MD Simulations of Full-Scale HIV-1 Lipid Envelope on LANL Grizzly Supercomputer [Slide]
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Final Conference Program and Registration List
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Three peroxisome proliferator-activated receptor paralogues (PPARα, -β and -γ) are currently recognized in vertebrate genomes. PPARγ is known to modulate nutrition, adipogenesis and immunity in vertebrates. Natural ligands of PPARγ have been proposed; however, the receptor also binds synthetic ligands such as endocrine disruptors. Two paralogues of PPARα and PPARβ have been documented in teleost species, a consequence of the 3R WGD. Recently, two PPARγ paralogue genes were also identified in Astyanax mexicanus. We aimed to determine whether the presence of two PPARγ paralogues is prevalent in other teleost genomes, through genomic and phylogenetic analysis. Our results showed that besides Characiformes, two PPARγ paralogous genes were also identified in other teleost taxa, coinciding with the teleost-specific, whole-genome duplication and with the retention of both genes prior to the separation of the Clupeocephala. To functionally characterize these genes, we used the European sardine (Sardina pilchardus) as a model. PPARγA and PPARγB display a different tissue distribution, despite the similarity of their functional profiles: they are unresponsive to tested fatty acids and other human PPARγ ligands yet yield a transcriptional response in the presence of tributyltin (TBT). This observation puts forward the relevance of comparative analysis to decipher alternative binding architectures and broadens the disruptive potential of man-made chemicals for aquatic species.
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Past work from our lab, focused on engineering the budding yeast Saccharomyces cerevisiae for fermentation of the non-native pentose sugar xylose, discovered that hyperactivation of the RAS/Protein Kinase A (PKA) pathway was needed for rapid anaerobic xylose fermentation. Interestingly, the mechanism of PKA hyperactivation has a dramatic impact on growth and metabolism on xylose; deletion of the RAS inhibitor IRA2 permits rapid growth and fermentation, while deletion of the PKA regulatory subunit BCY1 allows for fermentation without growth on xylose. To understand how a single deletion in the PKA pathway can decouple growth and metabolism, we performed transcriptomic analysis of these strains, predicting that altered PKA activity would impact global gene expression and identify pathways important for growth and metabolism coordination.
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This library of Python code is used for performing semantic segmentation of images using 6 different machine learning methods. Five of the methods are implemented entirely within the scikit-learn framework. The Convolutional Neural Network (CNN) method requires Keras with a TensorFlow backend and generally uses a different set of scripts in order to perform the complete training and evaluation.
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