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Category: biotech/medical

Age does not appear to drive cardiovascular risk in pregnancy

Underlying cardiovascular risk, rather than older age, drives complications such as venous thromboembolism, cardiomyopathy and heart failure during pregnancy, according to new Weill Cornell Medicine research. The findings may encourage doctors to more actively address cardiovascular health in patients before they become pregnant.

The study, published in Nature Communications, suggests that instead of pregnancy becoming inherently riskier as people get older, it amplifies a person’s baseline cardiovascular risk, regardless of age.

“Pregnancy seems to be a uniform stress test, so to speak,” said the study’s lead author, Dr. Hooman Kamel, vice chair of clinical research and chief of neurocritical care in the Department of Neurology and the Helen and Albert Moon Professor of Neurology at Weill Cornell Medicine.

A new way to recharge aging muscle stem cells by restoring a key metabolic component

Losing muscle strength is a natural part of aging. At the core of this decline is a drop in the number of muscle stem cells (MuSCs), the specialized cells responsible for maintaining and regenerating muscle tissue throughout our lives. Loss of muscle strength can severely affect mobility, increasing the risk of falls, fractures and, most importantly, the loss of independence.

Published in Nature Aging, a recent study took a crucial first step toward restoring stem cell function in aging muscles—gaining a clearer understanding of how metabolism changes when stem cells are activated and how these critical processes weaken with age.

The researchers’ investigation led them to glutamine metabolism, the process by which cells use the amino acid glutamine to support essential functions. They found that for MuSCs, glutamine is more than just a nutrient. It provides the raw material needed to produce fatty acids that help cells grow, divide, and repair damaged muscles.

Bioengineers condense protein engineering and testing to a single day

Proteins are critical to life—and to industry. There are countless proteins that could be engineered to treat and even cure serious diseases and cellular dysfunctions. Industrial applications are similarly promising, with proteins increasingly used as enzymes in food manufacturing and in consumer detergents.

While AI can help suggest improvements, each novel protein must still be created in the real world and tested for performance. It is a labor-intensive process that involves constructing the DNA instructions for each protein in yeast or bacteria and growing individual clones for protein production and testing. This can take many days for a single protein of interest and even longer if the protein needs to be tested in mammalian cells, a process that requires retrieving DNA from microbes for transfer to the mammalian cells.

In a new paper, Michael Z. Lin, a professor of neurobiology and of bioengineering in the schools of Engineering and Medicine, and graduate students, Yan Wu in bioengineering and Pengli Wang in chemical engineering, say they have condensed the time-intensive protein building and testing process to just 24 hours.

How looking through static can help people with a common degenerative disease see better

Age-related macular degeneration (AMD) is the leading cause of irreversible blindness among aging people globally. Around one in seven Australians over the age of 50 have some signs of AMD.

The disease results in blurred and distorted vision, and often loss of function at the center of the eye’s visual field.

The best current treatment involves a series of injections to slow the progression of the disease, but this process can be expensive and difficult with potentially negative long-term effects.

Stanford CS231N Deep Learning for Computer Vision I 2025

Computer Vision has become ubiquitous in our society, with applications in search, image understanding, apps, mapping, medicine, drones, and self-driving cars. Core to many of these applications are visual recognition tasks such as image classification, localization and detection. Recent developments in neural network (aka “deep learning”) approaches have greatly advanced the performance of these state-of-the-art visual recognition systems. This course is a deep dive into deep learning methods with a focus on end-to-end models for core vision tasks, alongside modern approaches such as transformers, diffusion models, and visual-language models that power today’s AI systems. During the 10-week course, students will learn to implement and train their own neural networks and gain a detailed understanding of cutting-edge research in computer vision. Additionally, the final assignment will give them the opportunity to train and apply multi-million parameter networks on real-world vision problems of their choice. Through multiple hands-on assignments and the final course project, students will acquire the toolset for setting up deep learning tasks and practical engineering tricks for training and fine-tuning deep neural networks. https://online.stanford.edu/courses/cs231n-deep-learning-computer-vision

Battery-free skin-conformal wearable system can measure electrocardiogram signals

A research team led by Prof. Jerald Yoo from the Department of Electrical and Computer Engineering at Seoul National University (SNU) has developed a skin-conformal wearable health care system, “SkinECG,” capable of measuring electrocardiogram (ECG) signals without a battery. By combining energy harvesting with human body–coupled power transfer, the study presents a new solution to one of the most critical challenges in wearable devices: power supply.

The findings are published in Science Advances.

Wearable health care systems are emerging as next-generation medical technologies that enable real-time monitoring of physiological signals through body-worn sensors, allowing early detection of disease-related abnormalities.

Small Study Shows One-time Cell Therapy Can Control HIV Infection

Unlike previous HIV “cures” involving cancer patients given bone marrow stem cells from a donor with a rare genetic mutation that resists HIV infection, researchers said CAR-T could be used by a much broader patient population. The Phase 1 trial involved CAR-T, a one-time therapy in which a patient’s T-cells are extracted, altered and multiplied in a lab and infused back into ⁠their body. In this case, the CAR-T targeted the CD4 and CCR5 binding sites of the HIV.

Of three trial patients ‌treated with a standard CAR-T dose, researchers said two maintained undetectable to ‌very low levels of HIV after stopping antiretroviral therapy — one for over two years so far and another for nearly a year. “The two that have ‌been off (HIV drugs) the longest and doing well were importantly diagnosed pretty quickly and put on therapy pretty quickly,” said Dr. Steven Deeks, professor of medicine at the University of California, San Francisco and the study’s lead investigator.

Currently, CAR-T ‌treatments are available for several types of blood cancer, and are being developed for autoimmune diseases like lupus and scleroderma. Tap the link to learn more about the recent study.

Re-engineering an HIV patient’s own immune cells to find and destroy the virus succeeded in controlling the infection in a small first-in-human study, but researchers said work is needed to confirm ⁠the findings and determine which patients are most likely to benefit.

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