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.

Myopic traction maculopathy(MTM)is a common vision-threatening complication in patients with high myopia. With the global increase in high myopia, the prevalence of MTM has been rising worldwide, leading to a growing burden of disease, economic costs,and social impact. The emergence and development of optical coherence tomography(OCT)have provided robust technical support for the staging of MTM. Based on the evolving understanding of its pathological mechanisms and natural course, various staging systems have been proposed and applied in clinical practice, offering crucial guidance for the personalized management of MTM patients. Additionally, innovations and refinements in surgical techniques and materials, such as pars plana vitrectomy(PPV), posterior scleral reinforcement, and macular buckling(MB), have expanded the therapeutic options for MTM. This article systematically reviews the staging systems and treatment strategies for MTM, focusing on the role of OCT-based staging in guiding individualized treatment plans. It also summarizes the current evidence on the efficacy and safety of existing and emerging surgical approaches, including PPV, MB, and their combined procedures. The review further proposes that future research should focus on developing predictive models integrating multimodal data to clarify surgical timing and indications, as well as conducting large-scale, multicenter randomized controlled trials to explore the selection of PPV, MB, or combined surgeries. The review aims to discuss personalized treatment for MTM, providing theoretical foundations and practical directions for optimizing clinical management and improving patient prognosis for MTM patients.

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.

Objective:To analyze the characteristics and general patterns of adverse drug reactions associated with aripiprazole, and to identify potential risk signals, thereby providing references for the safe and rational use of medications in clinical practice.Methods:This is a descriptive study that collected and summarized reports of adverse reactions to aripiprazole submitted by medical institutions in Anhui Province to the National Center for Adverse Drug Reaction Monitoring, China from January 2019 to December 2024. The basic characteristics of patients, the treatment regimens used, the timing of adverse drug reaction occurrence, the clinical manifestations of the affected systems, and the outcomes of these adverse drug reactions were statistically analyzed to identify the clinical characteristics and risk factors of adverse drug reactions associated with aripiprazole.Results:A total of 1 106 adverse reaction case reports related to aripiprazole were collected, with a male-to-female ratio of 1:1.29 ( χ2 = 8.64, P = 0.003) and an average age of (35 ± 16) years. The primary diseases treated included schizophrenia (768 cases, 69.44%), bipolar affective disorder (96 cases, 8.68%), and depressive disorder (75 cases, 6.78%). Adverse reactions occurred within the first 2 weeks of medication in 689 cases (62.29%). All medications were oral formulations, with 978 cases (88.43%) falling within the recommended daily dose range of 10-30 mg/d, while 15 cases (1.36%) exceeding the maximum recommended dose of 30 mg/d. The most common clinical manifestations were related to the nervous system (696 cases, 62.93%), followed by cardiovascular system manifestations (146 cases, 13.20%). The majority of adverse reactions showed improvement or recovery (1 052 cases, 95.12%). Conclusions:Aripiprazole is widely used in clinical practice, and the occurrence of adverse reactions is correlated with patient characteristics and treatment regimens. It is advisable to enhance the rational clinical use and monitoring of aripiprazole. Such measures will aid in preventing or reducing the occurrence of severe adverse reactions.

Objective:To develop a self-efficacy scale of milk donation and test its reliability and validity, in order to provide a scientific evaluation tool for the corresponding study.Methods:According to Bandura′s self-efficacy theory and consensus-based standards for the selection of health measurement instruments, the scale was developed by means of literature search, article pool establishment and expert letter consultation. A pre-survey was conducted on 30 newborn bereaved women, a formal investigation was conducted on 231 newborn bereaved women, and 115 newborn bereaved women were selected for exploratory factor analysis. Confirmatory factor analysis was performed on 116 parturients with neonatal loss to determine the reliability and validity of the scale.Results:The final scale includes 3 dimensions and 13 items. Three common factors were extracted by exploratory factor analysis, and the cumulative variance contribution rate was 77.962%. A scale with three dimensions, included breast milk donation resilience, breast milk donation cognition and breast milk donation motivation, and 13 items was determined. Confirmatory factor analysis showed that the model fit of the scale was good ( χ2/ df = 1.390, RMSEA = 0.063, RMR = 0.046, NFI = 0.924, NNFI = 0.971, GFI = 0.924, CFI = 0.977). The content validity index was 0.835. Cronbach′s α coefficient of the total volume table was 0.919, and the coefficients of each dimension were 0.892, 0.905 and 0.844, respectively. The broken half reliability of the scale was 0.893, and the broken half reliability of each dimension was 0.857, 0.881 and 0.711, respectively. The retest reliability of the scale was 0.814, and the retest reliability of each dimension was 0.803, 0.825 and 0.767, respectively. Conclusions:The scale has good reliability and validity, and can be used to evaluate the self-efficacy of milk donation in lost newborns.

This work was aimed at analyzing the protein characteristics of Coiled-Coil Domain-Containing Protein 115(CCDC115)and using Ccdc115-deficient mouse monocyte-macrophage leukemia cells(RAW264.7)to explore the influence of CCDC115 on the intracellular survival of Salmonella Typhimurium.Bioinformatics analysis was conducted to examine the fundamental attributes of CCDC115,which was determined to be an unstable protein consisting of two α-helices and an intervening disordered re-gion,devoid of any transmembrane structural domains.A RAW264.7-Ccdc115-KO cell line was successfully established with CRISPR/Cas9 gene-editing technology.To elucidate the effects of CCDC115 on the intracellular survival of Salmonella Typhimurium,we infected RAW264.7 cells with Salmonella Typhimurium.The expression of CCDC115 was found to be upregulated at both the mRNA and protein levels post-infection,according to RT-qPCR and western blot analysis.Via counting of colony-forming units(CFU),the proliferation rate of Salmonella Typhimurium within RAW264.7-Ccdc115-KO cells was found to be 1.5-fold higher than that in RAW264.7 cells.Acidification imaging studies indicated that,whereas Salmonella Typhimurium phagosomes underwent acidifi-cation in RAW264.7 cells,this process was absent in RAW264.7-Ccdc115-KO cells.In conclusion,the study successfully estab-lished a RAW264.7-Ccdc115-KO cell line and demonstrated that the expression of CCDC115 is elevated during Salmonella Ty-phimurium infection,thus potentially inhibiting the intracellular survival of Salmonella Typhimurium by facilitating phagosome acidifi-cation.This study lay a theoretical foundation for functional studies of CCDC115 and the investigation of mechanisms regulating the survival of intracellular Salmonella Typhimurium.

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*

Radiopharmaceuticals operate by combining radionuclides with carriers. The radiation energy emitted by radionuclides is utilized to selectively irradiate diseased tissues while minimizing damage to healthy tissues. In comparison to external beam radiation therapy, radionuclide drugs demonstrate research potential due to their biological targeting capabilities and reduced normal tissue toxicity. This article reviews the applications and research progress of radiopharmaceuticals in cancer treatment. Several key radionuclides are examined, including ²²³Ra, ⁹⁰Y, Lutetium-177 (¹⁷⁷Lu), ²¹²Pb, and Actinium-225 (²²⁵Ac). It also explores the current development trends of radiopharmaceuticals, encompassing the introduction of novel radionuclides, advancements in imaging technologies, integrated diagnosis and treatment approaches, and equipment-medication combinations. We review the progress in the development of new treatments, such as neutron capture therapy, proton therapy, and heavy ion therapy. Furthermore, we examine the challenges and breakthroughs associated with the clinical translation of radiopharmaceuticals and provide recommendations for the research and development of novel radionuclide drugs.
Humans ; Radiopharmaceuticals/therapeutic use* ; Neoplasms/radiotherapy* ; Radioisotopes/therapeutic use* ; Animals