The digitization of traditional Chinese medicine (TCM) has generated vast amounts of data. However, these data are characterized by significant heterogeneity and complex semantic structures, posing substantial challenges for systematic integration and intelligent analysis, and limiting its potential for modern clinical and computational research. To address the challenges posed by the high heterogeneity and complex structure in TCM data, we designed and developed the TCM Data Hub platform, which is powered by the YiYuan large language models (LLMs). This platform aims to enhance intelligent data processing capabilities and unlock the potential for clinical application of TCM data through systematic integration and efficient utilization, thereby bridging the gap between traditional knowledge and modern computational research. This study first analyzed the heterogeneity and complexity of TCM information with respect to data types, structures, and semantics. A standardized data framework was constructed to enhance data integration and interoperability. Based on the TCM Intelligent Computing Platform of the China Academy of Chinese Medical Sciences, we trained the YiYuan LLMs to acquire domain-specific semantic understanding of TCM, thereby improving the platform’s comprehension of specialized terminology and knowledge systems. Leveraging the natural language processing capabilities of the LLMs, we developed a human-in-the-loop data processing system to enable efficient extraction, cleansing, and structured organization of TCM data. In addition, utilizing Vue and Java technologies, we developed multiple LLM-powered intelligent agents and systems, including a human-in-the-loop data processing system, as well as automated prescription mining and network pharmacology analysis agents. Task-specific agents tailored to TCM data processing were developed to enhance the model’s effectiveness in clinical knowledge discovery. System functionality and platform infrastructure were implemented using Java and Vue technologies.The TCM Data Hub platform has completed system construction and core functionality implementation. It supported integrated management and efficient access to 8 key types of TCM data: prescriptions, materia medica, ingredients, targets, diseases (Western medicine), diseases (TCM), syndromes, and therapeutic methods. The human-in-the-loop data processing system achieved an accuracy of 95.34% in structuring TCM data and supported annotation for data requiring manual labeling. The intelligent agent-driven big-data analytics module enabled 1-click, end-to-end workflows for TCM prescription mining, herb-syndrome association analysis, network pharmacology, and molecular biology research, completing a full data mining task in approximately 30 minutes. Users can interact with and manipulate data through a visual front-end interface. The system demonstrated stable performance, strong scalability, and a user-friendly experience. Empowered by the YiYuan LLMs, the TCM Data Hub platform significantly improves the accessibility, usability, and intelligence of TCM data. It effectively bridges traditional TCM knowledge with modern intelligent technologies, providing robust data support and intelligent tools for TCM research and clinical applications.

BACKGROUND: The relationship between glycated hemoglobin (HbA1c) and cognitive impairment in older adults with coronary heart disease (CHD) remains unclear. METHODS: The present study used a prospective cohort study design and included 3244 participants aged ≥ 65 years in Beijing, China. The Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) were used to assess cognitive function. Serum HbA1c was detected at admission. All patients were divided into high HbA1c group (≥ 6.5 mmol/L) and low HbA1c group (< 6.5 mmol/L) based on their HbA1c levels. Logistic regression analyses were used to evaluate the association between HbA1c and cognitive impairment. RESULTS: In this study of 3244 participants, 1201 (37.0%) patients were in high HbA1c group and 2045 (63.0%) patients were in a state of cognitive impairment. Logistic regression analyses demonstrated that HbA1c was an independent risk factor for cognitive impairment regardless of whether the HbA1c was a continuous or categorical variable (OR = 1.27, 95% CI: 1.15-1.40, P < 0.001; OR = 1.79, 95% CI: 1.41-2.26, P ≤ 0.001, respectively). The restricted cubic spline curve exhibited that the relationship between the HbA1c and cognitive impairment was linear (p for non-linear = 0.323, P < 0.001). CONCLUSION Elevated levels of HbA1c were associated with an increased risk of cognitive impairment in older patients with CHD. These insights could be used to improve the accuracy and sensitivity of cognitive screening in these patient populations.

OBJECTIVE: To explore the potential effects and mechanisms of Liang-Ge-San (LGS) for the treatment of acute respiratory distress syndrome (ARDS) through network pharmacology analysis and to verify LGS activity through biological experiments. METHODS: The key ingredients of LGS and related targets were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. ARDS-related targets were selected from GeneCards and DisGeNET databases. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed using the Metascape Database. Molecular docking analysis was used to confirm the binding affinity of the core compounds with key therapeutic targets. Finally, the effects of LGS on key signaling pathways and biological processes were determined by in vitro and in vivo experiments. RESULTS: A total of LGS-related targets and 496 ARDS-related targets were obtained from the databases. Network pharmacological analysis suggested that LGS could treat ARDS based on the following information: LGS ingredients luteolin, wogonin, and baicalein may be potential candidate agents. Mitogen-activated protein kinase 14 (MAPK14), recombinant V-Rel reticuloendotheliosis viral oncogene homolog A (RELA), and tumor necrosis factor alpha (TNF-α) may be potential therapeutic targets. Reactive oxygen species metabolic process and the apoptotic signaling pathway were the main biological processes. The p38MAPK/NF-κ B signaling pathway might be the key signaling pathway activated by LGS against ARDS. Moreover, molecular docking demonstrated that luteolin, wogonin, and baicalein had a good binding affinity with MAPK14, RELA, and TNF α. In vitro experiments, LGS inhibited the expression and entry of p38 and p65 into the nucleation in human bronchial epithelial cells (HBE) cells induced by LPS, inhibited the inflammatory response and oxidative stress response, and inhibited HBE cell apoptosis (P<0.05 or P<0.01). In vivo experiments, LGS improved lung injury caused by ligation and puncture, reduced inflammatory responses, and inhibited the activation of p38MAPK and p65 (P<0.05 or P<0.01). CONCLUSION LGS could reduce reactive oxygen species and inflammatory cytokine production by inhibiting p38MAPK/NF-κ B signaling pathway, thus reducing apoptosis and attenuating ARDS.
Drugs, Chinese Herbal/pharmacology* ; Respiratory Distress Syndrome/enzymology* ; p38 Mitogen-Activated Protein Kinases/metabolism* ; NF-kappa B/metabolism* ; Animals ; Signal Transduction/drug effects* ; Molecular Docking Simulation ; Humans ; Male ; Network Pharmacology ; Apoptosis/drug effects* ; Mice

Large language models (LLMs) such as ChatGPT, Claude, Llama, and Qwen are emerging as transformative technologies for the diagnosis and treatment of various diseases. With their exceptional long-context reasoning capabilities, LLMs are proficient in clinically relevant tasks, particularly in medical text analysis and interactive dialogue. They can enhance diagnostic accuracy by processing vast amounts of patient data and medical literature and have demonstrated their utility in diagnosing common diseases and facilitating the identification of rare diseases by recognizing subtle patterns in symptoms and test results. Building on their image-recognition abilities, multimodal LLMs (MLLMs) show promising potential for diagnosis based on radiography, chest computed tomography (CT), electrocardiography (ECG), and common pathological images. These models can also assist in treatment planning by suggesting evidence-based interventions and improving clinical decision support systems through integrated analysis of patient records. Despite these promising developments, significant challenges persist regarding the use of LLMs in medicine, including concerns regarding algorithmic bias, the potential for hallucinations, and the need for rigorous clinical validation. Ethical considerations also underscore the importance of maintaining the function of supervision in clinical practice. This paper highlights the rapid advancements in research on the diagnostic and therapeutic applications of LLMs across different medical disciplines and emphasizes the importance of policymaking, ethical supervision, and multidisciplinary collaboration in promoting more effective and safer clinical applications of LLMs. Future directions include the integration of proprietary clinical knowledge, the investigation of open-source and customized models, and the evaluation of real-time effects in clinical diagnosis and treatment practices.
Humans ; Large Language Models ; Tomography, X-Ray Computed

Type 2 diabetes mellitus(T2DM) is a prevalent metabolic and endocrine disorder. Long-term hyperglycemia can lead to severe chronic complications, imposing substantial economic burdens on both society and patients. Despite the availability of various hypoglycemic agents for clinical use, these agents often fail to meet the therapeutic needs of T2DM and its complications. Consequently, there is an urgent need for novel therapeutic strategies and drugs. Lithocarpus litseifolius(L. litseifolius), commonly referred to as "cordyceps on trees", has a long history of use in traditional medicine and can be applied in tea, sugar, and medicine. Research indicates that L. litseifolius extracts are rich in dihydrochalcones, including trilobatin, phloridzin, and phloretin, which exhibit a range of pharmacological activities, such as anti-inflammatory, antioxidant, hypoglycemic, hypolipidemic, hepatoprotective, and cardioprotective effects. These properties suggest potential applications in the treatment of T2DM and its complications. This review systematically compiled and organized the relevant literature from the past decade on dihydrochalcones(trilobatin, phloridzin, and phloretin) from L. litseifolius extracts. It highlighted recent research progress regarding their role in treating T2DM and its complications through mechanisms such as reducing insulin resistance, regulating glucose transport, improving glucose and lipid metabolism, modulating enzyme activity, regulating gut microbiota, and alleviating inflammation and oxidative damage. The purpose of this review is to provide a reference and basis for future research on the prevention and treatment of T2DM and its complications using dihydrochalcones(trilobatin, phloridzin, and phloretin) from L. litseifolius extracts.
Chalcones/chemistry* ; Diabetes Mellitus, Type 2/metabolism* ; Humans ; Animals ; Elaeocarpaceae/chemistry* ; Drugs, Chinese Herbal/therapeutic use* ; Hypoglycemic Agents/chemistry* ; Plant Extracts/chemistry*

The number of patients with eye diseases in China is enormous,and the negative effects of these conditions,such as impaired visual function,psychological burdens,and restricted social participation,are becoming increasingly severe.Due to the limited and unevenly distributed ophthalmic resources,and the significant limitations of traditional diagnostic and therapeutic approaches in terms of accuracy and efficiency,there is an urgent need for more sensitive and efficient modalities.With the rapid advancement of artificial intelligence technology,ophthalmic diagnosis has entered a new stage of intelligent transformation.Facial photos,as a noninvasive and convenient medium,show unique advantages in eye disease diagnosis.Artificial intelligence systems based on facial photo analysis have been applied to the screening and diagnosis of conditions such as myopia,strabismus,ptosis,and thyroid eye disease,showing promising results.This review introduces the workflow of intelligent diagnosis for ocular diseases based on facial photographs,with a focus on recapitulating relevant research findings both domestically and internationally in recent years.It summarizes the innovative features and application advantages of intelligent diagnosis systems for eye diseases based on facial photos,analyzes the current technical bottlenecks and challenges in application,proposes corresponding countermeasures,and discusses future development directions,aiming to provide references and new insights for the intelligent screening and diagnosis of eye diseases.

The accumulation of uremic toxins such as urea nitrogen, blood creatinine, and uric acid of patients with renal failure in vivo would lead to aggravated kidney damage. In this study, coated aldehyde oxy-starch (CAO) was used as an adsorbent to investigate its in vitro adsorption performance on renal failure indexes for urea, indoxyl sulfate (INS), monomethylamine (MMA), dimethylamine (DMA), uric acid (UA), and creatinine (Cr). The effects of variables such as pH, temperature, concentration, dosage, and time on the adsorption capacity of CAO were systematically investigated, employing analytical techniques of high-performance liquid chromatography (HPLC) and gas chromatography (GC). The results revealed that CAO exhibited a strong adsorption capacity for urea, INS, and MMA, alongside a moderate adsorption capacity for DMA, UA, and Cr. The adsorption kinetics and thermodynamic studies indicated that the adsorption of urea and UA by CAO were fitted in pseudo-first-order kinetics, and the adsorption isotherm aligned with the Freundlich adsorption model. The enthalpy change ΔH of urea in adsorption was in the range of 40 to 60 kJ·mol^-1, which demonstrated the presence of strong adsorption force due to the interactions of coordinating groups. The ΔH of UA was greater than 80 kJ·mol^-1, indicating the generation of chemical bonds during the adsorption. Both of them, Gibbs free energy ΔG was less than 0, within the range of -20 to 0 kJ·mol^-1, suggested that the adsorption of urea and UA by CAO occurred spontaneously as physical adsorption process. The adsorption entropy ΔS of urea and UA was > 0, which indicated an increase in entropy throughout the adsorption. The infrared spectroscopygram showed the formation of a chemical bond, specifically the imine bond, following the adsorption of urea by CAO, thereby indicating a chemical reaction during the adsorption. This study elucidates the adsorption mechanism of CAO on various indexes of renal failure, providing a scientific basis for its clinical usage.

BACKGROUND:As a degradable scaffold material for bone tissue engineering,lactic acid is widely used in tissue regeneration and repair research,and plays an important role in promoting tissue healing,new bone formation and angiogenesis. OBJECTIVE:To observe the effect of lactic acid degradation products on osteoclasts and to investigate the effects of lactic-interfered osteoclast conditioned medium on the proliferation,migration and tube-forming capacity of human umbilical vein endothelial cells. METHODS:(1)The mouse monocyte macrophage cell line RAW264.7 at logarithmic growth period was selected,and adherent cells were cultured in the osteoclast induction medium(DMEM medium with nuclear factor-κB receptor-activating factor ligand and 10%fetal bovine serum)containing different concentrations of lactic acid(0,5,10,20 mmol/L).After 5 days of culture,tartrate-resistant acid phosphatase staining and cytoskeletal fibrillar actin staining were conducted.After 24 hours of culture,RT-PCR was used to detect the mRNA expression of tartrate-resistant acid phosphatase 5.(2)RAW264.7 cells at logarithmic growth period were selected and adherent cells were divided into two groups.Control group was cultured in the osteoclast induction medium,while experimental group was cultured in the osteoclast induction medium containing 10 mmol/L lactic acid.After 5 days of culture,the medium in each group was removed and the cells in the two groups were cultured in the serum-free DMEM medium for another 24 hours.Cell supernatant was then collected and used as the conditioned medium after mixed with an equal volume of DMEM medium containing 10%fetal bovine serum.Human umbilical vein endothelial cells at the logarithmic growth phase were taken and separately co-cultured with the conditioned medium of the control and experimental groups.The proliferation,migration and tube-forming ability of human umbilical vein endothelial cells were observed by cell counting kit-8 assay,migration assay,scratch assay and tube-forming assay.The mRNA and protein expression of angiogenesis-related genes and proteins were observed by RT-PCR and western blot. RESULTS AND CONCLUSION:Tartrate-resistant acid phosphatase staining and cytoskeletal fibrillar actin staining showed that 5 and 10 mmol/L lactic acid promoted osteoclastic differentiation of RAW264.7 cells and the promoting effect of 10 mmol/L lactate was more significant.RT-PCR results showed that the expression of tartrate-resistant acid phosphatase-5 mRNA of osteoclast-related genes was the highest when the lactic acid concentration was 5,10,and 20 mmol/L(P<0.05),especially 10 mmol/L.Compared with the control group,the proliferation,migration and tube-forming abilities of human umbilical vein endothelial cells were significantly increased in the experimental group(P<0.05).Compared with the control group,the expression levels of vascular endothelial growth factor and angiogenin 1 mRNA and protein were increased in the experimental group(P<0.05).To conclude,lactate-induced osteoclast conditioned medium could promote the angiogenesis of endothelial cells,and the mechanism may be related to the promotion of the expression of vascular endothelial growth factor and angiogenin 1.

Objective To investigate the status quo of indwelling needles use in the hospitals at all lev-els in Chongqing city,and to evaluate the normalization and safety of indwelling needles use by referring to Nursing Practice Standards for Intravenous Therapy.Methods A self-designed questionnaire was used in July 2023 to conduct a cross-sectional survey on the use of indwelling needles in the hospitals at all levels in Chongqing city.Results A total of 30 807 patients in 77 hospitals were included,among them 62.67%used indwelling needles.The closed type indwelling needles accounted for 88.87%and the safety type indwelling needles accounted for 41.74%.Non-needle infusion connectors accounted for 37.78%,and steel needle con-nected with heparin caps accounted for 51.69%.95.66%of puncture site was in the upper limb,the non-cor-rosive drug infusion accounted for 87.57%,and the complications occurrence rate was 2.46%.Among the 6 419 surveyed nurses,75.51%removed indwelling needles based on clinical indications.There were statistically significant differences in the usage rates of closed type indwelling needles and non-needle infusion connectors among hospitals at different levels(P<0.05).There were also statistically significant differences in the inci-dence rates of complication and phlebitis(P<0.05).Conclusion The overall application of indwelling needles in the hospitals at all levels in Chongqing city is generally standardized,but the use of safety type indwelling needles and needle-free infusion connectors still needs to be improved.

The number of patients with eye diseases in China is enormous,and the negative effects of these conditions,such as impaired visual function,psychological burdens,and restricted social participation,are becoming increasingly severe.Due to the limited and unevenly distributed ophthalmic resources,and the significant limitations of traditional diagnostic and therapeutic approaches in terms of accuracy and efficiency,there is an urgent need for more sensitive and efficient modalities.With the rapid advancement of artificial intelligence technology,ophthalmic diagnosis has entered a new stage of intelligent transformation.Facial photos,as a noninvasive and convenient medium,show unique advantages in eye disease diagnosis.Artificial intelligence systems based on facial photo analysis have been applied to the screening and diagnosis of conditions such as myopia,strabismus,ptosis,and thyroid eye disease,showing promising results.This review introduces the workflow of intelligent diagnosis for ocular diseases based on facial photographs,with a focus on recapitulating relevant research findings both domestically and internationally in recent years.It summarizes the innovative features and application advantages of intelligent diagnosis systems for eye diseases based on facial photos,analyzes the current technical bottlenecks and challenges in application,proposes corresponding countermeasures,and discusses future development directions,aiming to provide references and new insights for the intelligent screening and diagnosis of eye diseases.