The coronavirus-pandemic has a major impact on women's-mental and physical-health. Polycystic-ovary-syndrome (PCOS) has a high-predisposition to many cardiometabolic-risk factors that increase susceptibility to severe complications of COVID-19 and also exhibit an increased likelihood of subfertility. The study includes the extent of the effect of COVID-19-virus on renin-levels, glutathione-s-transferase-activity and other biochemical parameters in PCOS-women. The study included 120 samples of ladies that involved: 80 PCOS-patients, and 40 healthy-ladies. Both main groups were divided into subgroups based on COVID-19 infected or not. Blood-samples were collected from PCOS-patients in Kamal-Al-Samara Hospital, at the period between December until June. Some biochemical parameters were measured for all study-groups, which included: determination of serum renin levels by using the ELISA-technique, GST-activity, lipid-profile. FBS was assessed manually, and hormones were assessed using VIDAS-analyzer-hormones. The result showed a possible relationship between FBS-levels and renin in PCOS-ladies (Stein-Leventhal-Syndrome), while GST-activity were inversely associated with BMI in PCOS-ladies. Also, it was found that the renin-levels were higher in PCOS-patients groups compared with healthy-groups. On the other hand, the renin levels and Glutathione-S-Transferase-activity were lower in PCOS-patients-infected-with-COVID-19 than female-patients-without-COVID-19. The statistical-data-displayed that the level of renin is associated negatively with glutathione-s-transferase-activity in PCOS-cases. Renin level was higher in PCOS-ladies, this may lead to increase renal-dysfunction and risk of cardiovascular-disease that may be expected in patients. A decrease in the antioxidant-capacity may be because the high number of free-radicals that enter the body by the virus and high levels of renin which lead to a higher risk of PCOS-complication like cardiovascular-disease.
ABSTRACT
In this research been to use some of the semi-parametric methods the based on the different function penalty as well as the methods proposed by the researcher because these methods work to estimate and variable selection of significant at once for single index model including (SCAD-NPLS method , the first proposal SCAD-MAVE method , the second proposal ALASSO-MAVE method ) .As it has been using a method simulation time to compare between the semi-parametric estimation method studied , and various simulation experiments to identify the best method based on the comparison criteria (mean squares error(MSE) and average mean squares error (AMSE)).
And the use
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