The Effects of Selenium Supplementation on Gene Expression Related to Insulin and Lipid in Infertile Polycystic Ovary Syndrome Women Candidate for In Vitro Fertilization: a Randomized, Double-Blind, Placebo-Controlled Trial

Abstract This study was conducted to evaluate the effects of selenium supplementation on gene expression related to insulin and lipid in infertile women with polycystic ovary syndrome (PCOS) candidate for in vitro fertilization (IVF). This randomized double-blind, placebo-controlled trial was conducted among 40 infertile women with PCOS candidate for IVF. Subjects were randomly allocated into two groups to intake either 200-μg selenium (n = 20) or placebo (n = 20) per day for 8 weeks. Gene expression levels related to insulin and lipid were quantified in lymphocytes of women with PCOS candidate for IVF with RT-PCR method. Results of RT-PCR demonstrated that after the 8-week intervention, compared with the placebo, selenium supplementation upregulated gene expression of peroxisome proliferator-activated receptor gamma (PPAR-γ) (1.06 ± 0.15-fold increase vs. 0.94 ± 0.18-fold reduction, P = 0.02) and glucose transporter 1 (GLUT-1) (1.07 ± 0.20-fold increase vs. 0.87 ± 0.18-fold reduction, P = 0.003) in lymphocytes of women with PCOS candidate for IVF. In addition, compared with the placebo, selenium supplementation downregulated gene expression of low-density lipoprotein receptor (LDLR) (0.88 ± 0.17-fold reduction vs. 1.05 ± 0.22-fold increase, P = 0.01) in lymphocytes of women with PCOS candidate for IVF. We did not observe any significant effect of selenium supplementation on gene expression levels of lipoprotein(a) [LP(a)] in lymphocytes of women with PCOS candidate for IVF. Overall, selenium supplementation for 8 weeks in lymphocytes of women with infertile PCOS candidate for IVF significantly increased gene expression levels of PPAR-γ and GLUT-1 and significantly decreased gene expression levels of LDLR, but did not affect LP(a). Keywords Selenium supplementation Gene expression Insulin Lipid Polycystic ovary syndrom

The Effects of Selenium Supplementation on Clinical Symptoms and Gene Expression Related to Inflammation and Vascular Endothelial Growth Factor in Infertile Women Candidate for In Vitro Fertilization

This study was performed to determine the effects of selenium supplementation on clinical symptoms and gene expression related to inflammatory markers in infertile women with polycystic ovary syndrome (PCOS) who were candidate for in vitro fertilization (IVF). Thirty-six women candidate for IVF were recruited in this randomized double-blinded, placebo-controlled trial. They (n = 18/group) were randomly assigned into intervention groups to take either 200 μg/day of selenium or placebo for 8 weeks. RT-PCR findings indicated that selenium supplementation downregulated gene expression of interleukin-1 (IL-1) (P < 0.004) and tumor necrosis factor alpha (TNF-α) (P = 0.02) in lymphocytes of patients with PCOS compared with the placebo. In addition, selenium supplementation upregulated gene expression of vascular endothelial growth factor (VEGF) (P = 0.001) in lymphocytes of patients with PCOS compared with the placebo. Selenium supplementation had no significant effect on clinical symptoms and gene expression of IL-8 (P = 0.10) and transforming growth factor beta (TGF-β) (P = 0.63). Overall, our findings documented that selenium supplementation for 8 weeks to infertile women candidate for IVF improved IL-1, TNF-α, and VEGF gene expression, though selenium had no effect on clinical symptoms and, IL-8 and TGF-β gene expression. Clinical trial registration number: http://www.irct.ir: IRCT20170513033941N23. © 2019, Springer Science+Business Media, LLC, part of Springer Nature

Fuzzy evidence theory and Bayesian networks for process systems risk analysis

YesQuantitative risk assessment (QRA) approaches systematically evaluate the likelihood, impacts, and risk of adverse events. QRA using fault tree analysis (FTA) is based on the assumptions that failure events have crisp probabilities and they are statistically independent. The crisp probabilities of the events are often absent, which leads to data uncertainty. However, the independence assumption leads to model uncertainty. Experts’ knowledge can be utilized to obtain unknown failure data; however, this process itself is subject to different issues such as imprecision, incompleteness, and lack of consensus. For this reason, to minimize the overall uncertainty in QRA, in addition to addressing the uncertainties in the knowledge, it is equally important to combine the opinions of multiple experts and update prior beliefs based on new evidence. In this article, a novel methodology is proposed for QRA by combining fuzzy set theory and evidence theory with Bayesian networks to describe the uncertainties, aggregate experts’ opinions, and update prior probabilities when new evidences become available. Additionally, sensitivity analysis is performed to identify the most critical events in the FTA. The effectiveness of the proposed approach has been demonstrated via application to a practical system.The research of Sohag Kabir was partly funded by the DEIS project (Grant Agreement 732242)