Researchers conducted comprehensive safety assessments on triazine UV filters ethylhexyl triazone (EHT) and diethylhexyl butamido triazone (HEB). Through bacterial reverse mutation, chromosomal aberration, micronucleus assays, and 3T3 phototoxicity tests, both compounds showed no genotoxic or phototoxic effects even at high concentrations. These findings support the safety of EHT/HEB for topical use in sunscreens, addressing regulatory concerns.

A thermal management scheme is designed in this paper that can be applied to 51.2 Tbit/s co-packaged optics (CPO), which successfully solved the heat dissipation difficulties of high-bandwidth co-packaged optics.

Research has revealed energy back transfer in Yb³⁺/Er³⁺-doped materials under 980 nm excitation, which is crucial for optimizing the excitation power point for optical temperature measurements.

To deepen international academic collaboration and enhance the global impact of the journal, Yuan Qing, Party Secretary of the School of Medical Technology at Shanghai Jiao Tong University School of Medicine; Dai Jing, Deputy Director of the Department of Laboratory Medicine at Ruijin Hospital; and Wang Erliang, Director of the Editorial Office of LabMed Discovery (LMD), recently traveled to Europe for a series of academic exchanges. Centered on the core goals of "expanding cooperation, absorbing high-quality manuscript sources, and promoting scientific research projects", the delegation achieved significant outcomes through participation in international conferences, visits to leading institutions, and in-depth academic dialogues—injecting fresh momentum into the journal’s international development.

As urban drone logistics becomes a practical reality, balancing economic cost, ground safety risk, and noise impact poses a systemic challenge. A recent study proposes a novel approach to design urban low-altitude logistics networks, incorporating noise constraints into a multi-objective optimization framework. By combining a layered network model with a dual-population co-evolutionary algorithm, the research provides a new direction for the low-altitude logistics infrastructure of future cities.

Solid polymer electrolytes (SPEs) have garnered considerable interest in the field of lithium metal batteries (LMBs) owing to their exceptional mechanical strength, excellent designability, and heightened safety characteristics. However, their inherently low ion transport efficiency poses a major challenge for their application in LMBs. To address this issue, covalent organic framework (COF) with their ordered ion transport channels, chemical stability, large specific surface area, and designable multifunctional sites has shown promising potential to enhance lithium-ion conduction. Here, we prepared an anionic COF, TpPa-COOLi, which can catalyze the ring-opening copolymerization of cyclic lactone monomers for the in situ fabrication of SPEs. The design leverages the high specific surface area of COF to facilitate the absorption of polymerization precursor and catalyze the polymerization within the pores, forming additional COF-polymer junctions that enhance ion transport pathways. The partial exfoliation of COF achieved through these junctions improved its dispersion within the polymer matrix, preserving ion transport channels and facilitating ion transport across COF grain boundaries. By controlling variables to alter the crystallinity of TpPa-COOLi and the presence of –COOLi substituents, TpPa-COOLi with partial long-range order and –COOLi substituents exhibited superior electrochemical performance. This research demonstrates the potential in constructing high-performance SPEs for LMBs.

Joint health is critical for musculoskeletal (MSK) conditions that are affecting approximately one-third of the global population. Monitoring of joint torque can offer an important pathway for the evaluation of joint health and guided intervention. However, there is no technology that can provide the precision, effectiveness, low-resource setting, and long-term wearability to simultaneously achieve both rapid and accurate joint torque measurement to enable risk assessment of joint injury and long-term monitoring of joint rehabilitation in wider environments. Herein, we propose a piezoelectric boron nitride nanotubes (BNNTs)-based, AI-enabled wearable device for regular monitoring of joint torque. We first adopted an iterative inverse design to fabricate the wearable materials with a Poisson’s ratio precisely matched to knee biomechanics. A highly sensitive piezoelectric film was constructed based on BNNTs and polydimethylsiloxane and applied to precisely capture the knee motion, while concurrently realizing self-sufficient energy harvesting. With the help of a lightweight on-device artificial neural network, the proposed wearable device was capable of accurately extracting targeted signals from the complex piezoelectric outputs and then effectively mapping these signals to their corresponding physical characteristics, including torque, angle, and loading. A real-time platform was constructed to demonstrate the capability of fine real-time torque estimation. This work offers a relatively low-cost wearable solution for effective, regular joint torque monitoring that can be made accessible to diverse populations in countries and regions with heterogeneous development levels, potentially producing wide-reaching global implications for joint health, MSK conditions, ageing, rehabilitation, personal health, and beyond.

A recent study investigates the contrasting patterns of symbiotic nitrogen fixation (SNF) and asymbiotic nitrogen fixation (ANF) along altitudinal gradients in subtropical forests. The research found that SNF rates declined with increasing altitude due to higher soil nitrogen availability and lower air temperatures, while ANF rates showed a hump-shaped pattern, influenced by soil properties at lower altitudes and climatic factors at higher altitudes. The study underscores the importance of distinguishing between SNF and ANF in ecological studies and Earth system models, providing valuable insights for improving global BNF estimates and refining model predictions.