Developing an antibody to combat age-related muscle atrophy
Peer-Reviewed Publication
Updates every hour. Last Updated: 29-Apr-2025 11:08 ET (29-Apr-2025 15:08 GMT/UTC)
As we age, our muscles atrophy. Earlier this year, researchers at Kyushu University found that hepatocyte growth factor (HGF), a protein critical in skeletal muscle development loses its functionality due to nitration as we age. Now, the same team has developed a monoclonal antibody that blocks the nitration sites of HGF, effectively preventing the protein’s age induced loss of function. Their findings were validated utilizing rat muscles cell culture.
The IRB Barcelona spin-off Gate2Brain, a cutting-edge technology platform focused on enhancing drug delivery to the brain, has reached a major milestone in the fight against pediatric brain tumors by obtaining Orphan Drug Designation (ODD) from the European Medicines Agency (EMA) for its innovative product, G2B-002.
This designation recognizes G2B-002 as a potential treatment for a rare and severe disease, specifically granted to drugs aimed at conditions affecting fewer than 5 in 10,000 people in the European Union, and which offer significant advantages over limited or non-existent alternatives.
Cell-to-cell communication through nanosized particles, working as messengers and carriers, can now be analyzed in a whole new way, thanks to a new method involving CRISPR gene-editing technology. The particles, known as small extracellular vesicles (sEVs), play an important role in the spread of disease and as potential drug carriers. The newly developed system, named CIBER, enables thousands of genes to be studied at once, by labeling sEVs with a kind of RNA “barcode.” With this, researchers hope to find what factors are involved in sEV release from host cells. This will help advance our understanding of basic sEV biology and may aid in the development of new treatments for diseases, such as cancer.
Researchers from Qingdao University and the Qingdao Institute of Bioenergy and Bioprocess Technology (QIBEBT) of the Chinese Academy of Sciences have developed a novel method for rapidly and accurately assessing the metastatic potential of cancer cells. The new tool— combining Raman spectroscopy and machine learning—introduces the Ramanome-based Metastasis Index (RMI), offering an innovative means of diagnosing and managing cancer.
A new paper in Biology Methods and Protocols shows that scientists can train artificial intelligence models to distinguish brain tumors from healthy tissue. AI models can already find brain tumors in MRI images almost as well as a human radiologist.
MSU researchers now can identify more proteins, or biomarkers, in blood plasma, including those linked to specific diseases like cancer. By identifying these biomarkers earlier, medical researchers can create better diagnostic tests and drugs that target diseases sooner, improving patient outcomes.