477 research outputs found

    The Multilateral Agreement on Investment

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    The effects of recent mortgage refinancing

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    Rising home prices and generally falling interest rates in recent years, together with a desire to convert the accumulated equity in their homes into spendable funds, have prompted many homeowners to refinance their mortgages. In the spring of 1999, the Federal Reserve surveyed consumers to determine the extent of refinancing, the extent to which refinancing homeowners "cashed-out" some of their equity when they refinanced, how much equity they took out, and how they spent the funds. Survey results suggest that cash-out refinancings in 1998 and early 1999 likely boosted consumption spending a bit, may have had a larger effect on home improvement spending, and may have moderated the growth of consumer credit during that period.Mortgages ; Housing - Finance ; Interest rates

    Structure-based neural network protein–carbohydrate interaction predictions at the residue level

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    Carbohydrates dynamically and transiently interact with proteins for cell–cell recognition, cellular differentiation, immune response, and many other cellular processes. Despite the molecular importance of these interactions, there are currently few reliable computational tools to predict potential carbohydrate-binding sites on any given protein. Here, we present two deep learning (DL) models named CArbohydrate–Protein interaction Site IdentiFier (CAPSIF) that predicts non-covalent carbohydrate-binding sites on proteins: (1) a 3D-UNet voxel-based neural network model (CAPSIF:V) and (2) an equivariant graph neural network model (CAPSIF:G). While both models outperform previous surrogate methods used for carbohydrate-binding site prediction, CAPSIF:V performs better than CAPSIF:G, achieving test Dice scores of 0.597 and 0.543 and test set Matthews correlation coefficients (MCCs) of 0.599 and 0.538, respectively. We further tested CAPSIF:V on AlphaFold2-predicted protein structures. CAPSIF:V performed equivalently on both experimentally determined structures and AlphaFold2-predicted structures. Finally, we demonstrate how CAPSIF models can be used in conjunction with local glycan-docking protocols, such as GlycanDock, to predict bound protein–carbohydrate structures

    All n-3 PUFA are not the same: MD simulations reveal differences in membrane organization for EPA, DHA and DPA

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    Eicosapentaenoic (EPA, 20:5), docosahexaenoic (DHA, 22:6) and docosapentaenoic (DPA, 22:5) acids are omega-3 polyunsaturated fatty acids (n-3 PUFA) obtained from dietary consumption of fish oils that potentially alleviate the symptoms of a range of chronic diseases. We focus here on the plasma membrane as a site of action and investigate how they affect molecular organization when taken up into a phospholipid. All atom MD simulations were performed to compare 1-stearoyl-2-eicosapentaenoylphosphatylcholine (EPA-PC, 18:0–20:5PC), 1-stearoyl-2-docosahexaenoylphosphatylcholine (DHA-PC, 18:0–22:6PC), 1-stearoyl-2-docosapentaenoylphosphatylcholine (DPA-PC, 18:0–22:5PC) and, as a monounsaturated control, 1-stearoyl-2-oleoylphosphatidylcholine (OA-PC, 18:0–18:1PC) bilayers. They were run in the absence and presence of 20 mol% cholesterol. Multiple double bonds confer high disorder on all three n-3 PUFA. The different number of double bonds and chain length for each n-3 PUFA moderates the reduction in membrane order exerted (compared to OA-PC, ̅ = 0.152). EPA-PC (̅ = 0.131) is most disordered, while DPA-PC ( ̅ = 0.140) is least disordered. DHA-PC (̅ = 0.139) is, within uncertainty, the same as DPA-PC. Following the addition of cholesterol, order in EPA-PC (̅ = 0.169), DHA-PC (̅ = 0.178) and DPA-PC (̅ = 0.182) is increased less than in OA-PC (̅ = 0.214). The high disorder of n-3 PUFA is responsible, preventing the n-3 PUFA-containing phospholipids from packing as close to the rigid sterol as the monounsaturated control. Our findings establish that EPA, DHA and DPA are not equivalent in their interactions within membranes, which possibly contributes to differences in clinical efficacy

    Anatomically and functionally distinct lung mesenchymal populations marked by Lgr5 and Lgr6

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    The diversity of mesenchymal cell types in the lung that influence epithelial homeostasis and regeneration is poorly defined. We used genetic lineage tracing, single-cell RNA sequencing, and organoid culture approaches to show that Lgr5 and Lgr6, well-known markers of stem cells in epithelial tissues, are markers of mesenchymal cells in the adult lung. Lgr6+ cells comprise a subpopulation of smooth muscle cells surrounding airway epithelia and promote airway differentiation of epithelial progenitors via Wnt-Fgf10 cooperation. Genetic ablation of Lgr6+ cells impairs airway injury repair in vivo. Distinct Lgr5+ cells are located in alveolar compartments and are sufficient to promote alveolar differentiation of epithelial progenitors through Wnt activation. Modulating Wnt activity altered differentiation outcomes specified by mesenchymal cells. This identification of region- and lineage-specific crosstalk between epithelium and their neighboring mesenchymal partners provides new understanding of how different cell types are maintained in the adult lung.This work was supported by (J.-H.L. and J.C.) Wellcome Trust and the Royal Society (107633/Z/15/Z), European Research Council Starting Grant (679411), and the Cambridge Stem Cell Institute Core grant (07922/Z/11/Z) from Wellcome Trust and Medical Research Council; (J.-H.L.) the Hope Funds for Cancer Research; (M.P.) American Lung Association (400553); (A.R.) Howard Hughes Medical Institute, the Klarman Cell Observatory, and NCI grant 1U24CA180922; (A.R., T.T., and T.J.) the Koch Institute Core grant P30-CA14051 from the NCI; (T.T.) the National Cancer InstituteK99 CA187317, the Sigrid Juselius Foundation, the Hope Funds for Cancer Research; (T.J.) a Howard Hughes Medical Institute Investigator, a David H. Koch Professor of Biology and a Daniel K. Ludwig Scholar; and (C.F.K.) R01 HL090136, R01 HL132266, R01 HL125821, U01 HL100402, Harvard Stem Cell Institute, Alfred and Gilda Slifka, Gail and Adam Slifka, and the CFMS Fund

    Docosahexaenoic acid regulates the formation of lipid rafts: A unified view from experiment and simulation

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    Docosahexaenoic acid (DHA, 22:6) is an n-3 polyunsaturated fatty acid (n-3 PUFA) that influences immunological, metabolic, and neurological responses through complex mechanisms. One structural mechanism by which DHA exerts its biological effects is through its ability to modify the physical organization of plasma membrane signaling assemblies known as sphingomyelin/cholesterol (SM/chol)-enriched lipid rafts. Here we studied how DHA acyl chains esterified in the sn-2 position of phosphatidylcholine (PC) regulate the formation of raft and non-raft domains in mixtures with SM and chol on differing size scales. Coarse grained molecular dynamics simulations showed that 1-palmitoyl-2-docosahexaenoylphosphatylcholine (PDPC) enhances segregation into domains more than the monounsaturated control, 1-palmitoyl-2-oleoyl-phosphatidylcholine (POPC). Solid state 2H NMR and neutron scattering experiments provided direct experimental evidence that substituting PDPC for POPC increases the size of raft-like domains on the nanoscale. Confocal imaging of giant unilamellar vesicles with a non-raft fluorescent probe revealed that POPC had no influence on phase separation in the presence of SM/chol whereas PDPC drove strong domain segregation. Finally, monolayer compression studies suggest that PDPC increases lipid-lipid immiscibility in the presence of SM/chol compared to POPC. Collectively, the data across model systems provide compelling support for the emerging model that DHA acyl chains of PC lipids tune the size of lipid rafts, which has potential implications for signaling networks that rely on the compartmentalization of proteins within and outside of rafts
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