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Stem Cell-Derived Brain Models Offer a New Window Into How Anesthesia Works

Newswise — Every day, hundreds of thousands of people undergo general anesthesia, trusting they’ll drift into unconsciousness and wake safely after surgery. Yet despite decades of use, scientists still don’t fully understand how anesthetic drugs reshape the brain’s electrical activity to produce unconsciousness.

Studying the brain’s response to anesthesia has been difficult: in living humans, there’s no safe way to study the brain cell by cell, and in animals, the drugs act on many different brain regions at once, making it hard to isolate where the effects arise.

Now, UCLA researchers have shown for the first time that human stem cell-derived brain assembloids — tiny, three-dimensional models that recreate simplified human brain circuits — can reproduce the electrical changes seen during general anesthesia. Their findings were just published in the British Journal of Anaesthesia.

Physicists who uncovered the first particle accelerator were honored with a Nobel Prize 75 years ago — their work shaped physics, medicine and even art research

Particle accelerators aren’t just for testing the Standard Model. They’re also used to diagnose and treat disease and study world history.

Novel ‘speech clock’ can estimate a person’s chronological age

A large study shows that machine-learning clocks based on speech can estimate chronological age and may also offer a window into brain aging, biological aging, cognitive health, cumulative burden, and dementia.

The new study, just published in leading international journal Science Advances, outlines that researchers have developed a “speech clock” that can estimate a person’s chronological age from hundreds of acoustic and linguistic characteristics of their speech. The difference between a person’s actual age and their speech-predicted age (called the speech age gap) was also associated with multiple independent markers of biological aging, brain health, cognition, social adversity, and dementia.

The study analyzed 2,928 Spanish-speaking participants from Argentina, Chile, Colombia, Mexico, and Peru, including healthy adults and people with mild cognitive impairment, Alzheimer’s disease, and different forms of frontotemporal dementia. Rather than looking at a single property of the voice, the researchers used machine learning to analyse hundreds of features capturing how people speak and what they say: incorporating speech rate and pauses, pitch, emotional content, vocabulary, semantic precision, and the amount and organisation of verbal output. Machine-learning models combined these features to estimate chronological age and generate an individual speech age gap.

Small protein helps amplify cell signals from receptors targeted by many medicines

A small protein known as p11 may play a much broader role in cellular signaling than previously thought. Researchers at Karolinska institutet have now shown that p11 interacts with numerous receptors targeted by commonly used medicines, opening new possibilities for treating conditions such as pain, inflammation and depression. The research is published in the journal Science Advances.

“Cells communicate through complicated molecular networks, with most modern drugs acting by tuning these signals on or off. Our study identifies a key protein modulating signal transduction across G protein-coupled receptors, the largest receptor family in mammals. Decoding these signaling networks is essential to advance receptor biology and drive the development of next-generation therapies,” says Marcus Saarinen at the Department of Clinical Neuroscience and the lead author of the study.

AI method predicts retention times of small molecules more reliably

Whether in drug discovery, environmental analysis or metabolomics: anyone analyzing complex biological samples often needs to identify the small molecules they contain. Researchers at Friedrich Schiller University Jena, in collaboration with partners from the Helmholtz Zentrum München and the Technical University of Munich, have developed a method that addresses a problem in analytical chemistry that has persisted for decades.

The team, led by bioinformatician Prof. Dr. Sebastian Böcker, presents the new tool in Nature Methods.

‘Mini-brains’ model myelin damage and regeneration, offering new tool for MS drug testing

Researchers have developed 3D “mini-brains” they hope will help speed up the search for much-needed drug treatments for multiple sclerosis (MS), an autoimmune condition affecting almost 3 million people worldwide. Their research has been published in the journal Nature Neuroscience.

Led by The Florey Institute of Neuroscience and Mental Health and Monash University, scientists from Australia and New Zealand have used reprogrammed adult stem cells to engineer the human-like central nervous system cell model, which is the size of a grain of rice.

Among only a handful of MS organoids created globally, the “mini-brains” give researchers a highly detailed cellular view of myelin destruction (demyelination) and regeneration (remyelination) in human cells.

Scientists Develop Local Anesthetic That Lasts Weeks Instead of Hours

The findings could help researchers make local anesthetics last longer in people.

Patients recovering from surgery may need pain relief beyond the eight to 12 hours, or about a day at most, that most local anesthetics provide.

Seeking a longer-lasting option, researchers at Boston Children’s Hospital have redesigned liposomes, microscopic carriers made from fatty molecules, to release a numbing drug more gradually. In rats, the formulation sustained local anesthesia for two to three weeks, compared with about four to eight hours for a commercial formulation.

The Hidden Mathematics of Alzheimer’s Plaques Could Reveal New Treatment Strategies

Mathematics may offer a new way to investigate the complex chemistry behind Alzheimer’s-related plaque formation.

Plaques associated with Alzheimer’s disease begin with molecular interactions that are difficult to observe directly as they unfold. Shantia Yarahmadian, an associate professor at Mississippi State University, is using mathematics to simulate part of that process, focusing on how metals such as copper and zinc may influence the behavior of amyloid-beta proteins.

His latest model follows a chain of reactions that can lead amyloid-beta to aggregate, or clump together, and form plaque. It also allows researchers to test how two potential therapeutic approaches might interfere with those reactions. The work was published in Bulletin of Mathematical Biology and extends Yarahmadian’s earlier efforts to model Alzheimer’s disease mathematically.

Heart muscle stem cells see first clinical use in surgery in Japan

Tokyo – A hospital in Japan has carried out the world’s first surgery using sheets of commercially available heart muscle stem cells after the groundbreaking therapy was approved this year, one of the surgeons said.

Sheets of muscle cells derived from regenerative products known as induced pluripotent stem cells, or iPS cells, were transplanted into the heart of a woman in her 50s during the hourlong surgery performed on Tuesday.

It marked the first clinical use of the regenerative therapy since it received conditional government approval in March.

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