Machine learning to identify the factors that may determine the age of onset of Huntington’s disease
Reports and Proceedings
Updates every hour. Last Updated: 16-Jun-2026 11:16 ET (16-Jun-2026 15:16 GMT/UTC)
A team from the Faculty of Medicine and Health Sciences and the Institute of Neurosciences at the University of Barcelona (UBneuro) has applied advanced artificial intelligence techniques to better understand why Huntington’s disease can begin at very different ages in patients. This hereditary neurodegenerative condition, which causes motor, cognitive, and psychiatric impairments, is caused by a mutation in the HTT gene, which encodes the huntingtin protein.
Delivering therapies to the brain remains a major challenge due to the limited permeability of the blood-brain barrier. In a recent study published in Cell, researchers proposed a strategy to hijack skull-derived immune cells using drug-loaded nanoparticles, leveraging their unique migration mechanism through skull-meninges microchannels to bypass the blood-brain barrier. The team demonstrated efficient in situ construction of nanoparticle-loaded immune cells and their rapid migration to the disease site in response to CNS perturbations, enabling targeted delivery to brain lesions. In preclinical stroke models, this strategy achieved promising therapeutic efficacy in improving both short- and long-term outcomes. A prospective clinical trial further supports the translational feasibility of the calvarial immune access in treating malignant stroke. These findings establish a potentially clinically translatable platform for brain drug delivery.
On January 9, 2026, the latest edition of Applied Artificial Intelligence for Drug Discovery was published online as a Springer Nature volume, spanning 27 chapters authored by leading international experts to present state-of-the-art approaches in the whole drug discovery process. As a pioneering global biotechnology company, Insilico Medicine (3696.HK) made exclusive contributions to two chapters in the comprehensive and forward-looking volume, sharing experience in real-life application of AI in early drug target-related tasks including evaluation, and giving prospects for the future assisted with quantum computing. The book has obtained 1700+ accesses, only 10 days after publication.
A new University at Buffalo study examines what happens to discarded cigarette butts when released into the environment. Findings showing that one cigarette filter can release up to two dozen microfibers almost immediately upon contacting water. More than 100 additional microfibers may break free of the filter within 10 days depending on how the water is moving.
This quick release of cellulose acetate fibers – what most cigarette filters are made of – had not been precisely measured before. This builds upon the evidence that cigarette butts –the most littered item worldwide – are a direct and underestimated source of microplastic pollution.
Researchers have mapped the cellular diversity of the eye’s fluid drainage tissue, identifying a cell subtype that shows early signs of dysfunction in a genetic mouse model of glaucoma. Their study, published today in eLife as the final Version of Record after appearing previously as a Reviewed Preprint, provides what the editors say are fundamental findings, highlighting vitamin B3 treatment as a potential therapeutic strategy for preventing or slowing the development of glaucoma.