In a paper published in Science Bulletin, Chinese scientists have discovered that a PRA (prenylated Rab acceptor) protein, PIBP4 (PigmR-INTERACTING and BLAST RESISTANCE PROTEIN 4), interacts with both the NLR protein PigmR and the active form of the Rab GTPase, OsRab5a, thereby loads a portion of PigmR on trafficking vesicles that target to plasma membrane microdomains. Microdomain-localized PigmR interacts with and activates the small GTPase OsRac1, which triggers reactive oxygen species signalling and hypersensitive response, leading to immune responses against blast infection. This research discovers a previously unknown mechanism that deploys a PRA-Rab protein delivering hub to ensure ETI, linking the membrane trafficking machinery with NLR function and immune activation in plants.

Intercalation has been considered as an effective method to explore innovative two-dimensional (2D) materials. But the question remains: How does intercalation concentration affect the atomic structure and properties of two-dimensional materials? And what fine-tuning of growth conditions is required to synthesize the desired intercalation phase with precision?  In National Science Review, researchers have revealed the general rule for the effect of self-intercalation ratio on the atomic arrangements, and delved into the intricate relationship between structure and properties.

In a paper published in Science Bulletin, China’s scientists presented the newest evidence of how many trees exist in China. In 2020, China had ~142.6 billion trees—equivalent to ~100 trees per person.

Scientists have developed a new class of chiral metal-organic frameworks (CMOFs) featuring exceptional stability, ultrahigh surface areas, and cost-effective synthesis. These materials show great promise in asymmetric catalysis, offering scalable solutions for industrial applications.

Professor Can Wang from Tianjin University and Professor Zhurui Shen from Nankai University have achieved significant results in their collaborative research. In this study, monolayer Ti₃C₂T_x was prepared by etching and exfoliating Ti₃AlC₂, and then TiO₂/monolayer Ti₃C₂T_x (T/mT) was synthesized. The surface functional groups enhance the hydrophilicity and surface energy, and a Schottky heterojunction is formed with TiO₂, which improves the photocatalytic activity. Meanwhile, the hybrid material can closely bind to Escherichia coli cells and has a high affinity for cell membrane proteins. Experiments show that it has a high charge separation and transfer efficiency, a strong photocurrent signal, and low impedance. In the photocatalytic reaction device, the sterilization efficiency of T/mT reaches 3.3 log in only 12.8 seconds, far exceeding that of TiO₂. The various components and chemical bonds of cells have been damaged to varying degrees by active substances. This achievement points the way for the molecular structure design of photocatalytic air disinfection technology and is of far-reaching significance for promoting the progress of air disinfection technology.

In a paper published in National Science Review, an international team of scientists presented recent advancements in bioinformatics FMs that are applied across a range of downstream tasks, including genomics, transcriptomics, proteomics, drug discovery, and single-cell analysis.

Land subsidence, a significant geological hazard caused by natural and human activities, has become increasingly complex and widespread. Peridynamics, a physical model approach, has been introduced into the land subsidence research domain by the land subsidence research team at Capital Normal University in recent years. This method describes the mechanical behavior of materials by solving spatial integral equations and can conduct integrated modeling of regional land subsidence, including ground fissures. To further improve the land subsidence modeling and simulation, the research team has proposed an innovative strategy that combines peridynamics with deep learning techniques. By integrating neural networks and Gaussian Process Regression, the team optimized boundary conditions, thus significantly improving simulation results. The findings, published in the Journal of Geo-information Science, demonstrate a substantial reduction in prediction errors, offering a promising solution for regional land subsidence modeling.