1.Development of duration knowledge requirement questionnaire of myocardial infarction patients
Qinqin XU ; Weichao SHAN ; Ying WANG ; Hongwei YAN ; Dapeng JIN ; Weiying SHAN
Chinese Journal of Modern Nursing 2016;22(10):1392-1394,1395
Objective To develop the duration knowledge requirement questionnaire of myocardial infarction patients, in order to provide tools for understanding duration knowledge requirement of myocardial infarction patients. Methods By literature review and semi-structure interview as the main sources of questionnaire dimensions and items, the primary questionnaire had been formed by experts conference method, but the formal questionnaire was established after the confirmation and perfection by pre-survey and recognition interview. Results The duration knowledge requirement questionnaire of myocardial infarction patients included 5 dimensions 37 items. The Cronbach′s α coefficient of questionnaire reliability was 0. 839, each dimensions′ Cronbach′s αcoefficient was 0. 704-0. 825. The content of validity was 0. 86. Conclusions This questionnaire has favorable validity and reliability, which is suitable for the survey of duration knowledge requirement in myocardial infarction patients.
2.Correlation between serum osteopontin and osteopontin and type 2 diabetes mellitus with coronary heart disease
Yazhu WANG ; Yunfei GUO ; Chao LIU ; Weichao SHAN ; Wenfeng WANG ; Aiwen ZHANG ; Wanglexian SUN ; Ying ZHANG
Clinical Medicine of China 2022;38(1):47-52
Objective:To study the relationship between serum osteopontin and osteopontin and type 2 diabetes mellitus (T2DM) complicated with coronary heart disease, and to evaluate the correlation between the levels of serum osteopontin and osteopontin with the severity of coronary artery lesions in T2DM patients.Methods:A total of 100 T2DM patients who were suspected to have stable coronary heart disease and underwent coronary angiography from November 2019 to December 2020 were selected from the Affiliated Hospital of Chengde Medical College, according to coronary angiography results, 60 patients with confirmed coronary heart disease were classified as the case group and 40 patients with non-coronary heart disease were classified as the control group for retrospective analysis. The clinical data and biochemical indicators of all patients were recorded, and Gensini score was calculated. The concentration of osteopontin and osteopontin in serum was quantitatively determined by double-antibody enzyme linked immunosorbent assay method. Independent sample t-test was used to compare the mean of normal distribution measurement data between the two groups. The non normal distribution data are represented by M ( Q1, Q3), and Mann Whitney U test is used for comparison between groups. Composition comparison between count data groups χ 2 inspection. Spearman correlation analysis was used to analyze the correlation between serum osteopontin and osteopontin and Gensini score in patients with T2DM. Results:Univariate analysis showed that serum osteopontin and osteopontin were (13.076(8.433, 23.552) μg/L) and (0.437(0.300, 0.630) μg/L) significantly higher in the case group than in the control group (6.367(4.605, 9.048) μg/L) and (0.299(0.196, 0.399) μg/L) respectively, with statistically significant differences ( Z=5.12, 3.28, all P<0.001). Multi-factor logistic regression analysis showed that osteoprotegerin ( OR=2.887, 95% CI:1.850-8.515, P=0.024) and osteopontin ( OR=13.109, 95%CI: 2.557-67.204, P=0.002) were associated with T2DM combined with coronary heart disease, and the risk of T2DM combined with coronary heart disease increased with higher levels of osteoprotegerin and osteopontin. Spearman correlation analysis showed that serum osteopontin and osteoprotegerin were positively correlated with Gensini score in T2DM patients ( r=0.591, 0.467; all P<0.05). Conclusion:Serum osteopontin and osteoprotegerin are associated with T2DM combined with coronary heart disease, and high serum osteopontin and osteoprotegerin are risk factors for T2DM combined with coronary heart disease; serum osteopontin and osteoprotegerin are positively correlated with the degree of coronary artery disease in T2DM patients.
3.Correlation study of gamma-glutamyl transferase/high density lipoprotein cholesterol ratio,neutrophil/lymphocyte ratio and coronary heart disease
Yazhu WANG ; Yunfei GUO ; Ying ZHANG ; Weichao SHAN ; Wanglexian SUN ; Fei SHI ; Haoran ZHANG ; Wenping XUE
Clinical Medicine of China 2021;37(6):488-495
Objective:To investigate the correlation between gamma-glutamyl transferase/high-density lipoprotein cholesterol ratio (GHR), neutrophil/lymphocyte ratio (NLR) and coronary heart disease (CHD), and evaluated its pathogenic risk and predictive value for CHD.Methods:A total of 694 patients admitted to our hospital from December 2017 to December 2018 for suspected CHD and coronary angiography were selected. According to the results of coronary angiography,the patients were divided into CHD group ( n=527) and non-CHD group ( n=167). The clinical data of all patients were recorded. Gamma-glutamyl transferase (GGT), high-density lipoprotein cholesterol (HDL-C) and other biochemical indicators were recorded. Neutrophils, lymphocyte count and other hematological indicators were recorded. GHR, NLR and Gensini scores of the patients were calculated. Clinical data and GHR, NLR and other indicators were compared between the two groups. Receiver operating characteristic curve (ROC) was used to evaluate the predictive value of GHR, NLR in CHD, and to determine the optimal cut-off value; Logstic regression analysis was used to investigate the risk factors of CHD.Spearman correlation analysis was used to analyze the correlation between serum OPN, OPG and Gensini score in patients with CHD. Results:The GHR and NLR were 32.59(21.05, 48.24) and 3.53(2.18, 8.46) significantly higher in the CHD group than in the non-CHD group 16.56(10.07, 25.21) and 2.20(1.45, 3.28) respectively, with statistically significant differences ( Z=11.094, 9.055, P<0.05). ROC curve analysis showed that the AUC of NLR and MLR in diagnosing CHD was 0.785 and 0.732( P<0.05). When the critical values of GHR and NLR respectively were 19.805 and 2.678, respectively, the diagnostic efficiency of CHD was the highest, and the sensitivity and specificity were 79.30%, 62.90% and 63.80%, 68.30%, and the AUC of GGT in diagnosing CHD was 0.628. When the critical value was 19.500, the sensitivity and specificity were 80.50% and 39.50%, respectively,the AUC of GHR was greater than that of GGT ( Z=12.973, P<0.05). Multivariate Logistic regression analysis showed that Smoking ( OR=2.887, 95% CI:1.850-4.505, P<0.05), hypertension ( OR=2.009, 95% CI: 1.311-3.080, P<0.05), fasting plasma glucose ( OR=1.109, 95% CI:1.034-1.189, P<0.05), age ≥60 years ( OR=1.567, 95% CI:1.179-2.415, P<0.05), NLR ≥2.687 ( OR=3.152, 95% CI:2.066-4.808, P<0.05) and GHR ≥19.805 ( OR=4.768, 95% CI:3.131-7.262, P<0.05) was an independent risk factor for CHD. After gradually adjustment for risk factors such as smoking, hypertensive, fasting plasma glucose, age ≥60 years and NLR ≥2.687, GHR ≥19.805 was still an independent risk factor for coronary heart disease(OR and 95% CI were 4.620 (3.049-7.000), 4.768 (3.131-7.262), 6.567 (4.408-9.810), 4.768 (3.131-7.262), 4.768 (3.131-7.262), respectively; all P<0.001). Spearman correlation analysis showed that GHR and NLR were positively correlated with Gensini score ( r=0.312, 0.394; all P<0.05). Conclusion:GHR and NLR were positively correlated with the severity of coronary artery disease, which is of significance in the diagnosis of coronary heart disease. NLR ≥2.687 and GHR ≥19.805 were independent risk factors for CHD. GHR was superior to GGT and HDL-C alone in the diagnosis of CHD,and has certain clinical application value
4.Metformin suppresses hypoxia-inducible factor-1α expression in cancer-associated fibroblasts to block tumor-stromal cross-talk in breast cancer
Shan SHAO ; Weichao BAI ; Pengcheng ZHOU ; Minna LUO ; Xinhan ZHAO ; Jianjun LEI
Journal of Southern Medical University 2024;44(3):428-436
Objective To investigate the mechanism of metformin for regulating tumor-stromal cell cross-talk in breast cancer.Methods Tumor associated fibroblasts(CAFs)co-cultured with breast cancer cells were treated with metformin,and the changes in expressions of hypoxia-inducible factor-1α(HIF-1α),p-AMPK,stroma-derived factor-1(SDF-1)and interleukin-8(IL-8)in the CAFs were detected using ELISA,RT-qPCR or Western blotting;Transwell assay was used to evaluate the invasiveness of the tumor cells and its changes following treatment with exogenous SDF-1,IL-8 and TGF-β1.The effects of HIF-1α shRNA or overexpression plasmid,AMPK shRNA,and treatment with OG(a proline hydroxylase inhibitor)or 2-OXO(a proline hydroxylase activator)were examined on p-AMPK,HIF-1α,SDF-1 and IL-8 expressions and invasiveness of the CAFs.Results Metformin treatment significantly increased the expression levels of p-AMPK,SDF-1 and IL-8(P<0.05)and decreased HIF-1α expression(P<0.05)without affecting AMPK expression level(P>0.05)in the CAFs.The invasion ability of metformin-treated breast cancer cells was significantly decreased(P<0.05).Exogenous SDF-1 and IL-8,HIF-1α overexpression,and OG-induced upregulation of HIF-1α all significantly attenuated the inhibitory effects of metformin on breast cancer cell invasion(P<0.05)and HIF-1α,SDF-1 and IL-8 expressions in CAFs(P<0.05).Transfection with HIF-1α shRNA or treatment with 2-OXO significantly decreased the invasiveness of breast cancer cells(P<0.05).P-AMPK knockdown significantly suppressed the inhibitory effect of metformin on HIF-1α expression in CAFs and on invasion of breast cancer cells(P<0.05).Treatment with TGF-β1 partially decreased the inhibitory effect of metformin on HIF-1α expression in CAFs and invasiveness of the breast cancer cells(P<0.05).Conclusion Metformin suppresses HIF-1α expression in CAFs to block tumor-stromal cross talk in breast cancer.
5.Metformin suppresses hypoxia-inducible factor-1α expression in cancer-associated fibroblasts to block tumor-stromal cross-talk in breast cancer
Shan SHAO ; Weichao BAI ; Pengcheng ZHOU ; Minna LUO ; Xinhan ZHAO ; Jianjun LEI
Journal of Southern Medical University 2024;44(3):428-436
Objective To investigate the mechanism of metformin for regulating tumor-stromal cell cross-talk in breast cancer.Methods Tumor associated fibroblasts(CAFs)co-cultured with breast cancer cells were treated with metformin,and the changes in expressions of hypoxia-inducible factor-1α(HIF-1α),p-AMPK,stroma-derived factor-1(SDF-1)and interleukin-8(IL-8)in the CAFs were detected using ELISA,RT-qPCR or Western blotting;Transwell assay was used to evaluate the invasiveness of the tumor cells and its changes following treatment with exogenous SDF-1,IL-8 and TGF-β1.The effects of HIF-1α shRNA or overexpression plasmid,AMPK shRNA,and treatment with OG(a proline hydroxylase inhibitor)or 2-OXO(a proline hydroxylase activator)were examined on p-AMPK,HIF-1α,SDF-1 and IL-8 expressions and invasiveness of the CAFs.Results Metformin treatment significantly increased the expression levels of p-AMPK,SDF-1 and IL-8(P<0.05)and decreased HIF-1α expression(P<0.05)without affecting AMPK expression level(P>0.05)in the CAFs.The invasion ability of metformin-treated breast cancer cells was significantly decreased(P<0.05).Exogenous SDF-1 and IL-8,HIF-1α overexpression,and OG-induced upregulation of HIF-1α all significantly attenuated the inhibitory effects of metformin on breast cancer cell invasion(P<0.05)and HIF-1α,SDF-1 and IL-8 expressions in CAFs(P<0.05).Transfection with HIF-1α shRNA or treatment with 2-OXO significantly decreased the invasiveness of breast cancer cells(P<0.05).P-AMPK knockdown significantly suppressed the inhibitory effect of metformin on HIF-1α expression in CAFs and on invasion of breast cancer cells(P<0.05).Treatment with TGF-β1 partially decreased the inhibitory effect of metformin on HIF-1α expression in CAFs and invasiveness of the breast cancer cells(P<0.05).Conclusion Metformin suppresses HIF-1α expression in CAFs to block tumor-stromal cross talk in breast cancer.