A research team led by Professor Nicholas X. Fang from the Department of Mechanical Engineering from the Faculty of Engineering at The University of Hong Kong (HKU) have developed a world-leading innovation known as “SonoMeta”. This artificial intelligence (AI)-powered MetaLens effectively addresses a longstanding challenge in the medical field, bringing revolutionary advancements in cardiology, pulmonary medicine, and emergency care.

A multidisciplinary team from the LKS Faculty of Medicine at the University of Hong Kong (HKUMed), has conducted a series of landmark studies demonstrating that statins can lower the risk of cardiovascular disease (CVD) without increasing the incidence of major adverse events. These studies were conducted in several patient groups, including individuals with type 1 diabetes mellitus (T1DM), patients with kidney failure, and the elderly patients with chronic kidney disease. The findings strengthen the evidence base for the statin use in populations historically excluded from randomised controlled trials (RCTs), and guide future clinical practice in managing high cholesterol.

Researchers have developed the first platform of its kind that allows dynamic visualization of male reproductive function in living mice. In findings published in MedComm, they describe an approach that enables non-invasive, real-time monitoring of male fertility over time.

Psychiatric diagnosis still relies on symptom checklists that were never designed to reflect biology. A peer-reviewed invited review published in Brain Medicine now synthesizes recent advances across four converging domains: conceptual frameworks that move beyond categorical labels, molecular and neurobiological biomarkers, digital phenotyping through smartphones and wearable devices, and machine learning approaches capable of integrating these heterogeneous data streams. The review authors, based at the University of Cambridge, argue that combining objective biological measurement with clinical judgment could yield diagnostic subtypes that predict illness trajectory and guide personalized treatment. They also identify formidable barriers, from data scarcity and algorithmic opacity to regulatory fragmentation and the risk of deepening health inequities.

Epilepsy affects roughly 50 million people worldwide, yet the genetic roots of its most common forms have remained stubbornly obscure. A new mini-review published in Genomic Psychiatry brings together findings from the largest genome-wide association studies and exome sequencing efforts to date, revealing that thousands of common variants, each with tiny individual effects, collectively shape disease risk. The review identifies more than 20 genomic loci associated with genetic generalized epilepsy, highlights convergence between rare and common variant signals in ion channel and synaptic genes, documents extensive genetic overlap with psychiatric disorders, and outlines remaining challenges for polygenic risk prediction in clinical practice.

Researchers at the Icahn School of Medicine at Mount Sinai have created the first comprehensive sex-specific atlas of GLP-1 expression in the mouse brain, mapping the molecule mimicked by blockbuster weight-loss drugs such as semaglutide at single-transcript resolution across 25 brain regions in each sex. Key hindbrain regions showed higher GLP-1 densities in females, while the olfactory bulb showed significantly greater expression in males, and several brain nuclei expressed the peptide in only one sex. These findings provide a neuroanatomical framework that may help explain why GLP-1 appears to exert stronger metabolic effects in females, with implications for the emerging psychiatric applications of GLP-1 analogs.