Objective: To investigate factors influencing perioperative blood transfusion in patients with scarred uterus during pregnancy undergoing cesarean section, construct and validate a transfusion risk prediction model, and provide evidence for preoperative assessment and blood management. Methods: Clinical data of 405 patients undergoing cesarean section for scarred uterus during pregnancy at the First Affiliated Hospital of Xi'an Jiaotong University from January 2020 to December 2024 were retrospectively collected. The dataset was randomly divided into a training set (n=284) and a validation set (n=121) at a 7∶3 ratio. Within the training set, Firth-penalized logistic regression was employed for multivariate analysis to identify independent factors influencing perioperative blood transfusion and construct a predictive model. Model performance was evaluated in the validation set. Results: Multivariate Firth regression analysis showed that severe placenta previa (OR=75.566, 95%CI: 8.603-9979.174) and placenta accreta (OR=4.591, 95%CI: 1.120-19.416) were independent risk factors for perioperative blood transfusion, while preoperative red blood cell count (OR=0.189, 95%CI: 0.083-0.405) and fibrinogen levels (OR=0.588, 95%CI: 0.395-0.855) were protective factors. The predictive model constructed based on these four variables demonstrated good discriminatory performance, with areas under the receiver operating characteristic curves of 0.803 (95%CI: 0.740-0.867) and 0.753 (95%CI: 0.644-0.862) in the training and validation sets, respectively. Conclusion: For patients with scarred uterus during pregnancy undergoing cesarean section, severe placenta previa and placenta accreta significantly increase the risk of transfusion, while higher preoperative red blood cell count and fibrinogen levels exert a protective effect. The predictive model established in this study facilitates the identification of patients requiring transfusion, thereby enabling preoperative blood preparation and optimized blood management.

Objective To analyze the clinical manifestations of patients over 60 years old with acute respiratory infection in Pudong New Area of Shanghai and the risk factors of positive detection of novel coronavirus, and to provide reference for improving prevention and control strategies and measures. Methods General conditions, clinical features, basic complications and respiratory samples of inpatients over 60 years old with acute respiratory infection from eight hospitals in Pudong New Area of Shanghai from January to October 2023 were collected, and SARS-CoV-2 detection was carried out. Chi-square test and binary logistics regression were used for data analysis. Results A total of 604 patients over 60 years old were collected, including 356 (58.945) males with a median age of 77 (IQR:70-85) years. Of the 604 cases, 264 were detected positive for SARS-CoV-2, with a positive detection rate of 43.71%. The results of univariate analysis showed that there were significant differences in the detection rates of SARS-CoV-2 among different age groups (χ²=10.60, P=0.01) and different months (χ²=87.15, P=0.00), and among those with cough (χ²=5.28, P=0.02), sputum (χ²=4.19, P=0.04), sore throat (χ²=3.93, P=0.04), and hypertension (χ²=7.63, P=0.01). In the binary logistics regression analysis, month (P=0.00, OR=2.93, 95% CI=1.49-5.78) and age (P=0.00, OR=2.60, 95% CI=1.55-4.37) were independent risk factors for positive detection of SARS-CoV-2. Conclusion The majority of hospitalized cases of acute respiratory infection over 60 years old are male, and the risk factors for positive detection of novel coronavirus are age 80~89 years old and time between May and June.

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.

Objective: To analyze the spatio-temporal distribution of pulmonary tuberculosis (PTB) among students in Suzhou City, Jiangsu Province from 2015 to 2023, so as to provide the evidence for the prevention and control of PTB in schools. Methods: Data of PTB cases among students in Suzhou City from 2015 to 2023 were collected from Chinese Disease Prevention and Control Information System and Suzhou Report of Investigation and Disposal of Tuberculosis in Schools. The seasonal incidence of PTB among students was analyzed using seasonal index (SI). The spatio-temporal clustering characteristics of PTB among students were analyzed using spatial autocorrelation and retrospective spatio-temporal permutation scanning. Results: Totally 1 374 PTB cases among students were reported in Suzhou City from 2015 to 2023. PTB cases were reported in each month, and the SIs were 100.69%, 124.38%, 108.98%, 135.04%, 106.61% and 106.61% in April, May, July, September, October and November, respectively, indicating the prevalence of PTB among students. Spatial autocorrelation analysis showed there was a positive spatial correlation of PTB among students in 2019 and 2020 (Moran's I=0.053 and 0.089, both P<0.05). From 2015 to 2023, there were high-high clustering sites mainly in Hengtang Street and Shishan Street. Retrospective spatio-temporal permutation scanning showed a primary cluster in Hengtang Street, with aggregation time in 2017, and 6 secondary clusters covering 25 towns (streets). Conclusion From 2015 to 2023, the PTB cases among students in Suzhou City were mainly concentrated in summer and autumn, and were predominantly clustered in Hengtang Street and Shishan Street.

Object To study the efficacy and potential mechanism of Tongbianling capsule in constipation. Methods The effects of Tongbianling capsule on intestinal motility in normal mice and carbon powder propulsion rate in small intestine of constipation model mice after were observed administration. The potential targets and key pathways of Tongbianling capsule in treating constipation were identified through network pharmacology. To verify the mechanism, the expression of p-PI3K/PI3K, p-AKT/AKT and CASP3 proteins in mouse colon tissue was detected by the western blot. Results The time for mice to excrete the first black stool was shortened and the number of fecal particles was increased in Tongbianling capsule administration group, and the carbon powder propulsion rate of mice in each Tongbianling capsule administration group was increased. The results of network pharmacology showed that treatment of constipation by Tongbianling capsule may be related to signaling pathways such as PI3K-Akt signaling pathway and 5-HT. The protein expression of p-PI3K/PI3K, p-AKT/AKT, and CASP3 in mouse colon tissue could be significantly downregulated in administration group. Conclusion Tongbianling capsule could effectively promote intestinal peristalsis in mice, increase the frequency of defecation, and effectively treat constipation. The mechanism of its action may be related to the direct or indirect regulation of intestinal motility by the PI3K-Akt signaling pathway.

ObjectiveTo investigate the efficacy of Xingpi capsules （XPC） in treating diarrhea-predominant irritable bowel syndrome （IBS-D） with spleen deficiency and elucidate its potential molecular mechanisms. MethodsA rat model of IBS-D with spleen deficiency was established by administering senna leaf in combination with restrained stress and swimming fatigue for 14 d. Ten specific pathogen free （SPF）-grade healthy rats were used as the normal control group. After successful modeling， SPF-grade rats were randomly divided into a model group， a pinaverium bromide group （1.5 mg·kg^-1）， and low- and high-dose XPC groups （0.135 and 0.54 g·kg^-1）， with 10 rats in each group. Rats in the normal control group and the model group were given distilled water by gavage， while the remaining groups were administered corresponding drug solutions by gavage once a day for 14 consecutive days. The rat body weights and fecal condition were observed every day， and the Bristol score was recorded. Enzyme-linked immunosorbent assay （ELISA） was used to determine the levels of 5-hydroxytryptamine （5-HT） in serum and colon tissue. Transmission electron microscopy was used to observe the microvilli and tight junctions in the colon. The integrity of the colonic barrier， intestinal motility， and expression of related pathway proteins were evaluated by hematoxylin-eosin （HE） staining， immunohistochemistry， and Western blot. ResultsCompared with those in the normal control group， rats in the model group showed a significantly decreased body weight and increased diarrhea rate， diarrhea grade， and Bristol score （P<0.01）. HE staining revealed incomplete colonic mucosa in the model group， with evident congestion and edema observed. Electron microscopy results indicated decreased density and integrity of the colonic barrier， shedding and disappearance of microvilli， and significant widening of tight junctions. The expression levels of colonic tight junction proteins Occludin and Claudin-5 were downregulated （P<0.01）， and the levels of 5-HT in serum and colon tissue were elevated （P<0.01）. The small intestine propulsion rate significantly increased （P<0.01）， and the expression of contractile proteins Ras homolog family member A （RhoA） and Rho-associated coiled-coil containing protein kinase 2 （ROCK2） in colon and phosphorylation of myosin light chain （MLC₂₀） were upregulated （P<0.01）. Compared with the model group， the treatment groups showed alleviated diarrhea， diarrhea-associated symptoms， and pathological manifestations of colon tissue to varying degrees. Specifically， high-dose XPC exhibited effectively relieved diarrhea， promoted recovery of colonic mucosal structure， significantly reduced congestion and edema， upregulated expression of Occludin and Claudin-5 （P<0.01）， decreased levels of 5-HT in serum and colon tissue （P<0.05，P<0.01）， significantly slowed small intestine propulsion rate （P<0.01）， and significantly downregulated expression of contractile proteins RhoA and ROCK2 in colon and phosphorylation of MLC₂₀ （P<0.05，P<0.01）. ConclusionXPC effectively alleviates symptoms of spleen deficiency and diarrhea and regulates the secretion of brain-gut peptide. The characteristics of XPC are mainly manifested in alleviating IBS-D with spleen deficiency from the aspects of protecting intestinal mucosa and inhibiting smooth muscle contraction， and the mechanism is closely related to the regulation of the 5-HT-RhoA/ROCK2 pathway expression.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Objective To investigate the effect of resveratrol on airway remodeling induced by ovalbumin(OVA)in asthmatic young mice based on the sphingosine-1-phosphate(S1P)/transforming growth factor-β1(TGF-β1)pathway.Methods Young mice were randomly assigned into normal group,model group,S1P group,resveratrol group,and resveratrol+S1P group,with 12 mice in each group.A mouse model of asthma induced by OVA was established.The Wright Giemsa staining was applied to detect the number of inflammatory cells in bronchoalveolar lavage fluid(BALF).ELISA was applied to detect the levels of interleukin-4(IL),IL-5,and IL-13 in BALF.The colorimetric method was applied to detect the activities of SOD and CAT and the content of MDA in lung tissue.HE staining was applied to observe pathological changes in lung tissue,and the wall area of bronchial tube(Wat)and perimeter of basement membrane(Pbm)were analyzed.Masson staining was applied to observe the area of collagen fibers in lung tissue.Immunohistochemistry was applied to detect the expression of α-SMA in lung tissue.Western blot was applied to detect the expression of E-cadherin,N-cadherin,Snail,SP1,and TGF-β1 proteins in lung tissue.Results Compared with the normal group,the number of eosinophils,lymphocytes,neutrophils,levels of IL-4,IL-5,and IL-13 in BALF,lung tissue MDA content,Wat/Pm ratio,collagen fiber area,α-SMA positive expression,the protein levels of N-cadherin,Snail,SP1,TGF-β1 increased in the model group,while the activities of SOD,CAT,and the protein level of E-cadherin in lung tissue decreased(P＜0.05).Compared to the model group,the number of eosinophils,lymphocytes,neutrophils,levels of IL-4,IL-5,and IL-13 in BALF,lung tissue MDA content,Wat/Pm ratio,collagen fiber area,α-SMA positive expression,the protein levels of N-cadherin,Snail,SP1,TGF-β1 decreased in the resveratrol group,while the activities of SOD,CAT,and the protein level of E-cadherin in lung tissue increased(P＜0.05).The S1P recombinant protein could weaken the inhibitory effect of resveratrol on airway remodeling in asthmatic young mice.Conclusion Resveratrol can inhibit oxidative stress,airway inflammation,and epithelial mesenchymal transition,thereby suppressing airway remodeling in asthmatic young mice.Its effect is related to the inhibition of the S1P/TGF-β1 signaling pathway.

Obesity has been recognized by the World Health Organization(WHO)as a global public health issue and is closely associated with an increased risk of metabolic diseases such as type 2 diabetes,hypertension,dyslipidemia,and cardiovascular disease(CVD).Based on the presence or absence of metabolic abnormalities,obese individuals can be categorized into metabolically healthy obesity(MHO)and metabolically unhealthy obesity(MUO).This review aims to explore the significant differences between MHO and MUO individuals in terms of pathophysiological mechanisms,clini-cal characteristics,and cardiovascular disease risk.Compared to those with MHO,MUO individuals exhibit more pro-nounced insulin resistance,persistent state of inflammation,and ectopic lipid accumulation,resulting in a higher risk of CVD and necessitating active and effective interventions.Furthermore,growing evidence suggests that MHO is not a stable long-term metabolic condition but may transition to MUO;hence,its long-term CVD risk should not be overlooked.This article also discusses the potential mechanisms underlying metabolic heterogeneity in MHO and MUO,including the regulation of adipose tissue distribution and function by genetic and environmental factors,as well as the potential role of li-festyle interventions in improving metabolic health.Future research should further investigate the pathophysiological basis of MHO and MUO to facilitate early identification of obesity-related CVD risk and develop effective prevention and treatment strategies.

Objective To explore the changes in neural activity in patients with type 2 diabetes mellitus(T2DM)and their corre-lation with executive function,and to analyze the neural mechanisms underlying the decline in executive function in T2DM patients.Methods Thirty-one T2DM patients(T2DM group)and thirty-two healthy controls(HC)(HC group)matched for body mass index(BMI)underwent resting-state functional magnetic resonance imaging(rs-fMRI)scans and N-back task tests were included.Differ-ences in the amplitude of low-frequency fluctuation(ALFF),regional homogeneity(ReHo),and seed-based functional connectivity(FC)between the two groups were compared,and partial correlation analyses were performed between the difference results and N-back task performance.Results The T2DM group showed prolonged reaction time(RT)in the 1-back and 2-back tasks.T2DM patients exhibited increased ALFF in the bilateral caudate nucleus,left medial superior frontal gyrus,and right postcentral gyrus,as well as elevated ReHo in the right putamen.FC analysis revealed significant alterations in FC between the caudate nucleus,putamen,and multiple brain regions in T2DM patients,with some of these FC changes significantly correlated with RT and accuracy(ACC)in the N-back task.Conclusion The decline in executive function in T2DM patients may be associated with abnormal neural activity in brain regions such as the striatum,salience network,and frontoparietal control network.FC further decreases under increased cognitive load.These findings provide evidence for the study of the neural mechanisms of executive function impairment in T2DM patients.