Screening Estrogenic Activities of Chemicals or Mixtures In Vivo Using Transgenic (cyp19a1b-GFP) Zebrafish Embryos

The tg(cyp19a1b-GFP) transgenic zebrafish expresses GFP (green fluorescent protein) under the control of the cyp19a1b gene, encoding brain aromatase. This gene has two major characteristics: (i) it is only expressed in radial glial progenitors in the brain of fish and (ii) it is exquisitely sensitive to estrogens. Based on these properties, we demonstrate that natural or synthetic hormones (alone or in binary mixture), including androgens or progestagens, and industrial chemicals induce a concentration-dependent GFP expression in radial glial progenitors. As GFP expression can be quantified by in vivo imaging, this model presents a very powerful tool to screen and characterize compounds potentially acting as estrogen mimics either directly or after metabolization by the zebrafish embryo. This study also shows that radial glial cells that act as stem cells are direct targets for a large panel of endocrine disruptors, calling for more attention regarding the impact of environmental estrogens and/or certain pharmaceuticals on brain development. Altogether these data identify this in vivo bioassay as an interesting alternative to detect estrogen mimics in hazard and risk assessment perspective

Precision requirements for space-based XCO2 data

Author Posting. © American Geophysical Union, 2007. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 112 (2007): D10314, doi:10.1029/2006JD007659.Precision requirements are determined for space-based column-averaged CO2 dry air mole fraction (XCO2) data. These requirements result from an assessment of spatial and temporal gradients in XCO2, the relationship between XCO2 precision and surface CO2 flux uncertainties inferred from inversions of the XCO2 data, and the effects of XCO2 biases on the fidelity of CO2 flux inversions. Observational system simulation experiments and synthesis inversion modeling demonstrate that the Orbiting Carbon Observatory mission design and sampling strategy provide the means to achieve these XCO2 data precision requirements.This work was supported by the Orbiting Carbon Observatory (OCO) project through NASA’s Earth System Science Pathfinder (ESSP) program. SCO and JTR were supported by a NASA IDS grant (NAG5-9462) to JTR

Comparison of measured and modeled BRDF of natural targets

Communication to : 13rd annual international symposium aerosense SPIE 1999, Orlando (USA), April 05-09, 1999SIGLEAvailable from INIST (FR), Document Supply Service, under shelf-number : 22419, issue : a.1999 n.57 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

Understanding Quality of Learning in Digital Learning Environments: State of the Art and Research Needed

International audienceOver the last decade, the practice of higher education in Europe has become highly diversified and more complex. Among the visible phenomena related to the organization of studies that have appeared there are new forms of teaching and learning linked to digital learning environments. Faced with these developments, sometimes called a revolution, actors—policy makers, teachers, students—have very little in the way of scientific results to rely on. Such practices are still relatively new, and research done in this area rarely goes beyond feedback from experiences, case studies and satisfaction surveys. As such, research has not yet produced sufficient knowledge to provide a solid basis for decision-making. This chapter aims to start to address the current lack of scientific work in this area. More specifically, its ambition is to provide a theoretical framework based on the state of the art as well as research trials to answer two major questions: 1. How do student characteristics and those of digital learning environments interact? 2.What are the configurations emerging from these interactions that can lead to quality learning?. The overarching outcome will be to make new forms of teaching and learning linked to digital learning environments in higher education more intelligible