Industrial metal pollution in water and probabilistic assessment of human health risk

© 2016 Elsevier Ltd Concentration of eight heavy metals in surface and groundwater around Dhaka Export Processing Zone (DEPZ) industrial area were investigated, and the health risk posed to local children and adult residents via ingestion and dermal contact was evaluated using deterministic and probabilistic approaches. Metal concentrations (except Cu, Mn, Ni, and Zn) in Bangshi River water were above the drinking water quality guidelines, while in groundwater were less than the recommended limits. Concentration of metals in surface water decreased as a function of distance. Estimations of non-carcinogenic health risk for surface water revealed that mean hazard index (HI) values of As, Cr, Cu, and Pb for combined pathways (i.e., ingestion and dermal contact) were >1.0 for both age groups. The estimated risk mainly came from the ingestion pathway. However, the HI values for all the examined metals in groundwater were 1 × 10−4 for adult and children, respectively. Deterministic and probabilistic estimations of cancer risk through exposure to groundwater were well below the safety limit. Overall, the population exposed to Bangshi River water remained at carcinogenic and non-carcinogenic health threat and the risk was higher for adults. Sensitivity analysis identified exposure duration (ED) and ingestion rate (IR) of water as the most relevant variables affecting the probabilistic risk estimation model outcome

Bianchi Type-II String Cosmological Models in Normal Gauge for Lyra's Manifold with Constant Deceleration Parameter

The present study deals with a spatially homogeneous and anisotropic Bianchi-II cosmological models representing massive strings in normal gauge for Lyra's manifold by applying the variation law for generalized Hubble's parameter that yields a constant value of deceleration parameter. The variation law for Hubble's parameter generates two types of solutions for the average scale factor, one is of power-law type and other is of the exponential form. Using these two forms, Einstein's modified field equations are solved separately that correspond to expanding singular and non-singular models of the universe respectively. The energy-momentum tensor for such string as formulated by Letelier (1983) is used to construct massive string cosmological models for which we assume that the expansion ($\theta$) in the model is proportional to the component $\sigma^{1}_{~1}$ of the shear tensor $\sigma^{j}_{i}$. This condition leads to $A = (BC)^{m}$, where A, B and C are the metric coefficients and m is proportionality constant. Our models are in accelerating phase which is consistent to the recent observations. It has been found that the displacement vector $\beta$ behaves like cosmological term $\Lambda$ in the normal gauge treatment and the solutions are consistent with recent observations of SNe Ia. It has been found that massive strings dominate in the decelerating universe whereas strings dominate in the accelerating universe. Some physical and geometric behaviour of these models are also discussed.Comment: 24 pages, 10 figure

Design and utilization of epitope-based databases and predictive tools

In the last decade, significant progress has been made in expanding the scope and depth of publicly available immunological databases and online analysis resources, which have become an integral part of the repertoire of tools available to the scientific community for basic and applied research. Herein, we present a general overview of different resources and databases currently available. Because of our association with the Immune Epitope Database and Analysis Resource, this resource is reviewed in more detail. Our review includes aspects such as the development of formal ontologies and the type and breadth of analytical tools available to predict epitopes and analyze immune epitope data. A common feature of immunological databases is the requirement to host large amounts of data extracted from disparate sources. Accordingly, we discuss and review processes to curate the immunological literature, as well as examples of how the curated data can be used to generate a meta-analysis of the epitope knowledge currently available for diseases of worldwide concern, such as influenza and malaria. Finally, we review the impact of immunological databases, by analyzing their usage and citations, and by categorizing the type of citations. Taken together, the results highlight the growing impact and utility of immunological databases for the scientific community

Statistical analysis and significance testing of serial analysis of gene expression data using a Poisson mixture model

<p>Abstract</p> <p>Background</p> <p>Serial analysis of gene expression (SAGE) is used to obtain quantitative snapshots of the transcriptome. These profiles are count-based and are assumed to follow a Binomial or Poisson distribution. However, tag counts observed across multiple libraries (for example, one or more groups of biological replicates) have additional variance that cannot be accommodated by this assumption alone. Several models have been proposed to account for this effect, all of which utilize a continuous prior distribution to explain the excess variance. Here, a Poisson mixture model, which assumes excess variability arises from sampling a mixture of distinct components, is proposed and the merits of this model are discussed and evaluated.</p> <p>Results</p> <p>The goodness of fit of the Poisson mixture model on 15 sets of biological SAGE replicates is compared to the previously proposed hierarchical gamma-Poisson (negative binomial) model, and a substantial improvement is seen. In further support of the mixture model, there is observed: 1) an increase in the number of mixture components needed to fit the expression of tags representing more than one transcript; and 2) a tendency for components to cluster libraries into the same groups. A confidence score is presented that can identify tags that are differentially expressed between groups of SAGE libraries. Several examples where this test outperforms those previously proposed are highlighted.</p> <p>Conclusion</p> <p>The Poisson mixture model performs well as a) a method to represent SAGE data from biological replicates, and b) a basis to assign significance when testing for differential expression between multiple groups of replicates. Code for the R statistical software package is included to assist investigators in applying this model to their own data.</p

FungalRV: adhesin prediction and immunoinformatics portal for human fungal pathogens

<p>Abstract</p> <p>Background</p> <p>The availability of sequence data of human pathogenic fungi generates opportunities to develop Bioinformatics tools and resources for vaccine development towards benefitting at-risk patients.</p> <p>Description</p> <p>We have developed a fungal adhesin predictor and an immunoinformatics database with predicted adhesins. Based on literature search and domain analysis, we prepared a positive dataset comprising adhesin protein sequences from human fungal pathogens <it>Candida albicans, Candida glabrata, Aspergillus fumigatus, Coccidioides immitis, Coccidioides posadasii, Histoplasma capsulatum, Blastomyces dermatitidis, Pneumocystis carinii, Pneumocystis jirovecii and Paracoccidioides brasiliensis</it>. The negative dataset consisted of proteins with high probability to function intracellularly. We have used 3945 compositional properties including frequencies of mono, doublet, triplet, and multiplets of amino acids and hydrophobic properties as input features of protein sequences to Support Vector Machine. Best classifiers were identified through an exhaustive search of 588 parameters and meeting the criteria of best Mathews Correlation Coefficient and lowest coefficient of variation among the 3 fold cross validation datasets. The "FungalRV adhesin predictor" was built on three models whose average Mathews Correlation Coefficient was in the range 0.89-0.90 and its coefficient of variation across three fold cross validation datasets in the range 1.2% - 2.74% at threshold score of 0. We obtained an overall MCC value of 0.8702 considering all 8 pathogens, namely, <it>C. albicans, C. glabrata, A. fumigatus, B. dermatitidis, C. immitis, C. posadasii, H. capsulatum </it>and <it>P. brasiliensis </it>thus showing high sensitivity and specificity at a threshold of 0.511. In case of <it>P. brasiliensis </it>the algorithm achieved a sensitivity of 66.67%. A total of 307 fungal adhesins and adhesin like proteins were predicted from the entire proteomes of eight human pathogenic fungal species. The immunoinformatics analysis data on these proteins were organized for easy user interface analysis. A Web interface was developed for analysis by users. The predicted adhesin sequences were processed through 18 immunoinformatics algorithms and these data have been organized into MySQL backend. A user friendly interface has been developed for experimental researchers for retrieving information from the database.</p> <p>Conclusion</p> <p>FungalRV webserver facilitating the discovery process for novel human pathogenic fungal adhesin vaccine has been developed.</p

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Development of Immune-Specific Interaction Potentials and Their Application in the Multi-Agent-System VaccImm

Peptide vaccination in cancer therapy is a promising alternative to conventional methods. However, the parameters for this personalized treatment are difficult to access experimentally. In this respect, in silico models can help to narrow down the parameter space or to explain certain phenomena at a systems level. Herein, we develop two empirical interaction potentials specific to B-cell and T-cell receptor complexes and validate their applicability in comparison to a more general potential. The interaction potentials are applied to the model VaccImm which simulates the immune response against solid tumors under peptide vaccination therapy. This multi-agent system is derived from another immune system simulator (C-ImmSim) and now includes a module that enables the amino acid sequence of immune receptors and their ligands to be taken into account. The multi-agent approach is combined with approved methods for prediction of major histocompatibility complex (MHC)-binding peptides and the newly developed interaction potentials. In the analysis, we critically assess the impact of the different modules on the simulation with VaccImm and how they influence each other. In addition, we explore the reasons for failures in inducing an immune response by examining the activation states of the immune cell populations in detail

Regulation of the DNA Damage Response and Gene Expression by the Dot1L Histone Methyltransferase and the 53Bp1 Tumour Suppressor

Dot1L, a histone methyltransferase that targets histone H3 lysine 79 (H3K79), has been implicated in gene regulation and the DNA damage response although its functions in these processes remain poorly defined.Using the chicken DT40 model system, we generated cells in which the Dot1L gene is disrupted to examine the function and focal recruitment of the 53Bp1 DNA damage response protein. Detailed kinetic and dose response assays demonstrate that, despite the absence of H3K79 methylation demonstrated by mass spectrometry, 53Bp1 focal recruitment is not compromised in these cells. We also describe, for the first time, the phenotypes of a cell line lacking both Dot1L and 53Bp1. Dot1L⁻/⁻ and wild type cells are equally resistant to ionising radiation, whereas 53Bp1⁻/⁻/Dot1L⁻/⁻ cells display a striking DNA damage resistance phenotype. Dot1L and 53Bp1 also affect the expression of many genes. Loss of Dot1L activity dramatically alters the mRNA levels of over 1200 genes involved in diverse biological functions. These results, combined with the previously reported list of differentially expressed genes in mouse ES cells knocked down for Dot1L, demonstrates surprising cell type and species conservation of Dot1L-dependent gene expression. In 53Bp1⁻/⁻ cells, over 300 genes, many with functions in immune responses and apoptosis, were differentially expressed. To date, this is the first global analysis of gene expression in a 53Bp1-deficient cell line.Taken together, our results uncover a negative role for Dot1L and H3K79 methylation in the DNA damage response in the absence of 53Bp1. They also enlighten the roles of Dot1L and 53Bp1 in gene expression and the control of DNA double-strand repair pathways in the context of chromatin

Anti-Neuroinflammatory effects of the extract of Achillea fragrantissima

<p>Abstract</p> <p>Background</p> <p>The neuroinflammatory process plays a central role in the initiation and progression of neurodegenerative diseases such as Parkinson's and Alzheimer's diseases, and involves the activation of brain microglial cells. During the neuroinflammatory process, microglial cells release proinflammatory mediators such as cytokines, matrix metalloproteinases (MMP), Reactive oxygen species (ROS) and nitric oxide (NO). In the present study, extracts from 66 different desert plants were tested for their effect on lipopolysaccharide (LPS) - induced production of NO by primary microglial cells. The extract of <it>Achillea fragrantissima </it>(<it>Af</it>)<it/>, which is a desert plant that has been used for many years in traditional medicine for the treatment of various diseases, was the most efficient extract, and was further studied for additional anti-neuroinflammatory effects in these cells.</p> <p>Methods</p> <p>In the present study, the ethanolic extract prepared from <it>Af </it>was tested for its anti-inflammatory effects on lipopolysaccharide (LPS)-activated primary cultures of brain microglial cells. The levels of the proinflammatory cytokines interleukin1β (IL-1β) and tumor necrosis factor-α (TNFα) secreted by the cells were determined by reverse transcriptase-PCR and Enzyme-linked immunosorbent assay (ELISA), respectively. NO levels secreted by the activate cells were measured using Griess reagent, ROS levels were measured by 2'7'-dichlorofluorescein diacetate (DCF-DA), MMP-9 activity was measured using gel zymography, and the protein levels of the proinflammatory enzymes cyclooxygenase-2 (COX-2) and induced nitric oxide synthase (iNOS) were measured by Western blot analysis. Cell viability was assessed using Lactate dehydrogenase (LDH) activity in the media conditioned by the cells or by the crystal violet cell staining.</p> <p>Results</p> <p>We have found that out of the 66 desert plants tested, the extract of <it>Af </it>was the most efficient extract and inhibited ~70% of the NO produced by the LPS-activated microglial cells, without affecting cell viability. In addition, this extract inhibited the LPS - elicited expression of the proinflammatory mediators IL-1β, TNFα, MMP-9, COX-2 and iNOS in these cells.</p> <p>Conclusions</p> <p>Thus, phytochemicals present in the <it>Af </it>extract could be beneficial in preventing/treating neurodegenerative diseases in which neuroinflammation is part of the pathophysiology.</p

CUL-2^LRR-1 and UBXN-3 drive replisome disassembly during DNA replication termination and mitosis

Replisome disassembly is the final step of DNA replication in eukaryotes, involving the ubiquitylation and CDC48-dependent dissolution of the CMG helicase (CDC45-MCM-GINS). Using Caenorhabditis elegans early embryos and Xenopus laevis egg extracts, we show that the E3 ligase CUL-2(LRR-1) associates with the replisome and drives ubiquitylation and disassembly of CMG, together with the CDC-48 cofactors UFD-1 and NPL-4. Removal of CMG from chromatin in frog egg extracts requires CUL2 neddylation, and our data identify chromatin recruitment of CUL2(LRR1) as a key regulated step during DNA replication termination. Interestingly, however, CMG persists on chromatin until prophase in worms that lack CUL-2(LRR-1), but is then removed by a mitotic pathway that requires the CDC-48 cofactor UBXN-3, orthologous to the human tumour suppressor FAF1. Partial inactivation of lrr-1 and ubxn-3 leads to synthetic lethality, suggesting future approaches by which a deeper understanding of CMG disassembly in metazoa could be exploited therapeutically