Glycosylation, the process of attaching sugar chains to proteins, is emerging as a key regulator in kidney health and disease.

Cornelia de Lange syndrome (CdLS) is a developmental genetic disorder. The characteristics of CdLS remain unexplored in the Chinese population. Now, a group of researchers from the National Center for Children’s Health, China, have examined the clinical presentations, mutational profiles, and hormonal therapy responses of Chinese children with CdLS. Mutations in three genes, correlation between mutations in a development-related gene and clinical presentations, and differential responses to hormone therapy were identified in Chinese patients.

Embodied intelligence applications, such as autonomous robotics and smart transportation systems, require efficient coordination of multiple agents in dynamic environments. A critical challenge in this domain is the multi-agent pathfinding (MAPF) problem, which ensures that agents can navigate conflict-free while optimizing their paths. Conflict-based search (CBS) is a well-established two-level solver for the MAPF problem. However, as the scale of the problem expands, the computation time becomes a significant challenge for the implementation of CBS. Previous optimizations have mainly focused on reducing the number of nodes explored by the high-level or low-level solver. This paper takes a different perspective by proposing a parallel version of CBS, namely GPU-accelerated conflict-based search (GACBS), which significantly exploits the parallel computing capabilities of GPU. GACBS employs a task coordination framework to enable collaboration between the high-level and low-level solvers with lightweight synchronous operations. Moreover, GACBS leverages a parallel low-level solver, called GATSA, to efficiently find the shortest path for a single agent under constraints. Experimental results show that the proposed GACBS significantly outperforms CPU-based CBS, with the maximum speedup ratio reaching over 46.

Recently, the research team led by Prof. LI Hai at the Institute of Health and Medical Technology, the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, has developed a novel deep learning framework that significantly improves the accuracy and interpretability of detecting neurological disorders through speech. 

According to research published in Angewandte Chemie International Edition recently, a team led by Prof. HU Linhua. from Hefei Institutes of Physical Science of the Chinese Academy of Science develop a high mechanical durability hydrogel electrolyte using urea as a zincophilic solubilizer and Zn(Ac)₂ salt for its low cost and eco-friendly traits. As-prepared hydrogels can sustain 557% tensile elongation and 3.7 MPa compressive strength. In-situ polyurea solid electrolyte interphase (SEI) formed during aqueous zinc-ion batteries (AZIBs)  operation allows for stable Zn stripping/plating in a dendrite and passivation-free manner.

Recently, Prof. JIANG Changlong’s research team from the Institute of Solid State Physics, the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, used multi-emission metal organic framework hydrogel (Eu-Dy MOF gel) to construct a non-invasive wearable eye patch fluorescence sensor, combined with the color recognition function of a smartphone to analyze and monitor lysozyme in tears. 

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 (AI) systems to enhance the safety and efficiency of fusion energy experiments. 

A research team led by Prof. SHAO Dingfu from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, 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. SHAO Dingfu at the Institute of Solid State Physics, the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, has unveiled a new mechanism for achieving strong spin polarization using antiferromagnetic metal interfaces.