A research team led by Prof. WANG Shuqiang from the Shenzhen Institute of Advanced Technology of the Chinese Academy of Sciences introduced a Prior-Guided Adversarial Learning with Hypergraph (PALH) model for predicting abnormal connections in Alzheimer's disease.
A research team led by Prof. ZHANG Shihua from the Academy of Mathematics and Systems Science has proposed a new computational tool, STAGATE, to decipher tissue substructures from spatial resolved transcriptomics. The model uses artificial intelligence technology to integrate spatial location information and gene expression profile of spatial spots. In this algorithm, a graph attention autoencoder is introduced, with a graph attention mechanism in the middle hidden layer, which can learn the heterogeneous similarities between neighboring spots adaptively.
A research team led by Prof. SHAO Dingfu from the Hefei Institutes of Physical Science has predicted a new class of antiferromagnetic materials with unique cross-chain structures, termed "X-type antiferromagnets". These materials exhibit sublattice-selective spin transport and unconventional magnetic dynamics, offering new possibilities for next-generation spintronic devices.
A research team led by Prof. Xiaoqiang Huang from Nanjing University has developed a novel non-natural dynamic kinetic oxidation system by integrating ferrocene methanol-mediated anodic oxidation with thiamine diphosphate (ThDP)-dependent enzyme catalysis, marking a significant advance in the field of asymmetric electroenzymatic catalysis.
A research team led by Prof. YUAN Junying at the Shanghai Institute of Organic Chemistry of the Chinese Academy of Sciences revealed how PARP12, a mono-ADP-ribosyltransferase, modulates cell fate decisions during viral infection.
Prof. XIAO Zhengguo’s team from the University of Science and Technology of China of the Chinese Academy of Sciences has proposed a novel strategy based on weakly space-confined, large-grain crystals of all-inorganic perovskite to prepare perovskite films with larger crystalline grains and higher temperature resistance.
A collaborative research team from the Institute of Biophysics, Beijing Normal University, Chongqing Maternal and Child Health Hospital, and the University of Science and Technology of China has, for the first time, resolved the high-resolution in situ structure of the central Apparatus within the axoneme of mammalian sperm.
Researchers from the Shanghai Institute of Materia Medica of the Chinese Academy of Sciences and the collaborators developed a precise targeting strategy for tracheal inflammation. The strategy uses nanogrid-based delivery systems composed of gridded cyclodextrin cross-links (GCC), and enables multiscale 3D visualization and in-depth pharmacodynamic evaluation with micro-optical sectioning tomography (MOST) and fluorescence MOST (fMOST) systems.
Researchers led by Prof. ZHANG Yuanming from the Xinjiang Institute of Ecology and Geography have revealed the microstructure and expansion mechanism of cyanobacteria-dominated biological soil crusts. By employing micro-scale X-ray computed tomography, they visualized the internal structural responses of cyanobacteria-dominated BSCs in unprecedented detail.
A research team led by Prof. ZHANG Jie from the Institute of Oceanology of the Chinese Academy of Sciences has made progress in enhancing the photocatalytic antibacterial activity of manganese and sulfur co-doped ZnIn2S4 (ZIS), using a novel oxygen vacancy-rich α-MnO2 decomposition approach.
Researchers from the Institute of Computing Technology of the Chinese Academy of Sciences, along with collaborators, have developed a food-oriented large language model (LLM)—FoodSky, a domain-specific large LLM designed for culinary and nutritional applications.
A recent study has introduced a novel data-driven model that distinguishes between human-induced and natural water consumption in croplands, providing valuable insights into the sustainability of arid lake ecosystems.
A research team led by Prof. XIE Pinhua from the Hefei lnstitutes of Physical Science has developed a novel prediction model for surface ozone concentration in the North China Plain and Yangtze River Delta regions. The model leverages a sequential convolutional long short-term memory network framework to integrate spatiotemporal meteorological features, addressing key limitations in existing forecasting methods.
A research team led by Prof. ZHANG Tianshu at the Hefei Institutes of Physical Science developed a compact all-solid-state continuous-wave single-longitudinal-mode laser with high frequency stability using iodine-based frequency locking, advancing its application in atmospheric remote sensing and environmental monitoring.
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