153 resultados para cross infection


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We demonstrate a new technique to generate multiple light-sheets for fluorescence microscopy. This is possible by illuminating the cylindrical lens using multiple copies of Gaussian beams. A diffraction grating placed just before the cylindrical lens splits the incident Gaussian beam into multiple beams traveling at different angles. Subsequently, this gives rise to diffraction-limited light-sheets after the Gaussian beams pass through the combined cylindrical lens-objective sub-system. Direct measurement of field at and around the focus of objective lens shows multi-sheet pattern with an average thickness of 7.5 μm and inter-sheet separation of 380 μm. Employing an independent orthogonal detection sub-system, we successfully imaged fluorescently-coated yeast cells (≈4 μm) encaged in agarose gel-matrix. Such a diffraction-limited sheet-pattern equipped with dedicated detection system may find immediate applications in the field of optical microscopy and fluorescence imaging. © 2015 Optical Society of America

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An asymptotically-exact methodology is presented for obtaining the cross-sectional stiffness matrix of a pre-twisted moderately-thick beam having rectangular cross sections and made of transversely isotropic materials. The anisotropic beam is modeled from 3-D elasticity, without any further assumptions. The beam is allowed to have large displacements and rotations, but small strain is assumed. The strain energy of the beam is computed making use of the constitutive law and the kinematical relations derived with the inclusion of geometrical nonlinearities and initial twist. Large displacements and rotations are allowed, but small strain is assumed. The Variational Asymptotic Method is used to minimize the energy functional, thereby reducing the cross section to a point on the reference line with appropriate properties, yielding a 1-D constitutive law. In this method as applied herein, the 2-D cross-sectional analysis is performed asymptotically by taking advantage of a material small parameter and two geometric small parameters. 3-D strain components are derived using kinematics and arranged as orders of the small parameters. Warping functions are obtained by the minimization of strain energy subject to certain set of constraints that renders the 1-D strain measures well-defined. Closed-form expressions are derived for the 3-D non-linear warping and stress fields. The model is capable of predicting interlaminar and transverse shear stresses accurately up to first order.

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Ecoepidemiology is a well-developed branch of theoretical ecology, which explores interplay between the trophic interactions and the disease spread. In most ecoepidemiological models, however, the authors assume the predator to be a specialist, which consumes only a single prey species. In few existing papers, in which the predator was suggested to be a generalist, the alternative food supply was always considered to be constant. This is obviously a simplification of reality, since predators can often choose between a number of different prey. Consumption of these alternative prey can dramatically change their densities and strongly influence the model predictions. In this paper, we try to bridge the gap and explore a generic ecoepidemiological system with a generalist predator, where the densities of all prey are dynamical variables. The model consists of two prey species, one of which is subject to an infectious disease, and a predator, which consumes both prey species. We investigate two main scenarios of infection transmission mode: (i) the disease transmission rate is predator independent and (ii) the transmission rate is a function of predator density. For both scenarios we fulfil an extensive bifurcation analysis. We show that including a second dynamical prey in the system can drastically change the dynamics of the single prey case. In particular, the presence of a second prey impedes disease spread by decreasing the basic reproduction number and can result in a substantial drop of the disease prevalence. We demonstrate that with efficient consumption of the second prey species by the predator, the predator-dependent disease transmission can not destabilize interactions, as in the case with a specialist predator. Interestingly, even if the population of the second prey eventually vanishes and only one prey species finally remains, the system with two prey species may exhibit different properties to those of the single prey system.

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T-cell responses in humans are initiated by the binding of a peptide antigen to a human leukocyte antigen (HLA) molecule. The peptide-HLA complex then recruits an appropriate T cell, leading to cell-mediated immunity. More than 2000 HLA class-I alleles are known in humans, and they vary only in their peptide-binding grooves. The polymorphism they exhibit enables them to bind a wide range of peptide antigens from diverse sources. HLA molecules and peptides present a complex molecular recognition pattern, as many peptides bind to a given allele and a given peptide can be recognized by many alleles. A powerful grouping scheme that not only provides an insightful classification, but is also capable of dissecting the physicochemical basis of recognition specificity is necessary to address this complexity. We present a hierarchical classification of 2010 class-I alleles by using a systematic divisive clustering method. All-pair distances of alleles were obtained by comparing binding pockets in the structural models. By varying the similarity thresholds, a multilevel classification was obtained, with 7 supergroups, each further subclassifying to yield 72 groups. An independent clustering performed based only on similarities in their epitope pools correlated highly with pocket-based clustering. Physicochemical feature combinations that best explain the basis of clustering are identified. Mutual information calculated for the set of peptide ligands enables identification of binding site residues contributing to peptide specificity. The grouping of HLA molecules achieved here will be useful for rational vaccine design, understanding disease susceptibilities and predicting risk of organ transplants.

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In India, the low prevalence of HIV-associated dementia (HAD) in the Human immunodeficiency virus type 1 (HIV-1) subtype C infection is quite paradoxical given the high-rate of macrophage infiltration into the brain. Whether the direct viral burden in individual brain compartments could be associated with the variability of the neurologic manifestations is controversial. To understand this paradox, we examined the proviral DNA load in nine different brain regions and three different peripheral tissues derived from ten human subjects at autopsy. Using a highly sensitive TaqMan probe-based real-time PCR, we determined the proviral load in multiple samples processed in parallel from each site. Unlike previously published reports, the present analysis identified uniform proviral distribution among the brain compartments examined without preferential accumulation of the DNA in any one of them. The overall viral DNA burden in the brain tissues was very low, approximately 1 viral integration per 1000 cells or less. In a subset of the tissue samples tested, the HIV DNA mostly existed in a free unintegrated form. The V3-V5 envelope sequences, demonstrated a brain-specific compartmentalization in four of the ten subjects and a phylogenetic overlap between the neural and non-neural compartments in three other subjects. The envelope sequences phylogenetically belonged to subtype C and the majority of them were R5 tropic. To the best of our knowledge, the present study represents the first analysis of the proviral burden in subtype C postmortem human brain tissues. Future studies should determine the presence of the viral antigens, the viral transcripts, and the proviral DNA, in parallel, in different brain compartments to shed more light on the significance of the viral burden on neurologic consequences of HIV infection.

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The fluctuations exhibited by the cross sections generated in a compound-nucleus reaction or, more generally, in a quantum-chaotic scattering process, when varying the excitation energy or another external parameter, are characterized by the width Gamma(corr) of the cross-section correlation function. Brink and Stephen Phys. Lett. 5, 77 (1963)] proposed a method for its determination by simply counting the number of maxima featured by the cross sections as a function of the parameter under consideration. They stated that the product of the average number of maxima per unit energy range and Gamma(corr) is constant in the Ercison region of strongly overlapping resonances. We use the analogy between the scattering formalism for compound-nucleus reactions and for microwave resonators to test this method experimentally with unprecedented accuracy using large data sets and propose an analytical description for the regions of isolated and overlapping resonances.

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The purpose of this work was to develop a family of crosslinked poly(xylitol adipate salicylate)s with a wide range of tunable release properties for delivering pharmacologically active salicylic acid. The synthesis parameters and release conditions were varied to modulate polyester properties and to understand the mechanism of release. Varying release rates were obtained upon longer curing (35% in the noncured polymer to 10% in the cured polymer in 7 days). Differential salicylic acid loading led to the synthesis of polymers with variable cross-linking and the release could be tuned (100% release for the lowest loading to 30% in the highest loading). Controlled release was monitored by changing various factors, and the release profiles were dependent on the stoichiometric composition, pH, curing time, and presence of enzyme. The polymer released a combination of salicylic acid and disalicylic acid, and the released products were found to be nontoxic. Minimal hemolysis and platelet activation indicated good blood compatibility. These polymers qualify as ``bioactive'' and ``resorbable'' and can, therefore, find applications as immunomodulatory resorbable biomaterials with tunable release properties.

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Two-component systems (TCSs), which contain paired sensor kinase and response regulator proteins, form the primary apparatus for sensing and responding to environmental cues in bacteria. TCSs are thought to be highly specific, displaying minimal cross-talk, primarily due to the co-evolution of the participating proteins. To assess the level of cross-talk between the TCSs of Mycobacterium tuberculosis, we mapped the complete interactome of the M. tuberculosis TCSs using phosphotransfer profiling. Surprisingly, we found extensive crosstalk among the M. tuberculosis TCSs, significantly more than that in the TCSs in Escherichia coli or Caulobacter crescentus, thereby offering an alternate to specificity paradigm in TCS signalling. Nearly half of the interactions we detected were significant novel cross-interactions, unravelling a potentially complex signalling landscape. We classified the TCSs into specific `one-to-one' and promiscuous `one-to-many' and `many-to-one' circuits. Using mathematical modelling, we deduced that the promiscuous signalling observed can explain several currently confounding observations about M. tuberculosis TCSs. Our findings suggest an alternative paradigm of bacterial signalling with significant cross-talk between TCSs yielding potentially complex signalling landscapes.

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Bacterial biofilms are associated with 80-90% of infections. Within the biofilm, bacteria are refractile to antibiotics, requiring concentrations >1,000 times the minimum inhibitory concentration. Proteins, carbohydrates and DNA are the major components of biofilm matrix. Pseudomonas aeruginosa (PA) biofilms, which are majorly associated with chronic lung infection, contain extracellular DNA (eDNA) as a major component. Herein, we report for the first time that L-Methionine (L-Met) at 0.5 mu M inhibits Pseudomonas aeruginosa (PA) biofilm formation and disassembles established PA biofilm by inducing DNase expression. Four DNase genes (sbcB, endA, eddB and recJ) were highly up-regulated upon L-Met treatment along with increased DNase activity in the culture supernatant. Since eDNA plays a major role in establishing and maintaining the PA biofilm, DNase activity is effective in disrupting the biofilm. Upon treatment with L-Met, the otherwise recalcitrant PA biofilm now shows susceptibility to ciprofloxacin. This was reflected in vivo, in the murine chronic PA lung infection model. Mice treated with L-Met responded better to antibiotic treatment, leading to enhanced survival as compared to mice treated with ciprofloxacin alone. These results clearly demonstrate that L-Met can be used along with antibiotic as an effective therapeutic against chronic PA biofilm infection.

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Pluripotent stem cells are being actively studied as a cell source for regenerating damaged liver. For long-term survival of engrafting cells in the body, not only do the cells have to execute liver-specific function but also withstand the physical strains and invading pathogens. The cellular innate immune system orchestrated by the interferon (IFN) pathway provides the first line of defense against pathogens. The objective of this study is to assess the innate immune function as well as to systematically profile the IFN-induced genes during hepatic differentiation of pluripotent stem cells. To address this objective, we derived endodermal cells (day 5 post-differentiation), hepatoblast (day 15) and hepatocyte-like cells (day 21) from human embryonic stem cells (hESCs). Day 5, 15 and 21 cells were stimulated with IFN-alpha and subjected to IFN pathway analysis. Transcriptome analysis was carried out by RNA sequencing. The results showed that the IFN-alpha treatment activated STAT-JAK pathway in differentiating cells. Transcriptome analysis indicated stage specific expression of classical and non-classical IFN-stimulated genes (ISGs). Subsequent validation confirmed the expression of novel ISGs including RASGRP3, CLMP and TRANK1 by differentiated hepatic cells upon IFN treatment. Hepatitis C virus replication in hESC-derived hepatic cells induced the expression of ISGs - LAMP3, ETV7, RASGRP3, and TRANK1. The hESC-derived hepatic cells contain intact innate system and can recognize invading pathogens. Besides assessing the tissue-specific functions for cell therapy applications, it may also be important to test the innate immune function of engrafting cells to ensure adequate defense against infections and improve graft survival. (C) 2015 The Authors. Published by Elsevier B.V.

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Tetrabutyl ammonium iodide (TBAI) catalyzed alpha-aminoxylation of ketones using aq. TBHP as an oxidant has been accomplished. We have shown that the CDC (cross dehydrogenative coupling) reactions of ketones with N-hydroxyimidates such as N-hydroxysuccinimide (NHSI), N-hydroxyphthalimide (NHPI), N-hydroxybenzotriazole (HOBt) and 1-hydroxy-7-azabenzotriazole (HOAt) lead to the corresponding oxygenated products in good to moderate yields. The application of this method has been demonstrated by transforming a few coupled products into synthetically useful intermediates and products.

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The study considers earthquake shake table testing of bending-torsion coupled structures under multi-component stationary random earthquake excitations. An experimental procedure to arrive at the optimal excitation cross-power spectral density (psd) functions which maximize/minimize the steady state variance of a chosen response variable is proposed. These optimal functions are shown to be derivable in terms of a set of system frequency response functions which could be measured experimentally without necessitating an idealized mathematical model to be postulated for the structure under study. The relationship between these optimized cross-psd functions to the most favourable/least favourable angle of incidence of seismic waves on the structure is noted. The optimal functions are also shown to be system dependent, mathematically the sharpest, and correspond to neither fully correlated motions nor independent motions. The proposed experimental procedure is demonstrated through shake table studies on two laboratory scale building frame models.

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Objectives:To determine if there is a biological mechanism that explains the association between HIV disease progression and increased mortality with low circulating vitamin D levels; specifically, to determine if restoring vitamin D levels induced T-cell functional changes important for antiviral immunity.Design:This was a pilot, open-label, three-arm prospective phase 1 study.Methods:We recruited 28 patients with low plasma vitamin D (<50nmol/l 25-hydroxyvitamin D3), comprising 17 HIV+ patients (11 on HAART, six treatment-naive) and 11 healthy controls, who received a single dose of 200000IU oral cholecalciferol. Advanced T-cell flow cytometry methods measured CD4(+) T-cell function associated with viral control in blood samples at baseline and 1-month after vitamin D supplementation.Results:One month of vitamin D supplementation restored plasma levels to sufficiency (>75nmol/l) in 27 of 28 patients, with no safety issues. The most striking change was in HIV+ HAART+ patients, where increased frequencies of antigen-specific T cells expressing macrophage inflammatory protein (MIP)-1 - an important anti-HIV blocking chemokine - were observed, with a concomitant increase in plasma MIP-1, both of which correlated significantly with vitamin D levels. In addition, plasma cathelicidin - a vitamin D response gene with broad antimicrobial activity - was enhanced.Conclusion:Vitamin D supplementation modulates disease-relevant T-cell functions in HIV-infected patients, and may represent a useful adjunct to HAART therapy. Copyright (C) 2015 Wolters Kluwer Health, Inc. All rights reserved.

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Cross domain and cross-modal matching has many applications in the field of computer vision and pattern recognition. A few examples are heterogeneous face recognition, cross view action recognition, etc. This is a very challenging task since the data in two domains can differ significantly. In this work, we propose a coupled dictionary and transformation learning approach that models the relationship between the data in both domains. The approach learns a pair of transformation matrices that map the data in the two domains in such a manner that they share common sparse representations with respect to their own dictionaries in the transformed space. The dictionaries for the two domains are learnt in a coupled manner with an additional discriminative term to ensure improved recognition performance. The dictionaries and the transformation matrices are jointly updated in an iterative manner. The applicability of the proposed approach is illustrated by evaluating its performance on different challenging tasks: face recognition across pose, illumination and resolution, heterogeneous face recognition and cross view action recognition. Extensive experiments on five datasets namely, CMU-PIE, Multi-PIE, ChokePoint, HFB and IXMAS datasets and comparisons with several state-of-the-art approaches show the effectiveness of the proposed approach. (C) 2015 Elsevier B.V. All rights reserved.

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Cross domain and cross-modal matching has many applications in the field of computer vision and pattern recognition. A few examples are heterogeneous face recognition, cross view action recognition, etc. This is a very challenging task since the data in two domains can differ significantly. In this work, we propose a coupled dictionary and transformation learning approach that models the relationship between the data in both domains. The approach learns a pair of transformation matrices that map the data in the two domains in such a manner that they share common sparse representations with respect to their own dictionaries in the transformed space. The dictionaries for the two domains are learnt in a coupled manner with an additional discriminative term to ensure improved recognition performance. The dictionaries and the transformation matrices are jointly updated in an iterative manner. The applicability of the proposed approach is illustrated by evaluating its performance on different challenging tasks: face recognition across pose, illumination and resolution, heterogeneous face recognition and cross view action recognition. Extensive experiments on five datasets namely, CMU-PIE, Multi-PIE, ChokePoint, HFB and IXMAS datasets and comparisons with several state-of-the-art approaches show the effectiveness of the proposed approach. (C) 2015 Elsevier B.V. All rights reserved.