OBJECTIVETo investigate the effects of angiotensin II (Ang II) antagonist telmisartan on retina vessel endothelial cell apoptosis and its impact on the ACE2-Ang-(1-7)-Mas axis in spontaneous hypertensive rats (SHR).

METHODSThirty-six SHR 16 week-old were randomly divided into 3 groups (n = 12 each): SHR, SHRT (telmisartan 10 mg · kg-1 · d-1 by gastric gavage) and SHRTA group (telmisartan 10 mg · kg-1 · d-1 by gastric gavage plus intravenous injection of A-779 0.5 mg · kg-1 · d-1), twelve WKY rats served as normotensive control group. Systolic blood pressure was measured at pre-treatment and 8 weeks later. After 8 weeks, rats were sacrificed, the expression of ACE2 and Mas in retina were analyzed by qRT-PCR, Western blot and Immunohistochemistry, the Ang-(1-7) concentration in serum was measured by ELISA. Specimens were obtained and stained by hematoxylin and eosin, and the morphology of retina vessel was observed. Apoptosis of vessel endothelial cells were determined by using terminal deoxynucleotidyl transferase mediated dUTP nick end labeling method.

RESULTSThe systolic blood pressure of SHR, SHRT and SHRTA groups at baseline were significantly higher than age-matched WKY group (all P < 0.01). Eight weeks later, the systolic blood pressure group was significantly lower in SHRT group than in the SHR group (P < 0.01), this effect was partly reversed in SHRTA group. The retinal ACE2 mRNA and protein expression was significantly lower in SHR group than in WKY and SHRT groups (P < 0.01), which was similar between SHRT group and SHRTA group (P > 0.05). The retinal Mas mRNA and protein expression were significantly lower in SHR group compared to WKY and SHRT groups (all P < 0.01), which was significantly lower in SHRTA group than in the SHRT group (P < 0.05). ELISA results showed that serum Ang-(1-7) protein level was significantly lower in SHR group than in WKY group and SHRT group (both P < 0.05), which was lower in SHRTA group compared to SHRT group. Retinal vessel endothelial cell apoptosis was higher in SHR group than in WKY group, which could be reduced by cotreatment with telmisartan and this beneficial effect could be reversed by A-779.

CONCLUSIONTelmisartan can reduce retinal vessel endothelial cell apoptosis via upregulating the ACE2-Ang-(1-7)-Mas axis.

Angiotensin I ; metabolism ; Angiotensin II ; analogs & derivatives ; Angiotensin II Type 1 Receptor Blockers ; pharmacology ; Animals ; Apoptosis ; drug effects ; Benzimidazoles ; pharmacology ; Benzoates ; pharmacology ; Blood Pressure ; Endothelial Cells ; Peptide Fragments ; metabolism ; Peptidyl-Dipeptidase A ; Rats ; Rats, Inbred SHR ; Rats, Inbred WKY ; Retina ; Systole ; Up-Regulation

Objective:To investigate the regulatory effect of long non-coding RNA (lncRNA) FTX on gastric cancer cell proliferation through miR-22-3p/NOD-like receptor protein 3 (NLRP3) inflammasome pathway.Methods:The gastric cancer cell line NCI-N87 were divided into blank control group, si-FTX-NC group, si-FTX group, si-FTX+miR-22-3p inhibitor-NC group and si-FTX+miR-22-3p inhibitor group. Quantitative real-time fluorescent PCR was performed to analyze the expression levels of lncRNA FTX and miR-22-3p, clone formation assay was performed to analyze the proliferation ability of NCI-N87 cells, western blotting was performed to analyze the expressions of NLRP3 inflammasome pathway proteins, and dual-luciferase reporter assay was performed to analyze the targeting relationship between lncRNA FTX and miR-22-3p.Results:The relative expressions of lncRNA FTX in the blank control group, si-FTX-NC group, si-FTX group, si-FTX+miR-22-3p inhibitor-NC group and si-FTX+miR-22-3p inhibitor group were 1.03±0.09, 1.01±0.15, 0.42±0.08, 0.45±0.06 and 0.46±0.13 respectively, with a statistically significant difference ( F=52.19, P<0.001). The relative expressions of miR-22-3p were 1.04±0.12, 0.97±0.08, 2.26±0.15, 2.23±0.13 and 1.15±0.11 respectively, with a statistically significant difference ( F=178.53, P<0.001). Compared with the blank control group and si-FTX-NC group, the relative expressions of lncRNA FTX in the si-FTX group, si-FTX+miR-22-3p inhibitor-NC group and si-FTX+miR-22-3p inhibitor group decreased (all P<0.001). Compared with the blank control group, si-FTX-NC group and si-FTX+miR-22-3p inhibitor group, the relative expressions of miR-22-3p in the si-FTX group and si-FTX+miR-22-3p inhibitor-NC group increased (all P<0.001). The clones of the five groups were 115.50±7.25, 112.33±8.46, 54.83±5.17, 56.17±6.32 and 85.67±9.43, with a statistically significant difference ( F=91.67, P<0.001). The levels of NLRP3 protein in the five groups were 1.84±0.17, 1.86±0.12, 0.95±0.09, 0.97±0.11 and 1.28±0.19, with a statistically significant difference ( F=60.62, P<0.001). Compared with the blank control group and si-FTX-NC group, the number of clones and the level of NLRP3 protein of the si-FTX group, si-FTX+miR-22-3p inhibitor-NC group and si-FTX+miR-22-3p inhibitor group decreased (all P<0.05). Compared with the si-FTX+miR-22-3p inhibitor group, the number of clones and the level of NLRP3 protein in the si-FTX group and si-FTX+miR-22-3p inhibitor-NC group decreased (all P<0.05). The dual-luciferase reporter assay found that miR-22-3p was the target gene of lncRNA FTX. Conclusion:Silencing the expression of lncRNA FTX can inhibit the proliferation of gastric cancer cells, and the mechanism may be related to the regulation of lncRNA FTX on the miR-22-3p/NLRP3 inflammasome pathway.

Immune cell infiltration is of great significance for the diagnosis and prognosis of cancer. In this study, we collected gene expression data of non-small cell lung cancer (NSCLC) and normal tissues included in TCGA database, obtained the proportion of 22 immune cells by CIBERSORT tool, and then evaluated the infiltration of immune cells. Subsequently, based on the proportion of 22 immune cells, a classification model of NSCLC tissues and normal tissues was constructed using machine learning methods. The AUC, sensitivity and specificity of classification model built by random forest algorithm reached 0.987, 0.98 and 0.84, respectively. In addition, the AUC, sensitivity and specificity of classification model of lung adenocarcinoma and lung squamous carcinoma tissues constructed by random forest method 0.827, 0.75 and 0.77, respectively. Finally, we constructed a prognosis model of NSCLC by combining the immunocyte score composed of 8 strongly correlated features of 22 immunocyte features screened by LASSO regression with clinical features. After evaluation and verification, C-index reached 0.71 and the calibration curves of three years and five years were well fitted in the prognosis model, which could accurately predict the degree of prognostic risk. This study aims to provide a new strategy for the diagnosis and prognosis of NSCLC based on the classification model and prognosis model established by immune cell infiltration.
Algorithms ; Carcinoma, Non-Small-Cell Lung ; diagnosis ; physiopathology ; Humans ; Lung Neoplasms ; diagnosis ; physiopathology ; Machine Learning ; Prognosis