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.

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.

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.

Objective : To investigate the association between single nucleotide polymorphism ( SNP) rs558614， rs9552315，rs7317471 and rs9509492 in large tumor suppressor kinase 2 (LATS2) gene and the risk of colorectal cancer． Methods : A total of 390 colorectal cancer patients and 413 healthy subjects were genotyped by Taqman method．The odds ratio ( OR) and its 95% CI were calculated by unconditional logistic regression，to estimate the associations between SNP rs558614，rs9552315，rs7317471，rs9509492 in LATS2 gene and the risk of colorectal cancer，rectal cancer，as well as colon cancer under codominant，dominant，recessive，overdominant，and log-ad- ditive genetic models． Haplotypes were constructed by haploview software 4. 2 . Results : SNP rs558614， rs7317471，rs9552315 and rs9509492 in LATS2 gene were not associated with the risk of colorectal cancer，rectal cancer and colon cancer under codominant，dominant，recessive，overdominant，and log-additive genetic models. No haploid blocks were formed between the 4 SNPs． Conclusion SNP rs558614 ，rs7317471 ，rs9552315， rs9509492 in LATS2 gene may not play a major role in the development of colorectal cancer，rectal cancer and co- lon cancer.

Background Conjunctivochalasis (CCh) is a common age-related ocular surface diseases.Researches showed that the inflammatory factors are upregulated in conjunctiva and tear of CCh patients,inferring inflammation participates in the pathogenesis of CCh,however,its mechanism is unclear now.Studies also showed that the expression of matrix metalloproteinases (MMPs) in CCh conjunctiva is elevated.However,the association between inflammatory factors and MMPs is unknown.Objective This research was to observe the effects of tumor necrosisfactor-α (TNF-α) and interleukin-1 β (IL-1 β) on the expression of MMP-1,MMP-3,tumor necrosis factor-stimulatedgene-6(TSG-6) and pentraxin-3 (PTX3) in cultured CCh fibroblasts.Methods Conjunctival fibroblasts wereisolated and cultured from CCh-derived and cataract-derived human conjunctiva explants.The cells were treated using20 ng/ml PBS,TNF-α or IL-1β for 4 hours,respectively.The expression levels of MMP-1,MMP-3,TSG-6 and PTX3genes and proteins were detected by quantitative real time PCR and Western blot assay,respectively.Results Thesecond-generation cells showed a long and fusiform shape with ovoid nucleus and radial agreement,and the cellprocessors connected each other.The differences of the relative expression levels of MMP-1,MMP-3,TSG-6 and PTX3mRNA in the cells were significantly different between CCh group and cataract group after being treated by PBS,TNF-αand IL-1 β (MMP-1 mRNA:Fgroup =2.611,P =0.116;Fi =161.564,P =0.000;MMP-3 mRNA:Fgroup =5.201,P =0.029;Fintervene =211.021,P =0.000;TSG-6 mRNA:Fgroup =47.209,P =0.000;Fintervene =119.340,P =0.000;PTX3 mRNA:Fgroup =40.512,P =0.000;Fintervene =93.935,P =0.000).Compared with the cataract group with PBS treatment,the expression levels of MMP-1,MMP-3,TSG-6 and PTX3 mRNA were significantly elevated in the CCh group with PBS treatment or the cataract group with TNF-α and IL-1 β treatment (all at P＜0.05).Compared with the CCh group with PBS treatment,the expression levels of MMP-1,MMP-3,TSG-6 and PTX3 mRNA were significantly elevated in the CCh group with TNF-α and IL-1β treatment (all at P ＜ 0.05).The differences of the relative expression levels of MMP-1,MMP-3,TSG-6 and PTX3 proteins in the cells were significantly different between CCh group and cataract group after being treated by PBS,TNF-α and IL-1 β (MMP-1:Fgroup =84.702,P =0.000;Fint =48.900,P =0.000;MMP-3:Fgroup =112.818,P =0.000;Fint =194.980,P =0.000;TSG-6:Fgroup =56.867,P =0.000;Fint =70.356,P =0.000;PTX3:Fgroup =1.488,P =0.231;Fint =89.872,P =0.000),and the expression changes of MMP-1,MMP-3,TSG-6 and PTX3 proteins were coincident with the genes among the groups with various treatments.Conclusions The expressions of MMP-1,MMP-3,TSG-6 and PTX3 in conjunctival fibroblasts are upregulated in CCh eyes.The interaction of TNF-α and IL-1 β with MMPs is probably involved with the pathogenesis and development MMPs probably.

AIM:To investigate the effect of growth differentiation factor 11 ( GDF11 ) on the expansion of CD8 +memory stem T cells ( Tscm) and to further improve the effect of adoptive immunotherapy.METHODS:Healthy human peripheral blood mononuclear cells ( PBMCs) were isolated by density gradient centrifugation at first.Among the i-solated PBMCs, CD8 +T cells were further purified with MACS microbeads.The CD8 +T cells were then randomly divided into experimental groups and control group.The same volume of different concentrations of GDF11 were added into the ex-perimental groups, and the same volume of PBS solution was added into the control group.Finally, the expansion of Tscm in experimental groups and control group was measured by flow cytometry at several time points.RESULTS:GDF11 sig-nificantly increased the number of Tscm in CD8 +T cells in vitro expansion and also dramatically increased the ratio of Tscm in CD8 +T cells.Furthermore, 400 μg/L GDF11 treatment for 3 weeks was the optimal condition to induce CD8 +Tscm. CONCLUSION:GDF11 effectively increases the number and ratio of Tscm in the CD8 +T cells in cell culture growth, thereby creating a new strategy to further improve the efficiency of adoptive immunotherapy.