The study reveals a new regulatory mechanism controlling the biosynthesis of tanshinones and phenolic acids in Salvia miltiorrhiza (Danshen), a key herb in traditional Chinese medicine. Researchers identified SmCSN5, a subunit of the COP9 signalosome complex, as a stabilizing partner of the transcription factor SmMYB36, which simultaneously promotes tanshinone synthesis and represses phenolic acid formation. SmCSN5 prevents SmMYB36 degradation through the ubiquitin–proteasome pathway and enhances its transcriptional activity under methyl jasmonate induction. This work uncovers a post-translational control layer coordinating secondary metabolism in medicinal plants, providing new insights for metabolic engineering to selectively enhance pharmacologically active diterpenoid compounds.

Wearable ultrasound devices represent a transformative advancement in therapeutic applications, offering noninvasive, continuous, and targeted treatment for deep tissues. These systems leverage flexible materials (e.g., piezoelectric composites, biodegradable polymers) and conformable designs to enable stable integration with dynamic anatomical surfaces. Key innovations include ultrasound-enhanced drug delivery through cavitation-mediated transdermal penetration, accelerated tissue regeneration via mechanical and electrical stimulation, and precise neuromodulation using focused acoustic waves. Recent developments demonstrate wireless operation, real-time monitoring, and closed-loop therapy, facilitated by energy-efficient transducers and AI-driven adaptive control. Despite progress, challenges persist in material durability, clinical validation, and scalable manufacturing. Future directions highlight the integration of nanomaterials, 3D-printed architectures, and multimodal sensing for personalized medicine. This technology holds significant potential to redefine chronic disease management, postoperative recovery, and neurorehabilitation, bridging the gap between clinical and home-based care.

New findings underscore the importance of regular social interactions in life, shedding light on the strong link between loneliness and sustained social isolation to memory decline and conditions such as dementia, and why social and memory impairments often co-occur in psychiatric disorders.

Recurrent spontaneous abortion (RSA) is a complex, multifactorial condition that presents significant diagnostic challenges. Current clinical guidelines are often inadequate for idiopathic cases or emerging biomarkers, and artificial intelligence (AI) models struggle to integrate multimodal data.

To address these issues, this research developed RSA-KG, a graph-based, RAG-enhanced AI knowledge graph. The system synthesizes multimodal clinical data by integrating 5 international RSA guidelines, utilizing natural language processing (NLP) and multimodal models for data processing.

Evaluations demonstrated that Large Language Models (LLMs) enhanced by RSA-KG significantly outperformed both naive retrieval-augmented generation (RAG) and raw models in diagnostic accuracy. Furthermore, reproductive specialists rated the outputs from the RSA-KG system more favorably than those from raw models or other medical LLMs. RSA-KG represents a novel approach to RSA management, overcoming the limitations of traditional AI by modeling systemic interactions and integrating real-time evidence.