A research paper by scientists from Capital Medical University proposed a diffusion tensor imaging (DTI)-based DenseNet to identify SVCI from subcortical ischemic vascular disease (SIVD) and to profile multidomain cognitive risks.

The new research paper, published on May. 13 in the journal Cyborg and Bionic Systems, developed a deep‑learning framework that uses routine diffusion tensor imaging to both identify SVCI and profile an individual’s domain‑specific cognitive weaknesses.

Cambridge, MA — May 26, 2026 — Insilico Medicine (“Insilico”, 3696.HK), a clinical-stage generative artificial intelligence (AI)-driven biotechnology company, and Human Life Foundation Models, Inc. (HLFM), a newly launched company established by Human Longevity, Inc. today announced a multi-million-dollar AI co-development collaboration to build industry’s first large-scale foundation models dedicated to human longevity science.

Esophageal squamous cell carcinoma (ESCC) represents a significant global health burden characterized by a high mortality rate, primarily due to uncontrolled tumor proliferation and the prevalence of distant metastases at the time of diagnosis. Despite significant advances, there remains a critical need to identify the underlying molecular mechanisms to establish new therapeutic approaches.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains a significant global health threat, largely due to its rapid evolution and high mutation rate, which often compromises the performance of existing molecular diagnostics. While conventional double-antibody sandwich immunoassays are widely used for rapid testing, their effectiveness is frequently hindered by structural steric hindrance and limited sensitivity when detecting small viral components like the nucleocapsid (N) protein.

An artificial intelligence–driven transfer learning strategy enabled the discovery of a novel indolopyridine-based small molecule (Compound 8a) that directly targets gp130, potently suppresses the JAK2/STAT3 signaling pathway, and effectively inhibits colorectal cancer growth in vitro and in vivo, offering a promising lead and a feasible computational paradigm for developing gp130‑targeted anticancer agents.