These ancient hitchhikers, known as endogenous retroviruses, were long considered inert or 'junk' DNA, defanged of any ability to do damage. New CU Boulder research published July 17 in the journal Science Advances shows that, when reawakened, they can play a critical role in helping cancer survive and thrive.
Efforts to combat the increasing threat of drug-resistant bacteria are being assisted by a new approach for streamlining the search for antimicrobial drug candidates, pioneered by researchers at Hokkaido University, led by Assistant Professor Kazuki Yamamoto and Professor Satoshi Ichikawa of the Faculty of Pharmaceutical Sciences.
Type 2 diabetes is associated with an increased risk of death and disability, and imposes a significant economic burden on individuals and societies worldwide.
To bring light's benefits to these harder-to-access cancers, engineers and scientists at the University of Notre Dame have devised a wireless LED device that can be implanted.
Targeted alpha therapy (TAT) is emerging as a potential additional treatment for glioblastoma (GB), a disease which has confounded oncologists for decades due to its aggressive nature and strong resistance to existing therapies.
Notably, the study found people with diabetes who had been prescribed semaglutide by their physician and then filled the prescription were more than four times more likely to be diagnosed with NAION.
Since 2020, GSK and CureVac have worked together to develop mRNA vaccines for infectious diseases.
Researchers at UC San Francisco have figured out how to turn ordinary white fat cells, which store calories, into beige fat cells that burn calories to maintain body temperature.
Sipavibart is an investigational long-acting antibody designed to provide COVID-19 protection for immunocompromised patients who often do not respond adequately to vaccination alone and remain at high risk of serious outcomes from COVID-19.
Vivek Subbiah, MD, from the Sarah Cannon Research Institute, and coauthors, describe a shift toward predictive medicine,
The program, called TopoFormer, was developed by an interdisciplinary team led by Guowei Wei, a Michigan State University Research Foundation Professor in the Department of Mathematics. TopoFormer translates three-dimensional information about molecules into data that typical AI-based drug-interaction models can use, expanding those models' abilities to predict how effective a drug might be.