BU creates new language model to help people obtain more accurate answers to science, health questions
Peer-Reviewed Publication
Updates every hour. Last Updated: 12-Nov-2025 22:11 ET (13-Nov-2025 03:11 GMT/UTC)
In a new study, researchers from Boston University introduce a newly created computer program called PodGPT that learns from science and medicine podcasts to become smarter at understanding and answering scientific questions.
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Adding bile acids as farnesoid X receptor agonists to the culture medium supported the growth and development of unique stem cell-derived hepatic organoids, report researchers from Japan. These three-dimensional liver organoids were capable of sustained, long-term proliferation while retaining hepatocyte-like features. Their findings could have the potential to drive future research on chronic liver disease and result in newer therapeutic approaches to treat it.
Large language models (LLMs) can support clinical decision-making, but local versions often underperform compared to cloud-based ones. Japanese researchers tested whether retrieval-augmented generation (RAG) could enhance a local model’s performance in radiology contrast media consultations. In 100 synthetic cases, the RAG-enhanced model showed no hallucinations, faster responses, and better rankings by AI judges. These results suggest RAG can significantly boost the clinical usefulness of local LLMs while protecting sensitive patient data onsite.
In a significant step towards improving targeted cancer therapy, researchers from Japan have developed a novel nanocarrier system that delivers therapeutic antibodies directly to target antigens inside cancer cells. By utilizing a metal-polyphenol network, the system escapes endosomes, enabling intracellular targeting of antibodies, resulting in suppression of tumor growth and enhanced anti-cancer activity, offering a promising tool for targeted cancer therapy.