A research team led by Prof. WAN Yinhua from the Institute of Process Engineering has developed a machine learning framework to analysis virus filtration processes in therapeutic protein purification. The new method enables intelligent identification of critical parameters affecting virus retention efficiency and provides predictive guidance for process optimization.
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.
Using China's Five-hundred-meter Aperture Spherical Radio Telescope (FAST), researchers have uncovered new magnetic field structures in a rare class of binary star systems known as spider pulsars, offering valuable insights into their evolution and the mechanisms behind mass loss in their companion stars.
A research team led by Prof. LIANG Changhao from the Hefei Institutes of Physical Science, in collaboration with researchers from the University of Padova of Italy and Shanghai Jiao Tong University, has developed a novel laser-assisted synthesis method to fabricate platinum colloidosomes with promising applications in near-infrared (NIR) photocatalytic and enzyme-mimicking cancer therapy.
A collaborative research team from the Xinjiang Technical Institute of Physics and Chemistry of the Chinese Academy of Sciences, along with researchers from the Lawrence Livermore National Laboratory in the U.S. and the International Iberian Nanotechnology Laboratory in Portugal, has revealed at the atomic scale how factors such as size, defect density, and approach pathways influence crystal growth through coalescence.
Researchers from the Dalian Institute of Chemical Physics of the Chinese Academy of Sciences, Fudan University and Georgia Institute of Technology, uncovered the mechanisms underlying the anodic high-temperature oxygen evolution reaction in solid oxide electrolysis cells.
A recent study, conducted by researchers from the Beijing Institute of Genomics at the Chinese Academy of Sciences, the Institute of Zoology at CAS, and Sichuan University, has produced the first "molecular movie" that illustrates how organs age. The researchers tracked over 12,700 proteins across 13 different tissues from 76 individuals aged 14 to 68 using ultra-sensitive mass spectrometry and artificial intelligence.
A team led by Prof. CHEN Lingling from the Center for Excellence in Molecular Cell Science of the Chinese Academy of Sciences revealed a spatiotemporal separation in the processing of distinct rRNA precursors (pre-rRNAs) within the nucleolus, offering a new perspective on how nucleolar architecture is functionally organized.
A research group led by Prof. DING Weixin from the Institute of Soil Science of the Chinese Academy of Sciences has utilized a newly developed dynamic global wetland water level (WL) dataset to assess the spatiotemporal dynamics of wetland carbon sequestration from 2000 to 2020.
Researchers in China have uncovered the first direct evidence: Approximately 436-million-year-old brachiopods from the early Silurian period used tiny, bristle-like structures called setae to maintain orderly, "checkerboard" spacing—ensuring they had enough room to thrive on the ancient seafloor.
A research team led by Prof. CHENG Tianhai from the Aerospace Information Research Institute of the Chinese Academy of Sciences has made a breakthrough by developing a high-resolution satellite remote sensing method to quantify global methane emissions from landfills.
A research team led by Prof. ZHENG Hairong, Prof. LIU Chengbo, and Prof. ZHENG Wei from the Shenzhen Institute of Advanced Technology has developed a linear transducer-array-based hybrid microscope (LiTA-HM) that enables simultaneous, dynamic, high-resolution imaging of neuronal activity and microvascular behavior across the entire cortex of awake mice.
A research team from the Ningbo Institute of Materials Technology and Engineering of the Chinese Academy of Sciences has developed a new method to enhance the efficiency of dynamics modeling for industrial robots, tackling long-standing bottlenecks in real-time torque computation.
A research team led by Prof. SUN Youwen from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences has developed two innovative artificial intelligence systems to enhance the safety and efficiency of fusion energy experiments.
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