East Asia's tropical cyclone risk is moving steadily north
Peer-Reviewed Publication
Updates every hour. Last Updated: 22-Oct-2026 08:16 ET (22-Oct-2026 12:16 GMT/UTC)
First report of whole virome profiling of Naemorhedus griseus, identifying diverse viruses across multiple organ tissues. Identification and characterization of multiple mammalian viruses: including parvoviruses, picobirnaviruses, phenuivirus. Furthermore, this study provides insights into genetic diversity of Naemorhedus griseus-borne viruses and their cross-species transmission dynamics.
Even after receiving guideline‑directed treatment for acute coronary syndrome, many patients face persistent residual cardiovascular risk and repeated ischemic events. This narrative review published in Cardiology Discovery synthesizes recent clinical evidence to build a practical management framework for clinicians caring for acute coronary syndrome survivors. The authors organize residual risks into non-culprit lesion instability, lipid‑related, inflammatory, thrombotic and modifiable lifestyle‑driven categories, and summarize available pharmacologic and non‑pharmacologic interventions for each risk domain. The work supports personalized risk assessment to guide tailored secondary prevention plans. As a narrative review, it does not generate original clinical trial data and requires real‑world studies to validate the proposed clinical workflows.
The nightly closure or downward folding of leaves, a process known as sleep movement or nyctinasty, is a widespread phenomenon in legumes that helps optimize photosynthesis, conserve water, and reduce pathogen susceptibility. Although the physical process has been well characterized, the molecular regulation of nyctinasty remains poorly understood. Here, we combined temporal transcriptome profiling, photoperiod manipulation, and tissue-specific gene expression analysis to dissect the regulatory network in peanut (Arachis hypogaea) during nyctinastic leaf movement. Under normal light/dark cycles, leaves displayed distinct nyctinastic behavior, which was suppressed under continuous light, underscoring the importance of photoperiod for this process. Transcriptome analysis identified conserved light- and circadian-related genes exhibiting rhythmic expression patterns. Key candidates included light-responsive SWEET and aquaporin genes with distinct tissue-specific expression patterns, along with a pulvinus-enriched MYB transcription factor gene. Promoter-binding and reporter assays supported transcriptional links between circadian/light-signaling components and these candidate downstream genes. Together, these findings support a working model in which photoreceptors and the circadian clock coordinate the expression of transporter and regulatory genes, which may contribute to nyctinastic leaf movement in peanut. These findings provide a molecular framework for future functional investigations of nyctinasty in legumes.
Understanding electrochemical hydrogen evolution reaction (HER) mechanisms requires precise identification of key intermediates (H*, OH*, and H2O*). While in situ single-crystal studies have provided foundational mechanistic insights into interfacial dynamics and intermediate behavior during the HER, extending these findings to structurally complex nano-catalysts remains challenging. Recent advances in in situ characterization techniques have enabled real-time observation of reaction intermediates, yet a systematic understanding across diverse catalyst architectures remains incomplete. This review assesses HER intermediate research, bridging the gap from model single-crystals to nano-catalysts by: (i) discussing methods for intermediate identification and their roles in elucidating HER mechanisms, (ii) summarizing single-crystal surface modification strategies bridging single-crystal model and nano-catalyst studies, and (iii) highlighting current challenges and proposing future directions for catalyst design and intermediate characterization, offering valuable perspectives for developing advanced HER electrocatalysts.
The research team from National University of Defense Technology systematically described the memory efficiency issues in the training process of large language models (LLMs) with Transformer architecture for scientific fields. As the scale of models continues to expand, memory requirements have become a key bottleneck restricting their applications in scientific fields such as biology, medicine, chemistry, and meteorology. The article systematically reviewed memory-efficient pre-training technologies at the algorithm level, system level, and software-hardware collaborative optimization, and combined with the AlphaFold 2 case, demonstrated how customized memory optimization methods can reduce storage overhead while maintaining prediction accuracy.
Coronary artery disease remains the top global cause of death, yet standard angiography cannot visualize dangerous artery plaque, creating gaps for guiding percutaneous coronary intervention. This narrative review synthesizes 10 years of human studies, clinical trials and consensus documents covering established and emerging intravascular imaging plus computational tools. Hybrid catheter systems have completed first‑in‑human testing, while artificial‑intelligence plaque analysis delivers diagnostic accuracy comparable to expert readers. These technologies enable combined anatomical, compositional and functional vessel assessment, though broad clinical roll‑out still requires standardized validation and streamlined workflow integration.