Perfluorooctane Sulfonate (PFOS) and Related Compounds Induce Nuclear Receptor 4A1 (NR4A1)-Dependent Carcinogenesis.

Polyfluoroalkyl substances (PFAS) are widely used industrial compounds that have been identified as contaminants in almost every component of the global ecosystem, and in human studies, higher levels of PFAS have been correlated with increased incidence of multiple diseases. Based on the results of human and laboratory animal studies, we hypothesize that the orphan nuclear receptor 4A1 (NR4A1) may be a critical target for some PFAS such as the legacy linear polyfluorooctanesulfonate (PFOS) and other sulfonates. We show that PFOS and related compounds bound the ligand binding domain (LBD) of NR4A1 and induced the growth of several cancer cell lines and enhanced tumor growth in an athymic nude mouse model.

Activation of Genes by Nuclear Receptor/Specificity Protein (Sp) Interactions in Cancer.

The human nuclear receptor (NR) superfamily consists of 48 genes that are ligand-activated transcription factors that play a key role in maintaining cellular homeostasis and in pathophysiology. NRs are important drug targets for both cancer and non-cancer endpoints as ligands for these receptors can act as agonists, antagonists or inverse agonists to modulate gene expression. With two exceptions, the classical mechanism of action of NRs involves their interactions as monomers, dimers or heterodimers with their cognate response elements (cis-elements) in target gene promoters.

Artificial intelligence and machine learning in cell-free-DNA-based diagnostics.

The discovery of circulating fetal and tumor cell-free DNA (cfDNA) molecules in plasma has opened up tremendous opportunities in noninvasive diagnostics such as the detection of fetal chromosomal aneuploidies and cancers and in posttransplantation monitoring. The advent of high-throughput sequencing technologies makes it possible to scrutinize the characteristics of cfDNA molecules, opening up the fields of cfDNA genetics, epigenetics, transcriptomics, and fragmentomics, providing a plethora of biomarkers. Machine learning (ML) and/or artificial intelligence (AI) technologies that are known for their ability to integrate high-dimensional features have recently been applied to the field of liquid biopsy.

Effects of factors influencing cesarean section rates between 2008 and 2018 in Taiwan: A population-based cross-sectional study.

Many factors can affect delivery mode decisions. Therefore, this study aimed to explore the effects of maternal age, physician's sex, region, income, and hospital type on cesarean section (C/S) delivery rates between 2008 and 2018 in Taiwan. In this population-based cross-sectional study, data were extracted from the Taiwan National Health Insurance Research Database (2 million individuals).