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climate.gov2d agoResearchers have combined genome mining with enzyme engineering to develop new polyene antifungals that could one day replace the current gold standard treatment, according to GEN. The team identified Nys34 as a leading candidate after it demonstrated three-to-eightfold lower toxicity than amphotericin B in multiple human cell lines and reduced fungal burden in a mouse model of invasive aspergillosis. "We have discovered and engineered novel polyene antifungals that outperform the current gold standard therapy in preclinical studies, opening new possibilities for treating life threatening multi-drug resistant fungal infections." The findings, reported by communities.springernature.com, suggest the engineered compounds pack a stronger punch against drug-resistant pathogens while sparing healthy cells, a promising balance for a class of drugs notorious for side effects. "The world faces a critical need for new medicines to treat deadly fungal infections, and this enzymatic approach opens a new path to improve antifungal drug development." C&EN's coverage frames the work as a biocatalytic platform that offers a scalable strategy for tailoring natural products, meaning the same enzyme-based approach could be applied broadly rather than only to this single compound. Together, the reports point to Nys34 as a standout: it not only matched amphotericin B's antifungal activity but did so at a fraction of the toxicity, and the scalable platform behind it could speed development of other natural product derivatives as drug resistance continues to rise.
Identical CMEs were simulated to propagate through 18,000 instances of realistically structured solar wind over 4.5 solar cycles CME transit time/arrival speed at 1 AU can vary up to 47 hr/340 km...
agupubs.onlinelibrary.wiley.com·Climate Science·2d ago·52 min readEven when ketamine completely disconnects patients from the physical world, the brain continues to generate vivid, REM-like dreams without risking dangerou
talkingketamine.com·Science·2d ago·19 min read
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Shared by @kgusler.bsky.social ↗As a labor-augmenting technology, large language models (LLMs) have the potential to accelerate scientific activity across the research pipeline. But even if LLMs perform on par with human experts at selected tasks, their use will bring unintended consequ
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