News & Stories

A landmark study conducted by The Hong Kong University of Science and Technology (HKUST) has demonstrated that a genetic variant, TREM2 H157Y, significantly increases the risk of Alzheimer’s disease (AD) in individuals of ethnic Chinese descent. The research reveals that this variant confers a risk level comparable to that of the strongest known genetic risk factor for AD, APOE-ε4, and is associated with more rapid clinical progression and more severe neurodegeneration.This is the first in the field to conduct an in-depth family-based clinical case study on a Chinese-enriched genetic risk factor for AD, the TREM2 H157Y variant. The findings, published in Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, have profound implications for disease monitoring and patient management.

Membrane proteins are crucial for numerous biological processes and serve as important drug targets. For decades, scientists have relied on detergents to extract membrane proteins from cell membranes for structural studies. While detergent-based approaches have significantly advanced our understanding of membrane protein structures, they present certain limitations, such as resource-intensive detergent screening and the absence of native membrane lipids, which can hinder investigations into lipid-mediated regulation. To address these challenges, a research team led by Prof. DANG Shangyu from the Division of Life Science at the Hong Kong University of Science and Technology (HKUST) has developed a novel vesicle-based method that preserves the native lipid environment of membrane proteins, which can advance structural and functional studies.

A research team from the Hong Kong University of Science and Technology (HKUST), led by Professors Gan Jianping (Department of Ocean Science) and Professor Yang Can (Department of Mathematics), has developed a novel AI-powered tool named STIMP for diagnosing coastal ocean productivity and ecosystem health. STIMP introduces a novel paradigm that imputes missing data and then predicts Chlorophyll-a (Chl-a) concentrations across large spatiotemporal scales. In tests across four representative global coastal regions, STIMP significantly outperformed existing geoscience tools, reducing the mean absolute error (MAE) for imputation by up to 81.39% and for prediction by 58.99%. Accurate Chl-a prediction aids in early detection of harmful algal blooms, ecosystem protection, and provides data-driven insights for evidence-based policy-making.

A research team led by Prof. PAN Ding, Associate Professor from the Departments of Physics and Chemistry, and Dr. LI Shuo-Hui, Research Assistant Professor from the Department of Physics at the Hong Kong University of Science and Technology (HKUST), has developed a novel direct sampling method based on deep generative models. This method enables efficient sampling of the Boltzmann distribution across a continuous temperature range. The findings have been published in Physical Review Letters*.

The Hong Kong University of Science and Technology (HKUST) today received plaques from YIN Hejun, Minister of the Ministry of Science and Technology (MOST) for its three State Key Laboratories (SKLs) at the Government Headquarters of the Hong Kong Special Administrative Region (HKSAR). HKUST sincerely thanks MOST, and the Hong Kong Innovation, Technology, and Industry Bureau (ITIB) for their continued trust and recognition of the University’s research efforts. In addition to the two renamed SKLs following restructuring – the “State Key Laboratory of Nervous System Disorders (SKLNSD)” and the “State Key Laboratory of Displays and Opto-Electronics (SKLDOE)” – HKUST will also collaborate with The Hong Kong Polytechnic University (PolyU) to establish a new “State Key Laboratory of Climate Resilience for Coastal Cities (SKLCRCC)”.

The Hong Kong University of Science and Technology (HKUST) selected eight cutting-edge projects for the latest round of Sustainable Smart Campus as a Living Lab program for testing on campus. Covering a wide range of sustainability challenges on campus, the projects address energy efficiency, renewable energy optimization, water management, wellness, ecosystem enhancement, and predictive maintenance strategies, providing students and faculty with hands-on experience with prototypes before real-world implementation.

The Hong Kong University of Science and Technology (HKUST) today announced the launch of “Aivilization”, the largest-scale AI multi-agent social simulation sandbox to date. This innovative platform studies how human interaction with AI can shape a virtual society, where ‘AI inhabitants’ can organically develop their own governance structures, economies and cultural norms.   As AI becomes increasingly integrated into our daily lives, understanding the dynamics of communication between humans and artificial intelligence has become a crucial area of study. Previous simulation models like Project Sid1 and Stanford Smallville2 have explored similar themes, with community sizes of around 1,000 and dozens of AI agents respectively, to observe the evolution of AI civilizations.

MicroRNAs (miRNAs) are tiny RNA molecules that regulate gene expression by controlling messenger RNAs (mRNAs) and are critical for various biological processes, including development, stress responses, and epigenetic regulation. In plants, the enzyme DICER-LIKE 1 (DCL1) processes miRNA precursors into mature miRNAs, and mutations in DCL1 can lead to developmental issues like delayed flowering and abnormal leaves, making its precision essential for plant growth. A research team led by Prof. NGUYEN Tuan Anh from the Division of Life Science at HKUST has recently made significant strides in understanding miRNA biogenesis by developing a groundbreaking massively parallel dicing assay to investigate human DICER, which functions similarly to plant DCL1.