Anatomical UV Exposure in French Outdoor Workers.

BACKGROUND: Solar ultraviolet has been recognized as the main causative factor for skin cancer and is currently classified as a carcinogenic agent by International Agency for Research on Cancer. METHOD: Results from a previous phone survey conducted in 2012 in France were used to assess exposure conditions to sun among outdoor workers. Satellite data were used in combination with an exposure model to assess anatomical exposure. RESULT: The yearly median exposure of the outdoor worker population is 77  kJ/m2 to 116  kJ/m2. Road workers, building workers, and gardeners are the more exposed. About 70% of the yearly dose estimate is due to the cumulative summer and spring exposures. CONCLUSIONS: This study highlights the role of individual factors in anatomical exposure and ranks the most exposed body parts and outdoor occupations. Prevention messages should put emphasis on spring exposure, which is an important contributor to the yearly dose.

Acid-sensing ion channel 1a drives AMPA receptor plasticity following ischemia and acidosis in hippocampal CA1 neurons

The CA1 region of the hippocampus is particularly vulnerable to ischemic damage. While NMDA receptors play a major role in excitotoxicity, it is thought to be exacerbated in this region by two forms of post-ischemic AMPA receptor (AMPAR) plasticity - namely, anoxic long-term potentiation (a-LTP), and a delayed increase in the prevalence of Ca2+ -permeable GluA2-lacking AMPARs (CP-AMPARs). The acid-sensing ion channel 1a (ASIC1a) which is expressed in CA1 pyramidal neurons, is also known to contribute to post-ischemic neuronal death and to physiologically induced LTP. This raises the question - does ASIC1a activation drive the post-ischemic forms of AMPAR plasticity in CA1 pyramidal neurons? We have tested this by examining organotypic hippocampal slice cultures (OHSCs) exposed to oxygen glucose deprivation (OGD), and dissociated cultures of hippocampal pyramidal neurons (HPN) exposed to low pH (acidosis). We find that both a-LTP and the delayed increase in the prevalence of CP-AMPARs are dependent on ASIC1a activation during ischemia. Indeed, acidosis alone is sufficient to induce the increase in CP-AMPARs. We also find that inhibition of ASIC1a channels circumvents any potential neuroprotective benefit arising from block of CP-AMPARs. By demonstrating that ASIC1a activation contributes to post-ischemic AMPAR plasticity, our results identify a functional interaction between acidotoxicity and excitotoxicity in hippocampal CA1 cells, and provide insight into the role of ASIC1a and CP-AMPARs as potential drug targets for neuroprotection. We thus propose that ASIC1a activation can drive certain forms of CP-AMPAR plasticity, and that inhibiting ASIC1a affords neuroprotection.

Adaptation of Root Function by Nutrient-Induced Plasticity of Endodermal Differentiation.

Plant roots forage the soil for minerals whose concentrations can be orders of magnitude away from those required for plant cell function. Selective uptake in multicellular organisms critically requires epithelia with extracellular diffusion barriers. In plants, such a barrier is provided by the endodermis and its Casparian strips-cell wall impregnations analogous to animal tight and adherens junctions. Interestingly, the endodermis undergoes secondary differentiation, becoming coated with hydrophobic suberin, presumably switching from an actively absorbing to a protective epithelium. Here, we show that suberization responds to a wide range of nutrient stresses, mediated by the stress hormones abscisic acid and ethylene. We reveal a striking ability of the root to not only regulate synthesis of suberin, but also selectively degrade it in response to ethylene. Finally, we demonstrate that changes in suberization constitute physiologically relevant, adaptive responses, pointing to a pivotal role of the endodermal membrane in nutrient homeostasis.

Characterisation of anatomical properties of the human basal ganglia using magnetic resonance imaging

The detailed in-vivo characterization of subcortical brain structures is essential not only to understand the basic organizational principles of the healthy brain but also for the study of the involvement of the basal ganglia in brain disorders. The particular tissue properties of basal ganglia - most importantly their high iron content, strongly affect the contrast of magnetic resonance imaging (MRI) images, hampering the accurate automated assessment of these regions. This technical challenge explains the substantial controversy in the literature about the magnitude, directionality and neurobiological interpretation of basal ganglia structural changes estimated from MRI and computational anatomy techniques. My scientific project addresses the pertinent need for accurate automated delineation of basal ganglia using two complementary strategies: ? Empirical testing of the utility of novel imaging protocols to provide superior contrast in the basal ganglia and to quantify brain tissue properties; ? Improvement of the algorithms for the reliable automated detection of basal ganglia and thalamus Previous research demonstrated that MRI protocols based on magnetization transfer (MT) saturation maps provide optimal grey-white matter contrast in subcortical structures compared with the widely used Tl-weighted (Tlw) images (Helms et al., 2009). Under the assumption of a direct impact of brain tissue properties on MR contrast my first study addressed the question of the mechanisms underlying the regional specificities effect of the basal ganglia. I used established whole-brain voxel-based methods to test for grey matter volume differences between MT and Tlw imaging protocols with an emphasis on subcortical structures. I applied a regression model to explain the observed grey matter differences from the regionally specific impact of brain tissue properties on the MR contrast. The results of my first project prompted further methodological developments to create adequate priors for the basal ganglia and thalamus allowing optimal automated delineation of these structures in a probabilistic tissue classification framework. I established a standardized workflow for manual labelling of the basal ganglia, thalamus and cerebellar dentate to create new tissue probability maps from quantitative MR maps featuring optimal grey-white matter contrast in subcortical areas. The validation step of the new tissue priors included a comparison of the classification performance with the existing probability maps. In my third project I continued investigating the factors impacting automated brain tissue classification that result in interpretational shortcomings when using Tlw MRI data in the framework of computational anatomy. While the intensity in Tlw images is predominantly