Traditional Chinese medicine (TCM) features complex compatibility mechanisms involving multi-component, multi-target, and multi-pathway interactions. This study presents an interpretable graph artificial intelligence (GraphAI) framework to quantify such mechanisms in Chinese herbal formulas (CHFs). A multidimensional TCM knowledge graph (TCM-MKG; https://zenodo.org/records/13763953) was constructed, integrating seven standardized modules: TCM terminology, Chinese patent medicines (CPMs), Chinese herbal pieces (CHPs), pharmacognostic origins (POs), chemical compounds, biological targets, and diseases. A neighbor-diffusion strategy was used to address the sparsity of compound-target associations, increasing target coverage from 12.0% to 98.7%. Graph neural networks (GNNs) with attention mechanisms were applied to 6,080 CHFs, modeled as graphs with CHPs as nodes. To embed domain-specific semantics, virtual nodes medicinal properties, i.e., therapeutic nature, flavor, and meridian tropism, were introduced, enabling interpretable modeling of inter-CHP relationships. The model quantitatively captured classical compatibility roles such as "monarch-minister-assistant-guide," and uncovered TCM etiological types derived from diagnostic and efficacy patterns. Model validation using 215 CHFs used for coronavirus disease 2019 (COVID-19) management highlighted Radix Astragali-Rhizoma Phragmitis as a high-attention herb pair. Mass spectrometry (MS) and target prediction identified three active compounds, i.e., methylinissolin-3-O-glucoside, corydalin, and pingbeinine, which converge on pathways such as neuroactive ligand-receptor interaction, xenobiotic response, and neuronal function, supporting their neuroimmune and detoxification potential. Given their high safety and dietary compatibility, this herb pair may offer therapeutic value for managing long COVID-19. All data and code are openly available (https://github.com/ZENGJingqi/GraphAI-for-TCM), providing a scalable and interpretable platform for TCM mechanism research and discovery of bioactive herbal constituents.

Although the eradication of Helicobacter pylori is critical for preventing gastric cancer, current therapies often overlook the restoration of the gastric microenvironment, leading to a prevalence of delayed tissue healing and dysbiosis. Consequently, many patients remain in a persistent pathological state despite successful H. pylori clearance, presenting a major bottleneck in clinical treatment. This review summarizes recent advancements in gastric-targeted drug delivery systems, illustrating the evolution from a singular antibacterial approach to an integrated sequential strategy encompassing clearance, repair, and homeostasis reconstruction. We examine smart gastro-retentive and nanodelivery systems designed to overcome physiological barriers, highlighting formulations that extend gastric residence time and maintain local drug concentrations above the Minimum Inhibitory Concentration for prolonged periods. Furthermore, we discuss spatiotemporally controllable biomaterials, such as Janus hydrogels and ROS-responsive carriers. These systems demonstrate distinct pH-dependent release kinetics and high stability in simulated gastric fluids, effectively preserving bioactive payloads to modulate the immune microenvironment. By facilitating the transition from pro-inflammatory to anti-inflammatory phenotypes, these biomaterials support epithelial regeneration. The review concludes with an analysis of postbiotics and the proposed holistic strategy, offering a promising therapeutic framework for mitigating the inflammation-to-cancer transition and promoting gastric health remodeling.

Osteoporosis and its associated fractures affect nearly one-fifth of the global population, becoming a significant public health concern. While medical interventions can reduce these risks, Dual-energy X-ray Absorptiometry (DXA), the primary screening method, is limited due to its high cost, need for professional operation, and radiation exposure risks. However, in our Bioelectrical Impedance Analysis (BIA) conducted on 152,449 Chinese residents, we identified two distinct Muscle-to-Bone Mass Ratio (MBR) subgroups in both male and female elderly populations. The MBR range for males is 12.5-15.5 and 16.5-17.8; for females, it’s 11.2-15.2 and 16.5-18.2, with 16 being a significant threshold. Individuals with an MBR value exceeding 16 exhibit pronounced features of osteoporosis and an increased risk of fractures. For instance, the Bone Mineral Content (BMC) in males decreased by 19.18% (95%CI, 18.65%-19.73%), and in females by 29.84% (95%CI, 29.31%-30.36%). These individuals also showed lower body weight and BMI values. Females also displayed shorter stature and a higher body fat percentage, both indicators associated with osteoporosis. In contrast to the traditional Bone Mineral Density (BMD) T-score, the MBR sheds light on a specific physiological state in the elderly. In this condition, their risk of fractures significantly increases. This new understanding of osteoporosis suggests that we should not solely rely on the simple quantification of BMD. Furthermore, BIA measurements taken with domestic scales make MBR a safer, more efficient, and economical screening tool. This enables long-term MBR monitoring at home, offering continuous feedback for osteoporosis and fracture prevention, surpassing the limitations of DXA technology.