Cellular origin and microRNA profiles of circulating extracellular vesicles in different stages of diabetic nephropathy

Background: Diabetic nephropathy (DN) is a major complication of diabetes and the main cause of end-stage renal disease. Extracellular vesicles (EVs) are small cell-derived vesicles that can alter disease progression by microRNA (miRNA) transfer. Methods: In this study, we aimed to characterize the cellular origin and miRNA content of EVs in plasma samples of type 2 diabetes patients at various stages of DN. Type 2 diabetes patients were classified in three groups: normoalbuminuria, microalbuminuria and macroalbuminuria. The concentration and cellular origin of plasma EVs were measured by flow cytometry. A total of 752 EV miRNAs were profiled in 18 subjects and differentially expressed miRNAs were validated. Results: Diabetic patients with microalbuminuria and/or macroalbuminuria showed elevated concentrations of total EVs and EVs from endothelial cells, platelets, leucocytes and erythrocytes compared with diabetic controls. miR-99a-5p was upregulated in macroalbuminuric patients compared with normoalbuminuric and microalbuminuric patients. Transfection of miR-99a-5p in cultured human podocytes downregulated mammalian target of rapamycin (mTOR) protein expression and downregulated the podocyte injury marker vimentin. Conclusions: Type 2 diabetes patients with microalbuminuria and macroalbuminuria display differential EV profiles. miR-99a-5p expression is elevated in EVs from macroalbuminuria and mTOR is its validated mRNA target

HMDB: the Human Metabolome Database

The Human Metabolome Database (HMDB) is currently the most complete and comprehensive curated collection of human metabolite and human metabolism data in the world. It contains records for more than 2180 endogenous metabolites with information gathered from thousands of books, journal articles and electronic databases. In addition to its comprehensive literature-derived data, the HMDB also contains an extensive collection of experimental metabolite concentration data compiled from hundreds of mass spectra (MS) and Nuclear Magnetic resonance (NMR) metabolomic analyses performed on urine, blood and cerebrospinal fluid samples. This is further supplemented with thousands of NMR and MS spectra collected on purified, reference metabolites. Each metabolite entry in the HMDB contains an average of 90 separate data fields including a comprehensive compound description, names and synonyms, structural information, physico-chemical data, reference NMR and MS spectra, biofluid concentrations, disease associations, pathway information, enzyme data, gene sequence data, SNP and mutation data as well as extensive links to images, references and other public databases. Extensive searching, relational querying and data browsing tools are also provided. The HMDB is designed to address the broad needs of biochemists, clinical chemists, physicians, medical geneticists, nutritionists and members of the metabolomics community. The HMDB is available at

Small-Molecule Inhibitor of the Shigella flexneri Master Virulence Regulator VirF

This is the publisher's version, also available electronically from http://iai.asm.org/content/81/11/4220VirF is an AraC family transcriptional activator that is required for the expression of virulence genes associated with invasion and cell-to-cell spread by Shigella flexneri, including multiple components of the type three secretion system (T3SS) machinery and effectors. We tested a small-molecule compound, SE-1 (formerly designated OSSL_051168), which we had identified as an effective inhibitor of the AraC family proteins RhaS and RhaR, for its ability to inhibit VirF. Cell-based reporter gene assays with Escherichia coli and Shigella, as well as in vitro DNA binding assays with purified VirF, demonstrated that SE-1 inhibited DNA binding and transcription activation (likely by blocking DNA binding) by VirF. Analysis of mRNA levels using real-time quantitative reverse transcription-PCR (qRT-PCR) further demonstrated that SE-1 reduced the expression of the VirF-dependent virulence genes icsA, virB, icsB, and ipaB in Shigella. We also performed eukaryotic cell invasion assays and found that SE-1 reduced invasion by Shigella. The effect of SE-1 on invasion required preincubation of Shigella with SE-1, in agreement with the hypothesis that SE-1 inhibited the expression of VirF-activated genes required for the formation of the T3SS apparatus and invasion. We found that the same concentrations of SE-1 had no detectable effects on the growth or metabolism of the bacterial cells or the eukaryotic host cells, respectively, indicating that the inhibition of invasion was not due to general toxicity. Overall, SE-1 appears to inhibit transcription activation by VirF, exhibits selectivity toward AraC family proteins, and has the potential to be developed into a novel antibacterial agent

Id1 Interacts and Stabilizes the Epstein-Barr Virus Latent Membrane Protein 1 (LMP1) in Nasopharyngeal Epithelial Cells

The EBV-encoded latent membrane protein 1 (LMP1) functions as a constitutive active form of tumor necrosis factor receptor (TNFR) and activates multiple downstream signaling pathways similar to CD40 signaling in a ligand-independent manner. LMP1 expression in EBV-infected cells has been postulated to play an important role in pathogenesis of nasopharyngeal carcinoma. However, variable levels of LMP1 expression were detected in nasopharyngeal carcinoma. At present, the regulation of LMP1 levels in nasopharyngeal carcinoma is poorly understood. Here we show that LMP1 mRNAs are transcribed in an EBV-positive nasopharyngeal carcinoma (NPC) cell line (C666-1) and other EBV-negative nasopharyngeal carcinoma cells stably re-infected with EBV. The protein levels of LMP1 could readily be detected after incubation with proteasome inhibitor, MG132 suggesting that LMP1 protein is rapidly degraded via proteasome-mediated proteolysis. Interestingly, we observed that Id1 overexpression could stabilize LMP1 protein in EBV-infected cells. In contrary, Id1 knockdown significantly reduced LMP1 levels in cells. Co-immunoprecipitation studies revealed that Id1 interacts with LMP1 by binding to the CTAR1 domain of LMP1. N-terminal region of Id1 is required for the interaction with LMP1. Furthermore, binding of Id1 to LMP1 suppressed polyubiquitination of LMP1 and may be involved in stabilization of LMP1 in EBV-infected nasopharyngeal epithelial cells

The impact of compassion from others and self-compassion on psychological distress, flourishing, and meaning in life among university students

Objectives: Research shows that compassion from others and from the self may enable university students to face, overcome, and bounce back from adversity and generate a greater sense of thriving and meaning in life. However, the underlying processes are largely unknown. The present study aimed to examine the associations of compassion with psychological distress, flourishing, and meaning in life among university students and explore the mechanisms underlying these associations. Methods: A total of 536 Hong Kong university students completed questionnaires measuring their experiences of compassion from others, self-compassion, resilience, psychological distress, flourishing, and meaning in life. Results: Serial mediation analyses showed that compassion from others was associated positively with self-compassion, which was, in turn, linked to greater resilience and consequently lower levels of psychological distress and higher levels of flourishing and meaning in life. Conclusions: Our findings reveal the associations of compassion from others and self-compassion with the well-being and life meaning of university students. The findings highlight the importance of being open and receptive to love and kindness from others. The findings also point to the importance of developing a caring attitude toward oneself

Contextualising social capital in online brand communities

Online brand communities (OBC) are growing in number and becoming an increasingly important interface where marketers can effectively facilitate the relationship between their brand and consumers. A qualitative study using a four-month netnography over three OBCs followed by focus groups with OBC members explored the dynamics of social capital in these communities. Findings indicate that social capital is an important driver in the success of OBCs, and all the elements of social capital including a shared language, shared vision, social trust and reciprocity are evident. Moreover, results from this study indicate that these elements are crucial in developing the network ties that are integral to building loyalty and brand equity

Fine Mapping of the NRG1 Hirschsprung's Disease Locus

The primary pathology of Hirschsprung's disease (HSCR, colon aganglionosis) is the absence of ganglia in variable lengths of the hindgut, resulting in functional obstruction. HSCR is attributed to a failure of migration of the enteric ganglion precursors along the developing gut. RET is a key regulator of the development of the enteric nervous system (ENS) and the major HSCR-causing gene. Yet the reduced penetrance of RET DNA HSCR-associated variants together with the phenotypic variability suggest the involvement of additional genes in the disease. Through a genome-wide association study, we uncovered a ∼350 kb HSCR-associated region encompassing part of the neuregulin-1 gene (NRG1). To identify the causal NRG1 variants contributing to HSCR, we genotyped 243 SNPs variants on 343 ethnic Chinese HSCR patients and 359 controls. Genotype analysis coupled with imputation narrowed down the HSCR-associated region to 21 kb, with four of the most associated SNPs (rs10088313, rs10094655, rs4624987, and rs3884552) mapping to the NRG1 promoter. We investigated whether there was correlation between the genotype at the rs10088313 locus and the amount of NRG1 expressed in human gut tissues (40 patients and 21 controls) and found differences in expression as a function of genotype. We also found significant differences in NRG1 expression levels between diseased and control individuals bearing the same rs10088313 risk genotype. This indicates that the effects of NRG1 common variants are likely to depend on other alleles or epigenetic factors present in the patients and would account for the variability in the genetic predisposition to HSCR

The Human Serum Metabolome

Continuing improvements in analytical technology along with an increased interest in performing comprehensive, quantitative metabolic profiling, is leading to increased interest pressures within the metabolomics community to develop centralized metabolite reference resources for certain clinically important biofluids, such as cerebrospinal fluid, urine and blood. As part of an ongoing effort to systematically characterize the human metabolome through the Human Metabolome Project, we have undertaken the task of characterizing the human serum metabolome. In doing so, we have combined targeted and non-targeted NMR, GC-MS and LC-MS methods with computer-aided literature mining to identify and quantify a comprehensive, if not absolutely complete, set of metabolites commonly detected and quantified (with today's technology) in the human serum metabolome. Our use of multiple metabolomics platforms and technologies allowed us to substantially enhance the level of metabolome coverage while critically assessing the relative strengths and weaknesses of these platforms or technologies. Tables containing the complete set of 4229 confirmed and highly probable human serum compounds, their concentrations, related literature references and links to their known disease associations are freely available at http://www.serummetabolome.ca

Mechanism of electrochemical deposition and coloration of electrochromic V2O5 nano thin film: An in situ x-ray spectroscopy study

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Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing