Communications in Transportation Research (COMMTR), ranked #1 in its field with an Impact Factor of 14.5, transitions from Elsevier to Tsinghua University Press starting Volume 6 (2026). The journal will be published fully on the SciOpen platform, enhancing global visibility, supporting open science, and offering a seamless submission and publishing experience.

A comprehensive perspective article, authored by over 40 experts across China, delineates this trajectory, presenting an integrated roadmap that intertwines standardization, pioneering research, personalized health management, and industrial innovation.

Journal of Intelligent and Connected Vehicles (JICV), China’s first fully open-access English journal in its field, will transition from IEEE to Tsinghua University Press starting with Volume 9 (2026). The journal will be published on the SciOpen platform, reinforcing its commitment to open science and global scholarly exchange.

Durotomy frequently results in cerebrospinal fluid leakage, leading to serious secondary complications. Tissue adhesives have become a popular alternative to sutures for achieving rapid, watertight sealing of dural tears. However, current materials cause excessive swelling and unwanted tissue adhesion. Now, researchers have developed an innovative monolithic Janus patch using a simple method that enables rapid sealing of dural tears through low-energy visible-light activation, while exhibiting minimal swelling (reduced mass effect) and excellent biocompatibility.

Humanized mouse models are vital for studying human gene function, but fully replacing mouse genes with complete human sequences has been technically challenging. Researchers developed a streamlined two-step CRISPR method that inserts very large human genomic regions into mouse embryonic stem cells. The resulting mice showed human-like splicing, tissue-specific expression, and normal biological functions. The approach also supports adding disease-related mutations, offering a versatile platform for creating accurate, physiologically relevant humanized models.

Photodetectors can convert light energy into electrical signals, so are widely used in photovoltaics, photon counting, monitoring, and imaging. Photodetectors are easy to prepare high-resolution photochips because of their small size unit integration. However, these photodetector units often exhibit poor photoelectric performance due to material defects and inadequate structures, which greatly limit the functions of devices. Designing modification strategies and micro-/nanostructures can compensate for defects, adjust the bandgap, and develop novel quantum structures, which consequently optimize photovoltaic units and revolutionize optoelectronic devices. Here, this paper aims to comprehensively elaborate on the surface/interface engineering scheme of micro-/nano-photodetectors. It starts from the fundamentals of photodetectors, such as principles, types, and parameters, and describes the influence of material selection, manufacturing techniques, and post-processing. Then, we analyse in detail the great influence of surface/interface engineering on the performance of photovoltaic devices, including surface/interface modification and micro-/nanostructural design. Finally, the applications and prospects of optoelectronic devices in various fields such as miniaturization of electronic devices, robotics, and human–computer interaction are shown.

On 24 October 2025 at SBSTTA-27 in Panama City, CO-OP4CBD together with Biodiversa+ co-hosted a side event highlighting the vital role of knowledge holders in strengthening the science–policy interface for the implementation of the Kunming-Montreal Global Biodiversity Framework. The session showcased capacity-building initiatives and presented a preview of a jointly developed UN CBD Guide.

Can robots grasp diverse objects adaptively like humans? Published in National Science Review, researchers from Tsinghua University reports a human-taught sensory-control synergy approach that transfers human grasping experience to robots. Emulating brain’s neural cognition, multimodal tactile signals captured with tactile glove are encoded into semantic grasping states, then converted into grasping actions with experience-based fuzzy controller. The approach enables robots dexterously grasping like humans.