VivaxGEN: An open access platform for comparative analysis of short tandem repeat genotyping data in Plasmodium vivax populations.

BACKGROUND: The control and elimination of Plasmodium vivax will require a better understanding of its transmission dynamics, through the application of genotyping and population genetics analyses. This paper describes VivaxGEN (http://vivaxgen.menzies.edu.au), a web-based platform that has been developed to support P. vivax short tandem repeat data sharing and comparative analyses. RESULTS: The VivaxGEN platform provides a repository for raw data generated by capillary electrophoresis (FSA files), with fragment analysis and standardized allele calling tools. The query system of the platform enables users to filter, select and differentiate samples and alleles based on their specified criteria. Key population genetic analyses are supported including measures of population differentiation (FST), expected heterozygosity (HE), linkage disequilibrium (IAS), neighbor-joining analysis and Principal Coordinate Analysis. Datasets can also be formatted and exported for application in commonly used population genetic software including GENEPOP, Arlequin and STRUCTURE. To date, data from 10 countries, including 5 publicly available data sets have been shared with VivaxGEN. CONCLUSIONS: VivaxGEN is well placed to facilitate regional overviews of P. vivax transmission dynamics in different endemic settings and capable to be adapted for similar genetic studies of P. falciparum and other organisms

Lattice instabilities of cubic NiTi from first principles

The phonon dispersion relation of NiTi in the simple cubic B2 structure is computed using first-principles density-functional perturbation theory with pseudopotentials and a plane-wave basis set. Lattice instabilities are observed to occur across nearly the entire Brillouin zone, excluding three interpenetrating tubes of stability along the (001) directions and small spheres of stability centered at R. The strongest instability is that of the doubly degenerate M5' mode. The atomic displacements of one of the eigenvectors of this mode generate a good approximation to the observed B19' ground-state structure.Comment: 11 pages, 3 figure

Omics-squared: human genomic, transcriptomic and phenotypic data for genetic analysis workshop 19

Background The Genetic Analysis Workshops (GAW) are a forum for development, testing, and comparison of statistical genetic methods and software. Each contribution to the workshop includes an application to a specified data set. Here we describe the data distributed for GAW19, which focused on analysis of human genomic and transcriptomic data. Methods GAW19 data were donated by the T2D-GENES Consortium and the San Antonio Family Heart Study and included whole genome and exome sequences for odd-numbered autosomes, measures of gene expression, systolic and diastolic blood pressures, and related covariates in two Mexican American samples. These two samples were a collection of 20 large families with whole genome sequence and transcriptomic data and a set of 1943 unrelated individuals with exome sequence. For each sample, simulated phenotypes were constructed based on the real sequence data. ‘Functional’ genes and variants for the simulations were chosen based on observed correlations between gene expression and blood pressure. The simulations focused primarily on additive genetic models but also included a genotype-by-medication interaction. A total of 245 genes were designated as ‘functional’ in the simulations with a few genes of large effect and most genes explaining \u3c 1 % of the trait variation. An additional phenotype, Q1, was simulated to be correlated among related individuals, based on theoretical or empirical kinship matrices, but was not associated with any sequence variants. Two hundred replicates of the phenotypes were simulated. The GAW19 data are an expansion of the data used at GAW18, which included the family-based whole genome sequence, blood pressure, and simulated phenotypes, but not the gene expression data or the set of 1943 unrelated individuals with exome sequence

Gene expression profiling reveals different pathways related to Abl and other genes that cooperate with c-Myc in a model of plasma cell neoplasia

<p>Abstract</p> <p>Background</p> <p>To elucidate the genes involved in the neoplastic transformation of B cells, global gene expression profiles were generated using Affymetrix U74Av2 microarrays, containing 12,488 genes, for four different groups of mouse B-cell lymphomas and six subtypes of pristane-induced mouse plasma cell tumors, three of which developed much earlier than the others.</p> <p>Results</p> <p>Unsupervised hierarchical cluster analysis exhibited two main sub-clusters of samples: a B-cell lymphoma cluster and a plasma cell tumor cluster with subclusters reflecting mechanism of induction. This report represents the first step in using global gene expression to investigate molecular signatures related to the role of cooperating oncogenes in a model of Myc-induced carcinogenesis. Within a single subgroup, e.g., ABPCs, plasma cell tumors that contained typical T(12;15) chromosomal translocations did not display gene expression patterns distinct from those with variant T(6;15) translocations, in which the breakpoint was in the <it>Pvt-1 </it>locus, 230 kb 3' of c-<it>Myc</it>, suggesting that c-<it>Myc </it>activation was the initiating factor in both. When integrated with previously published Affymetrix array data from human multiple myelomas, the IL-6-transgenic subset of mouse plasma cell tumors clustered more closely with MM1 subsets of human myelomas, slow-appearing plasma cell tumors clustered together with MM2, while plasma cell tumors accelerated by v-Abl clustered with the more aggressive MM3-MM4 myeloma subsets. Slow-appearing plasma cell tumors expressed <it>Socs1 </it>and <it>Socs2 </it>but v-<it>Abl</it>-accelerated plasma cell tumors expressed 4–5 times as much. Both v-<it>Abl</it>-accelerated and non-v-<it>Ab</it>l-associated tumors exhibited phosphorylated STAT 1 and 3, but only v-Abl-accelerated plasma cell tumors lost viability and STAT 1 and 3 phosphorylation when cultured in the presence of the v-Abl kinase inhibitor, STI-571. These data suggest that the Jak/Stat pathway was critical in the transformation acceleration by v-Abl and that v-Abl activity remained essential throughout the life of the tumors, not just in their acceleration. A different pathway appears to predominate in the more slowly arising plasma cell tumors.</p> <p>Conclusion</p> <p>Gene expression profiling differentiates not only B-cell lymphomas from plasma cell tumors but also distinguishes slow from accelerated plasma cell tumors. These data and those obtained from the sensitivity of v-Abl-accelerated plasma cell tumors and their phosphorylated STAT proteins indicate that these similar tumors utilize different signaling pathways but share a common initiating genetic lesion, a c-<it>Myc</it>-activating chromosome translocation.</p

The human diabetes proteome project (HDPP): The 2014 update

Diabetes is an increasing worldwide problem leading to major associated health issues and increased health care costs. In 2012, 9.3% of the American population was affected by diabetes, according to the American Diabetes Association, with 1.7 million of new cases since during the year (www.diabetes.org). Proteome initiatives can provide a deeper understanding of the biology of this disease and help develop more effective treatments. The collaborative effort of the Human Diabetes Proteome Project (HDPP) brings together a wide variety of complementary resources to increase the existing knowledge about both type 1 and type 2 diabetes and their related complications. The goals are to identify proteins and protein isoforms associated with the pathology and to characterize underlying disease-related pathways and mechanisms. Moreover, a considerable effort is being made on data integration and network biology. Sharing these data with the scientific community will be an important part of the consortium. Here we report on: the content of the HDPP session held at the 12th HUPO meeting in Yokohama; recent achievements of the consortium; discussions of several HDPP workshops; as well as future HDPP directions as discussed at the 13th HUPO congress in Madrid, with a special attention given to the lists of prioritized, diabetes-related proteins and the proteomic means to study them.</p

EGFR, CD10 and proliferation marker Ki67 expression in ameloblastoma: possible role in local recurrence

<p>Abstract</p> <p>Background</p> <p>Ameloblastoma is an odontogenic neoplasm characterized by local invasiveness and tendency towards recurrence.</p> <p>Aims</p> <p>Studying the role played by EGFR, CD10 and Ki67 in the recurrence of ameloblastoma.</p> <p>Methods</p> <p>This study was carried out on 22 retrospective cases of mandibular ameloblastoma from the period from Jan 2002 to Jan 2008 with follow up period until Jan 2011 (3 to 8 years follow up peroid). Archival materials were obtained from pathology department, Mansoura university. Paraffin sections of tumor tissue from all cases were submitted for routine H&E stains and immunohistochemistry using EGFR, CD10 and Ki67 monoclonal antibodies. Statistical analysis using of clinical data for all patients, tumor type, EGFR, CD10 and Ki67 expression in relation to recurrence were evaluated.</p> <p>Results</p> <p>Among the 22 cases, 10 cases were males and 12 were females with sex ratio 1:1.2. Age ranged from 34 to 59 years old with a mean age 44.18 year. Five cases showed local recurrence within studied period and proved by biopsy. No statistically significant relation was found between local recurrence and patient age, tumor size, tumor type, EGFR expression. There was a significant relation between CD10 expression as well as Ki67 labelling index and recurrence (P value = 0.003, 0.000 respectively).</p> <p>Conclusion</p> <p>Evaluation of CD10 and Ki67 status together with conventional histological evaluation can help in providing more information about the biologic behavior of the tumor, while EGFR could be a target of an expanding class of anticancer therapies.</p> <p>Since ameloblastomas are EGFR-positive tumors, anti-EGFR agents could be considered to reduce the size of large tumors and to treat unresectable tumors that are in close proximity to vital structures.</p> <p>Virtual Slides</p> <p>The virtual slide(s) for this article can be found here:</p> <p><url>http://www.diagnosticpathology.diagnomx.eu/vs/1902106905645651</url></p

Perilipin 2 (PLIN2)-Deficiency Does Not Increase Cholesterol-Induced Toxicity in Macrophages

Interventions on macrophages/foam cells to redirect intracellular cholesterol towards efflux pathways could become a very valuable addition to our therapeutic arsenal against atherosclerosis. However, certain manipulations of the cholesteryl ester cycle, such as the inhibition of ACAT1, an ER-resident enzyme that re-esterifies cholesterol, are not well tolerated. Previously we showed that targeting perilipin-2 (PLIN2), a major lipid droplet (LD)-associated protein in macrophages, prevents foam cell formation and protects against atherosclerosis. Here we have assessed the tolerance of PLIN2-deficient bone marrow derived macrophages (BMM) to several lipid loading conditions similar to the found during atherosclerosis development, including exposure to modified low-density lipoprotein (mLDL) and 7-ketocholesterol (7-KC), a free cholesterol (FC) metabolite, in media with or without cholesterol acceptors. BMM isolated from mice that do or do not express PLIN2 were tested for apoptosis (TUNEL and cleaved caspase-3), ER stress (CHOP induction and XBP-1 splicing), and inflammation (TNF-α and IL-6 mRNA levels). Like in other cell types, PLIN2 deficiency impairs LD buildup in BMM. However, while most stress parameters were elevated in macrophages under ACAT inhibition and 7-KC loading, PLIN2 inactivation was well tolerated. The data support the safety of targeting PLIN2 to prevent foam cell formation and atherosclerosis

Proteome sequence features carry signatures of the environmental niche of prokaryotes

<p>Abstract</p> <p>Background</p> <p>Prokaryotic environmental adaptations occur at different levels within cells to ensure the preservation of genome integrity, proper protein folding and function as well as membrane fluidity. Although specific composition and structure of cellular components suitable for the variety of extreme conditions has already been postulated, a systematic study describing such adaptations has not yet been performed. We therefore explored whether the environmental niche of a prokaryote could be deduced from the sequence of its proteome. Finally, we aimed at finding the precise differences between proteome sequences of prokaryotes from different environments.</p> <p>Results</p> <p>We analyzed the proteomes of 192 prokaryotes from different habitats. We collected detailed information about the optimal growth conditions of each microorganism. Furthermore, we selected 42 physico-chemical properties of amino acids and computed their values for each proteome. Further, on the same set of features we applied two fundamentally different machine learning methods, Support Vector Machines and Random Forests, to successfully classify between bacteria and archaea, halophiles and non-halophiles, as well as mesophiles, thermophiles and mesothermophiles. Finally, we performed feature selection by using Random Forests.</p> <p>Conclusions</p> <p>To our knowledge, this is the first time that three different classification cases (domain of life, halophilicity and thermophilicity) of proteome adaptation are successfully performed with the same set of 42 features. The characteristic features of a specific adaptation constitute a signature that may help understanding the mechanisms of adaptation to extreme environments.</p