Exposome-Explorer (http://exposome-explorer.iarc.fr) is the first database dedicated to biomarkers of exposure to environmental risk factors. It contains detailed information on the nature of biomarkers, their concentrations in various human biospecimens, the study population where measured and the analytical techniques used for measurement. It also contains correlations with external exposure measurements and data on biological reproducibility over time. The data in Exposome-Explorer was manually collected from peer-reviewed publications and organized to make it easily accessible through a web interface for in-depth analyses. The database and the web interface were developed using the Ruby on Rails framework. A total of 480 publications were analyzed and 10 510 concentration values in blood, urine and other biospecimens for 692 dietary and pollutant biomarkers were collected. Over 8000 correlation values between dietary biomarker levels and food intake as well as 536 values of biological reproducibility over time were also compiled. Exposome-Explorer makes it easy to compare the performance between biomarkers and their fields of application. It should be particularly useful for epidemiologists and clinicians wishing to select panels of biomarkers that can be used in biomonitoring studies or in exposome-wide association studies, thereby allowing them to better understand the etiology of chronic diseases.

Individual cells take lineage commitment decisions in a way that is not necessarily uniform. We address this issue by characterising transcriptional changes in cord blood-derived CD34+ cells at the single-cell level and integrating data with cell division history and morphological changes determined by time-lapse microscopy. We show that major transcriptional changes leading to a multilineage-primed gene expression state occur very rapidly during the first cell cycle. One of the 2 stable lineage-primed patterns emerges gradually in each cell with variable timing. Some cells reach a stable morphology and molecular phenotype by the end of the first cell cycle and transmit it clonally. Others fluctuate between the 2 phenotypes over several cell cycles. Our analysis highlights the dynamic nature and variable timing of cell fate commitment in hematopoietic cells, links the gene expression pattern to cell morphology, and identifies a new category of cells with fluctuating phenotypic characteristics, demonstrating the complexity of the fate decision process (which is different from a simple binary switch between 2 options, as it is usually envisioned).