Objective: To explore the early effects of birth weight at different gestational ages on blood pressure trajectory among primary school students, so as to provide evidence for incorporating gestational age birth weight into individualized early warning and intervention strategies for childhood hypertension. Methods: From May to November 2023, a purposeful sampling method was used to recruit 1 676 students in grade 1-3 from three primary schools in a certain urban district of Chongqing. Follow up assessments were conducted in May 2024(T1), November 2024(T2), and May 2025(T3). General demographic and birth related information were collected via self administered questionnaires, while height, weight and blood pressure were obtained through physical examinations. Linear mixed effects model was used to analyze the associations between birth weight at different gestational ages and blood pressure trajectories. Results: During the T1-T3 period, the systolic blood pressure of boys were 98.5 (93.0, 104.5 ),98.5 (93.5, 105.0), and 97.5 (92.5, 103.5)mmHg, respectively, while the diastolic blood pressure were 60.5 (56.5, 65.0), 61.5 ( 57.0 , 65.5), and 60.0 (56.0, 64.0)mmHg, respectively. For girls, the systolic blood pressure were 95.5 (90.0, 102.0),95.5 (90.5, 101.5), and 96.0 (90.5, 101.5)mmHg, respectively, and the diastolic blood pressure were 60.5 (56.0, 64.5 ),61.5 (57.5, 65.5), and 59.5 (56.0, 63.0)mmHg, respectively. Through Friedman test within both boys and girls, diostolic blood pressure were statistically significant across three measurements( χ 2=48.85，81.54，both P <0.01). The proportion of normal blood pressure increased , and the proportion of prehypertension and hypertension decreased with time( χ 2=39.72，25.62，both P < 0.01 ). Linear mixed effects model analysis revealed that after adjusting for age, sex, household income monthly, parental education, family history of hypertension and maternal pregnancy complications, large for gestational age had significantly higher trajectories of systolic ( β = 1.50) and diastolic( β =0.94) blood pressure compared to appropriate for gestational age(both P <0.01). Conclusion Large for gestational age is associated with elevated blood pressure trajectories during school age, and it may be considered as an early indicator for individualized screening and intervention for childhood hypertension.

ObjectiveSpinal cord injury (SCI) directly impairs the regulatory function of the autonomic nervous system, induces intestinal dysfunction, and significantly reduces patients’ quality of life. Preclinical studies have shown that electroacupuncture (EA) therapy can regulate the brain-gut axis and is used to treat central nervous system diseases such as major depressive disorder, Alzheimer’s disease and Parkinson’s disease. Recent research has established that fecal microbiota transplantation (FMT) from EA-treated SCI rats restored intestinal motility and colonic morphology. However, it remains unclear whether the regulation of gut microbiota by EA therapy directly contributes to neural repair after SCI. This study aims to explore whether gut microbiota mediates the neuroprotective effect of EA in the treatment of SCI and its possible mechanism. MethodsThe study employed RNA transcriptome analysis of spinal cord tissue to characterize gene expression profiles and to identify key signaling pathways following EA treatment for SCI. Hematoxylin-Eosin (HE) staining and Nissl staining were used to observe the morphological changes in spinal cord tissue. Western blot (WB) and enzyme-linked immunosorbent assay (ELISA) were applied to detect the effects of EA on the expression of proteins related to nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) -dependent pyroptosis. Using 16S rDNA sequencing, the study observed alterations in gut microbiota diversity and community composition in SCI rats. Prior to establishing SCI models, rats were pretreated with an antibiotic cocktail to induce gut dysbiosis, and the effects on intestinal function and spinal cord neural repair were evaluated. FMT was performed to investigate the regulatory effects of post-EA FMT on motor function, general status, liver and spleen indices, and NLRP3-mediated pyroptosis in SCI rats. ResultsEA improved motor function and reduced regulated neuronal cell death in SCI rats. Transcriptomic analysis demonstrated the activation of immune- and inflammation-related pathways post-SCI, including NOD-like receptors, nuclear factor-kappa B(NF-κB), and Toll-like receptor (TLR) pathways. EA primarily influenced intestinal inflammation and autoimmune functions. 16S rDNA sequencing illustrated that EA did not alter the diversity of gut microbiota. However, EA altered the gut microbiota composition in SCI rats, increasing Lactobacillus and Akkermansia genera while rebalancing the Firmicutes/Bacteroidetes ratio. Furthermore, depletion of gut microbiota by antibiotics disrupted the intestinal barrier, reduced the expression of intestinal barrier proteins Zonula Occludens-1 (ZO-1) and Occludin, elevated serum lipopolysaccharide-binding protein (LBP) levels, exacerbated spinal cord tissue damage, and hindered motor function recovery in SCI rats. FMT from donors treated with EA reduced LBP levels in the intestine, blood, and spinal cord of rats, inhibited the TLR4 myeloid differentiation primary response protein 88 (MyD88)-NF‑κB pathway and NLRP3-dependent pyroptosis, and improved motor function. On the other hand, FMT treatment resulted in decreased body weight and food intake, whereas FMT using EA-treated donors effectively alleviated these alterations. ConclusionEA effectively alleviated neuroinflammatory responses in rats with SCI, primarily through regulating the gut microbiota and suppressing the NLRP3-dependent pyroptosis signaling pathway.

ObjectiveSpinal cord injury (SCI) directly impairs the regulatory function of the autonomic nervous system, induces intestinal dysfunction, and significantly reduces patients’ quality of life. Preclinical studies have shown that electroacupuncture (EA) therapy can regulate the brain-gut axis and is used to treat central nervous system diseases such as major depressive disorder, Alzheimer’s disease and Parkinson’s disease. Recent research has established that fecal microbiota transplantation (FMT) from EA-treated SCI rats restored intestinal motility and colonic morphology. However, it remains unclear whether the regulation of gut microbiota by EA therapy directly contributes to neural repair after SCI. This study aims to explore whether gut microbiota mediates the neuroprotective effect of EA in the treatment of SCI and its possible mechanism. MethodsThe study employed RNA transcriptome analysis of spinal cord tissue to characterize gene expression profiles and to identify key signaling pathways following EA treatment for SCI. Hematoxylin-Eosin (HE) staining and Nissl staining were used to observe the morphological changes in spinal cord tissue. Western blot (WB) and enzyme-linked immunosorbent assay (ELISA) were applied to detect the effects of EA on the expression of proteins related to nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) -dependent pyroptosis. Using 16S rDNA sequencing, the study observed alterations in gut microbiota diversity and community composition in SCI rats. Prior to establishing SCI models, rats were pretreated with an antibiotic cocktail to induce gut dysbiosis, and the effects on intestinal function and spinal cord neural repair were evaluated. FMT was performed to investigate the regulatory effects of post-EA FMT on motor function, general status, liver and spleen indices, and NLRP3-mediated pyroptosis in SCI rats. ResultsEA improved motor function and reduced regulated neuronal cell death in SCI rats. Transcriptomic analysis demonstrated the activation of immune- and inflammation-related pathways post-SCI, including NOD-like receptors, nuclear factor-kappa B(NF-κB), and Toll-like receptor (TLR) pathways. EA primarily influenced intestinal inflammation and autoimmune functions. 16S rDNA sequencing illustrated that EA did not alter the diversity of gut microbiota. However, EA altered the gut microbiota composition in SCI rats, increasing Lactobacillus and Akkermansia genera while rebalancing the Firmicutes/Bacteroidetes ratio. Furthermore, depletion of gut microbiota by antibiotics disrupted the intestinal barrier, reduced the expression of intestinal barrier proteins Zonula Occludens-1 (ZO-1) and Occludin, elevated serum lipopolysaccharide-binding protein (LBP) levels, exacerbated spinal cord tissue damage, and hindered motor function recovery in SCI rats. FMT from donors treated with EA reduced LBP levels in the intestine, blood, and spinal cord of rats, inhibited the TLR4 myeloid differentiation primary response protein 88 (MyD88)-NF‑κB pathway and NLRP3-dependent pyroptosis, and improved motor function. On the other hand, FMT treatment resulted in decreased body weight and food intake, whereas FMT using EA-treated donors effectively alleviated these alterations. ConclusionEA effectively alleviated neuroinflammatory responses in rats with SCI, primarily through regulating the gut microbiota and suppressing the NLRP3-dependent pyroptosis signaling pathway.

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.

This study aims to explore the protective effect of Chaihu Jia Longgu Muli Decoction on rats with heart failure after myocardial infarction, and to clarify its possible mechanisms, providing a new basis for basic research on the mechanism of classic Chinese medicinal formula-mediated inflammatory response in preventing and treating heart failure induced by apoptosis after myocardial infarction. A heart failure model after myocardial infarction was established in rats by coronary artery ligation. The rats were divided into sham group, model group, and low, medium, and high-dose groups of Chaihu Jia Longgu Muli Decoction, with 10 rats in each group. The low-dose, medium-dose, and high-dose groups of Chaihu Jia Longgu Muli Decoction were given 6.3, 12.6, and 25.2 g·kg~(-1) doses by gavage, respectively. The sham group and model group were given an equal volume of distilled water by gavage once daily for four consecutive weeks. Cardiac function was assessed using color Doppler echocardiography. Myocardial pathology was detected by hematoxylin-eosin(HE) staining, apoptosis was measured by TUNEL assay, and mitophagy was observed by transmission electron microscopy. The levels of tumor necrosis factor-α(TNF-α), interleukin(IL)-1β, and N-terminal pro-B-type natriuretic peptide(NT-proBNP) in serum were detected by enzyme-linked immunosorbent assay(ELISA). The expression of apoptosis-related proteins B-cell lymphoma 2(Bcl-2), Bcl-2-associated X protein(Bax), and cleaved caspase-3 was detected by Western blot. Additionally, the expression of phosphorylated nuclear transcription factor-κB(NF-κB) p65(p-NF-κB p65)(upstream) and nuclear factor kappa B inhibitor alpha(IκBα)(downstream) in the NF-κB signaling pathway was assessed by Western blot. The results showed that compared with the sham group, left ventricular ejection fraction(LVEF) and left ventricular short axis shortening(LVFS) in the model group were significantly reduced, while left ventricular end diastolic diameter(LVEDD) and left ventricular end systolic diameter(LVESD) increased significantly. Myocardial tissue damage was severe, with widened intercellular spaces and disorganized cell arrangement. The apoptosis rate was increased, and mitochondria were enlarged with increased vacuoles. Levels of TNF-α, IL-1β, and NT-proBNP were elevated, indicating an obvious inflammatory response. The expression of pro-apoptotic factors Bax and cleaved caspase-3 increased, while the anti-apoptotic factor Bcl-2 decreased. The expression of p-NF-κB p65 was upregulated, and the expression of IκBα was downregulated. In contrast, the Chaihu Jia Longgu Muli Decoction groups showed significantly improved of LVEF, LVFS and decreased LVEDD, LVESD compared to the model group. Myocardial tissue damage was alleviated, and intercellular spaces were reduced. The apoptosis rate decreased, mitochondrial volume decreased, and the levels of TNF-α, IL-1β, and NT-proBNP were lower. The expression of pro-apoptotic factors Bax and cleaved caspase-3 decreased, while the expression of the anti-apoptotic factor Bcl-2 increased. Additionally, the expression of p-NF-κB p65 decreased, while IκBα expression increased. In summary, this experimental study shows that Chaihu Jia Longgu Muli Decoction can reduce the inflammatory response and apoptosis rate in rats with heart failure after myocardial infarction, which may be related to the regulation of the IκBα/NF-κB signaling pathway.
Animals ; Apoptosis/drug effects* ; Drugs, Chinese Herbal/administration & dosage* ; Rats ; Myocardial Infarction/physiopathology* ; Male ; NF-kappa B/genetics* ; Heart Failure/etiology* ; Rats, Sprague-Dawley ; Signal Transduction/drug effects* ; NF-KappaB Inhibitor alpha/genetics* ; Humans ; Tumor Necrosis Factor-alpha/genetics*

OBJECTIVE: To assess the cardioprotective effect and impact of Qishen Granules (QSG) on different ischemic areas of the myocardium in heart failure (HF) rats by evaluating its metabolic pattern, substrate utilization, and mechanistic modulation. METHODS: In vivo, echocardiography and histology were used to assess rat cardiac function; positron emission tomography was performed to assess the abundance of glucose metabolism in the ischemic border and remote areas of the heart; fatty acid metabolism and ATP production levels were assessed by hematologic and biochemical analyses. The above experiments evaluated the cardioprotective effect of QSG on left anterior descending ligation-induced HF in rats and the mode of energy metabolism modulation. In vitro, a hypoxia-induced H9C2 model was established, mitochondrial damage was evaluated by flow cytometry, and nuclear translocation of hypoxia-inducible factor-1 α (HIF-1 α) was observed by immunofluorescence to assess the mechanism of energy metabolism regulation by QSG in hypoxic and normoxia conditions. RESULTS: QSG regulated the pattern of glucose and fatty acid metabolism in the border and remote areas of the heart via the HIF-1 α pathway, and improved cardiac function in HF rats. Specifically, QSG promoted HIF-1 α expression and entry into the nucleus at high levels of hypoxia (P<0.05), thereby promoting increased compensatory glucose metabolism; while reducing nuclear accumulation of HIF-1 α at relatively low levels of hypoxia (P<0.05), promoting the increased lipid metabolism. CONCLUSIONS QSG regulates the protein stability of HIF-1 α, thereby coordinating energy supply balance between the ischemic border and remote areas of the myocardium. This alleviates the energy metabolism disorder caused by ischemic injury.
Animals ; Myocardial Infarction/physiopathology* ; Male ; Hypoxia-Inducible Factor 1, alpha Subunit/metabolism* ; Rats, Sprague-Dawley ; Glucose/metabolism* ; Drugs, Chinese Herbal/therapeutic use* ; Energy Metabolism/drug effects* ; Rats ; Fatty Acids/metabolism* ; Myocardium/pathology*

ObjectiveThrough qualitatively and quantitatively analysis of the differences in chemical composition between the combined decoction and single decoction of Huaganjian and comparison of their core efficacy， to explore the rationality of the flexible clinical application of Huaganjian compound preparations and single-flavored dispensing granules. MethodsUltra performance liquid chromatography-quadrupole-electrostatic field orbitrap high resolution mass spectrometry（UPLC-Q-Exactive Orbitrap MS） was used to qualitatively analyze the combined decoction and single decoction samples of Huaganjian， and meanwhile， the contents of four index components（geniposide， paeoniflorin， hesperidin and paeonol） were quantitatively analyzed by high performance liquid chromatography（HPLC）. Nonalcoholic fatty liver disease（NAFLD） rat model induced by high-fat diet was applied to compare the efficacy of combined decoction and single decoction of Huaganjian. A total of 30 male SD rats were randomly divided into the control group， model group， lovastatin group（1.8 mg·kg^-1）， combined decoction group（1.26 g·kg^-1） and single decoction group（1.18 g·kg^-1）. After successful modeling， lovastatin group， combined decoction group and single decoction group were given corresponding doses of drugs by intragastric administration every day， and the control group and model group were given equal amounts of normal saline by intragastric administration， after 4 weeks of administration， the serum and liver tissues were collected， and the contents of alanine aminotransferase（ALT）， aspartate aminotransferase（AST）， total cholesterol（TC）， triglyceride（TG）， low-density lipoprotein cholesterol（LDL-C） and high-density lipoprotein cholesterol（HDL-C） in serum of rats were detected， and the liver pathological examination was carried out by hematoxylin-eosin（HE） staining and oil red O staining， so as to compare differences of their efficacy. ResultsSeventy chemical components were initially identified and attributed from the lyophilized powder of the combined decoction and single decoction samples of Huaganjian， and there was no obvious difference in composition between the two. Further quantitative analysis showed that the contents of geniposide， paeoniflorin， hesperidin and paeonol in the combined decoction samples were significantly increased when compared with those of the single decoction samples（P<0.01）. The pharmacodynamic results showed that compared with the model group， both the combined and single decoction groups of Huaganjian could improve the liver index of NAFLD rats， reduce the serum levels of AST， ALT， TC， TG and LDL-C， increase the serum level of HDL-C， and ameliorate the pathological changes of liver cell steatosis and fat accumulation. However， there was no significant difference in pharmacodynamic effects between the combined decoction group and the single decoction group. ConclusionThere is no significant difference between the combined decoction and single decoction of Huaganjian in terms of chemical composition， but the contents of the four index components show significantly difference. Both of them can significantly improve the fat accumulation and liver function in NAFLD rats. This study provides a reference basis for the rational clinical application and evaluation of famous classical formula compound preparations and single-flavored dispensing granules.

ObjectiveTo explore the construction of a machine learning model for the diagnosis of traditional Chinese medicine （TCM） syndromes in chronic cough and the optimization of this model using the Voting ensemble algorithm. MethodsA retrospective analysis was conducted using clinical data from 921 patients with chronic cough treated at the Respiratory Department of Dongfang Hospital， Beijing University of Chinese Medicine. After standardized processing， 84 clinical features were extracted to determine TCM syndrome types. A specialized dataset for TCM syndrome diagnosis in chronic cough was formed by selecting syndrome types with more than 50 cases. The synthetic minority over-sampling technique （SMOTE） was employed to balance the dataset. Four base models， logistic regression （LR）， decision tree （dt）， multilayer perceptron （MLP）， and Bagging， were constructed and integrated using a hard voting strategy to form a Voting ensemble model. Model performance was evaluated using accuracy， recall， precision， F1-score， receiver operating characteristic （ROC） curve， area under the curve （AUC）， and confusion matrix. ResultsAmong the 921 cases， six syndrome types had over 50 cases each， phlegm-heat obstructing the lung （294 cases）， wind pathogen latent in the lung （103 cases）， cold-phlegm obstructing the lung （102 cases）， damp-heat stagnating in the lung （64 cases）， lung yang deficiency （54 cases）， and phlegm-damp obstructing the lung （53 cases）， yielding a total of 670 cases in the specialized dataset. High-frequency symptoms among these patients included cough， expectoration， odor-induced cough， throat itchiness， itch-induced cough， and cough triggered by cold wind. Among the four base models， the MLP model showed the best diagnostic performance （test accuracy： 0.9104； AUC： 0.9828）. Compared with the base models， the Voting ensemble model achieved superior performance with an accuracy of 0.9289 on the training set and 0.9253 on the test set， showing a minimal overfitting gap of 0.0036. It also achieved the highest AUC （0.9836） in the test set， outperforming all base models. The model exhi-bited especially strong diagnostic performance for damp-heat stagnating in the lung （AUC： 0.9984） and wind pathogen latent in the lung （AUC： 0.9970）. ConclusionThe Voting ensemble algorithm effectively integrates the strengths of multiple machine learning models， resulting in an optimized diagnostic model for TCM syndromes in chronic cough with high accuracy and enhanced generalization ability.

Objective To explore the medication patterns of famous traditional Chinese medicine practitioners in treating challenging aspects of idiopathic membranous nephropathy(IMN)based on data mining.Methods Medical cases meeting the inclusion and exclusion criteria were collected.Statistical analysis of syndrome patterns,herb frequency,association rules,and cluster analysis were conducted for key challenges,including disease duration ≥ 1 year,renal function impairment,hypoalbuminemia,and hypertriglyceridemia.Results A total of 128 medical cases were included.Spleen-kidney deficiency syndrome was identified as the most common pattern.Based on herb frequency and association rule analysis,Huangqi,Baizhu,Fuling,Danggui,Danshen were the most frequently used in prescription.Cluster analysis revealed core herbal groupings primarily based on classical formulas such as Zhenwu decoction,Shenling Baizhu powder,and Shuilu Erxian dan.Conclusion In the medical cases addressing treatment challenges,the syndrome patterns were predominantly characterized by spleen-kidney deficiency.Core medications included Huangqi,Baizhu,Fuling,Danggui and Danshen.The treatment emphasizes strengthening invigorating spleen and kidney,with variations in medication patterns based on disease duration and complications.