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Who’s Really Winning At Longevity? (Featuring @Unaging.Crissman.Loomis)

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Scientists shed new light on the shared genetic basis of psychiatric disorders

New research uncovers how shared genes contribute to various psychiatric disorders. This breakthrough highlights the importance of pleiotropic genes—those affecting multiple conditions—and offers new avenues for mental health treatment development.

Children with better musical skills may benefit from a prolonged window of brain plasticity

Children who excel at keeping the beat may possess brains that mature more slowly, extending their capacity for learning. A new longitudinal twin study indicates that this prolonged development is shaped by both genetic predispositions and musical engagement.

Researchers uncover the earliest stages of human placenta formation

A gene that turns on very early in embryonic development could be key to the formation of the placenta, which provides the developing fetus with what it needs to thrive during gestation.

The placenta provides all of the nutrition, oxygen and antibodies that a developing human fetus needs to thrive throughout gestation. The temporary organ begins to form within six to 12 days after conception, just as the embryo implants itself in the lining of the uterus. Failure of the placenta to form correctly is the second leading cause of miscarriage during early pregnancy, after genetic abnormalities of the fetus that are incompatible with life.

However, the initial stages of placental formation have remained a mystery due to ethical considerations and technical constraints on studying the process in humans.

Machine learning reveals how disordered protein regions contribute to cancer-causing condensates

Fusion oncoproteins arise when a gene fuses with another gene and acquires new abilities. Such abilities can include the formation of biomolecular condensates, “droplets” of concentrated proteins, DNA or RNA.

The abnormal molecular condensates formed by fusion oncoproteins can disrupt cellular functions and drive cancer development, but the specific protein features behind this process remain unclear.

Scientists at St. Jude Children’s Research Hospital studied intrinsically disordered regions, unstructured protein segments that are often involved in condensate formation, to determine if they drive fusion oncoproteins to form condensates. They trained a machine learning model, called IDR-Puncta ML, with experimental data from intrinsically disordered regions in fusion oncoproteins to predict the behavior of other such regions.

Miniature microscope captures real-time voltage signals in awake animals

Researchers have built a tiny, lightweight microscope that captures neuron activity with unprecedented speed that can be used in freely moving animals. The new tool could give scientists a more complete view of how brain cells process information during natural behavior.

The microscope is designed to image genetically encoded voltage indicators —fluorescent dyes that rapidly change brightness when a neuron fires—through a small window in the skull while the animal is awake.

“Unlike most miniature microscopes that track slower calcium signals, ours captures electrical spikes at hundreds of frames per second,” said Emily Gibson from the University of Colorado Anschutz Medical Campus. “This makes it possible to capture the moment a neuron fires as well as the quieter signals that build up inside neurons before firing.”

Loss of brain protein eases Alzheimer’s symptoms and brain damage in mice

New research published in the journal eNeuro examined whether eliminating a protein that is elevated in the brains of those with Alzheimer’s could prevent or reduce damage and behavioral symptoms in a mouse model of Alzheimer’s disease.

“Previous work from our research team and others found evidence that a specific protein named Centaurin-α1 is involved in the progression of Alzheimer’s damage within neurons,” explained lead author of the study, Dr. Erzsebet Szatmari. “To confirm the role of this protein and see if it might be a good therapeutic target, we tested whether genetically removing it would prevent or slow disease progression in a mouse model of the disease.”

The scientists used a well-characterized model of Alzheimer’s disease in mice. The disease model (called J20) contains two genetic mutations associated with rare familial variants of Alzheimer’s disease. These animals develop changes in brain tissue and behavioral deficits characteristic of many symptoms seen in human Alzheimer’s disease, including neuroinflammation, accumulation of neuronal plaques, synapse loss, and impairments in spatial memory and learning.

AI model to detect skin cancer

Key findings from the study include:


Researchers have developed a new approach for identifying individuals with skin cancer that combines genetic ancestry, lifestyle and social determinants of health using a machine learning model. Their model, more accurate than existing approaches, also helped the researchers better characterize disparities in skin cancer risk and outcomes.

Skin cancer is among the most common cancers in the United States, with more than 9,500 new cases diagnosed every day and approximately two deaths from skin cancer occurring every hour. One important component of reducing the burden of skin cancer is risk prediction, which utilizes technology and patient information to help doctors decide which individuals should be prioritized for cancer screening.

Traditional risk prediction tools, such as risk calculators based on family history, skin type and sun exposure, have historically performed best in people of European ancestry because they are more represented in the data used to develop these models. This leaves significant gaps in early detection for other populations, particularly those with darker skin, who are less likely to be of European ancestry. As a result, skin cancer in people of non-European ancestry is frequently diagnosed at later stages when it is more difficult to treat. As a consequence of later stage detection, people of non-European ancestry also tend to have worse overall outcomes from skin cancer.

Autistic children born preterm often show more complex needs—but share similar genetic background

A new study shows that children born preterm who are later diagnosed with autism often present with more extensive support needs and a higher number of co-occurring conditions than autistic children born at full term. Surprisingly, however, the researchers found no differences in genetic variants across the genome, nor in specific genes already linked to autism, between the groups—a result that contradicted their initial hypothesis.

The study was conducted at KIND (Center of Neurodevelopmental Disorders at Karolinska Institutet) and published in October 2025 in the journal Genome Medicine.

“We did not observe any genetic differences between preterm and full-term autistic children, which was unexpected. We initially thought that preterm children might show fewer of the genetic factors associated with autism, as their early birth can be viewed as an environmental factor,” says Yali Zhang, doctoral student at Tammimies research group at KIND and first author of the study.

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