154 research outputs found

    Graph Neural Networks as Gradient Flows: understanding graph convolutions via energy

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    Gradient flows are differential equations that minimize an energy functional and constitute the main descriptors of physical systems. We apply this formalism to Graph Neural Networks (GNNs) to develop new frameworks for learning on graphs as well as provide a better theoretical understanding of existing ones. We derive GNNs as a gradient flow equation of a parametric energy that provides a physics-inspired interpretation of GNNs as learning particle dynamics in the feature space. In particular, we show that in graph convolutional models (GCN), the positive/negative eigenvalues of the channel mixing matrix correspond to attractive/repulsive forces between adjacent features. We rigorously prove how the channel-mixing can learn to steer the dynamics towards low or high frequencies, which allows to deal with heterophilic graphs. We show that the same class of energies is decreasing along a larger family of GNNs; albeit not gradient flows, they retain their inductive bias. We experimentally evaluate an instance of the gradient flow framework that is principled, more efficient than GCN, and achieves competitive performance on graph datasets of varying homophily often outperforming recent baselines specifically designed to target heterophily.Comment: First two authors equal contribution; 39 page

    Athena

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    The Athena simulation software supports an analyst from DoD or other federal agency in making stability and reconstruction projections for operational analyses in areas like Iraq or Afghanistan. It encompasses the use of all elements of national power: diplomatic, information, military, and economic (DIME), and anticipates their effects on political, military, economic, social, information, and infrastructure (PMESII) variables in real-world battle space environments. Athena is a stand-alone model that provides analysts with insights into the effectiveness of complex operations by anticipating second-, third-, and higher-order effects. For example, the first-order effect of executing a curfew may be to reduce insurgent activity, but it may also reduce consumer spending and keep workers home as second-order effects. Reduced spending and reduced labor may reduce the gross domestic product (GDP) as a third-order effect. Damage to the economy will have further consequences. The Athena approach has also been considered for application in studies related to climate change and the smart grid. It can be applied to any project where the impacts on the population and their perceptions are important, and where population perception is important to the success of the project

    A multi-tissue atlas of regulatory variants in cattle:Cattle Genotype-Tissue Expression Atlas

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    Characterization of genetic regulatory variants acting on the livestock gene expression is essential for interpreting the molecular mechanisms underlying traits of economic value and for increasing the rate of genetic gain through artificial selection. Here we build a Cattle Genotype-Tissue Expression atlas (CattleGTEx) as part of the pilot phase of Farm animal GTEx (FarmGTEx) project for the research community based on publicly available 7,180 RNA-Seq samples. We describe the transcriptomic landscape of over 100 tissues/cell types and report hundreds of thousands of genetic associations with gene expression and alternative splicing for 23 distinct tissues. We evaluate the tissue-sharing patterns of these genetic regulatory effects, and functionally annotate them using multi-omics data. Finally, we link gene expression in different tissues to 43 economically important traits using both transcriptome-wide association and colocalization analyses to decipher the molecular regulatory mechanisms underpinning such agronomic traits in cattle

    Ancient homology underlies adaptive mimetic diversity across butterflies

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    Convergent evolution provides a rare, natural experiment with which to test the predictability of adaptation at the molecular level. Little is known about the molecular basis of convergence over macro-evolutionary timescales. Here we use a combination of positional cloning, population genomic resequencing, association mapping and developmental data to demonstrate that positionally orthologous nucleotide variants in the upstream region of the same gene, WntA, are responsible for parallel mimetic variation in two butterfly lineages that diverged >65 million years ago. Furthermore, characterization of spatial patterns of WntA expression during development suggests that alternative regulatory mechanisms underlie wing pattern variation in each system. Taken together, our results reveal a strikingly predictable molecular basis for phenotypic convergence over deep evolutionary time.We thank the governments of Ecuador, Costa Rica and the United States for permission to collect butterflies. In addition, we thank Larry Gilbert, Durrell Kapan, Ryan Hill, Kenny Kronforst and Nicholas Crawford for their assistance in collecting butterflies. The funding was provided by National Science Foundation awards to S. P. M., M. R. K. and R.D.R. (National Science Foundation

    Molecular and cellular mechanisms underlying the evolution of form and function in the amniote jaw.

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    The amniote jaw complex is a remarkable amalgamation of derivatives from distinct embryonic cell lineages. During development, the cells in these lineages experience concerted movements, migrations, and signaling interactions that take them from their initial origins to their final destinations and imbue their derivatives with aspects of form including their axial orientation, anatomical identity, size, and shape. Perturbations along the way can produce defects and disease, but also generate the variation necessary for jaw evolution and adaptation. We focus on molecular and cellular mechanisms that regulate form in the amniote jaw complex, and that enable structural and functional integration. Special emphasis is placed on the role of cranial neural crest mesenchyme (NCM) during the species-specific patterning of bone, cartilage, tendon, muscle, and other jaw tissues. We also address the effects of biomechanical forces during jaw development and discuss ways in which certain molecular and cellular responses add adaptive and evolutionary plasticity to jaw morphology. Overall, we highlight how variation in molecular and cellular programs can promote the phenomenal diversity and functional morphology achieved during amniote jaw evolution or lead to the range of jaw defects and disease that affect the human condition

    Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

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    Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

    Fibronectin Matrix Assembly Suppresses Dispersal of Glioblastoma Cells

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    Glioblastoma (GBM), the most aggressive and most common form of primary brain tumor, has a median survival of 12–15 months. Surgical excision, radiation and chemotherapy are rarely curative since tumor cells broadly disperse within the brain. Preventing dispersal could be of therapeutic benefit. Previous studies have reported that increased cell-cell cohesion can markedly reduce invasion by discouraging cell detachment from the tumor mass. We have previously reported that α5β1 integrin-fibronectin interaction is a powerful mediator of indirect cell-cell cohesion and that the process of fibronectin matrix assembly (FNMA) is crucial to establishing strong bonds between cells in 3D tumor-like spheroids. Here, we explore a potential role for FNMA in preventing dispersal of GBM cells from a tumor-like mass. Using a series of GBM-derived cell lines we developed an in vitro assay to measure the dispersal velocity of aggregates on a solid substrate. Despite their similar pathologic grade, aggregates from these lines spread at markedly different rates. Spreading velocity is inversely proportional to capacity for FNMA and restoring FNMA in GBM cells markedly reduces spreading velocity by keeping cells more connected. Blocking FNMA using the 70 KDa fibronectin fragment in FNMA-restored cells rescues spreading velocity, establishing a functional role for FNMA in mediating dispersal. Collectively, the data support a functional causation between restoration of FNMA and decreased dispersal velocity. This is a first demonstration that FNMA can play a suppressive role in GBM dispersal

    Interplay between phosphorylation and palmitoylation mediates plasma membrane targeting and sorting of GAP43.

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    Phosphorylation and lipidation provide posttranslational mechanisms that contribute to the distribution of cytosolic proteins in growing nerve cells. The growth-associated protein GAP43 is susceptible to both phosphorylation and S-palmitoylation and is enriched in the tips of extending neurites. However, how phosphorylation and lipidation interplay to mediate sorting of GAP43 is unclear. Using a combination of biochemical, genetic, and imaging approaches, we show that palmitoylation is required for membrane association and that phosphorylation at Ser-41 directs palmitoylated GAP43 to the plasma membrane. Plasma membrane association decreased the diffusion constant fourfold in neuritic shafts. Sorting to the neuritic tip required palmitoylation and active transport and was increased by phosphorylation-mediated plasma membrane interaction. Vesicle tracking revealed transient association of a fraction of GAP43 with exocytic vesicles and motion at a fast axonal transport rate. Simulations confirmed that a combination of diffusion, dynamic plasma membrane interaction and active transport of a small fraction of GAP43 suffices for efficient sorting to growth cones. Our data demonstrate a complex interplay between phosphorylation and lipidation in mediating the localization of GAP43 in neuronal cells. Palmitoylation tags GAP43 for global sorting by piggybacking on exocytic vesicles, whereas phosphorylation locally regulates protein mobility and plasma membrane targeting of palmitoylated GAP43
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