Metabolic differences in women with premature ovarian insufficiency: a systematic review and meta-analysis.

Objective: This review aimed to investigate the metabolic profile of women with premature ovarian insufficiency (POI) compared relative to women with normal ovarian functioning.

Methods: A systematic search of PubMed, EMBASE, and the Web of Science for observational studies published up until the 6 of July 2021 that compared the metabolic profile of POI women with a healthy control group were assessed. Mean differences (MD) and 95% confidence interval (CI) were pooled using the fixed or random effect models.

Establishment and Analysis of a Combined Diagnostic Model of Polycystic Ovary Syndrome with Random Forest and Artificial Neural Network.

Polycystic ovary syndrome (PCOS) is one of the most common metabolic and reproductive endocrinopathies. However, few studies have tried to develop a diagnostic model based on gene biomarkers. In this study, we applied a computational method by combining two machine learning algorithms, including random forest (RF) and artificial neural network (ANN), to identify gene biomarkers and construct diagnostic model.

Sweetness-induced activation of membrane dipole potential in STC-1 taste cells.

The biological functions of cell membranes strongly influence the binding and transport of molecular species. We developed STC-1 cell line stably expressing the sweet taste receptor (T1R2/T1R3), and explored the possible correlation between sweeteners and membrane dipole potential of STC-1 cells. In this study, sweetener-induced dipole potential activation was elucidated using a fluorescence-based measurement technique, by monitoring the voltage sensitive probe Di-8-ANEPPS using a dual wavelength ratiometric approach.