BACKGROUND:Studies have shown that rheumatoid arthritis and osteoporosis are positively correlated,but the causal relationship and related mechanisms have not yet been confirmed.With the cross-fertilization of computer science and life sciences,Mendelian randomization and bioinformatics analyses based on genome-wide association study(GWAS)and transcriptome sequencing data can assess the causal relationship between two diseases,explore the related mechanisms,and mine the therapeutic targets,which will be beneficial to the precision treatment of rheumatoid arthritis combined with osteoporosis.OBJECTIVE:To explore the causal relationship between rheumatoid arthritis and osteoporosis using two-sample Mendelian randomization and to mine potential co-morbid targets and potential targeted drugs through summary-data-based Mendelian randomization and bioinformatics analyses,aiming to provide theoretical basis for mechanism exploration and precision treatment in the field of rheumatoid arthritis combined with osteoporosis.METHODS:(1)Firstly,GWAS data of rheumatoid arthritis,osteoporosis,and cis-expression quantitative trait locus(cis-eQTL)in Asian and European populations were downloaded from the GWAS Catalog,IEU Open GWAS,FinnGen,and eQTLGen databases,and were used for two-sample Mendelian randomization analysis and summary-data-based Mendelian randomization analysis.(2)Transcriptome sequencing data of rheumatoid arthritis(GSE93272 and GSE15573)were downloaded from the GEO database for bioinformatics analysis.(3)Subsequently,forward and inverse Mendelian randomization analyses between rheumatoid arthritis and osteoporosis were performed,and inverse variance weighted was used as the main metric for the analyses,and the results were corroborated with MR Egger,simple mode,weighted median and weighted mode.(4)Then,the genes closely related to rheumatoid arthritis and osteoporosis were identified based on the summary-data-based Mendelian randomization analysis,and the co-disease targets of rheumatoid arthritis and osteoporosis were mined based on cross-analysis.Meanwhile,the biological functions of the co-morbid targets were verified based on bioinformatics analysis and cellular experiments.(5)In addition,a rheumatoid arthritis risk prediction nomogram was constructed based on DYRK2,and its prediction performance was verified by receiver operating characteristic curve,correction curve and decision curve.Finally,the target potential drugs were mined based on Enrichr database and molecular docking was performed.RESULTS AND CONCLUSION:(1)Forward Mendelian randomization analysis of rheumatoid arthritis and osteoporosis showed statistically significant results except for GCST90044540 and GCST90086118,and all other results indicated a significant causal relationship and positive correlation between rheumatoid arthritis and osteoporosis.(2)Inverse Mendelian randomization analysis suggested that no significant causal relationship was seen between osteoporosis and rheumatoid arthritis.(3)Summary-data-based Mendelian randomization analysis identified a total of 412 and 344 genes positively associated with rheumatoid arthritis and osteoporosis,and 421 and 347 genes negatively associated.Based on the cross-analysis,26 co-morbid genes were subsequently obtained.Among them,DYRK2 was a potential therapeutic target,and subsequent bioinformatics analysis and cellular experiments confirmed its important role in the progression of rheumatoid arthritis and osteoporosis.(4)Furthermore,the constructed nomogram has excellent predictive performance.Finally,four potential DYRK2-targeting drugs(undecanoic acid,metyrapone,JNJ-38877605,and ACA)were discovered and molecular docking also demonstrated reliable targeting ability.(5)In conclusion,based on GWAS data from Asian and European populations,we successfully demonstrated that rheumatoid arthritis and osteoporosis are causally related at the genetic level,DYRK2 is a potential therapeutic target,and four small molecules are potential target drugs.

OBJECTIVE To evaluate the clinical comprehensive value of four Chinese patent medicines （Xuezhikang， Zhibitai， Zhibituo， Jiangzhiling） in the treatment of hyperlipidemia， and provide a reference for rational clinical drug use. METHODS A clinical comprehensive evaluation index system was established in accordance with the Evidence and Value： Impact on Decision-Making （EVIDEM） framework and Technical Guideline for Clinical Comprehensive Evaluation of Cardiovascular Drugs （2022 edition， trial implementation）. CNKI， Wanfang data， VIP， PubMed， ScienceDirect， Embase and official websites were retrieved to collect the literature such as drug instructions， guidelines and consensus statements， and systematic reviews/meta-analyses for the four Chinese patent medicines. A comprehensive evaluation was conducted from seven dimensions： effectiveness， safety， economy， suitability， accessibility， innovation and characteristics of traditional Chinese medicine. RESULTS This evaluation index system included 7 first-level indicators， 15 second-level indicators and 30 third-level indicators. Xuezhikang achieved the highest comprehensive evaluation score of 81.4 points， and was classified as class Ⅰ recommendation. Zhibitai with 76.0 points and Zhibituo with 60.9 points were both classified as class Ⅱ recommendation. Jiangzhiling with 48.8 points was classified as class Ⅳ recommendation. CONCLUSIONS Xuezhikang demonstrates the optimal clinical comprehensive value for treating hyperlipidemia. Zhibitai exhibits certain advantages in terms of safety and characteristics of traditional Chinese medicine； Zhibituo shows a moderate performance in all aspects； Jiangzhiling has a relatively low score. Appropriate medicines can be selected clinically according to actual conditions and patients’ characteristics.

BACKGROUND:Studies have shown that rheumatoid arthritis and osteoporosis are positively correlated,but the causal relationship and related mechanisms have not yet been confirmed.With the cross-fertilization of computer science and life sciences,Mendelian randomization and bioinformatics analyses based on genome-wide association study(GWAS)and transcriptome sequencing data can assess the causal relationship between two diseases,explore the related mechanisms,and mine the therapeutic targets,which will be beneficial to the precision treatment of rheumatoid arthritis combined with osteoporosis.OBJECTIVE:To explore the causal relationship between rheumatoid arthritis and osteoporosis using two-sample Mendelian randomization and to mine potential co-morbid targets and potential targeted drugs through summary-data-based Mendelian randomization and bioinformatics analyses,aiming to provide theoretical basis for mechanism exploration and precision treatment in the field of rheumatoid arthritis combined with osteoporosis.METHODS:(1)Firstly,GWAS data of rheumatoid arthritis,osteoporosis,and cis-expression quantitative trait locus(cis-eQTL)in Asian and European populations were downloaded from the GWAS Catalog,IEU Open GWAS,FinnGen,and eQTLGen databases,and were used for two-sample Mendelian randomization analysis and summary-data-based Mendelian randomization analysis.(2)Transcriptome sequencing data of rheumatoid arthritis(GSE93272 and GSE15573)were downloaded from the GEO database for bioinformatics analysis.(3)Subsequently,forward and inverse Mendelian randomization analyses between rheumatoid arthritis and osteoporosis were performed,and inverse variance weighted was used as the main metric for the analyses,and the results were corroborated with MR Egger,simple mode,weighted median and weighted mode.(4)Then,the genes closely related to rheumatoid arthritis and osteoporosis were identified based on the summary-data-based Mendelian randomization analysis,and the co-disease targets of rheumatoid arthritis and osteoporosis were mined based on cross-analysis.Meanwhile,the biological functions of the co-morbid targets were verified based on bioinformatics analysis and cellular experiments.(5)In addition,a rheumatoid arthritis risk prediction nomogram was constructed based on DYRK2,and its prediction performance was verified by receiver operating characteristic curve,correction curve and decision curve.Finally,the target potential drugs were mined based on Enrichr database and molecular docking was performed.RESULTS AND CONCLUSION:(1)Forward Mendelian randomization analysis of rheumatoid arthritis and osteoporosis showed statistically significant results except for GCST90044540 and GCST90086118,and all other results indicated a significant causal relationship and positive correlation between rheumatoid arthritis and osteoporosis.(2)Inverse Mendelian randomization analysis suggested that no significant causal relationship was seen between osteoporosis and rheumatoid arthritis.(3)Summary-data-based Mendelian randomization analysis identified a total of 412 and 344 genes positively associated with rheumatoid arthritis and osteoporosis,and 421 and 347 genes negatively associated.Based on the cross-analysis,26 co-morbid genes were subsequently obtained.Among them,DYRK2 was a potential therapeutic target,and subsequent bioinformatics analysis and cellular experiments confirmed its important role in the progression of rheumatoid arthritis and osteoporosis.(4)Furthermore,the constructed nomogram has excellent predictive performance.Finally,four potential DYRK2-targeting drugs(undecanoic acid,metyrapone,JNJ-38877605,and ACA)were discovered and molecular docking also demonstrated reliable targeting ability.(5)In conclusion,based on GWAS data from Asian and European populations,we successfully demonstrated that rheumatoid arthritis and osteoporosis are causally related at the genetic level,DYRK2 is a potential therapeutic target,and four small molecules are potential target drugs.

Objective To analyze the predictive value of the combined application of triglyceride-glucose index (TyG) and triglyceride-glucose-body mass index (TyG-BMI) for the severity of coronary artery lesions in postmenopausal patients with coronary heart disease (CHD). Methods Menopausal women who were diagnosed by coronary angiography and received treatment in the cardiovascular department were selected as the research subjects. According to the Gensini score, the patients were divided into a moderate group (n=151) and a severe group (n=203). The clinical indexes of the two groups were compared and ROC analysis was used to predict the efficacy. Results The BMI, age, hypertension rate, WBC, PLT, NEUT, TC, TG, LCI, TyG, and TyG‑BMI in the severe group were significantly higher than those in the moderate group, while ALB was significantly lower than that in the moderate group (P<0.05). Multivariate logistic regression showed that age, hypertension, WBC, TyG, and TyG‑BMI were independent risk factors for severe coronary artery disease in postmenopausal women (P<0.05). ROC curve analysis showed that the AUC of TyG was 0.745, the AUC of TyG‑BMI was 0.797, and the AUC of TyG combined with TyG‑BMI was 0.803, all showing good predictive performance. Conclusion TyG and TyG‑BMI are effective indicators for predicting the severity of coronary artery disease in postmenopausal CHD patients. The combination of the two can further improve predictive efficacy, providing a simple and economical reference for early clinical risk stratification.

Due to the immaturity of visualization and quantitative analysis methods,the utilization rate of level 3 characteristics is seriously insufficient.In this work,based on the wet-membrane method and scanning electrochemical microscopy(SECM),and the introduction of conductive black ink to enhance the visualization effect,a systematic level 3 feature quantitative method was developed.Firstly,the feasibility and effect of the multi-level characteristics extraction strategy of latent fingerprints was investigated.Then,the influences of various deposition conditions on the level 3 features were explored.The results showed that the higher the deposition pressure,the wider the ridges,and the smaller the pore size.Moreover,excessive oil content could cause the pore size to be smaller and even been covered.Subsequently,the quantitative method was established from various pore characteristics such as pore number,pore activity,pore size,pore-to-pore distance and pore-to-pore angle.The stability of the level 3 features(pore number,pore-to-pore distance and pore-to-pore angle)was confirmed via repeated experiments on the same fingerprint region.After stability test,the recognition ability of three indicators was investigated for different fingerprints,verifying the uniqueness of pore-to-pore distance and pore-to-pore angle.Finally,a multiple recognition strategy was proposed that combined frequency distribution fitting curves for pore-to-pore distance and angle with other level 3 details,and was successfully applied to incomplete fingerprint recognition.This ink-enhanced optical and electrochemical extraction method and quantitative analysis provided a new path for fingerprint recognition.

Objective:To evaluate the anti-reflux effect of digestive tract reconstruction using esophageal-tubular gastric asymmetric anastomosis after radical resection of esophageal and esophagogastric junction cancer.Methods:The main steps were as follows:(1)oblique incision of the lower esophagus;(2)curved incision of the tubular anterior gastric wall;(3)the lower end of the esophagus was anastomosed to the tubular gastric incision with a 90-degree torsion; (4)The anterior wall of the anastomosis was reinforced with a transverse-inverted suture,the posterior wall with a folded suture,and the corners of the gastric stump were buried with sutures.The anastomosis operation time,postoperative complications and postoperative hospital stay were recorded;the reconstructed structure and anti-reflux effect of the anastomosis were observed by digestive tract radiography,gastroscopy and follow-up investigation.Results:The Department of Gastrointestinal and Thoracic Surgery of Huaian First People's Hospital, affiliated to Nanjing Medical University, treated 5 patients of esophagogastric junction cancer and 20 esophageal cancer cases between August 2022 and November 2024, including 19 men and 6 women, with a mean age of (66.7±7.4) years. The mean anastomosis time was (35.4±5.9) minutes, the intraoperative blood loss was (117.6±33.4) ml and the mean postoperative hospital stay was(16.6±5.2) days, with no complications such as anastomotic leakage and bleeding. Postoperative digestive tract radiography (Trendelenburg position)showed that all the patients had no contrast reflux,gastroscopy showed no signs of reflux esophagitis and bile reflux gastritis, the anastomosis showed an inverted whiskers valve-like structure. The median follow-up time was (16.8±6.3) months, and all patients had no reflux symptoms such as acid reflux and belching,and no acid suppressive medication was needed.Conclusion:The esophageal-tubular gastric asymmetric anastomosis is a safe and effective antireflux reconstruction technique.

Objective To explore the potential of CS-AI technique in accelerating cranial three-dimensional double inversion recovery(3D DIR)sequence imaging.Methods Twenty-six healthy volunteers were prospectively recruited for brain sagittal 3D DIR sequence scanning.The 3D DIR sequences were accelerated with four different acceleration factor(AF)(4,6,8,10)and reconstructed using the traditional compressed sensing(CS)algorithm and a new CS-AI algorithm.Subjective image quality was assessed by two observers using a 5-point Likert scale.Objective image quality was evaluated by calculating contrast(CN)and contrast-to-noise ratio(CNR).Firstly,using CS 4 as the standard,the optimal CS AF was derived after comparing the CN,CNR and subjective scores of CS 4 with those of CS 6,8 and 10 images in a comprehensive judgement,and then further comparing the optimal CS AF with images of CS-AI with different AF to validate the efficacy of the CS-AI,and to select the final optimal CS-AI AF.Results The comparison results between CS 4 and different CS AF indicated that CS 6 was selected as the optimal AF for CS.In further comparisons between CS and different CS-AI AF,the CS-AI technique outperformed the CS technique overall.CS-AI 8 was the maximum applicable AF.Conclusion The CS-AI is overall even better in terms of image quality with higher acceleration potential than the CS.The CS-AI 8 serves as the optimal AF and reduces scanning times by up to 50％while maintaining image quality.

In recent decades,the incidence of human papillomavirus(HPV)-associated oropharyngeal squamous cell carcinoma(OPSCC)has shown a marked increase.Significant changes have also occurred in the OPSCC diagnosis and treatment paradigm.Deter-mining HPV status prior to treatment is now essential,and radiotherapy/chemotherapy,immunotherapy,and minimally invasive surgical techniques have progressively emerged as key modalities for managing OPSCC.However,alongside these paradigm shifts,a comprehen-sive technical consensus guiding the entire diagnostic and therapeutic process for OPSCC patients is currently lacking.Given China's large population base and the rising incidence of OPSCC,an expert panel convened to develop a clinical technical consensus on OPSCC diagno-sis and management tailored to China's specific context.This consensus aims to further enhance and standardize understanding of OPSCC management techniques among relevant healthcare professionals.

Acupuncture is an ancient treatment method used in traditional Chinese medicine and has been popularized worldwide. Over the past decade, there has been an increase in the amount of acupuncture research, mostly comprised of randomized controlled trials (RCTs) that aimed to answer the question on the efficacy of acupuncture. However, poor methodology and low replicability in these acupuncture RCTs have resulted in uncertainty about the efficacy of acupuncture. In this review, current advancements and challenges in acupuncture RCTs, regarding the methodological aspects of randomization, blinding, sham acupuncture and quality of reporting, were discussed. While there have been advancements in various aspects, current acupuncture RCTs still face pressing issues such as inadequate randomization and blinding, unviable sham acupuncture controls, and poor reporting quality. Given these limitations, this review seeks to identify the methodological problems that are responsible for these problems and to suggest solutions that could help to overcome them so as to improve the quality of future studies evaluating the efficacy of acupuncture. Please cite this article as: Seetoh WS, Lim RQR, Xu RB, Sun MX, Zhang P, Wang MN. Advancements and challenges of acupuncture randomized controlled trials. J Integr Med. 2025; 23(4): 333-343.
Acupuncture Therapy ; Humans ; Randomized Controlled Trials as Topic/methods* ; Research Design

OBJECTIVE: To investigate the associations between eight serum per- and polyfluoroalkyl substances (PFASs) and regional fat depots, we analyzed the data from the National Health and Nutrition Examination Survey (NHANES) 2011-2018 cycles. METHODS: Multiple linear regression models were developed to explore the associations between serum PFAS concentrations and six fat compositions along with a fat distribution score created by summing the concentrations of the six fat compositions. The associations between structurally grouped PFASs and fat distribution were assessed, and a prediction model was developed to estimate the ability of PFAS exposure to predict obesity risk. RESULTS: Among females aged 39-59 years, trunk fat mass was positively associated with perfluorooctane sulfonate (PFOS). Higher concentrations of PFOS, perfluorohexane sulfonate (PFHxS), perfluorodecanoate (PFDeA), perfluorononanoate (PFNA), and n-perfluorooctanoate (n-PFOA) were linked to greater visceral adipose tissue in this group. In men, exposure to total perfluoroalkane sulfonates (PFSAs) and long-chain PFSAs was associated with reductions in abdominal fat, while higher abdominal fat in women aged 39-59 years was associated with short-chain PFSAs. The prediction model demonstrated high accuracy, with an area under the curve (AUC) of 0.9925 for predicting obesity risk. CONCLUSION PFAS exposure is associated with regional fat distribution, with varying effects based on age, sex, and PFAS structure. The findings highlight the potential role of PFAS exposure in influencing fat depots and obesity risk, with significant implications for public health. The prediction model provides a highly accurate tool for assessing obesity risk related to PFAS exposure.
Humans ; Fluorocarbons/blood* ; Female ; Adult ; Middle Aged ; Male ; Environmental Pollutants/blood* ; Abdominal Fat ; Nutrition Surveys ; Alkanesulfonic Acids/blood* ; Obesity ; Environmental Exposure