1.A Study on the Quality of Life and its Influencing Factors among Type 2 Diabetes Mellitus Patients
Pingling WU ; Taisheng CAI ; Jian LIU
Journal of Chinese Physician 2001;0(10):-
Objective To study the quality of life(QOL) of the type 2 diabetes mellitus and its influencing factors.Methods The three hundred and seventy-six cases of the type 2 diabetes mellitus were investigated with the short form 36(SF-36) measuring scale in Changsha.Results The results demonstrated that medical care,alcohol intake,physical activity,dwelling coneition,occupation and marriage were the main effective factors.Conclusion It was very important to pay more attention to enhancing psychological and behavioral health education,and improving the QOL in patients of diabetes mellitus.
2.Transcriptome sequencing of transgelin-2 inhibiting high glucose induced microglia inflammation
Pingling SHI ; Yuanmeng WEI ; Zixu HUANG ; Cong LU ; Qixiang YANG ; Pan LI ; Chengye WU ; Zongming SONG
Chinese Journal of Ocular Fundus Diseases 2023;39(2):153-162
Objective:To analyze the change of differential genes and signaling pathways in high glucose induced BV2 cells, and to explore the mechanism of transgelin-2 (TAGLN2) regulating cellular inflammatory response and metabolic process.Methods:An experimental study. The cultured BV2 cells were divided into mannitol treatment (Man) group, glucose treatment (Glu) group, overexpression control Glu treatment (Con) group, overexpression TAGLN2 Glu treatment group, silence control Glu treatment (shCon Glu) group, and silence TAGLN2 Glu treatment (shTAGLN2 Glu) group. Cells in the Man group were cultured in modified Eagle high glucose medium (DMEM) containing 25 mmol/L mannitol and 25 mmol/L glucose, cells in other groups (Glu group, Con Glu group, TAGLN2 Glu group, shCon Glu group and shTAGLN2 Glu group) were cultured in DMEM medium containing 50 mmol/L glucose. After 24 hours of cells culture, transcriptome sequencing of cells in each group were performed using high-throughput sequencing technology, and significantly differentially expressed genes (DEG) were screened. |log 2 (fold change)|≥1 and P≤0.05 were adopted as criteria to screen for DEG. Gene Ontology (GO) function enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and protein-protein interaction network analysis were performed. Real-time polymerase chain reaction (RT-PCR) was used to detect the relative expression level of DEG mRNA. The data between groups were compared by independent sample t-test. Results:When compared with Man group, a total of 517 differentially expressed genes were screened in Glu group, which including 277 up-regulated genes and 240 down-regulated genes. KEGG pathway enrichment analysis showed that the up-regulated genes were significantly enriched in immune system processes such as nuclear factor (NF)-κB signal pathway, Jak-signal transducers and activators of transcription (STAT) signal pathway, while down-regulated genes were significantly enriched in glycosaminoglycan degradation and glyceride metabolic pathway. Compared with Con Glu group, a total of 480 DEG were screened in TAGLN2 Glu group, among which 147 up-regulated and 333 down-regulated genes were detected. Up-regulated genes were significantly enriched in the metabolic processes of fatty acid, glyceride and pyruvate, while down-regulated genes were significantly enriched in immune system processes such as NF-κB signal pathway, Jak-STAT signal pathway and tumor necrosis factor (TNF) signal pathway. Compared with shCon Glu group, a total of 582 DEG were screened in shTAGLN2 Glu group, among which 423 up-regulated and 159 down-regulated genes were detected. Up-regulated DEG were significantly enriched in immune system processes such as TNF signal pathway and chemokine signal pathway, while down-regulated DEG were significantly enriched in pattern recognition receptor signal pathway. RT-PCR results showed that the relative expression levels of DEG mRNA Card11 ( t=13.530), Icos ( t=3.482), Chst3 ( t=6.949), Kynu ( t=5.399), interleukin (IL)-1β ( t=2.960), TNF-α ( t=5.800), IL-6 ( t=3.130), interferon-γ ( t=7.690) and IL-17 ( t=6.530) in the TAGLN2 Glu treatment group were decreased significantly compared with Con Glu group, and the difference was statistically significant. Conclusion:TAGLN2 can inhibit glucose induced microglia inflammation by NF-κB and Jak-STAT signaling pathways, Card11, Icos, Chst3 and Kynu play an important role in the anti-inflammatory process of TAGLN2.