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.

ObjectiveTo enhance teaching in postoperative cancer rehabilitation, this study developed an integrative Chinese-Western medicine postoperative oncology rehabilitation system, termed the medical oncology generative pre-trained transformer (MedOncoGPT). By introducing MedOncoGPT as an intelligent assistant, an integrated teaching model combining Chinese and Western medicine was established. The study evaluated its impact on students’ integrative clinical reasoning and practical abilities, providing support for instructional reform in related courses. MethodsUsing teaching resources as the knowledge base, MedOncoGPT was built upon the open-source ChatGLM model and incorporated Low-Rank Adaptation (LoRA) fine-tuning and retrieval-augmented generation (RAG) techniques to address postoperative integrative oncology scenarios. The system was applied in courses and clinical clerkships related to integrative oncology. In alignment with course objectives, a five-stage instructional process—pre-class preparation, in-class inquiry, simulated multidisciplinary consultation, clinical reinforcement, and teaching reflection—was designed to guide students in completing syndrome differentiation, comprehensive assessment, and follow-up planning within real or simulated case contexts. Comparative analyses of student engagement, syndrome differentiation thinking, evidence-based awareness, and interdisciplinary integration skills before and after the teaching reform were conducted using questionnaires, course assessments, classroom observations, and semi-structured interviews. ResultsFollowing the implementation of MedOncoGPT, students demonstrated improved performance in case analysis, prescription formulation, and integrative Chinese-Western medical evaluation compared with those receiving traditional instruction. Classroom participation and the relevance of student inquiries also increased. Self-assessment results indicated high levels of satisfaction with respect to clarity of integrative clinical reasoning, ability to retrieve and apply guideline-based evidence, and awareness of appropriate use of intelligent tools in clinical decision-making. More than 92% of students reported that the system facilitated understanding of abstract theoretical concepts presented in textbooks. Instructors noted that the system helped reduce lesson preparation time, enriched typical case materials and discussion scenarios, and promoted the translation of research findings into classroom teaching. Pilot data showed that, with MedOncoGPT assistance, the mean time for initial syndrome differentiation decreased from 18.4 min to 12.1 min, and the agreement rate increased from 68.3% to 82.5%. In the teaching pilot, the experimental group achieved a higher mean score on the final case analysis assessment than the control group (82.6 vs. 74.3). ConclusionThe integration of MedOncoGPT into teaching on postoperative integrative cancer rehabilitation enabled the establishment of a stable instructional process within existing curricula and enhanced students’ integrative clinical reasoning and evidence-based practice capabilities. The approach demonstrates positive potential for advancing the integration of research, clinical practice, and education and represents a valuable exploratory strategy for instructional reform in courses on integrative Chinese-Western medicine.

ObjectiveTo enhance teaching in postoperative cancer rehabilitation, this study developed an integrative Chinese-Western medicine postoperative oncology rehabilitation system, termed the medical oncology generative pre-trained transformer (MedOncoGPT). By introducing MedOncoGPT as an intelligent assistant, an integrated teaching model combining Chinese and Western medicine was established. The study evaluated its impact on students’ integrative clinical reasoning and practical abilities, providing support for instructional reform in related courses. MethodsUsing teaching resources as the knowledge base, MedOncoGPT was built upon the open-source ChatGLM model and incorporated Low-Rank Adaptation (LoRA) fine-tuning and retrieval-augmented generation (RAG) techniques to address postoperative integrative oncology scenarios. The system was applied in courses and clinical clerkships related to integrative oncology. In alignment with course objectives, a five-stage instructional process—pre-class preparation, in-class inquiry, simulated multidisciplinary consultation, clinical reinforcement, and teaching reflection—was designed to guide students in completing syndrome differentiation, comprehensive assessment, and follow-up planning within real or simulated case contexts. Comparative analyses of student engagement, syndrome differentiation thinking, evidence-based awareness, and interdisciplinary integration skills before and after the teaching reform were conducted using questionnaires, course assessments, classroom observations, and semi-structured interviews. ResultsFollowing the implementation of MedOncoGPT, students demonstrated improved performance in case analysis, prescription formulation, and integrative Chinese-Western medical evaluation compared with those receiving traditional instruction. Classroom participation and the relevance of student inquiries also increased. Self-assessment results indicated high levels of satisfaction with respect to clarity of integrative clinical reasoning, ability to retrieve and apply guideline-based evidence, and awareness of appropriate use of intelligent tools in clinical decision-making. More than 92% of students reported that the system facilitated understanding of abstract theoretical concepts presented in textbooks. Instructors noted that the system helped reduce lesson preparation time, enriched typical case materials and discussion scenarios, and promoted the translation of research findings into classroom teaching. Pilot data showed that, with MedOncoGPT assistance, the mean time for initial syndrome differentiation decreased from 18.4 min to 12.1 min, and the agreement rate increased from 68.3% to 82.5%. In the teaching pilot, the experimental group achieved a higher mean score on the final case analysis assessment than the control group (82.6 vs. 74.3). ConclusionThe integration of MedOncoGPT into teaching on postoperative integrative cancer rehabilitation enabled the establishment of a stable instructional process within existing curricula and enhanced students’ integrative clinical reasoning and evidence-based practice capabilities. The approach demonstrates positive potential for advancing the integration of research, clinical practice, and education and represents a valuable exploratory strategy for instructional reform in courses on integrative Chinese-Western medicine.

Purpose To investigate the role of secreted protein acidic and rich in cysteine(SPARC)expression in the diagnosis and differential diagnosis of mesothelioma.Methods Immunohistochemical EnVision two-step method was used to detect SPARC expression in 40 cases of mesothelioma,4 cases of well-differentiated mesothelial tumour(WDPMT),40 cases of poorly differentiated squamous cell carcinoma of the lung,40 cases of poorly differentiated ad-enocarcinoma of the lung,20 cases each of low-grade and high-grade serous carcinoma of the ovary.The sensitivity and specificity of SPARC,Calretinin,D2-40,and WT-1 expression in mesothelioma were compared and analyzed.Results SPARC showed diffuse strong positive expression in mesothelioma(37/40 cases),medium positive expression in WDPMT(3/4 cases),and focal weak positive expression in a few cases of poorly differentiated squamous cell carcino-ma of the lung(1/40 cases),poorly differentiated adenocarcinoma of the lung(2/40 cases),low-grade serous carci-noma of the ovary(0/20 cases),and high-grade serous carcinoma of the ovary(1/20 cases).In 40 mesotheliomas,the sensitivity of SPARC was 92.5％,and the specificity of SPARC in control tumors(squamous carcinoma of the lung,adenocarcinoma of the lung,and serous carcinoma of the ovary)was 96.7％.Conclusion SPARC is widely expressed in mesotheliomas,with a sensitivity similar to that of Calretinin,D2-40,and WT-1,but with a much higher specificity than other mesothelial markers.It is of great significance in distinguishing between mesothelioma and pulmo-nary poorly differentiated carcinoma and ovarian serous carcinoma.

Purpose To investigate the expression of Versican(VCAN)and thrombospondin 2(THBS2)and their relationship with cancer-associated fibroblast(CAFs)and clinicopathological significance in papillary thyroid car-cinoma(PTC).Methods Bioinformatics analyses were performed using PTC single-cell sequencing data from the GEO and TCGA database.Weighted correlation network analysis identified CAFs-related genes,and enrichment analy-sis highlighted pivotal genes associated with CAFs;the expression of VCAN,THBS2,and α-SMA in 130 PTC tissue samples were detected by immunohistochemistry EnVision method.Masson staining evaluated tumor stromal fibrosis.Relationships between these markers,clinicopathological parameters,and CAF proliferation were analyzed.Results Bioinformatics analysis identified VCAN and THBS2 as core genes significantly associated with CAFs,and extracellular matrix-related pathways.The proliferation rate of CAFs in PTC was 83.1％(108/130),with positivity rate of 96.9％(126/130)for VCAN and 75.4％(98/130)for THBS2.The median mesenchymal fibrosis index was 32.4(inter-quartile range:22.7-50.0).High CAF proliferation correlated positively with lymph node metastasis(P＜0.001),higher TNM stage(P＜0.05),and specific histologic subtypes of PTC.Similarly,VCAN expression,THBS2 expres-sion,and the degree of PTC stromal fibrosis were positively correlated with lymph node metastasis(P＜0.001,P＜0.05,and P＜0.001,respectively).Both THBS2 expression and the degree of PTC stromal fibrosis correlated with the histologic subtype of PTC.The percentage of tumor mesenchymal α-SMA-positive cells strongly correlated with the im-mune response score(IRS)of VCAN and THBS2(rs=0.713,P＜0.001;rs=0.646,P＜0.001).Additionally,the percentage of Masson-stained area was positively correlated with the percentage of tumor mesenchymal α-SMA-posi-tive cells,and the IRS of VCAN and THBS2(rs=0.892,P＜0.001;rs=0.729,P＜0.001;rs=0.616,P＜0.001).Conclusion VCAN and THBS2 serve as potential markers for assessing invasiveness and lymph node metas-tasis of PTC.Their strong association with CAFs provides a basis for further investigation of the malignant biological be-havior of PTC.

Background:The incidence and mortality rates of severe acute pancreatitis(SAP)have been increasing year by year.Therefore,early and rapid identification,along with timely intervention in the progression of acute pancreatitis(AP),is of particular importance.Aims:To explore the value of red blood cell distribution width(RDW)combined with BISAP score in the early prediction of SAP.Methods:A total of 561 AP patients admitted from January 2019 to December 2021 at the General Hospital of the Central Theater Command of the PLA were enrolled and divided into SAP group and non-SAP group according to the disease severity.Venous blood samples were collected within 24 hours of admission.The relevant clinical data,laboratory indices,BISAP score,and MCTSI score were compared between the two groups.Logistic regression analysis was used to identify the risk factors for SAP.Spearman correlation coefficient was employed to assess the correlation of these risk factors with the severity of AP,as well as the correlation of RDW with BISAP score and MCTSI score.The predictive values of these risk factors for SAP were evaluated by ROC curve analysis.Results:Compared with the non-SAP group,the prevalence of hypertension,length and cost of hospital stay,neutrophil count(NEUT),neutrophil-to-lymphocyte ratio(NLR),RDW,serum potassium,aspartate transaminase(AST),blood urea nitrogen(BUN),serum creatinine(SCr),BISAP score and MCTSI score were significantly increased in the SAP group(all P<0.05),while the lymphocyte count(LYM),serum calcium and albumin(ALB)were significantly decreased(all P<0.05).RDW(OR=1.582,95%CI:1.066-2.348,P=0.023),SCr(OR=1.018,95%CI:1.001-1.035,P=0.040),BISAP score(OR=6.210,95%CI:3.121-12.356,P<0.001),and MCTSI score(OR=2.917,95%CI:2.160-3.939,P<0.001)were the independent risk factors for SAP.RDW(rs=0.320,P<0.001),SCr(rs=0.103,P=0.015),BISAP score(rs=0.516,P<0.001),and MCTSI score(rs=0.512,P<0.001)were positively correlated with the severity of AP.Moreover,RDW was positively correlated with BISAP score(rs=0.428,P<0.001)and MCTSI score(rs=0.408,P<0.001).ROC curve analysis revealed that the areas under the ROC curve of RDW,SCr,BISAP score,MCTSI score,and combination of RDW and BISAP score for predicting SAP were 0.753,0.581,0.889,0.888,and 0.905,respectively.Conclusions:RDW,SCr,BISAP score,and MCTSI score are the independent risk factors for SAP.RDW combined with BISAP score can enhance the predictive value for SAP.

The eIF3i gene was amplified from lamb testicular(LT)cells by PCR and cloned into pCold vector to construct the pCold-eIF3i plasmid.Plasmid PCR,double enzyme digestion and se-quencing were used to verify the results.The recombinant eIF3i protein was induced under the op-timized expression conditions.The expression and reactogenicity of the target protein were detected by SDS-PAGE and Western blot.New Zealand white rabbits were immunized with purified recom-binant eIF3i protein combined with Freund's complete and incomplete adjuvants for three times.Se-rum samples were collected after immunization.Indirect ELISA was used to detect antiserum titer,and Western blot was used to analyze antibody specificity.Indirect immunofluorescence assay(IFA)was used to detect the application effect of antibodies.The results showed that the size of LT eIF3i gene was 978 bp.The optimal expression conditions for the eIF3i recombinant protein were as follows:IPTG concentration of 0.2 mmol/L,temperature of 37 ℃,and induction time of 8 h.The recombinant eIF3i protein was expressed as an inclusion body with a size of about 36 kDa.The titer of polyclonal antibody against eIF3i protein was 1∶51 200.Western blot and IFA showed that the prepared polyclonal antibody against eIF3i protein had good reactivity and specificity.In conclusion,we successfully prepared rabbit anti-eif3i polyclonal antibody and confirmed that it could specifically recognize endogenous eIF3i protein,which laid a foundation for further study on the biological function of eIF3i protein.

This study aims to establish a convenient,new and visual detection method for the field diagnosis of Pasteurella multocida(Pm).With reference to the Pm kmt1 gene conserved sequence published in GenBank,PCR amplification primers were designed,the amplified kmt1 gene was cloned into pMD19-T vector,and the recombinant plasmid standard pMD19-T-kmt 1 was estab-lished and identified by PCR and sequencing.Using pMD1 9-T-kmt 1 plasmid as template and kmt1 gene as target gene,basic primers were designed and synthesized.According to the requirements of LFD,a probe(Pm-P)was designed,and the RPA-LFD method for Pm detection was established by optimizing the reaction conditions.Specificity and sensitivity tests were carried out,and 64 clini-cal samples were tested by the method.The results showed that the established Pm RPA-LFD method could be amplified at 37 ℃ for 15 min.Escherichia coli(E.coli),Salmonella enteriditis(SE),Riemerella anatipestifer(RA),Staphylococcus,goose parvovirus(GPV),duck plague virus(DPV),Muscovy duck parvovirus(MDPV)DNA was extracted as the template,and plasmid standard pMD19-T-kmt 1 was used as the positive control.All the positive controls were negative,indicating that the method had good specificity.The plasmid standard pMD1 9-T-kmt 1 was diluted with a 10-fold ratio,and the plasmid standard with a concentration of 107-100 copies/μL was used as the template.The sensitivity was 1.50×101 copies/μ,,which was 100 times higher than that of PCR.A total of 64 clinical samples with suspected RA were subjected to testing using PCR,RPA and LAMP-LFD,with a 100％compliance rate for all three detection tests.The results show that the established RPA-LFD method has the characteristics of strong specificity,high sensitivity,fast speed and visualization,and can be applied to the field detection of Pm.

Purpose To investigate the expression of FAM134B in hepatocellular carcinoma(HCC)and its clini-cal significance.Methods Immunohistochemical EnVision two-step method was used to detect the expression of FAM134B in 60 cases of HCC tissue and adjacent non-tumor liver tissue.The relationship between FAM134B expres-sion and clinicopathological characteristics and prognosis of HCC was analyzed.Transwell assays,CCK-8 assays and clone formation assays were used to assess the effects of FAM134B knockdown on HCC cell migration,invasion and proliferation.Results FAM134B had a high expression rates of 70.0％(42/60)in HCC tissues and 40.0％(24/60)in adjacent normal tissues.Compared to adjacent non-tumor tissues,FAM134B expression was significantly higher in HCC tissues(P all＜0.001),and it was positively correlated with vascular invasion,tumor maximum diameter,and early recurrence(P all＜0.05).Survival analysis showed that high expression of FAM134B was an independent poor prognostic factor and a high recurrence risk factor for HCC patients(P all＜0.05).In vitro experiments demonstrated that knockdown FAM134B inhibited HCC cell migration,invasion and proliferation(P all＜0.05).GSEA analysis u-sing the TCGA database indicated that the expression of FAM134B was positively correlatied with the AKT/mTOR path-way.Conclusion High expression of FAM134B may be a marker of high recurrence risk and poor prognosis in HCC and holds potential as a therapeutic target for HCC.