Cannabidiol protects oligodendrocyte progenitor cells from inflammation-induced apoptosis by attenuating endoplasmic reticulum stress

Cannabidiol (CBD) is the most abundant cannabinoid in Cannabis sativa that has no psychoactive properties. CBD has been approved to treat inflammation, pain and spasticity associated with multiple sclerosis (MS), of which demyelination and oligodendrocyte loss are hallmarks. Thus, we investigated the protective effects of CBD against the damage to oligodendrocyte progenitor cells (OPCs) mediated by the immune system. Doses of 1 μM CBD protect OPCs from oxidative stress by decreasing the production of reactive oxygen species. CBD also protects OPCs from apoptosis induced by LPS/IFNγ through the decrease of caspase 3 induction via mechanisms that do not involve CB1, CB2, TRPV1 or PPARγ receptors. Tunicamycin-induced OPC death was attenuated by CBD, suggesting a role of endoplasmic reticulum (ER) stress in the mode of action of CBD. This protection against ER stress-induced apoptosis was associated with reduced phosphorylation of eiF2α, one of the initiators of the ER stress pathway. Indeed, CBD diminished the phosphorylation of PKR and eiF2α induced by LPS/IFNγ. The pro-survival effects of CBD in OPCs were accompanied by decreases in the expression of ER apoptotic effectors (CHOP, Bax and caspase 12), and increased expression of the anti-apoptotic Bcl-2. These findings suggest that attenuation of the ER stress pathway is involved in the ‘oligoprotective' effects of CBD during inflammation

Epithelial-Mesenchymal Transition in Cancer: Parallels Between Normal Development and Tumor Progression

From the earliest stages of embryonic development, cells of epithelial and mesenchymal origin contribute to the structure and function of developing organs. However, these phenotypes are not always permanent, and instead, under the appropriate conditions, epithelial and mesenchymal cells convert between these two phenotypes. These processes, termed Epithelial-Mesenchymal Transition (EMT), or the reverse Mesenchymal-Epithelial Transition (MET), are required for complex body patterning and morphogenesis. In addition, epithelial plasticity and the acquisition of invasive properties without the full commitment to a mesenchymal phenotype are critical in development, particularly during branching morphogenesis in the mammary gland. Recent work in cancer has identified an analogous plasticity of cellular phenotypes whereby epithelial cancer cells acquire mesenchymal features that permit escape from the primary tumor. Because local invasion is thought to be a necessary first step in metastatic dissemination, EMT and epithelial plasticity are hypothesized to contribute to tumor progression. Similarities between developmental and oncogenic EMT have led to the identification of common contributing pathways, suggesting that the reactivation of developmental pathways in breast and other cancers contributes to tumor progression. For example, developmental EMT regulators including Snail/Slug, Twist, Six1, and Cripto, along with developmental signaling pathways including TGF-β and Wnt/β-catenin, are misexpressed in breast cancer and correlate with poor clinical outcomes. This review focuses on the parallels between epithelial plasticity/EMT in the mammary gland and other organs during development, and on a selection of developmental EMT regulators that are misexpressed specifically during breast cancer

Multi-temporal dynamics of suspended particulate matter in a macro- tidal river Plume (the Gironde) as observed by satellite data

International audienceThe Gironde River plume area is unique in terms of Suspended Particulate Matter (SPM) dynamics. Multiple factors contribute to the variations of SPM at multiple time scales, from river outputs to wind stress, currents and tidal cycles. The formation and evolution of the Maximum Turbidity Zone (MTZ) inside the estuary also plays a significant role. Thus, detailed analyses and monitoring of the region is important for better understanding the mechanisms governing the turbid plume dynamics, for proper future management and monitoring of SPM export from the estuary to the coastal ocean. In this study we use an unprecedented volume of satellite data to capture and better understand the dynamics of the river plume. We combine two types of satellite information in order to achieve these goals: data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensors. The integrated information allows accounting for multiple time scales, i.e. from seasonal to diurnal cycles. We show and parameterize the overall effects of river discharge rates over the plume extension. Seasonal variations are also analyzed and an overall relationship between river discharge rates and plume magnitude is computed. For the first time, we clearly observe and explain the diurnal cycle of SPM dynamics in the river plume. Despite the limited capabilities of the SEVIRI sensor, geostationary data was successfully used to derive such information and results similar to in-situ datasets were obtained. The same patterns are observed, with significant increase in SPM plume during spring/ebb tide periods. Results from our study can be further used to refine sediment transport models and to gain a better perspective on the ecological implications of the sediment output in the continental shelf area

Atmospheric Corrections and Multi-Conditional Algorithm for Multi-Sensor Remote Sensing of Suspended Particulate Matter in Low-to-High Turbidity Levels Coastal Waters

The accurate measurement of suspended particulate matter (SPM) concentrations in coastal waters is of crucial importance for ecosystem studies, sediment transport monitoring, and assessment of anthropogenic impacts in the coastal ocean. Ocean color remote sensing is an efficient tool to monitor SPM spatio-temporal variability in coastal waters. However, near-shore satellite images are complex to correct for atmospheric effects due to the proximity of land and to the high level of reflectance caused by high SPM concentrations in the visible and near-infrared spectral regions. The water reflectance signal ((w)) tends to saturate at short visible wavelengths when the SPM concentration increases. Using a comprehensive dataset of high-resolution satellite imagery and in situ SPM and water reflectance data, this study presents (i) an assessment of existing atmospheric correction (AC) algorithms developed for turbid coastal waters; and (ii) a switching method that automatically selects the most sensitive SPM vs. (w) relationship, to avoid saturation effects when computing the SPM concentration. The approach is applied to satellite data acquired by three medium-high spatial resolution sensors (Landsat-8/Operational Land Imager, National Polar-Orbiting Partnership/Visible Infrared Imaging Radiometer Suite and Aqua/Moderate Resolution Imaging Spectrometer) to map the SPM concentration in some of the most turbid areas of the European coastal ocean, namely the Gironde and Loire estuaries as well as Bourgneuf Bay on the French Atlantic coast. For all three sensors, AC methods based on the use of short-wave infrared (SWIR) spectral bands were tested, and the consistency of the retrieved water reflectance was examined along transects from low- to high-turbidity waters. For OLI data, we also compared a SWIR-based AC (ACOLITE) with a method based on multi-temporal analyses of atmospheric constituents (MACCS). For the selected scenes, the ACOLITE-MACCS difference was lower than 7%. Despite some inaccuracies in (w) retrieval, we demonstrate that the SPM concentration can be reliably estimated using OLI, MODIS and VIIRS, regardless of their differences in spatial and spectral resolutions. Match-ups between the OLI-derived SPM concentration and autonomous field measurements from the Loire and Gironde estuaries' monitoring networks provided satisfactory results. The multi-sensor approach together with the multi-conditional algorithm presented here can be applied to the latest generation of ocean color sensors (namely Sentinel2/MSI and Sentinel3/OLCI) to study SPM dynamics in the coastal ocean at higher spatial and temporal resolutions

Monitoring spatio-temporal variability of the Adour River turbid plume (Bay of Biscay, France) with MODIS 250-m imagery

Increased loads of land-based pollutants through river plumes are a major threat to the coastal water quality, ecosystems and sanitary heath. Identifying the coastal areas impacted by potentially polluted freshwaters is necessary to inform management policies and prevent degradation of the coastal environment. This study presents the first monitoring of the Adour River turbid plume (south-eastern Bay of Biscay, France) using multi-annual MODIS data. Satellite data are processed using a regional algorithm that allows quantifying and mapping suspended matter in coastal waters. The results are used to investigate the spatial and temporal variability of the Adour River turbid plume and to identify the risk of exposure of coastal ecosystems to the turbid plume waters. Changes in river plume orientation and spatial extent as well as suspended matter discharged through the river are correlated to the main hydro-climatic forcings acting in the south-eastern Bay of Biscay. The Adour River turbid plume is shown to be a highly reactive system mainly controlled by the river discharge rates and modulated by the wind changes. Despite the relatively small size of the Adour River, the Adour River turbid plume can have a non-negligible impact on the water quality of the southern Bay of Biscay and the MSM and associated contaminants/nutrients transported within the Adour turbid river plume have the potential to be disseminated far away along the northern shoreline or offshore. The main areas of influence of the river plume are defined over multi-annual (3 years) and seasonal periods. The results presented in this study show the potential of 250-m MODIS images to monitor small river plumes systems and support management and assessment of the water quality in the south-eastern Bay of Biscay

Water quality monitoring in Basque coastal areas using local chlorophyll-a algorithm and MERIS images

Accurate estimation of chlorophyll-a (chl-a), a proxy of the eutrophication risk, is necessary in coastal areas for the assessment of water quality in accordance with European Directives. Local parameterization of remote sensing algorithms is useful to cope with the variability and specificity of optically-active in-water constituents. Using the Bay of Biscay coastal waters, affected by Basque river runoffs, as a case study, the objectives of this investigation are to: 1. develop an empirical algorithm to estimate water surface chl-a for the optically-complex Basque coastal waters; 2. explore the influence of suspended matter, phytoplankton species, and pigment content on the algorithm developed for medium resolution imaging spectrometer instrument (MERIS) imagery; 3. compare the local algorithm to three ocean color algorithms (OC4v6, Gitelson's algorithm, and the OC5); and 4. apply the local algorithm to the MERIS images. For this purpose, two surveys were undertaken within the study area, the Batel-1 survey in 2007, and the Batel-2, in 2009. The empirical algorithm was developed with remote sensing reflectances (Rrs), undertaken with a TriOS field spectrometer, and chl-a measured in situ from the Batel-2 survey. The algorithm was not affected by different concentrations of suspended matter in surface waters, within the range from 0.0 to 6.6 g · m−3. There was no significant effect of 23 accessory pigments found in the area on the algorithm. Eighty-four Rrs and chl-a measurements from the Batel-1 survey were used to validate the local algorithm and to compare it with output of the other algorithms. The local algorithm provided the lowest root-mean-square difference (RMS 1/4 1.7 mg · m−3), the best correlation with the observed data (R 1/4 0.8), together with the best slope-intercept combination between predicted and observed chl-a (slope1/4 0.5, intercept 1/4 0.6). The chl-a algorithm developed here for MERIS imagery can assist in the assessment of water ecological status in the southeastern part of the Bay of Biscay, in a cost-effective manner

Potential of High Spatial and Temporal Ocean Color Satellite Data to Study the Dynamics of Suspended Particles in a Micro-Tidal River Plume

International audienceOcean color satellite sensors are powerful tools to study and monitor the dynamics of suspended particulate matter (SPM) discharged by rivers in coastal waters. In this study, we test the capabilities of Landsat-8/Operational Land Imager (OLI), AQUA&TERRA/Moderate Resolution Imaging Spectroradiometer (MODIS) and MSG-3/Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensors in terms of spectral, spatial and temporal resolutions to (i) estimate the seawater reflectance signal and then SPM concentrations and (ii) monitor the dynamics of SPM in the Rhône River plume characterized by moderately turbid surface waters in a micro-tidal sea. Consistent remote-sensing reflectance (Rrs) values are retrieved in the red spectral bands of these four satellite sensors (median relative difference less than ~16% in turbid waters). By applying a regional algorithm developed from in situ data, these Rrs are used to estimate SPM concentrations in the Rhône river plume. The spatial resolution of OLI provides a detailed mapping of the SPM concentration from the downstream part of the river itself to the plume offshore limits with well defined small-scale turbidity features. Despite the low temporal resolution of OLI, this should allow to better understand the transport of terrestrial particles from rivers to the coastal ocean. These details are partly lost using MODIS coarser resolutions data but SPM concentration estimations are consistent, with an accuracy of about 1 to 3 g·m−3 in the river mouth and plume for spatial resolutions from 250 m to 1 km. The MODIS temporal resolution (2 images per day) allows to capture the daily to monthly dynamics of the river plume. However, despite its micro-tidal environment, the Rhône River plume shows significant short-term (hourly) variations, mainly controlled by wind and regional circulation, that MODIS temporal resolution failed to capture. On the contrary, the high temporal resolution of SEVIRI makes it a powerful tool to study this hourly river plume dynamics. However, its coarse resolution prevents the monitoring of SPM concentration variations in the river mouth where SPM concentration variability can reach 20 g·m−3 inside the SEVIRI pixel. Its spatial resolution is nevertheless sufficient to reproduce the plume shape and retrieve SPM concentrations in a valid range, taking into account an underestimation of about 15%–20% based on comparisons with other sensors and in situ data. Finally, the capabilities, advantages and limits of these satellite sensors are discussed in the light of the spatial and temporal resolution improvements provided by the new and future generation of ocean color sensors onboard the Sentinel-2, Sentinel-3 and Meteosat Third Generation (MTG) satellite platforms