Employing bibliometric methods and adhering to principles of textual research， this study systematically investigated prescription source， formula name， composition evolution， dose evolution， origin， processing， ancient and modern applications of Xiaofengsan. Xiaofengsan， also known as Renshen Xiaofengsan and Chantui Xiaofengsan， was first recorded in the Taiping Huimin Hejijufang（hereafter referred to as Jufang） of the Southern Song dynasty. The formula composition included Schizonepetae Spica， Glycyrrhizae Radix et Rhizoma， Chuanxiong Rhizoma， Notoptery Rhizoma et Radix， Bombyx Batryticatus， Saposhnikoviae Radix， Poria， Cicadae Periostracum， Pogostemonis Herba， Ginseng Radix et Rhizoma， Magnoliae Officinalis Cortex and Citri Reticulatae Pericarpium， a total of 12 medicinal materials. In terms of the evolution of formula composition， formulas across dynasties largely aligned with those recorded in Jufang， with only minor variations in application. The results of the formula dosage research indicated that one dose of medication in Jufang corresponded to the following modern dosages：Schizonepetae Spica of 82.6 g， Glycyrrhizae Radix et Rhizoma of 82.6 g， Chuanxiong Rhizoma of 82.6 g， Notoptery Rhizoma et Radix of 82.6 g， Bombyx Batryticatus of 82.6 g， Saposhnikoviae Radix of 82.6 g， Poria of 82.6 g， Cicadae Periostracum of 82.6 g， Pogostemonis Herba of 82.6 g， Ginseng Radix et Rhizoma of 82.6 g， Magnoliae Officinalis Cortex of 20.65 g and Citri Reticulatae Pericarpium of 20.65 g， the origins of all the constituent drugs were consistent with the 2020 edition of Pharmacopoeia of the People's Republic of China. The results of the investigation into the decoction method indicated that the aforementioned drugs should be finely ground into powder（pass through the No.5 sieve）， and 8.26 g was taken for each dose， which was taken with the clear liquid obtained by steeping tea leaves in boiling water for several minutes. This mixture was administered three times daily， 30 min after meals. The ancient functional indications of this formula mainly involved dispelling wind-heat， eliminating pathogenic factors and regulating the middle Jiao. It primarily treated all wind-heat syndromes manifesting as skin diseases， predominantly affecting the upper body， especially the head and face. The diseases involved in modern applications were mostly dermatological diseases， including urticaria， eczema， atopic dermatitis and others. In this paper， by combing the relevant ancient literature， the key information of Xiaofengsan was textual researched， in order to provide reference for the modern application and development of this formula.

ObjectiveTo address the challenges of unstructured classical Chinese expressions， nested entity relationships， and limited annotated data in famous traditional Chinese medicine（TCM） case records， this study proposes a joint relation extraction framework that integrates data augmentation and entity mapping， aiming to support the construction of TCM diagnostic knowledge graphs and clinical pattern mining. MethodsWe developed an annotation structure for entities and their relationships in TCM case texts and applied a data augmentation strategy by incorporating multiple ancient texts to expand the relation extraction dataset. A cascade binary tagging framework for relation triple extraction（CasRel） model for TCM semantics was designed， integrating a pre-trained bidirectional encoder representations from transformers（BERT） layer for classical TCM texts to enhance semantic representation， and using a head entity-relation-tail entity mapping mechanism to address entity nesting and relation overlapping issues. ResultsExperimental results showed that the CasRel model， combining data augmentation and entity mapping， outperformed the pipeline-based Bert-Radical-Lexicon（BRL）-bidirectional long short-term memory（BiLSTM）-Attention model. The overall precision， recall， and F₁-score across 12 relation types reached 65.73%， 64.03%， and 64.87%， which represent improvements of 14.26%， 7.98%， and 11.21% compared to the BRL-BiLSTM-Attention model， respectively. Notably， the F₁-score for tongue syndrome relations increased by 22.68%（69.32%）， and the prescription-syndrome relations performed the best with the F₁-score of 70.10%. ConclusionThe proposed framework significantly improves the semantic representation and complex dependencies in TCM texts， offering a reusable technical framework for structured mining of TCM case records. The constructed knowledge graph can support clinical syndrome differentiation， prescription optimization， and drug compatibility， providing a methodological reference for TCM artificial intelligence research.

Objective To investigate the roles of glucose-regulated protein 75(GRP75)and voltage-dependent anion channel 1(VDAC1)in heroin-induced arrhythmia.Methods Based on transcriptomic data from primary myocardial cells treated with heroin and the GSE31821 dataset from the Gene Expression Omnibus(GEO),differentially expressed genes(DEGs)were identified using R software.Enrichment analysis of DEGs was performed.The protein-protein interaction(PPI)network was constructed using STRING database,and key genes were selected using Cytoscape.Molecular docking of key genes was performed using HDOCK,followed by in vivo valida-tion.A total of 60 SD rats were randomly divided into control,model,model+7 d,model+14 d,and model+21 d groups.A rat model of heroin addiction was established,and the expression levels of DEGs in myocardial tissue were assessed using immunohistochemical staining and quantitative real-time PCR.Results A total of 51 DEGs primarily enriched in muscle cell development,myofibrils,actin binding,arrhythmic right ventricular cardiomyopathy,calcium signaling,and apoptosis pathways were identified.Based on the PPI and Cytoscape analyses,GRP75 and VDAC1 were identified as key genes.Molecular docking indicated a strong interaction between GRP75 and VDAC1,which form a stable complex.The results of immunohistochemical staining and qRT-PCR showed that the expression levels of GRP75 and VDAC1 were significantly increased in the model group compared to those in the control group(P＜0.05),and their expres-sion increased(P＜0.05)with the intervention period of heroin in a time-dependent manner.Conclusion GRP75 and VDAC1 may con-tribute to heroin-induced arrhythmogenesis.

Objective:To explore the impulsivity characteristics of patients with attention deficit hyperactivity disorder(ADHD)comorbid with borderline personality disorder(BPD)and the mediating role of emotion regula-tion strategies.Methods:A total of 96 patients with ADHD meeting the diagnostic criteria of the American Diagnos-tic and Statistical Manual of Mental Disorders,Fourth Edition(DSM-Ⅳ)were enrolled,48 of whom had comorbid BPD.Impulsivity was assessed with the Barratt Impulse Scale(BIS)and the impulse control difficulty dimensions of Emotional Regulation Difficulty Scale(DERS).Emotion regulation strategies were evaluated with the Emotion Regulation Questionnaire(ERQ).Results:No significant differences were found between the ADHD with and with-out BPD group in cognitive impulsivity,motor impulsivity,or non-planning impulsivity as assessed with the BIS(Ps＞0.05).However,the ADHD with BPD group showed higher scores on the DERS impulse control difficulty subscale(P＜0.001)and less frequent use of cognitive reappraisal strategies(P＜0.001).Cognitive reappraisal partially mediated the relationship between ADHD with BPD and impulse control difficulties,with an effect size of 25.9％.Conclusion:ADHD patients comorbid with BPD exhibit heightened emotional impulsivity,which might be partially mediated by reduced use of cognitive reappraisal.

Glioblastoma (GBM) is the most aggressive malignant tumor of the adult central nervous system, with limited treatment options and poor prognosis. Radiotherapy (RT) remains a cornerstone of GBM treatment; however, tumor cell resistance to RT severely limits its efficacy. Recently, metabolic reprogramming (MR) has gained widespread attention as a critical mechanism enabling GBM cells to evade RT‐induced stress. In this review, the central roles of glucose, lipid, and amino acid metabolic reprogramming in GBM's resistance to RT were outlined, highlighting how GBM remodels metabolic pathways to enhance DNA damage repair, antioxidant defenses, and immune evasion after RT. Although combining metabolic inhibitors with RT has shown potential in improving GBM treatment outcomes, challenges such as overcoming the blood‐brain barrier and addressing tumor heterogeneity remain. The integration of nanomedicine‐based delivery systems and immunotherapy offers new hope for GBM treatment. Future research should focus on developing multidimensional, personalized metabolic targeting strategies, combined with immunotherapy and emerging technologies, to further improve therapeutic outcomes and survival rates for GBM patients.

Objective:To evaluate the clinical performance of high-risk human papillomavirus (HR-HPV) genotyping in cervical cancer screening.Methods:Between June and July 2017, a prospective cervical cancer screening cohort was established in Xiaye Town, Jiyuan City, Henan Province, China by recruiting 3 254 women aged 21 to 64 years. At baseline screening, cervical exfoliated cell specimens were collected for HR-HPV genotyping and liquid-based cytology testing. Follow-ups were conducted over a 3-year period, with cytology testing in the first and second years and both HR-HPV genotyping and cytology testing in the third year. Women meeting the referral criteria were referred for colposcopy, with cervical biopsy and histopathological diagnosis performed as necessary. The endpoint was defined as cervical intraepithelial neoplasia grade 2 (CIN2) or higher confirmed by histopathological diagnosis. The sensitivity and specificity for detecting CIN2 or higher lesions of HR-HPV genotyping were calculated, as well as the cumulative risk of developing CIN2 or higher lesions over the 4-year study period in women with different baseline HR-HPV genotyping results.Results:A total of 2 741 women were included in the statistical analysis. Baseline HR-HPV genotyping detected 453 HR-HPV positive cases (16.53%), including 98 HPV 16/18 positive cases (3.58%) and 355 other HR-HPV positive cases (12.95%). During the 4-year period, 83 cases of CIN2 or higher were diagnosed. The sensitivity and specificity of baseline HR-HPV positivity for CIN2 or higher were 89.16% (95% CI: 80.66%-94.19%) and 85.74% (95% CI: 84.36%-87.02%), respectively. The corresponding rates for HPV 16/18 positivity were 43.37% (95% CI: 33.24%-54.09%) and 97.67% (95% CI: 97.02%-98.18%). The 4-year cumulative absolute risk of CIN2 or higher was highest in the HPV 16/18 positive group (36.73%, 95% CI: 27.85%-46.62%), followed by other HR-HPV positive groups (10.70%, 95% CI: 7.87%-14.38%), and the HR-HPV negative group was the lowest (0.39%, 95% CI: 0.19%-0.76%). Conclusions:HR-HPV genotyping testing exhibits high sensitivity and specificity for detecting CIN2 or higher lesions in cervical cancer screening. It also provides a scientific basis for stratifying the individual risk of developing CIN2 or higher lesions to guide subsequent management. Therefore, the HR-HPV genotyping testing can be considered as an effective method for cervical cancer screening.

Objective:By analyzing the genetic risk of triglyceride-glucose index(Tyg)and insulin resistance(IR)for cardiovascular disease(CVD), to elucidate the extent to which the contribution of Tyg to the risk of CVD development is influenced by IR genetic risk.Methods:In this study, we selected data from a cohort of elderly people in the Kunshan community, screened 7, 385 individuals with both clinical and genomic data, and calculated the polygenic risk score of insulin resistance(IRPRS)for each participant based on publicly available IR genome-wide association data, and assessed the effect of genetic risk and Tyg level on the risk of developing CVD using a multivariate Cox proportional risk model.Calculating interactions to assess the effects of genetic risk and Tyg levels on the risk of developing CVD, the effects of Tyg tertile grouping and IRPRS on the risk of developing CVD were assessed using a multivariate Cox proportional risk model, and subgroup analyses were performed for gender to assess the effects of Tyg tertile grouping and IRPRS on the risk of developing CVD by gender.Results:In the univariate Cox model, Q3 and IRPRS with the highest TYG levels were significantly associated with the risk of CVD, respectively( HR=1.59, 95% CI: 1.33-1.89; P<0.001; HR=1.61, 95% CI: 1.18-2.20; P=0.003).After adjusting for multiple confounders, the Q3 Group with the highest TYG level was still significantly associated with the risk of CVD( HR=1.28, 95% CI: 1.05-1.57; P=0.014), the Association of TYG with the risk of CVD did not change significantly( HR=1.29, 95% CI: 1.05-1.57; P=0.014).We conducted a subgroup analysis by sex and found that among older men, 13, the highest levels of TYG and IRPRS were significantly associated with CVD risk, respectively( HR=1.70, 95% CI: 1.31.2.20; P<0.001; HR=1.98, 95% CI: 1.24-3.15; P=0.004).After adding IRPRS to the model, the Association of TYG with the risk of CVD remained unchanged( HR=1.69, 95% CI: 1.31-2.19; P<0.001).After adjusting for various confounders, Tyg remained significantly associated with the risk of CVD( HR=1.39, 95% CI: 1.04-1.88; P=0.028), the results showed that TYG remained significantly associated with the risk of CVD( HR=1.41, 95% CI: 1.05-1.90; P=0.023), and the association did not decrease.No Association of IRPRS with CVD risk was found in older women. Conclusions:IRPRS and TYG are the risk factors of CVD, and diet, exercise, drugs and other external factors on TYG are the main risk factors of CVD.For individuals with high genetic factors, the risk of CVD can still be reduced by lifestyle adjustments such as diet, exercise and drug intervention.

Objective:To investigate the prospective association between lifestyle and the risk for all-cause mortality in middle-aged and elderly residents in China.Methods:The data from China Health and Retirement Longitudinal Study were used. Baseline information about the lifestyle were collected through questionnaire survey and physical measurements, and the mortality data were obtained through surveys conducted at 2-3 year intervals. A total of 5 436 study participants were included. A comprehensive lifestyle including smoking, alcohol consumption, sleep, BMI and physical activity was constructed, and a multivariate-adjusted Cox proportional hazards regression model was used to estimate the association between lifestyle and the risk for all-cause mortality.Results:During the follow-up of average 8.2 years, 695 deaths were recorded. The comprehensive lifestyle score was linearly associated with the risk for all-cause mortality. Compared with the study participants with comprehensive lifestyle score of 0-1, those with score of 2-5 all had lower risk for all-cause mortality, with HRs of 0.78 (95% CI: 0.62-0.98), 0.56 (95% CI: 0.44-0.72), 0.36 (95% CI:0.27-0.48), and 0.33 (95% CI: 0.21-0.52), respectively. The results of Cox proportional hazards regression model analysis of single lifestyle showed that compared with those with unhealthy lifestyles, the HRs of all-cause mortality for study participants who never smoked, had moderate alcohol consumption, had appropriate night sleep, maintained healthy body weight and kept active physical activity were 0.70 (95% CI: 0.57-0.84), 0.76 (95% CI: 0.64-0.90), 0.79 (95% CI: 0.67-0.94), 0.73 (95% CI: 0.62-0.87), and 0.68 (95% CI: 0.58-0.80), respectively. Conclusions:Keeping healthy lifestyles can significantly reduce the risk for all-cause mortality in middle-aged and elderly residents China. The higher the healthy lifestyle level, the lower the risk for all-cause mortality.

Recently, the number of artificial intelligence methods used to develop clinical risk prediction models has rapidly increased. To ensure the value of clinical prediction model research, researchers must report the research content transparently, completely, and accurately. Updated Guidance for Reporting Clinical Prediction Models that Use Regression or Machine Learning Methods (TRIPOD+AI) was released in 2024 and covers a checklist of 27 major items. It aims to promote the complete reporting of global clinical prediction model research and facilitate research evaluation, model evaluation, and model implementation. This article interprets and compares aspects such as the formulation process, checklist content, applicable scenarios, and advantages of TRIPOD+AI, as well as the original Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) checklist. It also analyzes an example of predicting the depression of elderly patients using artificial intelligence methods, providing references for researchers to standardize the reporting of clinical prediction models.

Objective:To evaluate the effect of acupuncture on postoperative delirium (POD) in diabetic patients undergoing surgery under general anesthesia.Methods:In this randomized controlled trial, 92 diabetic patients of either sex, aged 30-80 yr, with a body mass index of 18-28 kg/m 2, of American Society of Anesthesiologists Physical Status classification Ⅱ or Ⅲ, scheduled for elective surgery under general anesthesia, were divided into 2 groups ( n=46 each) using a table of random numbers: control group (group C) and acupuncture group (group A). Group A received acupuncture at the Baihui (GV20), Shenting (GV24) and Sishencong (EX-HN1) acupoints before anesthesia. The needles were retained for 30 min, with manual stimulation applied every 10 min for 10 s each time. After 4 stimulations, routine anesthesia was carried out. Group C received routine anesthesia only. Regional cerebral oxygen saturation was recorded on admission to the operating room (T 0), after anesthesia induction (T 1), at the start of surgery (T 2), at the end of surgery (T 3), and immediately after tracheal extubation (T 4). The POD developed within 3 days after surgery was assessed. The occurrence of needle-related adverse effects such as fainting, subcutaneous bleeding, and local paresthesia was recorded. Results:Compared with group C, the incidence of POD was significantly reduced, and the regional cerebral oxygen saturation was increased at T 1, 4 in group A ( P<0.05). Conclusions:Acupuncture can decrease the development of POD in diabetic patients undergoing surgery under general anesthesia, which is related to an increase in regional cerebral oxygen saturation.