6,887 research outputs found

    Evolving symbolic density functionals

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    Systematic development of accurate density functionals has been a decades-long challenge for scientists. Despite the emerging application of machine learning (ML) in approximating functionals, the resulting ML functionals usually contain more than tens of thousands parameters, which makes a huge gap in the formulation with the conventional human-designed symbolic functionals. We propose a new framework, Symbolic Functional Evolutionary Search (SyFES), that automatically constructs accurate functionals in the symbolic form, which is more explainable to humans, cheaper to evaluate, and easier to integrate to existing density functional theory codes than other ML functionals. We first show that without prior knowledge, SyFES reconstructed a known functional from scratch. We then demonstrate that evolving from an existing functional ω\omegaB97M-V, SyFES found a new functional, GAS22 (Google Accelerated Science 22), that performs better for the majority of molecular types in the test set of Main Group Chemistry Database (MGCDB84). Our framework opens a new direction in leveraging computing power for the systematic development of symbolic density functionals

    Expression profiling of metalloproteinases and tissue inhibitors of metalloproteinases in normal and degenerate human achilles tendon

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    To profile the messenger RNA (mRNA) expression for the 23 known genes of matrix metalloproteinases (MMPs), 19 genes of ADAMTS, 4 genes of tissue inhibitors of metalloproteinases (TIMPs), and ADAM genes 8, 10, 12, and 17 in normal, painful, and ruptured Achilles tendons. Tendon samples were obtained from cadavers or from patients undergoing surgical procedures to treat chronic painful tendinopathy or ruptured tendon. Total RNA was extracted and mRNA expression was analyzed by quantitative real-time reverse transcription–polymerase chain reaction, normalized to 18S ribosomal RNA. In comparing expression of all genes, the normal, painful, and ruptured Achilles tendon groups each had a distinct mRNA expression signature. Three mRNA were not detected and 14 showed no significant difference in expression levels between the groups. Statistically significant (P < 0.05) differences in mRNA expression, when adjusted for age, included lower levels of MMPs 3 and 10 and TIMP-3 and higher levels of ADAM-12 and MMP-23 in painful compared with normal tendons, and lower levels of MMPs 3 and 7 and TIMPs 2, 3, and 4 and higher levels of ADAMs 8 and 12, MMPs 1, 9, 19, and 25, and TIMP-1 in ruptured compared with normal tendons. The distinct mRNA profile of each tendon group suggests differences in extracellular proteolytic activity, which would affect the production and remodeling of the tendon extracellular matrix. Some proteolytic activities are implicated in the maintenance of normal tendon, while chronically painful tendons and ruptured tendons are shown to be distinct groups. These data will provide a foundation for further study of the role and activity of many of these enzymes that underlie the pathologic processes in the tendon

    Seroconversion to Pandemic (H1N1) 2009 Virus and Cross-Reactive Immunity to Other Swine Influenza Viruses

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    To assess herd immunity to swine influenza viruses, we determined antibodies in 28 paired serum samples from participants in a prospective serologic cohort study in Hong Kong who had seroconverted to pandemic (H1N1) 2009 virus. Results indicated that infection with pandemic (H1N1) 2009 broadens cross-reactive immunity to other recent subtype H1 swine viruses

    The impact of contact tracing in clustered populations

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    The tracing of potentially infectious contacts has become an important part of the control strategy for many infectious diseases, from early cases of novel infections to endemic sexually transmitted infections. Here, we make use of mathematical models to consider the case of partner notification for sexually transmitted infection, however these models are sufficiently simple to allow more general conclusions to be drawn. We show that, when contact network structure is considered in addition to contact tracing, standard “mass action” models are generally inadequate. To consider the impact of mutual contacts (specifically clustering) we develop an improvement to existing pairwise network models, which we use to demonstrate that ceteris paribus, clustering improves the efficacy of contact tracing for a large region of parameter space. This result is sometimes reversed, however, for the case of highly effective contact tracing. We also develop stochastic simulations for comparison, using simple re-wiring methods that allow the generation of appropriate comparator networks. In this way we contribute to the general theory of network-based interventions against infectious disease

    Antibodies to the Mr 64,000 (64K) protein in islet cell antibody positive non-diabetic individuals indicate high risk for impaired Beta-cell function

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    A prospective study of a normal childhood population identified 44 islet cell antibody positive individuals. These subjects were typed for HLA DR and DQ alleles and investigated for the presence of antibodies to the Mr 64,000 (64K) islet cell antigen, complement-fixing islet cell antibodies and radiobinding insulin autoantibodies to determine their potency in detecting subjects with impaired Beta-cell function. At initial testing 64K antibodies were found in six of 44 islet cell antibody positive subjects (13.6%). The same sera were also positive for complement-fixing islet cell antibodies and five of them had insulin autoantibodies. During the follow-up at 18 months, islet cell antibodies remained detectable in 50% of the subjects studied. In all six cases who were originally positive, 64K antibodies were persistently detectable, whereas complement-fixing islet cell antibodies became negative in two of six and insulin autoantibodies in one of five individuals. HLA DR4 (p < 0.005) and absence of asparic acid (Asp) at position 57 of the HLA DQ chain (p < 0.05) were significantly increased in subjects with 64K antibodies compared with control subjects. Of 40 individuals tested in the intravenous glucose tolerance test, three had a first phase insulin response below the first percentile of normal control subjects. Two children developed Type 1 (insulin-dependent) diabetes mellitus after 18 and 26 months, respectively. Each of these subjects was non-Asp homozygous and had persistent islet cell and 64K antibodies. We conclude that 64K antibodies, complement-fixing islet cell antibodies and insulin autoantibodies represent sensitive serological markers in assessing high risk for a progression to Type 1 diabetes in islet cell antibody positive non-diabetic individuals

    Inhibitory Effects of Skin Permeable Glucitol-core Containing Gallotannins from Red Maple Leaves on Elastase and their Protective Effects on Human Keratinocytes

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    Glucitol-core containing gallotannins (GCGs) from the red maple (Acer rubrum) species have been reported to exhibit skin beneficial activities but their inhibitory effects on elastase remain unclear. Herein, we evaluated a series of GCGs for their anti-elastase activity, skin permeability, and cytoprotective effects in human keratinocytes HaCaT cells. GCGs’ anti-elastase effects were enhanced as their number of galloyl groups increased, which may be attributed to the formation of more stable protein–ligand complexes. In addition, GCGs were predicted to have moderate skin permeability and ginnalin A (GA) showed favorable permeability in the PAMPA model and cell uptake assay. Moreover, GA, ginnalin B, and maplexin F (at 50 µM) reduced H2O2-induced reactive oxygen species in HaCaT cells by 70.8, 92.8, and 84.6%, respectively. In conclusion, red maple GCGs are skin permeable elastase inhibitors with antioxidant activity, which may contribute to their overall skin beneficial effects and support their potential for cosmeceutical applications

    A mixed effect model for bivariate meta-analysis of diagnostic test accuracy studies using a copula representation of the random effects distribution

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    Diagnostic test accuracy studies typically report the number of true positives, false positives, true negatives and false negatives. There usually exists a negative association between the number of true positives and true negatives, because studies that adopt less stringent criterion for declaring a test positive invoke higher sensitivities and lower specificities. A generalized linear mixed model (GLMM) is currently recommended to synthesize diagnostic test accuracy studies. We propose a copula mixed model for bivariate meta-analysis of diagnostic test accuracy studies. Our general model includes the GLMM as a special case and can also operate on the original scale of sensitivity and specificity. Summary receiver operating characteristic curves are deduced for the proposed model through quantile regression techniques and different characterizations of the bivariate random effects distribution. Our general methodology is demonstrated with an extensive simulation study and illustrated by re-analysing the data of two published meta-analyses. Our study suggests that there can be an improvement on GLMM in fit to data and makes the argument for moving to copula random effects models. Our modelling framework is implemented in the package CopulaREMADA within the open source statistical environment R
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