A groundbreaking study reveals that a protein found in bats could hold the key to fighting inflammatory diseases and aging in humans. Bats have remarkably long lifespans and are resilient to viruses that are harmful to humans. The researchers identified a protein called “bat ASC2” that suppresses the inflammatory response in bats, allowing them to live disease-free. When this protein was genetically modified in mice, they demonstrated the same anti-inflammatory defenses as bats, and human cells became more resilient as well. This protein, with its therapeutic potential, could potentially contribute to longevity and reduced mortality from viruses in humans.
In other news, the Food and Drug Administration has finalized new guidelines for blood donation, allowing gay and bisexual men in monogamous relationships to donate blood without abstaining from sex. The new approach replaces past restrictions that required abstinence periods before donation. Instead, all potential donors will be screened using an HIV risk questionnaire. Donors reporting recent risky behavior will be deferred until a later date. These changes mark a significant step towards inclusivity and equity in blood donations.
The American Psychological Association (APA) issued its first advisory on guiding teens’ social media use. The APA recommends establishing limits and boundaries, providing social media literacy training, and reducing exposure to harmful content that could lead to self-harm. parents are encouraged to review their children’s social media and have ongoing discussions about the content. The advisory aims to help teens understand that social media presents a curated view of people’s lives and appearances. Problematic social media use is prevalent among teens, and this guidance aims to address and mitigate its negative effects.
Artificial intelligence (AI) could revolutionize heart attack diagnosis. Researchers at the University of Edinburgh developed an AI algorithm called CoDE-ACS that can outperform current testing methods in ruling out heart attacks. The algorithm analyzes patient data, such as age, sex, medical history, and troponin levels, to predict the likelihood of a heart attack. This algorithm can rule out heart attacks in more patients and with a higher accuracy rate of 99.6%. This development could significantly alleviate pressure on emergency departments and reduce hospital admissions by quickly identifying patients who require immediate care.
