11 research outputs found

    Chez les plantes aussi, des gÚnes font de la résistance

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    Non-Gaussian Diffusion Imaging for Enhanced Contrast of Brain Tissue Affected by Ischemic Stroke

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    Recent diffusion MRI studies of stroke in humans and animals have shown that the quantitative parameters characterising the degree of non-Gaussianity of the diffusion process are much more sensitive to ischemic changes than the apparent diffusion coefficient (ADC) considered so far as the "gold standard". The observed changes exceeded that of the ADC by a remarkable factor of 2 to 3. These studies were based on the novel non-Gaussian methods, such as diffusion kurtosis imaging (DKI) and log-normal distribution function imaging (LNDFI). As shown in our previous work investigating the animal stroke model, a combined analysis using two methods, DKI and LNDFI provides valuable complimentary information. In the present work, we report the application of three non-Gaussian diffusion models to quantify the deviations from the Gaussian behaviour in stroke induced by transient middle cerebral artery occlusion in rat brains: the gamma-distribution function (GDF), the stretched exponential model (SEM), and the biexponential model. The main goal was to compare the sensitivity of various non-Gaussian metrics to ischemic changes and to investigate if a combined application of several models will provide added value in the assessment of stroke. We have shown that two models, GDF and SEM, exhibit a better performance than the conventional method and allow for a significantly enhanced visualization of lesions. Furthermore, we showed that valuable information regarding spatial properties of stroke lesions can be obtained. In particular, we observed a stratified cortex structure in the lesions that were well visible in the maps of the GDF and SEM metrics, but poorly distinguishable in the ADC-maps. Our results provided evidence that cortical layers tend to be differently affected by ischemic processes

    Regulation of P-glycoprotein and Breast Cancer Resistance Protein Expression Induced by Focused Ultrasound-Mediated Blood-Brain Barrier Disruption: A Pilot Study

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    The blood-brain barrier (BBB) controls brain homeostasis; it is formed by vascular endothelial cells that are physically connected by tight junctions (TJs). The BBB expresses efflux transporters such as P-glycoprotein (P-gp) and breast cancer resistance protein (BCRP), which limit the passage of substrate molecules from blood circulation to the brain. Focused ultrasound (FUS) with microbubbles can create a local and reversible detachment of the TJs. However, very little is known about the effect of FUS on the expression of efflux transporters. We investigated the in vivo effects of moderate acoustic pressures on both P-gp and BCRP expression for up to two weeks after sonication. Magnetic resonance-guided FUS was applied in the striatum of 12 rats. P-gp and BCRP expression were determined by immunohistochemistry at 1, 3, 7, and 14 days postFUS. Our results indicate that FUS-induced BBB opening is capable of (i) decreasing P-gp expression up to 3 days after sonication in both the treated and in the contralateral brain regions and is capable of (ii) overexpressing BCRP up to 7 days after FUS in the sonicated regions only. Our findings may help improve FUS-aided drug delivery strategies by considering both the mechanical effect on the TJs and the regulation of P-gp and BCRP

    A multicriteria method to evaluate the resilience of grass-based dairy farms to climate change in Brittany

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    International audienceGrass-based dairy systems have proven their interest for sustainability, but their resilience to climate change has been less studied. As crop diversification is usually seen as good practice for more resilient farming systems, we want to study if the sole use of grasslands as forage resources is less resilient than the use of grass and maize. To do so, we designed a three-step method for assessing the resilience of dairy farms to climate change. First, we established correlations between farm performance indicators and climatic variables during the last 5 years, to estimate their vulnerability and their adaptations to these external drivers. Then, we compared the different farming systems through a multi-criteria approach of resilience co-designed with the farmers. Our results show that climatic variables have a low impact on the performances of studied farms. However, grass-based systems experience more inter-annual variationsin milk production than grass maize systems, while their economic performances are more robust. This work provides a useful tool for resilience assessment of dairy farms

    A multicriteria method to evaluate the resilience of grass-based dairy farms to climate change in Brittany

    No full text
    International audienceGrass-based dairy systems have proven their interest for sustainability, but their resilience to climate change has been less studied. As crop diversification is usually seen as good practice for more resilient farming systems, we want to study if the sole use of grasslands as forage resources is less resilient than the use of grass and maize. To do so, we designed a three-step method for assessing the resilience of dairy farms to climate change. First, we established correlations between farm performance indicators and climatic variables during the last 5 years, to estimate their vulnerability and their adaptations to these external drivers. Then, we compared the different farming systems through a multi-criteria approach of resilience co-designed with the farmers. Our results show that climatic variables have a low impact on the performances of studied farms. However, grass-based systems experience more inter-annual variationsin milk production than grass maize systems, while their economic performances are more robust. This work provides a useful tool for resilience assessment of dairy farms
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