The ability to control the electrode interfaces in an electrochemical energy storage system is essential for achieving the desired electrochemical performance. However, achieving this ability requires an in-depth understanding of the detailed interfacial nanostructures of the electrode under electrochemical operating conditions. In-situ transmission electron microscopy (TEM) is one of the most powerful techniques for revealing electrochemical energy storage mechanisms with high spatiotemporal resolution and high sensitivity in complex electrochemical environments. These attributes play a unique role in understanding how ion transport inside electrode nanomaterials and across interfaces under the dynamic conditions within working batteries. This review aims to gain an in-depth insight into the latest developments of in-situ TEM imaging techniques for probing the interfacial nanostructures of electrochemical energy storage systems, including atomic-scale structural imaging, strain field imaging, electron holography, and integrated differential phase contrast imaging. Significant examples will be described to highlight the fundamental understanding of atomic-scale and nanoscale mechanisms from employing state-of-the-art imaging techniques to visualize structural evolution, ionic valence state changes, and strain mapping, ion transport dynamics. The review concludes by providing a perspective discussion of future directions of the development and application of in-situ TEM techniques in the field of electrochemical energy storage systems.

Progesterone (P4) is the optimal agent for luteal support in assisted reproductive technologies. Despite the availability of various formulations, the impacts of P4 treatment administered through different routes on offspring growth remain unevaluated. This study aimed to investigate and compare the effects of P4 administration through three different routes in pregnant rats during the teratogenesis-sensitive period on fertility outcomes and the behavior, plasma P4 and pregnenolone levels, and alterations in gut microbiota in the filial generation (F1) of offspring.

After rigorous evaluation and review, LabMed Discovery was officially included in China Open Access Journal Database (COAJ) in May 2025. This progress marks that LabMed Discovery has been officially recognized in terms of academic quality, publishing standards and open access.

In May 2025, under the review of the Polish ICI World of Journals (Copernicus Index Database), LabMed Discovery magazine was officially included in the ICI World of Journals database. This marks an important step for LabMed Discovery on the international academic stage, and is also a high recognition of the journal's long-term efforts in improving academic quality and promoting academic exchanges.

The 2025 Guangci Laboratory Medicine Innovation and Development Conference was successfully concluded at Shanghai Qingsongcheng Hotel! With the theme of "Innovation, Leadership, and Development", this conference successfully brought together nearly 100 well-known experts and scholars at home and abroad, and carried out in-depth dialogues and collisions of ideas around the cutting-edge hotspots in the field of clinical and laboratory medicine.

According to the previous studies, it has been found that long non-coding RNA H19 (lncRNA H19)-ITGB3-miR-124-3p axis can regulate cell proliferation and invasion of the ectopic endometrium, which could be the potential pathway for treating endometriosis by a key medicine. The aim of this study was to investigate the roles of metformin, aspirin, artemisinin, and berberine in regulating the expression of lncRNA H19 in ectopic endometrial stromal cells (ecESCs) and explore novel medicines for the treatment of endometriosis.

This article introduces Crack-Net, a deep learning framework that efficiently predicts crack propagation and stress–strain curves in particulate composites. It leverages implicit constraints to enhance accuracy and reduce data needs, offering a practical solution for fracture prediction in complex materials.

Discover how integrating decentralized water systems, source separation, and low-carbon technologies can transform urban water management. This comprehensive strategy aims to reduce carbon emissions while promoting resource conservation and recovery, offering a sustainable approach to meet global climate goals.

A novel real-time automated damage detection method leveraging reinforcement learning has been unveiled in a recent study published in Engineering. The research, spearheaded by Chengwen Zhang, Qing Chun, and Yijie Lin from Southeast University, China, introduces an innovative approach that significantly enhances the efficiency and accuracy of damage detection in structural health monitoring (SHM) systems, particularly for architectural heritage.