A research paper by scientists at Beijing Friendship Hospital develop a systematic approach for automated ossicular-chain segmentation and measurement using ultra-high-resolution computed tomography (U-HRCT).

Enzymatic biofuel cells (EBFCs), which generate electricity through electrochemical reactions between metabolites and O₂/air, are considered a promising alternative power source for wearable and implantable bioelectronics. However, the main challenges facing EBFCs are the poor stability of enzymes and the low electron transfer efficiency between enzymes and electrodes. To enhance the efficiency of EBFCs, researchers have been focusing on the development of novel functional nanomaterials. This mini-review first introduces the working principles and types of EBFCs, highlighting the key roles of nanomaterials, such as enzyme immobilization and stabilization, promotion of electron transfer and catalytic activity. It then summarizes the recent advancements in their application in wearable and implantable devices. Finally, it explores future research direction and the potential of high-performance EBFCs for practical applications.

A study published in Frontiers in Energy by researchers from Shanghai Jiao Tong University, led by Zulipiya Shadike and Junliang Zhang, introduces a novel boron-based electrolyte additive—tris(2,2,2-trifluoroethyl) borate (TTFEB)—to enhance the cyclic stability of NMC811 cathodes. The work systematically compares TTFEB with other boron-based additives and identifies its superior ability to form a stable, LiF-rich CEI.

With climate change posing an unprecedented global challenge, the demand for environmentally friendly solvents in green chemical processes and carbon dioxide capture has surged. Ionic liquids (ILs) have emerged as promising "designer solvents" due to their negligible volatility, broad liquid temperature range, and exceptional thermal stability. However, the immense chemical space of ILs—with theoretically up to 10¹⁸ possible cation-anion combinations—has created a critical bottleneck in efficient screening and design. Traditional experimental methods are costly and time-consuming, while theoretical calculations like molecular dynamics and quantum chemistry remain computationally prohibitive for large-scale screening. This urgent need for accelerated discovery has set the stage for a transformative technological leap.

Understanding how plant architectural traits change over time is essential for improving crop breeding efficiency and production management. 

Effective hydrophobic barriers were essential for plants to survive on land, yet how these barriers became specialized across different tissues has remained unclear. 

 Undiagnosed trauma is a silent driver of chronic illness, often missed by healthcare systems. This study introduces Emotional Memory Images (EMIs) as subconscious imprints formed in overwhelming moments that continue to affect mental and physical health, offering a rapid, non-invasive method to clear them.

This article explores the potential of large language models (LLMs) in reliability systems engineering, highlighting their applications in improving industrial efficiency and flexibility. It also examines the challenges, including data deficiencies and complexity, and suggests future directions for integrating LLMs into complex engineering processes.

A new study in Engineering introduces a novel MRI technique enabling real-time, artifact-free navigation of magnetic robots. Using a multi-frequency dual-echo sequence, researchers achieved a 30-millisecond repetition time, allowing precise control and high-resolution imaging. Demonstrations in maze, phantom vessel, and in vivo trials highlight its potential for minimally invasive therapies.