ALA, EPA and DHA differentially Modulate Palmitate-induced Lipotoxicity through Alterations of its Metabolism and Storage in C12C12 Muscle Cells

On that occasion, the two French societies dedicated to lipid science and technology, GERLI and SFEL, will combine their efforts to assist the scientific committee to establish an attractive program for the Euro Fed Lipid congress.Since few decades, incidence of obesity and type 2 diabetes (T2D) is increasing. Excessive intake of energy leads to fat overload and formation of lipotoxic compounds mainly derived from the saturated fatty acid palmitate in insulin-sensitive tissues (muscle, liver and white adipose tissue), promoting insulin resistance (IR, a well-known metabolic disorder in T2D). Supplementation with n-3 fatty acids (n-3FA) is suggested to reduce lipotoxicity and IR. We hypothesized that, according to the n-3FA used, differential and specific effects on palmitate metabolism in muscle cells will be demonstrated. C2C12 myotubes were treated with 500 µM of palmitate without or with 50 µM of alpha-linolenic acid (ALA), eicosapentaenoic acid (EPA) or docosahexaenoic acid (DHA) for 16 hours and collected for measurement of membrane fluidity using diphenyl-hexatriene, ceramide content, insulin-dependent Akt protein phosphorylation (as an index of IR). The assessment of the intracellular metabolism and incorporation of palmitate into lipid fractions (triglycerides, phospholipids, diglycerides) was performed after treatment for 3 hours with [1-14C]-palmitate. As expected, palmitate-induced IR was restored by EPA and DHA supplementation whereas ALA had no effect compared to palmitate alone. EPA and DHA significantly improved C2C12 membrane fluidity compared to palmitate alone (+8.5% and +13% respectively, p<0.05). Furthermore, palmitate incorporation into the diglyceride fraction was decreased by 31 and 47% by EPA and DHA vs. palmitate, respectively (p=0.05). However, DHA significantly increased the ratio of diglycerides to total lipids vs. palmitate alone (p<0.05), whereas EPA did not. Finally, EPA was more potent to decrease palmitate-induced ceramide accumulation (+174%, p<0.05 vs. control) compared to DHA (-50% and -29% repectively, p<0.05). In conclusion and contrary to ALA, EPA and DHA treatment improved the insulin signalling pathway by differently modulating membrane fluidity and lipid and palmitate metabolism, thus demonstrating that n-3FA have different metabolic impacts on C2C12 lipid metabolism

Evolving a Deep Neural Network Training Time Estimator

We present a procedure for the design of a Deep Neural Net- work (DNN) that estimates the execution time for training a deep neural network per batch on GPU accelerators. The estimator is destined to be embedded in the scheduler of a shared GPU infrastructure, capable of providing estimated training times for a wide range of network architectures, when the user submits a training job. To this end, a very short and simple representation for a given DNN is chosen. In order to compensate for the limited degree of description of the basic network representation, a novel co-evolutionary approach is taken to fit the estimator. The training set for the estimator, i.e. DNNs, is evolved by an evolutionary algorithm that optimizes the accuracy of the estimator. In the process, the genetic algorithm evolves DNNs, generates Python-Keras programs and projects them onto the simple representation. The genetic operators are dynamic, they change with the estimator’s accuracy in order to balance accuracy with generalization. Results show that despite the low degree of information in the representation and the simple initial design for the predictor, co-evolving the training set performs better than near random generated population of DNNs

Correction of interferometric and vegetation biases in the SRTMGL1 spaceborne DEM with hydrological conditioning towards improved hydrodynamics modeling in the Amazon Basin

In the Amazon basin, the recently released SRTM Global 1 arc-second (SRTMGL1) remains the best topographic information for hydrological and hydrodynamic modeling purposes. However, its accuracy is hindered by errors, partly due to vegetation, leading to erroneous simulations. Previous efforts to remove the vegetation signal either did not account for its spatial variability or relied on a single assumed percentage of penetration of the SRTM signal. Here, we propose a systematic approach over an Amazonian floodplain to remove the vegetation signal, addressing its heterogeneity by combining estimates of vegetation height and a land cover map. We improve this approach by interpolating the first results with drainage network, field and altimetry data to obtain a hydrological conditioned DEM. The averaged interferometric and vegetation biases over the forest zone were found to be -2.0 m and 7.4 m, respectively. Comparing the original and corrected DEM, vertical validation against Ground Control Points shows a RMSE reduction of 64%. Flood extent accuracy, controlled against Landsat and JERS-1 images, stresses improvements in low and high water periods (+24% and +18%, respectively). This study also highlights that a ground truth drainage network, as a unique input during the interpolation, achieves reasonable results in terms of flood extent and hydrological characteristics

Effets comparatifs des acides gras omega-3 (ALA, EPA, DHA) sur la sensibilité à l’insuline des cellules musculaires C2C12 dans un contexte lipotoxique

Objectifs :Etudier le rôle des ω3 sur la lipotoxicité induite par l’acide gras saturé palmitate (PAL, C16:0) dans un modèle de cellule musculaire C2C12.Identifier les effets propres de chaque w3 (ALA, EPA et DHA) à dose équivalente sur la fluidité des membranes et la réponse à l’insuline.Suivre le devenir intracellulaire du [1-14C]-palmitate en présence d’un w3 et définir les classes de lipides altérées.Rechercher les voies de signalisation impliquées dans la modulation de la réponse à l’insuline

A Model for Energy-efficient Task Mapping on Milliclusters

This paper exposes the mismatch between the classic problem representation in the scheduling problem of independent task mapping and the reality of multi-core proces- sors, operating system driven power management and time sharing for overlapping I/O with computation. A new, simple, model is proposed to address this gap. The model, along with a scheduling heuristic, are applied to the evaluation of software pipelin- ing in the context of the recent millicomputing initiative