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Estimation of Quercetin Treatment Effects in Polycystic Ovarian Syndrome (PCOS) Induced Rats
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Polycystic ovary syndrome (PCOS), also known as a common polygenic endocrine condition, affects the ovaries and results in infertility and abortion. Dyslipidemia, Diabetes, hypertension, endometrial cancer, and other illnesses may all be made more likely by PCOS. Various drugs are used to treat PCOS, but they have several drawbacks and cannot effectively cure the condition. Therefore, and due to its strong antioxidant activity, anti-obesity, anti-inflammation, and other actions, the flavonoid quercetin has been proven to have health-promoting properties. The purpose of the study was to assess quercetin's impact activity in the treatment of PCOS - induced rats. A PCOS rat model was developed using testosterone.  Female albino Wistar rats (170±10 g) were subcutaneously injected with either testosterone propionate (TP) 10 mg/kg/day body weight or propylene glycol (PG) as vehicle 0.5ml daily, for 28 days (induction stage). The PCOS-induced rats were divided into two groups, one was treated orally with the vehicle (PG) and the other was treated orally with quercetin 25mg/kg/day over a period of 35 days (treatment stage). So, the biochemical assays proved the efficacy of quercetin on lipid profile and glucose uptake, in rat treatment with quercetin significantly decreased (P < 0.05) in body weight and fasting blood glucose, fasting insulin, cholesterol and triglyceride levels unlike PCOS-induced rats also, a significant increase in HDL level was achieved in quercetin - treated group compared to PCOS group. Thus, we conclude that quercetin is an effective remedy in modulating metabolic features and treating PCOS.

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Publication Date
Sat Dec 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
The Cluster Analysis by Using Nonparametric Cubic B-Spline Modeling for Longitudinal Data
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Longitudinal data is becoming increasingly common, especially in the medical and economic fields, and various methods have been analyzed and developed to analyze this type of data.

In this research, the focus was on compiling and analyzing this data, as cluster analysis plays an important role in identifying and grouping co-expressed subfiles over time and employing them on the nonparametric smoothing cubic B-spline model, which is characterized by providing continuous first and second derivatives, resulting in a smoother curve with fewer abrupt changes in slope. It is also more flexible and can pick up on more complex patterns and fluctuations in the data.

The longitudinal balanced data profile was compiled into subgroup

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