Pluripotency-independent induction of human trophoblast stem cells from fibroblasts.

Human trophoblast stem cells (hTSCs) can be derived from embryonic stem cells (hESCs) or be induced from somatic cells by OCT4, SOX2, KLF4 and MYC (OSKM). Here we explore whether the hTSC state can be induced independently of pluripotency, and what are the mechanisms underlying its acquisition. We identify GATA3, OCT4, KLF4 and MYC (GOKM) as a combination of factors that can generate functional hiTSCs from fibroblasts.

Prediction of neonatal subgaleal hemorrhage using first stage of labor data: A machine-learning based model.

Background: Subgaleal hemorrhage (SGH) is a rare neonatal condition, mainly associated with instrumental delivery, mainly vacuum extractor (VE). The aim of this study was to develop a machine learning model that would allow a personalized prediction algorithm for Subgaleal hemorrhage (SGH) following vacuum extraction (VE), based on maternal and fetal variables collected during the first stage of labor.

Materials And Methods: A retrospective cohort study on data from a university affiliated hospital, recorded between January 2013 and February 2017.

Real-time data analysis using a machine learning model significantly improves prediction of successful vaginal deliveries.

Background: The process of childbirth is one of the most crucial events in the future health and development of the offspring. The vulnerability of parturients and fetuses during the delivery process led to the development of intrapartum monitoring methods and to the emergence of alternative methods of delivery. However, current monitoring methods fail to accurately discriminate between cases in which intervention is unnecessary, partly contributing to the high rates of cesarean deliveries worldwide.