GC-MS-based untargeted plasma metabolomics identifies a 2-biomarker panel for possible diagnosis of precancerous cervical intraepithelial neoplasia stages from cervical cancer.

Cervical cancer (CC) remains a major health concern globally, much of the brunt of which is experienced by the low- and middle-income countries where screening in terms of cytology and DNA genotyping for the high-risk oncogenic subtypes of the human papilloma virus (hr-HPV) is either inadequate or performed rather late. In this study, we aimed to determine biomarkers or panels of biomarkers that are capable of diagnosing the precancerous cervical intraepithelial neoplasia (CIN) stages from healthy and CC patients via untargeted gas chromatography-mass spectrometry-based metabolomics. Various cross-comparisons were conducted from which differential metabolites were identified.

A Fuzzy Expert System to Predict the Risk of Postpartum Hemorrhage.

Introduction: The American College of Obstetricians and Gynecologists (ACOG) defines postpartum hemorrhage (PPH) as a blood loss of >500mL following vaginal delivery or >1000mL following cesarean section. PPH is widely recognized as a common cause of maternal death. However, there is currently no effective method to predict its risk of occurrence.

Ginsenoside Rg1 and the control of inflammation implications for the therapy of type 2 diabetes: A review of scientific findings and call for further research.

The incidence of type 2 diabetes (T2D) is gradually assuming pandemic proportions, leaving in its trail increased morbidity and mortality. This trend is mainly credited to the adoption of unhealthy lifestyles resulting in increased cases of overweightness and obesity. Traditionally, T2D is considered a metabolic disorder epitomized by prolonged elevated levels of glucose due to insulin resistance and/or decreased insulin secretion resulting from pancreatic β-cells dysfunction.