Recently, Science Bulletin published the research findings of Professors Shi Weiqun and Mei Lei from the Institute of High Energy Physics, Chinese Academy of Sciences. The study presents a viable approach for engineering acyl-type metal nodes to create oxygen-rich interior sites within MOCs, enabling the specific recognition of metal ions, including radioactive contaminants, while preserving the structural integrity of the MOCs. 

A recently published paper in Science China Life Sciences reports an interdisciplinary study utilizing single-cell sequencing data analysis to identify GPCRs involved in the regulation of adipogenesis. Through both in vitro and in vivo validation, the authors find that ADGRD1 promotes adipogenesis, whereas GPR39 inhibits this process.

A new study published in National Science Review examines China's trends in primary particulate matter (PM) emissions from 1960 to 2019, revealing significant transformations in PM size fractions and carbonaceous compositions. Despite an overall decline in emissions, finer particles like PM2.5 and carbonaceous fractions (e.g., black carbon and organic carbon) have increased. These findings underscore the critical role of technological advancements and policy-driven measures in shaping the trajectory of air quality improvements.

A groundbreaking study by researchers from the University of Namur, Belgium introduces a novel, contactless method for identifying animal species used in historical parchment manuscripts, an essential aspect of cultural heritage studies. Traditionally, species identification has been performed using slightly invasive methods, but this innovative classification model instead uses reflectance spectrophotometry, covering the ultraviolet, visible and near-infrared spectra, combined with machine learning for data analysis. This research was published Oct. 17 in Intelligent Computing, a Science Partner Journal, in an article titled “Animal Species Identification in Historical Parchments by Continuous Wavelet Transform–Convolutional Neural Network Classifier Applied to Ultraviolet–Visible–Near-Infrared Spectroscopic Data.”

Young rabbits with cystic fibrosis (CF) exhibit significant pancreatic endocrine dysfunction, including smaller islet sizes and impaired glucose metabolism. This innovative model highlights the potential for rabbits to bridge gaps in understanding CF-related diabetes and other pancreatic conditions.