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.

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 investigate the learning curve of real-life vaginal delivery,including its difficult steps and influencing factors,to optimize the future training of vaginal delivery for residents in department of obstetrics and gynecology.Methods From 25 Sep 2020 to 12 Mar 2022,OBGYN residents without previous experiences in vaginal delivery were prospectively enrolled in Obstetrics and Gynecology Hospital,Fudan University.Residents performed normal vaginal delivery under the supervision of senior obstetricians and midwives.The performance score(PS)of vaginal delivery and its 9 steps were evaluated via a questionnaire fulfilled by the supervisor once each delivery was finished.Logistic regression models were performed for univariate and multivariate analyses to evaluate the factors that might be correlated with the PS.Results Eventually,233 deliveries performed by 60 residents were analyzed.Results showed that more than 10 deliveries were needed for 70%of residents to obtain minimal competence of vaginal delivery.Perineal protection,delivery of the fetal head,delivery of the fetal shoulders and repair of episiotomy or laceration were found to be the most difficult steps,which required more practices to achieve minimal competence level.Univariate analyses showed the delivery experience,the times of observation/simulation/training,and humanistic care skills might influence the total PS(P<0.05).However,only delivery experience(OR=1.43,95%CI:1.22-1.67)and the times of observation(OR=1.02,95%CI:1.00-1.04)were found to be independently correlated with the total PS in multivariate analyses.Conclusion More than 10 real-life practices were required to achieve the minimal competence of normal vaginal delivery.Enhancing the training on the four difficult steps of vaginal delivery might improve the learning efficiency when delivery opportunities are limited.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

OBJECTIVE: Huachansu injection (HCSI), a promising anti-cancer Chinese medicine injection, has been reported to have the potential for reducing the toxicity of chemotherapy and improving the quality of life for colorectal cancer (CRC) patients. The objective of this study is to explore the synergistic and detoxifying effects of HCSI when used in combination with irinotecan (CPT-11). METHODS: To investigate the effect of HCSI on anti-CRC efficacy and intestinal toxicity of CPT-11, we measured changes in the biological behavior of LoVo cells in vitro, and anti-tumor effects in LoVo cell xenograft nude mice models in vivo. Meanwhile, the effect of HCSI on intestinal toxicity and the uridine diphosphate-glucuronosyltransferase 1A1 (UGT1A1) expression was investigated in the CPT-11-induced colitis mouse model. Subsequently, we measured the effect of HCSI and its 13 constituent bufadienolides on the expression of UGT1A1 and organic anion transporting polypeptides 1B3 (OATP1B3) in HepG2 cells. RESULTS: The combination index (CI) results showed that the combination of HCSI and CPT-11 exhibited a synergistic effect (CI < 1), which significantly suppressing the LoVo cell migration, enhancing G2/M and S phase arrest, and inhibiting tumor growth in vivo. Additionally, the damage to intestinal tissues was attenuated by HCSI in CPT-11-induced colitis model, while the increased expression of UGT1A1 in HepG2 cells and in mouse was observed. CONCLUSION The co-therapy with HCSI alleviated the intestinal toxicity induced by CPT-11 and exerted an enhanced anti-CRC effect. The detoxifying mechanism may be related to the increased expression of UGT1A1 and OATP1B3 by HCSI and its bufadienolides components. The findings of this study may serve as a theoretical insights and strategies to improve CRC patient outcomes. Please cite this article as: Jiang B, Meng ZY, Hu YJ, Chen JJ, Zong L, Xu LY, Zhang XQ, Zhang JX, Han YL. Huachansu injection enhances anti-colorectal cancer efficacy of irinotecan and alleviates its induced intestinal toxicity through upregulating UGT1A1-OATP1B3 expression in vitro and in vivo. J Integr Med. 2025; 23(5):576-590.
Irinotecan/therapeutic use* ; Animals ; Glucuronosyltransferase/genetics* ; Humans ; Colorectal Neoplasms/metabolism* ; Drugs, Chinese Herbal/therapeutic use* ; Mice, Nude ; Mice ; Up-Regulation/drug effects* ; Male ; Xenograft Model Antitumor Assays ; Mice, Inbred BALB C ; Hep G2 Cells ; Cell Line, Tumor ; Intestines/drug effects* ; Amphibian Venoms

This study aims to explore the pharmacodynamic material basis of Jinbei Oral Liquid(JBOL) against idiopathic pulmonary fibrosis(IPF) based on serum pharmacochemistry and network pharmacology. The ultra-high performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry(UHPLC-Q-TOF-MS/MS) technology was employed to analyze and identify the components absorbed into rat blood after oral administration of JBOL. Combined with network pharmacology, the study explored the pharmacodynamic material basis and potential mechanism of JBOL against IPF through protein-protein interaction(PPI) network construction, "component-target-pathway" analysis, Gene Ontology(GO) functional enrichment, and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis. First, a total of 114 compounds were rapidly identified in JBOL extract according to the exact relative molecular mass, fragment ions, and other information of the compounds with the use of reference substances and a self-built compound database. Second, on this basis, 70 prototype components in blood were recognized by comparing blank serum with drug-containing serum samples, including 28 flavonoids, 25 organic acids, 4 saponins, 4 alkaloids, and 9 others. Finally, using these components absorbed into blood as candidates, the study obtained 212 potential targets of JBOL against IPF. The anti-IPF mechanism might involve the action of active ingredients such as glycyrrhetinic acid, cryptotanshinone, salvianolic acid B, and forsythoside A on core targets like AKT1, TNF, and ALB and thereby the regulation of multiple signaling pathways including PI3K/AKT, HIF-1, and TNF. In conclusion, JBOL exerts the anti-IPF effect through multiple components, targets, and pathways. The results would provide a reference for further study on pharmacodynamic material basis and pharmacological mechanism of JBOL.
Drugs, Chinese Herbal/pharmacokinetics* ; Animals ; Tandem Mass Spectrometry ; Network Pharmacology ; Rats ; Chromatography, High Pressure Liquid ; Rats, Sprague-Dawley ; Male ; Idiopathic Pulmonary Fibrosis/metabolism* ; Humans ; Administration, Oral ; Protein Interaction Maps/drug effects* ; Signal Transduction/drug effects*

The chemical components of Carthami Flos were investigated by using macroporous resin, silica gel column chromatography, reversed-phase octadecylsilane(ODS) column chromatography, Sephadex LH-20, and semi-preparative high-performance liquid chromatography(HPLC). The planar structures of the compounds were established based on their physicochemical properties and ultraviolet-visible(UV-Vis), infrared(IR), high-resolution electrospray ionization mass spectrometry(HR-ESI-MS), and nuclear magnetic resonance(NMR) spectroscopic technology. The absolute configurations were determined by comparing the calculated and experimental electronic circular dichroism(ECD). Six flavonoid C-glycosides were isolated from the 30% ethanol elution fraction of macroporous resin obtained from the 95% ethanol extract of Carthami Flos, and identified as saffloquinoside F(1), 5-hydroxysaffloneoside(2), iso-5-hydroxysaffloneoside(3), isosafflomin C(4), safflomin C(5), and vicenin 2(6). Among these, the compounds 1 to 3 were new chalcone C-glycosides. The compounds 1, 2, 4, and 5 could significantly increase the viability of H9c2 cardiomyocytes damaged by oxygen-glucose deprivation/reoxygenation(OGD/R) at a concentration of 50 μmol·L~(-1), showing their good cardioprotective activity.
Glycosides/pharmacology* ; Flowers/chemistry* ; Drugs, Chinese Herbal/pharmacology* ; Carthamus tinctorius/chemistry* ; Chalcones/pharmacology* ; Animals

PURPOSE: The rate of complications among patients undergoing surgery has increased due to infection with SARS-CoV-2 and other variants of concern. However, Omicron has shown decreased pathogenicity, raising questions about the risk of postoperative complications among patients who are infected with this variant. This study aimed to investigate complications and related factors among patients with recent Omicron infection prior to undergoing orthopedic surgery. METHODS: A historical control study was conducted. Data were collected from all patients who underwent surgery during 2 distinct periods: (1) between Dec 12, 2022 and Jan 31, 2023 (COVID-19 positive group), (2) between Dec 12, 2021 and Jan 31, 2022 (COVID-19 negative control group). The patients were at least 18 years old. Patients who received conservative treatment after admission or had high-risk diseases or special circumstances (use of anticoagulants before surgery) were excluded from the study. The study outcomes were the total complication rate and related factors. Binary logistic regression analysis was used to identify related factors, and odds ratio (OR) and 95% confidence interval (CI) were calculated to assess the impact of COVID-19 infection on complications. RESULTS: In the analysis, a total of 847 patients who underwent surgery were included, with 275 of these patients testing positive for COVID-19 and 572 testing negative. The COVID-19-positive group had a significantly higher rate of total complications (11.27%) than the control group (4.90%, p < 0.001). After adjusting for relevant factors, the OR was 3.08 (95% CI: 1.45-6.53). Patients who were diagnosed with COVID-19 at 3-4 weeks (OR = 0.20 (95% CI: 0.06-0.59), p = 0.005), 5-6 weeks (OR = 0.16 (95% CI: 0.04-0.59), p = 0.010), or ≥7 weeks (OR = 0.26 (95% CI: 0.06-1.02), p = 0.069) prior to surgery had a lower risk of complications than those who were diagnosed at 0-2 weeks prior to surgery. Seven factors (age, indications for surgery, time of operation, time of COVID-19 diagnosis prior to surgery, C-reactive protein levels, alanine transaminase levels, and aspartate aminotransferase levels) were found to be associated with complications; thus, these factors were used to create a nomogram. CONCLUSION Omicron continues to be a significant factor in the incidence of postoperative complications among patients undergoing orthopedic surgery. By identifying the factors associated with these complications, we can determine the optimal surgical timing, provide more accurate prognostic information, and offer appropriate consultation for orthopedic surgery patients who have been infected with Omicron.
Humans ; COVID-19/complications* ; Male ; Female ; Middle Aged ; Postoperative Complications/epidemiology* ; SARS-CoV-2 ; Orthopedic Procedures/adverse effects* ; Aged ; Nomograms ; Adult ; Retrospective Studies ; Risk Factors

Recent data suggest that vascular endothelial growth factor receptor inhibitor (VEGFRi) can enhance the anti-tumor activity of the anti-programmed cell death-1 (anti-PD-1) antibody in colorectal cancer (CRC) with microsatellite stability (MSS). However, the comparison between this combination and standard third-line VEGFRi treatment is not performed, and reliable biomarkers are still lacking. We retrospectively enrolled MSS CRC patients receiving anti-PD-1 antibody plus VEGFRi (combination group, n=54) or VEGFRi alone (VEGFRi group, n=32), and their efficacy and safety were evaluated. We additionally examined the immune characteristics of the MSS CRC tumor microenvironment (TME) through single-cell and spatial transcriptomic data, and an MSS CRC immune cell-related signature (MCICRS) that can be used to predict the clinical outcomes of MSS CRC patients receiving immunotherapy was developed and validated in our in-house cohort. Compared with VEGFRi alone, the combination of anti-PD-1 antibody and VEGFRi exhibited a prolonged survival benefit (median progression-free survival: 4.4 vs. 2.0 months, P=0.0024; median overall survival: 10.2 vs. 5.2 months, P=0.0038) and a similar adverse event incidence. Through single-cell and spatial transcriptomic analysis, we determined ten MSS CRC-enriched immune cell types and their spatial distribution, including naive CD4⁺ T, regulatory CD4⁺ T, CD4⁺ Th17, exhausted CD8⁺ T, cytotoxic CD8⁺ T, proliferated CD8⁺ T, natural killer (NK) cells, plasma, and classical and intermediate monocytes. Based on a systemic meta-analysis and ten machine learning algorithms, we obtained MCICRS, an independent risk factor for the prognosis of MSS CRC patients. Further analyses demonstrated that the low-MCICRS group presented a higher immune cell infiltration and immune-related pathway activation, and hence a significant relation with the superior efficacy of pan-cancer immunotherapy. More importantly, the predictive value of MCICRS in MSS CRC patients receiving immunotherapy was also validated with an in-house cohort. Anti-PD-1 antibody combined with VEGFRi presented an improved clinical benefit in MSS CRC with manageable toxicity. MCICRS could serve as a robust and promising tool to predict clinical outcomes for individual MSS CRC patients receiving immunotherapy.
Humans ; Colorectal Neoplasms/drug therapy* ; Male ; Female ; Immunotherapy ; Middle Aged ; Aged ; Tumor Microenvironment/immunology* ; Retrospective Studies ; Microsatellite Instability ; Transcriptome ; Single-Cell Analysis ; Programmed Cell Death 1 Receptor/immunology* ; Gene Expression Profiling ; Immune Checkpoint Inhibitors/therapeutic use* ; Adult ; Receptors, Vascular Endothelial Growth Factor/antagonists & inhibitors*

Objective To evaluate the influence of the wearing position of dosimeters outside lead aprons on effective dose estimation for interventional radiology workers, analyze the differences between single and double dosimeter methods in effective dose estimation, and provide a reference for the personal dose monitoring of interventional radiology workers. Methods This study employed a combined approach of on-site monitoring and Monte Carlo simulation to evaluate the impact of the wearing position of dosimeters outside lead aprons on effective dose estimation, as well as the differences between effective doses measured using single and double dosimeters. Interventional radiology workers wore dosimeters at three positions: the neck outside the lead collar, the left chest outside the lead apron, and inside the lead apron. Effective doses were estimated using the single and double dosimeter methods specified in GBZ 128-2019 Specifications for individual monitoring of occupational external exposure, and the impact of different wearing positions on the estimation results was compared. Geant4 Monte Carlo simulations were used to model dose distributions at the neck outside the lead collar and at the left chest outside the lead apron for operators performing cardiovascular interventions under tube voltages of 70, 80, 90, and 100 kVp and exposure angles of posteroanterior (PA), anteroposterior (AP), and left anterior oblique 45° (LAO45°) positions. The study assessed the impact of dosimeter wearing position on effective dose estimation. Results Monte Carlo simulations demonstrated that neck doses consistently exceeded left chest doses across different tube voltages and exposure angles, with neck-to-chest dose ratios of 0.80-0.90. Under identical tube voltage conditions, AP showed the highest doses, followed by LAO45°, and PA demonstrated the lowest doses. The single and double dosimeter methods exhibited consistent patterns in effective dose estimation. Single dosimeter method generally yielded higher effective doses with relative deviations of 9.9% to 83%, though these deviations decreased under high tube voltages. Field monitoring data indicated that most interventional radiology workers maintained relative deviations between single and double dosimeter calculations below 6%, with neck-to-chest dose ratios of 0.95-1.1. The estimation patterns remained consistent across both methods, though single dosimeter method showed slightly higher results. Conclusion Under PA, AP, or LAO45°, the doses at the neck consistently exceeded those at the left chest. Therefore, when wearing lead protective equipment, the dosimeter should be properly positioned at the neck outside the lead collar to accurately reflect the radiation doses of surgeons. Some interventional radiology workers improperly positioned the dosimeter (intended at the neck outside the lead collar) at the left chest outside the lead apron, and this may result in an underestimation of the effective dose.