BACKGROUND:Glucose metabolism plays a crucial role in maintaining the normal physiological function of the body.Glucose metabolism disorder can lead to a range of health problems.At present,the molecular mechanism of glucose metabolism and potential gene targets in osteoarthritis need to be further studied.OBJECTIVE:To analyze the genes related to glucose metabolism in osteoarthritis by bioinformatics methods,and to verify them by cell experiments in vitro,so as to provide new ideas for prevention and treatment of osteoarthritis from the perspective of glucose metabolism.METHODS:Differentially expressed genes and glucose metabolism related genes were screened out from GEO database and GeneCards database.The genes related to both osteoarthritis and glucose metabolism were obtained.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis were used to screen the functions and pathways of these genes.To further investigate the interactions between these genes,a protein-protein interaction network was constructed and computational methods using Cytoscape software were utilized to identify key genes(Hub genes)for osteoarthritis glucose metabolism.In addition,CIBERSORT algorithm was used to analyze immune cell infiltration in GSE98918 data set.Finally,the expression of Hub gene was verified by cell experiment in vitro.RESULTS AND CONCLUSION:A total of 134 osteoarthritis glucose metabolism-related genes were obtained.GO enrichment analysis showed that GO was mainly involved in the reaction of toxic substances,the positive regulation of inflammatory reaction,the reaction of lipopolysaccharide and so on.KEGG enrichment analysis showed that it was closely related to PI3K-Akt signaling pathway,interleukin-17 signaling pathway,and AGE-RAGE signaling pathway in diabetic complications.Macrophages,monocytes,resting natural killer cells,regulatory T cells,and CD8+T cells were the main infiltrating cells obtained by immune infiltration analysis.In vitro cell experiments showed that the expression of Hub genes SERPINF1,TAC1,GLUL,APOE,and TMEM176A in the experimental group was significantly different from that in the control group.The mRNA expression of HLA-DRA was not statistically significant.The results show that SERPINF1,TAC1,Glul,APOE,and TMEM176A may be the key genes of glucose metabolism in osteoarthritis,and may be potential new targets for the prevention and treatment of osteoarthritis.

To achieve the national objectives of improving medical quality and safety,the Shanghai Shenkang Hospital Development Center has formulated a list of major targets,tasks,and key results based onthe Objective and Key Results (OKR) method.The primary approaches adopted include establishing an organizational structure to advance medical quality and safety supervision,setting up a series of quantitative indicators for medical quality and safety targets,formulating standardized management systems,building an information platform,and strengthening supervision.It argues that the adoption of OKR can effectively promote the implementation of national target management for improving medical quality and safety,establish a cross-institutional management network for medical quality and safety,strengthen process management,and effectively drive continuous improvement in medical quality and safety.

BACKGROUND:Glucose metabolism plays a crucial role in maintaining the normal physiological function of the body.Glucose metabolism disorder can lead to a range of health problems.At present,the molecular mechanism of glucose metabolism and potential gene targets in osteoarthritis need to be further studied.OBJECTIVE:To analyze the genes related to glucose metabolism in osteoarthritis by bioinformatics methods,and to verify them by cell experiments in vitro,so as to provide new ideas for prevention and treatment of osteoarthritis from the perspective of glucose metabolism.METHODS:Differentially expressed genes and glucose metabolism related genes were screened out from GEO database and GeneCards database.The genes related to both osteoarthritis and glucose metabolism were obtained.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis were used to screen the functions and pathways of these genes.To further investigate the interactions between these genes,a protein-protein interaction network was constructed and computational methods using Cytoscape software were utilized to identify key genes(Hub genes)for osteoarthritis glucose metabolism.In addition,CIBERSORT algorithm was used to analyze immune cell infiltration in GSE98918 data set.Finally,the expression of Hub gene was verified by cell experiment in vitro.RESULTS AND CONCLUSION:A total of 134 osteoarthritis glucose metabolism-related genes were obtained.GO enrichment analysis showed that GO was mainly involved in the reaction of toxic substances,the positive regulation of inflammatory reaction,the reaction of lipopolysaccharide and so on.KEGG enrichment analysis showed that it was closely related to PI3K-Akt signaling pathway,interleukin-17 signaling pathway,and AGE-RAGE signaling pathway in diabetic complications.Macrophages,monocytes,resting natural killer cells,regulatory T cells,and CD8+T cells were the main infiltrating cells obtained by immune infiltration analysis.In vitro cell experiments showed that the expression of Hub genes SERPINF1,TAC1,GLUL,APOE,and TMEM176A in the experimental group was significantly different from that in the control group.The mRNA expression of HLA-DRA was not statistically significant.The results show that SERPINF1,TAC1,Glul,APOE,and TMEM176A may be the key genes of glucose metabolism in osteoarthritis,and may be potential new targets for the prevention and treatment of osteoarthritis.

BACKGROUND:Endoplasmic reticulum stress is closely associated with the occurrence and progression of osteoarthritis,but the key genes and regulatory mechanisms remain unclear.OBJECTIVE:Utilizing bioinformatics to identify crucial endoplasmic reticulum stress-related genes in osteoarthritis,followed by experimental validation in cell models,aiming to offer new strategies for the prevention and treatment of osteoarthritis from the perspective of endoplasmic reticulum stress.METHODS:Osteoarthritis-related dataset GSE55235 was downloaded from the GEO database.Differential genes in synovial tissue of osteoarthritis were obtained through WGCNA machine learning algorithm and intersected with endoplasmic reticulum stress-related genes from the GeneCard database to acquire differential endoplasmic reticulum stress-related genes in osteoarthritis(ERSDEGs).These genes underwent GO and KEGG enrichment analysis,construction of a protein-protein interaction network,and validation of diagnostic efficiency in external datasets.Human primary synovioblast model of osteoarthritis was constructed.The control group was not treated,and the experimental group received 20 ng/mL lipopolysaccharide to simulate osteoarthritic synoviocyte modeling.Real-time fluorescence quantitative PCR was then performed to validate the expression level of each differential gene followed by immune infiltration analysis.RESULTS AND CONCLUSION:A total of 27 key endoplasmic reticulum stress-related genes in osteoarthritis were identified.GO enrichment analysis revealed that these genes were mainly enriched in collagen metabolism,chemokine,antigen binding,and immunoglobulin receptor binding processes.KEGG analysis indicated that they were mainly enriched in pathways such as rheumatoid arthritis and relaxin signaling pathways.The protein-protein interaction network was constructed,and the top five genes with the highest scores were identified using the Degree algorithm in Cytoscape software,including matrix metallopeptidase 1,tumor necrosis factor ligand superfamily member 11,matrix metallopeptidase 9,collagen type 1 alpha 1,and chemokine C-X-C motif ligand 12.Immune infiltration analysis showed that immune cells were mainly distributed in M2 macrophages,chemokine C-X-C motif ligand 12 showed a significant positive correlation with resting mast cells(r=0.70,P＜0.001)and a significant negative correlation with resting memory CD4+T cells(r=-0.72,P＜0.001).Matrix metallopeptidase 9 showed a significant positive correlation with MO macrophages(r=0.94,P＜0.001).Collagen type 1 alpha 1 was significantly positively correlated with resting NK cells(r=0.77,P＜0.001)and MO macrophages(r=0.76,P＜0.001).Receiver operator characteristic curve analysis in external datasets GSE77298 and GSE1919 showed that the five key genes had good disease prediction value.In vitro cell experiments demonstrated significant differences in the expression levels of matrix metallopeptidase 1,tumor necrosis factor ligand superfamily member 11,matrix metallopeptidase 9,and chemokine C-X-C motif ligand 12 in the osteoarthritic cell model compared to the control group.These results showed that the key genes related to endoplasmic reticulum stress in osteoarthritis,including matrix metallopeptidase 1,tumor necrosis factor ligand superfamily member 11,matrix metallopeptidase 9,and chemokine C-X-C motif ligand 12,influence the occurrence and development of osteoarthritis through the links of collagen degradation and immune regulation,which are expected to provide new insights into the targeted treatment of osteoarthritis.

Objective To evaluate the practical application of the Media Fill Test(MFT)in assessing aseptic compounding competency of personnel in Pharmacy Intravenous Admixture Services(PIVAS).Methods A multicenter controlled study was conducted across six tertiary hospitals(center ①-⑥)in China.Participants were divided into an inexperienced group(Group A,n=118)and an experienced group(Group B,n=118),each performing five MFT operations.Positive controls validated medium efficacy.Contamination rates and pass rates were analyzed using chi-square and Fisher's exact tests.Results Valid samples included 584 for Group A and 588 for Group B.The sample pass rate was 66.78%(390/584)in Group A and 91.67%(539/588)in Group B,while personnel pass rates were 46.15%(54/117)and 80.51%(95/118),respectively,with significant intergroup differences(both P<0.01).All centers except Center ⑥ showed significantly higher pass rates in Group B(all P<0.05).Conclusion MFT effectively differentiates technical proficiency levels and is suitable for training evaluation of novice PIVAS staff.

Objective To evaluate the practical application of the Media Fill Test(MFT)in assessing aseptic compounding competency of personnel in Pharmacy Intravenous Admixture Services(PIVAS).Methods A multicenter controlled study was conducted across six tertiary hospitals(center ①-⑥)in China.Participants were divided into an inexperienced group(Group A,n=118)and an experienced group(Group B,n=118),each performing five MFT operations.Positive controls validated medium efficacy.Contamination rates and pass rates were analyzed using chi-square and Fisher's exact tests.Results Valid samples included 584 for Group A and 588 for Group B.The sample pass rate was 66.78%(390/584)in Group A and 91.67%(539/588)in Group B,while personnel pass rates were 46.15%(54/117)and 80.51%(95/118),respectively,with significant intergroup differences(both P<0.01).All centers except Center ⑥ showed significantly higher pass rates in Group B(all P<0.05).Conclusion MFT effectively differentiates technical proficiency levels and is suitable for training evaluation of novice PIVAS staff.

Objective:To develop and validate a Self-care Ability Scale for Arteriovenous Fistula (AVF) in Maintenance Hemodialysis (MHD) patients.Methods:Guided by Orem's self-care theory, the initial item pool of the scale was developed through a literature review, semi-structured interviews, and group discussions. The initial scale was finalized after two rounds of expert consultation using the Delphi method. A convenience sampling method was used to recruit 418 MHD patients using AVF in January 2024 for item analysis, exploratory factor analysis and reliability testing. Another 293 MHD patients using AVF were recruited in March 2024 for confirmatory factor analysis.Results:The self-care ability scale for AVF in MHD patients included four dimensions: knowledge and skills of AVF self-care, willingness and attitude toward AVF self-care, recognition and prevention of AVF complications, and patient self-adjustment and adaptation, comprising 38 items. The content validity index at the scale level was 0.98. Exploratory factor analysis extracted four common factors with a cumulative variance contribution rate of 84.706%. Confirmatory factor analysis indicated good model fit, strong convergent validity, and ideal discriminant validity. The total Cronbach's α coefficient of the scale was 0.987; the split-half reliability coefficient was 0.902, and the test-retest reliability coefficient was 0.979.Conclusions:The Self-care Ability Scale for AVF in MHD patients demonstrates excellent reliability and validity, making it a suitable tool for assessing patients' ability to self-care for their AVF.

AIM: To identify the primary active components and underlying mechanisms of Yijing Decoction(YJD)in treating early diabetic retinopathy(DR)based on liquid chromatography-mass spectrometry and network pharmacology.METHODS: Active components of YJD were characterized through LC-MS. Components with optimal ADME(absorption, distribution, metabolism, excretion)properties were selected as key bioactive candidates. Network pharmacology approaches were employed to predict YJD-DR therapeutic targets. Protein-protein interaction(PPI)networks, gene ontology(GO)enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis were subsequently conducted to predict core targets and networks. Critical targets and pathways were experimentally validated through Western blot.RESULTS: Ten core therapeutic targets were identified, including TNF, Alb, EGFR, STAT3, PTGS2, ESR1, PPAR, MMP9, TLR4, and MAPK. YJD was related to cancer-related signaling, fluid shear stress and atherosclerosis, and neurodegenerative diseases, encompassing key biological processes such as inflammatory response regulation, programmed cell death activation, and enhanced cell migration. Furthermore, Western blot analysis confirmed that YJD significantly inhibited high glucose-induced phosphorylation of STAT3(P-STAT3/STAT3)and ERK(P-ERK/ERK)in rat retinal microvascular endothelial cells.CONCLUSION: This study revealed YJD's pharmacodynamical basis and its multi-component, multi-target, and multi-paths pharmacology. YJD exerts therapeutic effects on DR by coordinately regulating critical signaling pathways and alleviating intraocular inflammation, thus preserving retinal vascular endothelial cells, maintaining blood-retinal barrier integrity, and facilitating retinal neurovascular repair.

Objective To establish an individualized nomogram model and evaluate its efficacy to provide a possible evaluation basis for the prognosis of lower third and abdominal part of oesophageal adenocarcinoma (EAC). Methods Lower third and abdominal part of EAC patients from 2010 to 2015 were chosen from the SEER Research Plus Database (17 Regs, 2022nov sub). The patients were randomly allocated to the training cohort and the internal validation cohort with a ratio of 7∶3 using bootstrap resampling. The Cox proportional hazards regression analysis was used to determine significant contributors to overall survival (OS) in EAC patients, which would be elected to construct the nomogram prediction model. C-index, calibration curve and receiver operating characteristic (ROC) curve were performed to evaluate its efficacy. Finally, the efficacy to evaluate the OS of EAC patients was compared between the nomogram prediction model and TNM staging system. Results In total, 3945 patients with lower third and abdominal part of EAC were enrolled, including 3475 males and 470 females with a median age of 65 (57-72) years. The 2761 patients were allocated to the training cohort and the remaining 1184 patients to the internal validation cohort. In the training and the internal validation cohorts, the C-index of the nomogram model was 0.705 and 0.713, respectively. Meanwhile, the calibration curve also suggested that the nomogram model had a strong capability of predicting 1-, 3-, and 5-year OS rates of EAC patients. The nomogram also had a higher efficacy than the TNM staging system in predicting 1-, 3-, and 5-year OS rates of EAC patients. Conclusion This nomogram prediction model has a high efficiency for predicting OS in the patients with lower third and abdominal part of EAC, which is higher than that of the current TNM staging system.

To achieve the national objectives of improving medical quality and safety,the Shanghai Shenkang Hospital Development Center has formulated a list of major targets,tasks,and key results based onthe Objective and Key Results (OKR) method.The primary approaches adopted include establishing an organizational structure to advance medical quality and safety supervision,setting up a series of quantitative indicators for medical quality and safety targets,formulating standardized management systems,building an information platform,and strengthening supervision.It argues that the adoption of OKR can effectively promote the implementation of national target management for improving medical quality and safety,establish a cross-institutional management network for medical quality and safety,strengthen process management,and effectively drive continuous improvement in medical quality and safety.