Objective To observe the effect of excess oxygen supply for different time periods on the mitochondrial energy metabolism in alveolar epithelial type Ⅱ cells. Methods Rat RLE-6TN cells were assigned into a control group (21% O₂ for 4 h) and excess oxygen supply groups (95% O₂ for 1,2,3,and 4 h,res-pectively).The content of adenosine triphosphate (ATP),the activity of mitochondrial respiratory chain complex V,and the mitochondrial membrane potential were determined by luciferase assay,micro-assay,and fluorescent probe JC-1,respectively.Real-time fluorescence quantitative PCR was employed to determine the mRNA levels of NADH dehydrogenase subunit 1 (ND1),cytochrome b (Cytb),cytochrome C oxidase subunit I (COXI),and adenosine triphosphatase 6 (ATPase6) in the core subunits of mitochondrial respiratory chain complexes Ⅰ,Ⅲ,Ⅳ,and Ⅴ,respectively. Results Compared with the control group,excess oxygen supply for 1,2,3,and 4 h down-regulated the mRNA levels of ND1 (q=24.800,P<0.001; q=13.650, P<0.001; q=9.869, P<0.001; q=20.700, P<0.001 ) , COXI ( q=16.750, P<0.001; q=10.120, P<0.001; q=8.476, P<0.001; q=14.060, P<0.001 ) , and ATPase6 ( q=22.770, P<0.001; q=15.540, P<0.001; q=12.870, P<0.001;q=18.160,P<0.001).Moreover,excess oxygen supply for 1 h and 4 h decreased the ATPase activity (q=9.435,P<0.001;q=11.230,P<0.001) and ATP content (q=5.615,P=0.007;q=5.029,P=0.005).The excess oxygen supply for 2 h and 3 h did not cause significant changes in ATPase activity (q=0.156,P=0.914;q=3.197,P=0.116) and ATP content (q=0.859,P=0.557;q=1.273,P=0.652).There was no significant difference in mitochondrial membrane potential among the groups (F=0.303,P=0.869). Conclusion Short-term excess oxygen supply down-regulates the expression of the core subunits of mitochondrial respiratory chain complexes and reduces the activity of ATPase,leading to the energy metabolism disorder of alveolar epithelial type Ⅱ cells.

Objective To screen out the key genes leading to diabetic cardiomyopathy by analyzing the mRNA array associated with diabetic cardiomyopathy in the GEO database. Methods The online tool GEO2R of GEO was used to mine the differentially expressed genes (DEG) in the datasets GSE4745 and GSE5606.R was used to draw the volcano map of the DEG,and the Venn diagram was established online to identify the common DEG shared by the two datasets.The clusterProfile package in R was used for gene ontology annotation and Kyoto encyclopedia of genes and genomes pathway enrichment of the DEG.GSEA was used for gene set enrichment analysis,and STRING for the construction of a protein-protein interaction network.The maximal clique centrality algorithm in the plug-in Cytohubba of Cytoscape was used to determine the top 10 key genes. The expression of key genes was studied in the primary cardiomyocytes of rats and compared between the normal control group and high glucose group. Results The expression of Pdk4,Ucp3,Hmgcs2,Asl6,and Slc2a4 was consistent with the array analysis results.The expression of Pdk4,Ucp3,and Hmgcs2 was up-regulated while that of Acsl6 and Slc2a4 was down-regulated in the cardiomyocytes stimulated by high glucose (25 mmol/L) for 72 h. Conclusion Pdk4,Ucp3,Hmgcs2,Asl6,and Slc2a4 may be associated with the occurrence and development of diabetic cardiomyopathy,and may serve as the potential biomarkers of diabetic cardiomyopathy.

Objective To clarify the hotspots and trends of multimorbidity research and to provide evidence for further research in China. Methods Papers on multimorbidity were retrieved from PubMed and Web of Science (from inception to August 11,2021).BICOMB and gCLUTO were used for bibliometric and clustering analysis,and CiteSpace was employed for analysis of authors and citations,and burst detection of keywords. Results The research on multimorbidity has been on the rise.Among the authors,Mercer SW published the most papers on this topic and Fortin M was the most cited author.Karolinska Institute topped the institutions in the number of published papers,and the paper published in Lancet by Barnett K in 2012 was the most cited.A total of 75 high-frequency keywords were extracted,on the basis of which seven research hotspots were summarized:epidemiology (including the prevalence and trend),medication (involving polypharmacy,medication compliance,etc.),medical expenditure (including cost and medical services),aging (such as elderly patients,frailty,and disability),psychology (involving mental health,social support,etc.),multimorbidity management (such as the treatment,primary health care,and integrated care),and comorbidity of cardiovascular and metabolic diseases (involving obesity,stroke,diabetes,etc.). Conclusions Multimorbidity is concerned as a major health threat and public health problem worldwide.The management of multimorbidity is more complex than that of one disease,which thus faces more challenges.Therefore,researchers,health care providers,and policy-makers should underscore it.

Objective To screen the potential key genes of osteosarcoma by bioinformatics methods and analyze their immune infiltration patterns. Methods The gene expression profiles GSE16088 and GSE12865 associated with osteosarcoma were obtained from the Gene Expression Omnibus(GEO),and the differentially expressed genes(DEGs)related to osteosarcoma were screened by bioinformatics tools.Gene Ontology(GO)annotation,Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment,and analysis of immune cell infiltration were then carried out for the DEGs.The potential Hub genes of osteosarcoma were identified by protein-protein interaction network,and the expression of Hub genes in osteosarcoma and normal tissue samples was verified via the Cancer Genome Atlas(TCGA). Results A total of 108 DEGs were screened out.GO annotation and KEGG pathway enrichment revealed that the DEGs were mainly involved in integrin binding,extracellular matrix (ECM) structural components,ECM receptor interactions,and phosphatidylinositol 3-kinase/protein kinase B(PI3K/Akt)signaling pathway.Macrophages were the predominant infiltrating immune cells in osteosarcoma.Secreted phosphoprotein 1(SPP1),matrix metallopeptidase 2(MMP2),lysyl oxidase(LOX),collagen type V alpha(II)chain(COL5A2),and melanoma cell adhesion molecule(MCAM)presented differential expression between osteosarcoma and normal tissue samples(all P<0.05). Conclusions SPP1,MMP2,LOX,COL5A2,and MCAM are all up-regulated in osteosarcoma,which may serve as potential biomarkers of osteosarcoma.Macrophages are the key infiltrating immune cells in osteosarcoma,which may provide new perspectives for the treatment of osteosarcoma.