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Category: biotech/medical – Page 13

Cancer cells release antioxidants to prevent immune cells from destroying them

Molecules called reactive oxygen species, which include so-called “free radicals,” have long been viewed as damaging byproducts of our body’s metabolism—a reason antioxidant supplements have been considered a potential way to reduce cancer risk.

Now, scientists have discovered that certain immune cells depend on these molecules to activate and destroy cancer cells and that tumors exploit this dependency by releasing natural antioxidants to shut down the immune attack.

The findings, published today in Science, could help improve the effectiveness of cancer immunotherapies.

Psilocybin prevents chemotherapy-related nerve injury and associated symptoms in preclinical models

In a breakthrough study, researchers at The University of Texas MD Anderson Cancer Center discovered that psilocybin given before chemotherapy prevented the onset of nerve injury in preclinical models, even after repeated treatment cycles. The findings could help prevent pain, numbness and other common chemotherapy side effects.

The study, published in Science and co-led by Moran Amit, M.D., Ph.D., professor of Head and Neck Surgery, and Patrick Dougherty, Ph.D., professor of Pain Medicine, uncovers a previously unrecognized neuroprotective role of serotonin receptors and suggests psilocybin as a first-in-class intervention for the prevention of chemotherapy-induced peripheral neuropathy.

“There is an urgent need for treatments that prevent nerve injury without interfering with lifesaving chemotherapy,” Amit said. “These findings offer important insights into how psilocybin may protect nerves before damage occurs, rather than treating symptoms after they become persistent. At UT MD Anderson, we are actively exploring the multiple facets of psychedelics to pursue interventions that improve the lives of our patients.”

Type 1 Diabetes May Actually Be Two Different Diseases, Massive International Study Finds

Identifying distinctive types of conditions like diabetes is helpful in two ways.

It means treatments can be personalized more precisely to individuals, and gives researchers a better idea of how to make those treatments more effective going forward.

When it comes to type 1 diabetes, there are two genetic patterns called HLA-DR3 and HLA-DR4 that are associated with a higher risk of the disease. However, while the end result is the same (type 1 diabetes), the early signs differ between the two patterns.

The Way You Draw Can Reveal Parkinson’s Disease With Up to 99% Accuracy, Study Reveals

The warning signs of Parkinson’s appear to be all around us.

Scientists have found clues to the disease’s emergence in people’s hair, in their blood, and in their earwax too.

The way you talk, your mental health, and even where you live have all shown varying links to the condition, which affects movement and muscle control.

Frontiers: The review *The Phantastic Organ* traces how this concept evolved from Helmholtz’s “unconscious inference” through predictive coding and ultimately to today’s Bayesian brain and Free Energy Principle frameworks

And that raises a fascinating possibility: what we experience as “reality” may be the brain’s best continuously updated explanation of the signals it receives.

Rewiring of protein interaction networks by autism mutations

For more than two decades, researchers have identified hundreds of genes that increase the risk of autism spectrum disorder (ASD). Yet multiple fundamental questions have remained unanswered: among them, how do mutations in these genes lead directly to changes in brain development and how can that knowledge be translated into more effective therapies?

In a landmark study published in Science, scientists have taken a major step toward answering both questions. The findings are the result of more than a decade of work. By building the largest-ever molecular interaction map of autism, the team revealed how hundreds of genes and dozens of mutations converge within a surprisingly small number of shared protein networks, hurdling a major roadblock to the development of new precision medicines.

Rather than focusing only on the genes linked to autism, the researchers mapped the proteins encoded by those genes and discovered exactly how individual disease-causing mutations can rewire the molecular machinery of the developing brain. The work uncovers an entirely new layer of disease biology that can be targeted therapeutically and provides a framework for designing medicines that directly address a wide range of underlying molecular causes of autism.

Targeting Tumor ‘Softness’ Enhances Immunotherapy

Researchers at the University of Southern California (USC) developed a novel tool in which they can detect ‘softness’ of a tumor and help inform therapeutic outcomes. The physical attributes of tumors, particularly hardness, is a persistent obstacle for cancer immunotherapy. Historically, firmness of most solid tumors correlates with the penetration of therapy and could lead to drug resistance. Scientists that developed this technology recently published their findings in Nature Biomedical Engineering. The team, led by Dr. Yingxiao Wang, details how the softness of tumors can allow them to adapt and evade the immune system and treatment. This finding is contradictory from what previous articles in the field have stated.

Wang is the Dwight C. and Hildagarde E. Baum Chair in Biomedical Engineering and Professor of Biomedical Engineering and Molecular Microbiology & Immunology in the USC Viterbi School of Engineering and associated with the Keck School of Medicine. Collaborations with the Wang Lab developed a way to target soft stem-like cancer cells, which are extremely hard to treat. Cancer stem-cells are key drivers of tumor growth, drug resistance, and immune evasion. These cells are a major topic of interest in the Wang Lab. Wang and his team also focus their research on techniques to detect biomarkers and visualize molecular events in cells. These investigations could lead to optimal treatment delivery to the tumor site and enhancement of immunotherapy.

Researchers are using an immunotherapy known as chimeric antigen receptor (CAR)- T cells, which programs T cells to specifically target the tumor. T cells are specialized immune cells tasked with identifying and eliminating disease. They are a critical component of the immune system and correlate to survival. However, in the context of cancer, they become inert and less active due to tumor-secreting molecules and proteins that dysregulate their function. As a result, scientists in the field of immuno-oncology (IO) have focused on these cells to overcome therapeutic resistance. To generate CAR-T cells, scientists take T cells from a patient and engineer them to redirect the immune response toward the tumor. The CAR-T cells are then able to identify specific proteins on the tumor, which reduce off-target cell death and limit toxicity. Unfortunately, CAR-T cells are less effective against solid tumors.

New AI tool maps the hidden universe of small molecules

The human body and its gut microbiome produce thousands of small molecules that shape how the body functions—influencing immunity, metabolism and more. Identifying what those molecules actually are has been one of the biomedical sciences’ most persistent bottlenecks. More than 80% of compounds detected in a typical biological sample cannot be matched to any known structure using current methods.

Researchers at the Boyce Thompson Institute (BTI) and Cornell University have developed a tool that begins to change that. AIMe, short for AI Molecule Explorer, uses a form of artificial intelligence called neuro-symbolic AI to predict, organize and search the mass spectra of more than 100 million known small organic molecules—effectively building a vast searchable map of chemical space that can accelerate hypothesis generation and compound identification.

The work is a collaboration between Frank Schroeder, professor at BTI and in Cornell’s Department of Chemistry and Chemical Biology, and Carla Gomes, professor of computing and information science and director of Cornell’s AI for Science Institute.

Ultrafast electrons and lasers reveal unexpectedly strong radiation signals in common semiconductors

Detecting radiation is key to technologies ranging from particle accelerators and scientific instruments to medical imaging and security screening. But current detectors must often make trade-offs, providing signals that are strong but slow or fast but weak. The trade-off between signal strength and speed can limit precision detection.

In new research, Stanford University researchers worked with the Department of Energy’s SLAC National Accelerator Laboratory on a unique experimental setup to detect radiation across a range of materials.

What they found surprised them. Not only did the researchers observe an unexpectedly strong ultrafast radiation signal, they also found that the charge within the materials acted differently than expected.

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