelligence reshapes workplaces worldwide, a new study provides early evidence suggesting AI exposure has not, thus far, caused widespread harm to workers' mental health or job satisfaction. In fact, the data reveals that AI may even be linked to modest improvements in worker physical health, particularly among employees with less than a college degree.

But the authors caution: It is way too soon to draw definitive conclusions.

The paper, "Artificial Intelligence and the Wellbeing of Workers," published June 23 in Nature: Scientific Reports, uses two decades of longitudinal data from the German Socio-Economic Panel. Using that rich data, the researchers -- Osea Giuntella of the University of Pittsburgh and the National Bureau of Economic Research (NBER), Luca Stella of the University of Milan and the Berlin School of Economics, and Johannes King of the German Ministry of Finance -- explored how workers in AI-exposed occupations have fared in contrast to workers in less-exposed roles.

"Public anxiety about AI is real, but the worst-case scenarios are not inevitable," said Professor Stella, who is also affiliated with independent European bodies the Center for Economic Studies (CESifo) and the Institute for Labor Economics (IZA). "So far, we find little evidence that AI adoption has undermined workers' well-being on average. If anything, physical health seems to have slightly improved, likely due to declining job physical intensity and overall job risk in some of the AI-exposed occupations."

Yet the study also highlights reasons for caution.

The analysis relies primarily on a task-based measure of AI exposure -- considered more objective -- but alternative estimates based on self-reported exposure reveal small negative effects on job and life satisfaction. In addition, the sample excludes younger workers and only covers the early phases of AI diffusion in Germany.

"We may simply be too early in the AI adoption curve to observe its full effects," Stella emphasized. "AI's impact could evolve dramatically as technologies advance, penetrate more sectors, and alter work at a deeper level."

Key findings from the study include:

• No significant average effects of AI exposure on job satisfaction, life satisfaction, or mental health.
• Small improvements in self-rated physical health and health satisfaction, especially among lower-educated workers.
• Evidence of reduced physical job intensity, suggesting that AI may alleviate physically demanding tasks.
• A modest decline in weekly working hours, without significant changes in income or employment rates.
• Self-reported AI exposure suggests small but negative effects on subjective well-being, reinforcing the need for more granular future research.

• Due to the data supply, the study focuses on Germany -- a country with strong labor protections and a gradual pace of AI adoption. The co-authors noted that outcomes may differ in more flexible labor markets or among younger cohorts entering increasingly AI-saturated workplaces.

  "This research is an early snapshot, not the final word," said Pitt's Giuntella, who previously conducted significant research into the effect of robotics on households and labor, and on types of workers. "As AI adoption accelerates, continued monitoring of its broader impacts on work and health is essential. Technology alone doesn't determine outcomes -- institutions and policies will decide whether AI enhances or erodes the conditions of work."

   

  Journal Reference:

• Osea Giuntella, Johannes Konig, Luca Stella. Artificial intelligence and the wellbeing of workers. Scientific Reports, 2025; 15 (1) DOI: 10.1038/s41598-025-98241-3 

Courtesy:

University of Pittsburgh. "Artificial intelligence isn’t hurting workers—It might be helping." ScienceDaily. ScienceDaily, 23 June 2025. <www.sciencedaily.com/eleases/2025/06/250623072753.htm>.