Toggle light / dark theme

Rejuvenating the blood: New pharmacological strategy targets RhoA in hematopoietic stem cells

Aging is defined as the deterioration of function over time, and it is one of the main risk factors for numerous chronic diseases. Although aging is a complex phenomenon affecting the whole organism, it is proved that the solely manifestation of aging in the hematopoietic system affects the whole organism. Last September, Dr. M. Carolina Florian and her team revealed the significance of using blood stem cells to pharmacologically target aging of the whole body, thereby suggesting rejuvenating strategies that could extend healthspan and lifespan.

Now, in a Nature Aging, they propose rejuvenating aged blood stem cells by treating them with the drug Rhosin, a small molecule that inhibits RhoA, a protein that is highly activated in aged hematopoietic stem cells. This study combined in vivo and in vitro assays at IDIBELL together with innovative machine learning techniques by the Barcelona Institute for Global Health (ISGlobal), a center supported by the “la Caixa” Foundation, and the Barcelona Supercomputing Center.

AI learns from the tree of life to support rare disease diagnosis

Researchers have created an artificial intelligence model that can identify which mutations in human proteins are most likely to cause disease, even when those mutations have never been seen before in any person.

The model, called popEVE, was created using data from hundreds of thousands of different species and of genetic variation across the human population. The vast evolutionary record allows the tool to see which parts of every one of the roughly 20,000 human proteins are essential for life and which can tolerate change.

That allows popEVE to not only identify disease-causing mutations but also rank how severe they are across the body. The findings, published today in Nature Genetics by researchers at Harvard Medical School and the Center for Genomic Regulation (CRG) in Barcelona, could transform how doctors diagnose genetic disease.

Automated Benchtop Synthesis of a Quadrillion-Plus Member Core@Multishell Nanoparticle Library Using a Massively Generalizable Nanochemical Reaction

Rapidly expanding advances in computational prediction capabilities have led to the identification of many potential materials that were previously unknown, including millions of solid-state compounds and hundreds of nanoparticles with complex compositions and morphologies. Autonomous workflows are being developed to accelerate experimental validation of these bulk and nanoscale materials through synthesis. For colloidal nanoparticles, such strategies have focused primarily on compositionally simple systems, due in part to limitations in the generalizability of chemical reactions and incompatibilities between automated setups and mainstream laboratory methods. As a result, the scope of theoretical versus synthesizable materials is rapidly diverging. Here, we use a simple automated platform to drive a massively generalizable reaction capable of producing more than 651 quadrillion distinct core@multishell nanoparticles using a single set of reaction conditions. As a strategic model system, we chose a family of seven isostructural layered rare earth (RE) oxychloride compounds, REOCl (RE = La, Ce, Pr, Nd, Sm, Gd, Dy), which are well-known 2D materials with composition-dependent optical, electronic, and catalytic properties. By integrating a computer-driven, hobbyist-level pump system with a laboratory-scale synthesis setup, we could grow up to 20 REOCl shells in any sequence on a REOCl nanoparticle core. Reagent injection sequences were programmed to introduce composition gradients, luminescent dopants, and binary through high-entropy solid solutions, which expands the library to a near-infinite scope. We also used ChatGPT to randomly select several core@multishell nanoparticle targets within predefined constraints and then direct the automated setup to synthesize them. This platform, which includes both massively generalizable nanochemical reactions and laboratory-scale automated synthesis, is poised for plug-and-play integration into autonomous materials discovery workflows to expand the translation of prediction to realization through efficient synthesis.

Chinese humanoid robot sets guinness world record with 106-km inter-city walk

New research shows that the magnetic part of light actively shapes how light interacts with matter, challenging a 180-year-old belief.

The team demonstrated that this magnetic component significantly contributes to the Faraday Effect, even accounting for up to 70% of the rotation in the infrared range. By proving that light can magnetically torque materials, the findings open unexpected pathways for advanced optical and magnetic technologies.

Revealing Light’s Hidden Magnetic Power

Dr. Carina Kern — CEO, LinkGevity — Necrosis Inhibitors To Pause The Diseases Of Aging

Necrosis Inhibitors To Pause The Diseases Of Aging — Dr. Carina Kern Ph.D. — CEO, LinkGevity


Dr. Carina Kern, Ph.D. is the CEO of LinkGevity (https://www.linkgevity.com/), an AI-powered biotech company driving innovation in drug discovery for aging and resilience loss.

Dr. Kern has developed a new Blueprint Theory of Aging, which takes an integrative approach to understanding aging, combining evolutionary theory, genetics, molecular mechanisms and medicine, and is used to structure LinkGevity’s AI.

Dr. Kern’s labs are based at the Babraham Research Campus, affiliated with the University of Cambridge and her research has led to the development of a first-in-class necrosis inhibitor targeting cellular degeneration (Anti-Necrotic™). This novel therapeutic is ready to begin Phase II clinical trials later this year, as a potential breakthrough treatment for aging, with UK Government, Francis Crick Institute KQ labs, and European Union (Horizon) support.

The Anti-Necrotic™ has also been selected as one of only 12 global innovations for NASA’s Space-Health program, recognizing its potential to mitigate accelerated aging in astronauts on long-duration space missions.

A new artificial muscle could let humanoid robots lift 4,400 times their weight

A new material bends that rule.

Researchers in South Korea say they have built a soft, magnetic artificial muscle that hits hard numbers without turning into a stiff piston. The material flexes, contracts and relaxes like flesh, yet ramps up stiffness on demand when asked to do real work. That mix has long sat out of reach for humanoid robots that need both agility and strength.

Most humanoids move with a cocktail of motors, gears and pneumatic lines. These systems deliver power, but they also add bulk and make contact risky. Soft actuators change the equation. They integrate into limbs, cushion impacts and tolerate misalignment. They also weigh far less than hydraulic stacks and slot neatly inside compact forms like hands, faces and torsos.

/* */