1.Regulation of energy metabolism in colon cancer cells by chidamide
Mu HE ; Zhixin QIAO ; Suping REN ; Changlan LI ; Yanbing WANG ; Qiyuan GUI ; Yu WANG ; Yunjing LUO ; Qun YU
Chinese Journal of Pharmacology and Toxicology 2016;30(5):539-544
OBJECTIVE To observe the regulation effect of chidamide on energy metabolism in HCT-8 and HT-29 cells. METHODS HCT-8 and HT-29 cells were treated with chidamide 5,10 and 20 μmol · L-1. Morphological changes of these cells were observed under an ordinary optical microscope. Cell proliferation was detected by MTT. ATP production was determined by CellTiter-Glo? assay kit. Metabolic changes were tested by glycolytic stress kit. The mRNA level of lactate dehydrogenase A (LDH-A)was analyzed by real-time quantitative PCR,whereas the protein level of LDH-A was analyzed by Western blotting. RESULTS Compared with control group,cell morphology of HCT-8 and HT-29 cells in chidamide treated group was irregular,accompanied by deformation,shrinkage and cell debris, and the inhibitory rate of proliferation increased(P<0.05). There was no significant difference in ATP total content between chidamide 5 and 10 μmol · L-1 16 h treatment groups,but in chidamide 20 μmol · L-1 treatment group it was decreased(P<0.05). Chidamide 20μmol · L-1 had no effect on oxygen consumption rate, but glycolysis ATP generation rate was reduced by 30.7% and 37.9%(P<0.05),respectively. Chidamide 20μmol · L-1 had no effect on LDH-A mRNA level,but it decreased the protein level of LDH-A(P<0.01). CONCLUSION Chidamide can abate the respiratory metabolic ability of HCT-8 and HT-29 cells. The mechanism may be related to the down-regulation of LDH-A.
2.Predictive value of coagulation indexes in maintenance peritoneal dialysis patients on the risk of all-cause death
International Journal of Surgery 2021;48(6):378-383,F3
Objective:To construct nomogram model based on coagulation indicators to predict the risk of all-cause death in maintenance peritoneal dialysis patients.Methods:One hundred and sixty-five patients who underwent maintenance peritoneal dialysis treatment at the Department of Nephrology, Urumqi Friendred Hospital from January 2010 to December 2018 were selected retrospectively as the research objects and were followed up once a month after the start of peritoneal dialysis treatment: inpatients were in the patient′s ward; in-home treatment were followed up by telephone. The follow-up time of all the study subjects was until death or 24 months. After the end of the follow-up period, the study subjects were divided into survival group and death group according to whether they died. General information, blood coagulation indicators, renal function indicators, blood lipids, blood potassium, blood calcium, blood phosphorus and blood glucose of the research subjects were recorded and compared the differences between the two groups of patients. The measurement data conforming to the normal distribution were expressed as mean±standarad deviation ( Mean± SD), and the student t-test was used for comparison between groups; the Chi-square test was used for comparison of enumeration data between groups. Two categories Cox regression analysis was used to determine independent risk factors for death in peritoneal dialysis patients, Nomogram prediction model was constructed, and receiver operating characteristic (ROC) was drawn to evaluate the predictive ability of the nomogram model. Results:Combined diabetes, high platelet count, short prothrombin time, short activated partial thrombin time, low international standardization ratio, high fibrinogen level, short thrombin time, high prothrombin activity, high D-dimer level and advanced age were independent risk factors for death in peritoneal dialysis patients. The Nomogram model constructed based on these risk factors had a good fitting effect, and the area under the ROC curve was 0.809 (0.792-0.825), indicating that it had strong predictive ability.Conclusions:Abnormal coagulation indicators were closely related to the risk of death in peritoneal dialysis patients. Diabetes and advanced age also had a certain predictive ability for all-cause death in peritoneal dialysis patients. Nomogram model constructed in this study could be used as a quantitative tool to predict the risk of all-cause death in peritoneal dialysis patients, help to develop individualized treatment plans for peritoneal dialysis patients and improve the prognosis of patients.