ABSTRACT
Objective @#To investigate the effects of luteolin on invasion and migration of endometriosis stromal cells and whether its mechanism is related to the regulation of 15-hydroxyprostaglandin dehydrogenase (HPGD) expres- sion．@*Methods @#The endometrial stromal cells HEM15A were divided into control group (cells were cultured in nor- mal medium) ，luteolin group ( cells were treated with different concentrations of luteolin) ，si-HPGD group ( cells were transfected with si-HPGD) ，si-NC group ( cells were transfected with si-NC ) ，luteolin + si-HPGD Group (cells were transfected with si-HPGD and treated with 20 μmol / L luteolin) ，Luteolin + si-NC Group ( cells were transfected with si-NC and treated with 20 μmol / L luteolin) . Real-time quantitative PCR was used to detect mRNA level of HPGD．Cell proliferation was detected by CCK-8 assay，Transwell and scratch assays were used to detect cell invasion and migration．The protein expression of proliferating cell nuclear antigen (PCNA) ，matrix metallopro- teinase (MMP-2) ，MMP-9 and HPGD were detected by Western blot，and the level of prostaglandin E2 ( PGE2) was detected by ELISA. @*Results @#Compared with 0 μmol / L luteolin，luteolin at 20，50 and 100 μmol / L significantly inhibited the proliferation activity of hEM15A cells，and reduced PCNA expression ( all P＜0. 05) ．Compared with the control group，20 μmol / L of luteolin significantly inhibited cell invasion and migration (P ＜0. 05) ，decreased the expressions of MMP-2 and MMP-9 (P＜0. 05) ，and up-regulated the mRNA and protein levels of HPGD (P < 0. 05) ，while inhibited cellular PGE2 level (P＜0. 05) ．Compared with the luteolin group，the luteolin + si-HPGD group increased cell invasion and migration (P ＜0. 05 ) ，increased the expressions of MMP-2 and MMP-9 (P < 0. 05) ．@*Conclusion @#Luteolin regulates HPGD / PGE2 signaling pathway to inhibit the invasion and migration of en- dometrial stromal cells.
ABSTRACT
Objective To build a predictive model of depression with secondary mild cognitive impairment (MCI) in elderly patients based on current clinical diagnosis and treatment technology,and to analyze its application.Methods Elderly patients with depression hospitalized in three hospitals were consecutively included in our study from September 2013 to December 2015 for collecting relevant clinical data,and followed up for 18 months to confirm a prognosis.The follow-up results were used to predict influencing indices for secondary MCI risk,and to verify judgement effectiveness of the critical value of the relevant indices on the window of time of the secondary MCI.Results A total of 216 elderly patients with depression were included in this study,of whom 9 patients were lost to follow-up.Finally,27 patients had secondary MCI,and 180 patients had normal cognitive function during the follow-up period.Cox multiple regression analysis showed that the risk model of secondary MCI in elderly patients with depression was composed of age (HR:1.30,95 ％ CI:1.12-1.64,P =0.03),education years (HR:0.56,95 ％ CI:0.41-0.80,P =0.01),regular psychological treatment (HR:0.73,95％ CI:0.58-0.92,P=0.03),and BSSI scale (HR:1.24,95％ CI:1.08-1.56,P=0.03).Age and BSSI scale were risk factors,while education years and regular group psychotherapy were protective factors.For an elderly patient with depression who was characterized by age ≥ 72.3 years,education years ＜8.3 years,and BSSI scale ≥75.1,the window of time for secondary MCI was shorter,and these critical values of the independent factors had significant judgement effectiveness.Conclusions Age,education years,regular psychological treatment,and BSSI scale are independently influencing factors for secondary MCI in elderly patients receiving the treatment for depression.Furthermore,age ≥72.3 years,the education period ＜8.3 years,and BSSI scale ≥75.1 points are critical values of secondary MCI.