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.

Conventional ICSI vs. physiological selection of spermatozoa for ICSI (picsi) in sibling oocytes.

Background: Physiological selection of spermatozoa for ICSI (PICSI) is a sperm selection method based on sperm binding to hyaluronic acid. Previous studies on the effect of hyaluronic acid binding assays on fertilization and embryo quality have shown inconsistent results. Previous sibling oocyte studies have not found a significant improvement in fertilization or embryo development with hyaluronic acid binding assays.

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.

Prediction of vaginal birth after cesarean deliveries using machine learning.

Background: Efforts to reduce cesarean delivery rates to 12-15% have been undertaken worldwide. Special focus has been directed towards parturients who undergo a trial of labor after cesarean delivery to reduce the burden of repeated cesarean deliveries. Complication rates are lowest when a vaginal birth is achieved and highest when an unplanned cesarean delivery is performed, which emphasizes the need to assess, in advance, the likelihood of a successful vaginal birth after cesarean delivery.

Elevated circulating micro-ribonucleic acid (miRNA)-200b and miRNA-429 levels in anovulatory women.

Objective: To study the role of micro-RNA (miRNA)-200b and miRNA-429 in human ovulation and to measure their expression levels in ovulatory and anovulatory patients.

Design: Micro-RNA-200b and miRNA-429 expression analysis in human serum and granulosa cells at different phases of the ovulation cycle in normal cycling women and women undergoing assisted reproductive technology cycles.

Setting: University-affiliated hospital and academic research laboratory.

Communication between residents and attending doctors on call after hours.

Rationale, Aims And Objectives: Off-hours medical care in hospitals is provided by residents, while attendings on call are available for assistance. This study evaluated the gap between residents' expectations and professional guidelines' requirements of attendings on call and what actually occurs during night shifts, while comparing surgical and medical specialties.

Methods: Two questionnaires based on professional guidelines were filled by residents.