This paper outlines the development of artificial intelligence （AI） and its applications in traditional Chinese medicine （TCM） research， and elucidates the roles and advantages of large language models， knowledge graphs， and natural language processing in advancing syndrome identification， prescription generation， and mechanism exploration. Using spleen-stomach diseases as an example， it demonstrates the empowering effects of AI in classical literature mining， precise clinical syndrome differentiation， efficacy and safety prediction， and intelligent education， highlighting an upgraded research paradigm that evolves from data-driven and knowledge-driven approaches to intelligence-driven models. To address challenges related to privacy protection and regulatory compliance in cross-institutional data collaboration， a "trusted federated evidence-based analysis platform for TCM spleen-stomach diseases" is proposed， integrating blockchain-based smart contracts， federated learning， and secure multi-party computation. The deep integration of AI with privacy-preserving computing is reshaping research and clinical practice in TCM spleen-stomach diseases， providing feasible pathways and a technical framework for building a high-quality， trustworthy TCM big-data ecosystem and achieving precision syndrome differentiation.

As a distinctive resource of Chinese civilization， traditional Chinese medicine （TCM） technology transfer faces significant opportunities under the background of digital and intelligent transformation， while also being constrained by unique challenges such as the complexity of its theoretical system， lengthy industrial chains， and multidimensional policy restrictions， resulting in a "high-value-high-threshold" paradox. At present， TCM technology transfer is deeply trapped in a "threefold reluctance" dilemma， i.e.， unwillingness to transfer， inability to transfer， and lack of capacity to transfer. Specifically， the disconnection between scientific research evaluation systems and market demand leads to low conversion rates of research achievements， unclear ownership and compliance risks suppress innovation incentives， and the absence of professional services intensifies supply-demand mismatches. This article systematically analyzes the specific characteristics of TCM technology transfer and proposes a breakthrough pathway centered on full-chain digital and intelligent transformation. By integrating technologies such as intelligent sorting systems， blockchain-based traceability， and AI diagnostic models， the TCM ecosystem spanning "cultivation-production-service" can be reconstructed. In terms of standardization， promoting the progression from "experience-based data conversion" to "data standardization" and further to "intelligent standardization" is advocated to resolve quality control challenges. For example， a "three-no-one-full" certification system can strengthen quality trust. Policy coordination should focus on optimizing mechanisms for the transformation of scientific and technological achievements， while exploring intellectual property securitization and risk-sharing models to stimulate research momentum. In terms of internationalization， reliance on the Belt and Road Initiative platform to promote the export of geo-authentic medicinal material brands and standards is recommended to build a dual-driven model of "technology plus culture". Looking ahead， through the construction of national-level databases， the cultivation of interdisciplinary talent， and the mutual recognition of international standards， a new paradigm of "scientific intelligent manufacturing" can be formed， providing systematic solutions for the modernization of TCM and global health governance.

Objective: To compare the consistency between bioelectrical impedance analysis (BIA) and dual energy X ray absorptiometry (DXA) in measuring body composition among Tibetan children and adolescents and to explore the applicability of BIA in plateau region, so as to provide scientific and convenient body composition measurement support among children and adolescents. Methods: From May to June, 2022, a total of 344 Tibetan children and adolescents aged 6-17 years were selected from Golmud Municipal National Middle School and Changjiangyuan Nationality Primary School in Qinghai Province by cluster sampling method, and their fat mass, fat mass percentage and lean mass were measured by DXA and BIA. The consistency and correlation between the two methods were assessed by using the Wilcoxon rank-sum test, Spearman correlation analysis, intraclass correlation coefficient (ICC), and Bland-Altman analysis. Results: DXA measured fat mass and fat mass percentage were significantly higher than those obtained by BIA (6-12 years old: Z =9.91, 11.28; 13-17 years old: Z =9.02, 10.21), while lean mass and lean mass percentage were significantly lower than BIA results (6-12 years old: Z =-11.60, -11.30; 13-17 years old: Z =-10.77, -10.36) (all P < 0.05 ). The two methods showed strong correlations in fat mass and lean mass (all r >0.80, all ICC >0.90), but exhibited poor agreement in fat mass percentage and lean mass percentage (6-12 years old: Lin s CCC =0.64, 0.41; 13-17 years old: Lin s CCC = 0.79 , 0.35). Bland-Altman analysis showed that the difference between the two methods was negatively correlated with the average value in FM%(6-12 years old: r =-0.75, 13-17 years old: r =-0.79, both P <0.01). Conclusion BIA and DXA show high consistency in measuring body fat mass and lean body mass in Tibetan children and adolescents, although some bias is still present in certain individuals.

RNA modifications constitute a crucial class of post-transcriptional chemical alterations that profoundly influence RNA stability and translational efficiency, thereby shaping cellular protein expression profiles. These diverse chemical marks are ubiquitously involved in key biological processes, including cell proliferation, differentiation, apoptosis, and metastatic potential, and they exert precise regulatory control over these functions. A major advance in the field is the recognition that RNA modifications do not act in isolation. Instead, they participate in complex, dynamic interactions—through synergistic enhancement, antagonism, competitive binding, and functional crosstalk—forming what is now termed the “RNA modification interactome” or “RNA modification interaction network.” The formation and functional operation of this interactome rely on a multilayered regulatory framework orchestrated by RNA-modifying enzymes—commonly referred to as “writers,” “erasers,” and “readers.” These enzymes exhibit hierarchical organization within signaling cascades, often functioning in upstream-downstream sequences and converging at critical regulatory nodes. Their integration is further mediated through shared regulatory elements or the assembly into multi-enzyme complexes. This intricate enzymatic network directly governs and shapes the interdependent relationships among various RNA modifications. This review systematically elucidates the molecular mechanisms underlying both direct and indirect interactions between RNA modifications. Building upon this foundation, we introduce novel quantitative assessment frameworks and predictive disease models designed to leverage these interaction patterns. Importantly, studies across multiple disease contexts have identified core downstream signaling axes driven by specific constellations of interacting RNA modifications. These findings not only deepen our understanding of how RNA modification crosstalk contributes to disease initiation and progression, but also highlight its translational potential. This potential is exemplified by the discovery of diagnostic biomarkers based on interaction signatures and the development of therapeutic strategies targeting pathogenic modification networks. Together, these insights provide a conceptual framework for understanding the dynamic and multidimensional regulatory roles of RNA modifications in cellular systems. In conclusion, the emerging concept of RNA modification crosstalk reveals the extraordinary complexity of post-transcriptional regulation and opens new research avenues. It offers critical insights into the central question of how RNA-modifying enzymes achieve substrate specificity—determining which nucleotides within specific RNA transcripts are selectively modified during defined developmental or pathological stages. Decoding these specificity determinants, shaped in large part by the modification interactome, is essential for fully understanding the biological and pathological significance of the epitranscriptome.

Objective To analyze the clinical efficacy of valve surgeries for infective endocarditis and the affecting factors, and compare the early- and long-term postoperative outcomes of different surgery approaches. Methods The patients with infective endocarditis who underwent valve replacement/valvuloplasty in our hospital from 2010 to 2022 were retrospectively collected. The clinical data of the patients were analyzed. Results A total of 343 patients were enrolled, including 197 patients with mechanical valve replacement, 62 patients with bioprosthetic valve replacement, and 84 patients with valvuloplasty. There were 238 males and 105 females with an average age of (44.2±14.8) years. Single-valve endocarditis was present in 200 (58.3%) patients, and multivalve involvement was present in 143 (41.7%) patients. Sixty (17.5%) patients had suffered thrombosis before surgery, including cerebral embolisms in 32 patients. The mean follow-up time was (60.6±43.8) months. Early mortality within one month after the surgery occurred in 17 (5.0%) patients, while later mortality occurred in 19 (5.5%) patients. Eight (2.3%) patients underwent postoperative dialysis, 13 (3.8%) patients suffered postoperative stroke, 6 patients underwent reoperation, and 3 patients suffered recurrence of infective endocarditis. Smoking (P=0.002), preoperative embolisms (P=0.001), duration of surgery (P=0.001), and postoperative dialysis (P=0.001) were risk factors for early mortality, and left ventricular ejection fraction ≥60% (P=0.022) was protective factor for early mortality. New York Heart Association classification Ⅲ-Ⅳ (P=0.010) and ≥3 valve procedures (P=0.028) were risk factors for late mortality. The rate of composite endpoint events was significantly lower in the valvuloplasty group than that in the valve replacement group. Conclusion For patients with infective endocarditis, smoking and preoperative embolisms are associated with high postoperative mortality, multiple-valve surgery is associated with a poorer prognosis, and valvuloplasty has advantages over valve replacement and should be attempted in the surgical management of patients with infective endocarditis.

INTRODUCTION: Comparison of patient health-related quality of life (HRQOL) scores to a reference group is needed to quantify the HRQOL impact of disease or treatment. This study aimed to establish population norms for 2 HRQOL questionnaires-EuroQol 5-dimension 5-level questionnaire (EQ-5D-5L) and European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire-Core Question-naire 30 (EORTC QLQ-C30) according to age, sex and ethnicity-and to explore relationships between the EQ-5D-5L, EORTC QLQ-C30 and sociodemographic characteristics. We used a representative sample of adult Singapore residents aged 21 years and above. METHOD: This study used data collected from a cross-sectional household survey in which 600 adult Singaporeans completed questions on sociodemo-graphic characteristics-the EQ-5D-5L and the EORTC QLQ-C30. Multiple linear regression analyses were conducted to explore associations between sociodemographic characteristics, the EQ-5D-5L scores and the EORTC QLQ-C30 scores. Regression-based population norms were computed for each subgroup using a post-stratification method. RESULTS: In multiple linear regression analysis, age was significantly associated with EQ-5D-5L index and visual analogue scale (VAS) scores, while no sociodemographic characteristics were significantly associated with EORTC QLQ-C30 summary scores. The normative EQ-5D-5L index and VAS scores decreased in adults aged 65 years and above, and EQ-5D-5L index scores were slightly lower in females than males and in non-Chinese than Chinese. The normative EORTC QLQ-C30 summary scores were slightly higher in Chinese than in the non-Chinese group and in the 45-64 age group than other age groups. CONCLUSION This study provides population norms for the EQ-5D-5L and EORTC QLQ-C30 for the general adult population in Singapore. Future studies of patient populations in Singapore using EQ-5D-5L or QLQ-C30 can use these normative data to interpret the HRQOL data collected.
Humans ; Quality of Life ; Singapore ; Male ; Female ; Middle Aged ; Adult ; Cross-Sectional Studies ; Aged ; Surveys and Questionnaires ; Young Adult ; Health Status ; Age Factors ; Linear Models ; Aged, 80 and over

INTRODUCTION: An interdisciplinary panel, comprising professionals from medicine, AI and data science, law and ethics, and patient advocacy, convened to discuss key principles on regulation, implementation and evaluation of AI models in healthcare for Singapore. METHOD: The panel considered 14 statements split across 4 themes: "The Role and Scope of Regulatory Entities," "Regulatory Processes," "Pre-Approval Evaluation of AI Models" and "Medical AI in Practice". Moderated by a thematic representative, the panel deliberated on each statement and modified it until a majority agreement threshold is met. The roundtable meeting was convened in Singapore on 1 July 2024. While the statements reflect local perspectives, they may serve as a reference for other countries navigating similar challenges in AI governance in healthcare. RESULTS: Balanced testing approaches, differentiated regulatory standards for autonomous and assistive AI, and context-sensitive requirements are essential in regulating AI models in healthcare. A hybrid approach-integrating global standards with local needs to ensure AI comple-ments human decision-making and enhances clinical expertise-was recommended. Additionally, the need for patient involvement at multiple levels was underscored. There are active ongoing efforts towards development and refinement of AI governance guidelines and frameworks balancing between regulation and freedom. The statements defined therein provide guidance on how prevailing values and viewpoints can streamline AI implementation into healthcare. CONCLUSION This roundtable discussion is among the first in Singapore to develop a structured set of state-ments tailored for the regulation, implementation and evaluation of AI models in healthcare, drawing on interdisciplinary expertise from medicine, AI, data science, law, ethics and patient advocacy.
Singapore ; Humans ; Artificial Intelligence/standards* ; Delivery of Health Care/organization & administration*

BACKGROUND: Chronic kidney disease (CKD) is associated with common pathophysiological processes, such as inflammation and fibrosis, in both the heart and the kidney. However, the underlying molecular mechanisms that drive these processes are not yet fully understood. Therefore, this study focused on the molecular mechanism of heart and kidney injury in CKD. METHODS: We generated an microRNA (miR)-26a knockout (KO) mouse model to investigate the role of miR-26a in angiotensin (Ang)-II-induced cardiac and renal injury. We performed Ang-II modeling in wild type (WT) mice and miR-26a KO mice, with six mice in each group. In addition, Ang-II-treated AC16 cells and HK2 cells were used as in vitro models of cardiac and renal injury in the context of CKD. Histological staining, immunohistochemistry, quantitative real-time polymerase chain reaction (PCR), and Western blotting were applied to study the regulation of miR-26a on Ang-II-induced cardiac and renal injury. Immunofluorescence reporter assays were used to detect downstream genes of miR-26a, and immunoprecipitation was employed to identify the interacting protein of LIM and senescent cell antigen-like domain 1 (LIMS1). We also used an adeno-associated virus (AAV) to supplement LIMS1 and explored the specific regulatory mechanism of miR-26a on Ang-II-induced cardiac and renal injury. Dunnett's multiple comparison and t -test were used to analyze the data. RESULTS: Compared with the control mice, miR-26a expression was significantly downregulated in both the kidney and the heart after Ang-II infusion. Our study identified LIMS1 as a novel target gene of miR-26a in both heart and kidney tissues. Downregulation of miR-26a activated the LIMS1/integrin-linked kinase (ILK) signaling pathway in the heart and kidney, which represents a common molecular mechanism underlying inflammation and fibrosis in heart and kidney tissues during CKD. Furthermore, knockout of miR-26a worsened inflammation and fibrosis in the heart and kidney by inhibiting the LIMS1/ILK signaling pathway; on the contrary, supplementation with exogenous miR-26a reversed all these changes. CONCLUSIONS Our findings suggest that miR-26a could be a promising therapeutic target for the treatment of cardiorenal injury in CKD. This is attributed to its ability to regulate the LIMS1/ILK signaling pathway, which represents a common molecular mechanism in both heart and kidney tissues.
Animals ; MicroRNAs/metabolism* ; Angiotensin II/toxicity* ; Mice ; Renal Insufficiency, Chronic/chemically induced* ; Mice, Knockout ; Disease Models, Animal ; Male ; Signal Transduction/genetics* ; LIM Domain Proteins/genetics* ; Mice, Inbred C57BL ; Cell Line ; Humans

This study aims to explore whether Naoxintong Capsules improve multiple cerebral infarctions and myocardial injury via promoting angiogenesis, thereby exerting a simultaneous treatment effect on both the brain and heart. Male SD rats were randomly divided into six groups: sham-operated group, model group, high-dose, medium-dose, and low-dose groups of Naoxintong Capsules(440, 220, and 110 mg·kg~(-1)), and nimodipine group(10.8 mg·kg~(-1)). Rat models of multiple cerebral infarctions were established by injecting autologous thrombus, and samples were collected and tested seven days after modeling. Evaluations included multiple cerebral infarction model assessments, neurological function scores, grip strength tests, and rotarod tests, so as to evaluate neuromotor functions. Morphological structures of brain and heart tissue were observed using hematoxylin-eosin(HE) staining, Nissl staining, and Masson staining. Network pharmacology was employed to screen the mechanisms of Naoxintong Capsules in improving multiple cerebral infarctions and myocardial injury. Neuronal and myocardial cell ultrastructures were observed using transmission electron microscopy. Apoptosis rate in brain neuronal cells was detected by TdT-mediated dUTP nick end labeling(TUNEL) staining, and reactive oxygen species(ROS) levels in myocardial cells were measured. Immunofluorescence was used to detect the expression of platelet endothelial cell adhesion molecule-1(CD31), antigen identified by monoclonal antibody Ki67(Ki67), hematopoietic progenitor cell antigen CD34(CD34), and hypoxia inducible factor-1α(HIF-1α) in brain and myocardial tissue. Western blot, and real-time quantitative polymerase chain reaction(RT-qPCR) were used to detect the expression of HIF-1α, vascular endothelial growth factor(VEGF), vascular endothelial growth factor receptor 2(VEGFR2), sarcoma(Src), basic fibroblast growth factor(bFGF), angiopoietin-1(Ang-1), and TEK receptor tyrosine kinase(Tie-2). Compared with the model group, the medium-dose group of Naoxintong Capsules showed significantly lower neurological function scores, increased grip strength, and prolonged time on the rotarod. Pathological damage in brain and heart tissue was reduced, with increased and more orderly arranged mitochondria in neurons and cardiomyocytes. Apoptosis in brain neuronal cells was decreased, and ROS levels in cardiomyocytes were reduced. The microvascular density and endothelial cells of new blood vessels in brain and heart tissue increased, with increased overlapping regions of CD31 and Ki67 expression. The relative protein and mRNA expression levels of HIF-1α, VEGF, VEGFR2, Src, Ang-1, Tie-2, and bFGF were elevated in brain tissue and myocardial tissue. Naoxintong Capsules may improve multiple cerebral infarctions and myocardial injury by mediating HIF-1α/VEGF expression to promote angiogenesis.
Animals ; Male ; Drugs, Chinese Herbal/administration & dosage* ; Rats, Sprague-Dawley ; Rats ; Cerebral Infarction/genetics* ; Hypoxia-Inducible Factor 1, alpha Subunit/genetics* ; Vascular Endothelial Growth Factor A/genetics* ; Capsules ; Signal Transduction/drug effects* ; Humans ; Brain/metabolism* ; Myocardium/metabolism* ; Apoptosis/drug effects*

The chemical constituents were systematically separated from the roots of Berberis polyantha by various chromatographic methods, including silica gel column chromatography, HP20 column chromatography, polyamide column chromatography, reversed-phase C_(18) column chromatography, and preparative high-performance liquid chromatography. The structures of the compounds were identified by physicochemical properties and spectroscopic techniques(1D NMR, 2D NMR, UV, MS, and CD). Four phenylpropanoids were isolated from the methanol extract of the roots of B. polyantha, and they were identified as(2R)-1-(4-hydroxy-3,5-dimethoxyphenyl)-1-propanone-O-β-D-glucopyranoside(1), methyl 4-hydroxy-3,5-dimethoxybenzoate(2),(+)-syringaresinol(3), and syringaresinol-4-O-β-D-glucopyranoside(4). Compound 1 was a new compound, and other compounds were isolated from this plant for the first time. The anti-inflammatory activity of these compounds was evaluated based on the release of nitric oxide(NO) in the culture of lipopolysaccharide(LPS)-induced RAW264.7 macrophages. At a concentration of 10 μmol·L~(-1), all the four compounds inhibited the LPS-induced release of NO in RAW264.7 cells, demonstrating potential anti-inflammatory properties.
Plant Roots/chemistry* ; Animals ; Mice ; Berberis/chemistry* ; RAW 264.7 Cells ; Macrophages/immunology* ; Drugs, Chinese Herbal/isolation & purification* ; Nitric Oxide/metabolism* ; Molecular Structure ; Anti-Inflammatory Agents/isolation & purification*