Scientific reports
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Sepsis causes multiple-organ dysfunction including pancreatic injury, thus resulting in high mortality. Innate immune molecule surfactant protein D (SP-D) plays a critical role in host defense and regulating inflammation of infectious diseases. In this study we investigated SP-D functions in the acute pancreatic injury (API) with C57BL/6 Wild-type (WT) and SP-D knockout (KO) mice in cecal ligation and puncture (CLP) model. ⋯ Molecular analysis revealed increased NF-κB-p65 and phosphorylated IκB-α levels along with higher serum levels of TNF-α and IL-6 in septic KO mice compared to septic WT mice (p < 0.01). Furthermore, in vitro islet cultures stimulated with LPS produced higher TNF-α and IL-6 (p < 0.05) from KO mice compared to WT mice. Collectively, these results demonstrate SP-D plays protective roles by inhibiting apoptosis and modulating NF-κB-mediated inflammation in CLP-induced API.
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The 1000 Genomes Project provides a unique source of whole genome sequencing data for studies of human population genetics and human diseases. The last release of this project includes more than 2,500 sequenced individuals from 26 populations. Although relationships among individuals have been investigated in some of the populations, inbreeding has never been studied. ⋯ Thus, we propose subsets of unrelated and outbred individuals, for use by the scientific community. In addition, because admixed populations are present in the 1000 Genomes Project, we performed simulations to study the robustness of inbreeding coefficient estimates in the presence of admixture. We found that our multi-point approach (FSuite) was quite robust to admixture, unlike single-point methods (PLINK).
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Link prediction is a fundamental problem with applications in many fields ranging from biology to computer science. In the literature, most effort has been devoted to estimate the likelihood of the existence of a link between two nodes, based on observed links and nodes' attributes in a network. ⋯ To solve this problem, we propose a community-based link prediction method. We find that our method has high prediction accuracy and is very effective in reconstructing the inter-community links.