326 research outputs found

    Neurochemical Changes in the Mouse Hippocampus Underlying the Antidepressant Effect of Genetic Deletion of P2X7 Receptors.

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    Recent investigations have revealed that the genetic deletion of P2X7 receptors (P2rx7) results in an antidepressant phenotype in mice. However, the link between the deficiency of P2rx7 and changes in behavior has not yet been explored. In the present study, we studied the effect of genetic deletion of P2rx7 on neurochemical changes in the hippocampus that might underlie the antidepressant phenotype. P2X7 receptor deficient mice (P2rx7-/-) displayed decreased immobility in the tail suspension test (TST) and an attenuated anhedonia response in the sucrose preference test (SPT) following bacterial endotoxin (LPS) challenge. The attenuated anhedonia was reproduced through systemic treatments with P2rx7 antagonists. The activation of P2rx7 resulted in the concentration-dependent release of [3H]glutamate in P2rx7+/+ but not P2rx7-/- mice, and the NR2B subunit mRNA and protein was upregulated in the hippocampus of P2rx7-/- mice. The brain-derived neurotrophic factor (BDNF) expression was higher in saline but not LPS-treated P2rx7-/- mice; the P2rx7 antagonist Brilliant blue G elevated and the P2rx7 agonist benzoylbenzoyl ATP (BzATP) reduced BDNF level. This effect was dependent on the activation of NMDA and non-NMDA receptors but not on Group I metabotropic glutamate receptors (mGluR1,5). An increased 5-bromo-2-deoxyuridine (BrdU) incorporation was also observed in the dentate gyrus derived from P2rx7-/- mice. Basal level of 5-HT was increased, whereas the 5HIAA/5-HT ratio was lower in the hippocampus of P2rx7-/- mice, which accompanied the increased uptake of [3H]5-HT and an elevated number of [3H]citalopram binding sites. The LPS-induced elevation of 5-HT level was absent in P2rx7-/- mice. In conclusion there are several potential mechanisms for the antidepressant phenotype of P2rx7-/- mice, such as the absence of P2rx7-mediated glutamate release, elevated basal BDNF production, enhanced neurogenesis and increased 5-HT bioavailability in the hippocampus

    Early Secreted Antigen ESAT-6 of Mycobacterium tuberculosis Promotes Protective T Helper 17 Cell Responses in a Toll-Like Receptor-2-dependent Manner

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    Despite its relatively poor efficacy, Bacillus Calmette-Guérin (BCG) has been used as a tuberculosis (TB) vaccine since its development in 1921. BCG induces robust T helper 1 (Th1) immune responses but, for many individuals, this is not sufficient for host resistance against Mycobacterium tuberculosis (M. tb) infection. Here we provide evidence that early secreted antigenic target protein 6 (ESAT-6), expressed by the virulent M. tb strain H37Rv but not by BCG, promotes vaccine-enhancing Th17 cell responses. These activities of ESAT-6 were dependent on TLR-2/MyD88 signalling and involved IL-6 and TGF-β production by dendritic cells. Thus, animals that were previously infected with H37Rv or recombinant BCG containing the RD1 region (BCG::RD1) exhibited improved protection upon re-challenge with virulent H37Rv compared with mice previously infected with BCG or RD1-deficient H37Rv (H37RvΔRD1). However, TLR-2 knockout (TLR-2-/-) animals neither showed Th17 responses nor exhibited improved protection in response to immunization with H37Rv. Furthermore, H37Rv and BCG::RD1 infection had little effect on the expression of the anti-inflammatory microRNA-146a (miR146a) in dendritic cells (DCs), whereas BCG and H37RvΔRD1 profoundly induced its expression in DCs. Consistent with these findings, ESAT-6 had no effect on miR146a expression in uninfected DCs, but dramatically inhibited its upregulation in BCG-infected or LPS-treated DCs. Collectively, our findings indicate that, in addition to Th1 immunity induced by BCG, RD1/ESAT-6-induced Th17 immune responses are essential for optimal vaccine efficacy

    Digital payments adoption research: A meta-analysis for generalising the effects of attitude, cost, innovativeness, mobility and price value on behavioural intention

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    yesThe rapid evolution of mobile-based technologies and applications has led to the development of several different forms of digital payment methods (DPMs) but with limited enthusiasm in consumers for adopting them. Hence, several academic studies have already been conducted to examine the role of various antecedents that determines consumers’ intention to adopt DPMs. The degree of effect and significance of several antecedents found to be inconsistent across different studies. This provided us a basis for undertaking a meta-analysis of existing research for estimating the cumulative effect of such antecedents. Therefore, this study aims to perform a meta-analysis of five antecedents (i.e. attitude, cost, mobility, price value and innovativeness) for confirming their overall influence on intentions to adopt DPMs. The results of this study suggest that the cumulative effect of four out of five antecedents found to be significant while influence of price value was found insignificant on behavioural intentions. The recommendations drawn from this research would help to decide if and when to use such antecedents for predicting consumer intention to adopt DPMs

    Identification strategy for unknown pollutants using high-resolution mass spectrometry: Androgen-disrupting compounds identified through effect-directed analysis

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    Effect-directed analysis has been applied to a river sediment sample of concern to identify the compounds responsible for the observed effects in an in vitro (anti-)androgenicity assay. For identification after non-target analysis performed on a high-resolution LTQ-Orbitrap, we developed a de novo identification strategy including physico-chemical parameters derived from the effect-directed analysis approach. With this identification strategy, we were able to handle the immense amount of data produced by non-target accurate mass analysis. The effect-directed analysis approach, together with the identification strategy, led to the successful identification of eight androgen-disrupting compounds belonging to very diverse compound classes: an oxygenated polyaromatic hydrocarbon, organophosphates, musks, and steroids. This is one of the first studies in the field of environmental analysis dealing with the difficult task of handling the large amount of data produced from non-target analysis. The combination of bioassay activity assessment, accurate mass measurement, and the identification and confirmation strategy is a promising approach for future identification of environmental key toxicants that are not included as priority pollutants in monitoring programs

    Effect of Operating and Sampling Conditions on the Exhaust Gas Composition of Small-Scale Power Generators

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    Small stationary diesel engines, like in generator sets, have limited emission control measures and are therefore responsible for 44% of the particulate matter (PM) emissions in the United States. The diesel exhaust composition depends on operating conditions of the combustion engine. Furthermore, the measurements are influenced by the used sampling method. This study examines the effect of engine loading and exhaust gas dilution on the composition of small-scale power generators. These generators are used in different operating conditions than road-transport vehicles, resulting in different emission characteristics. Experimental data were obtained for gaseous volatile organic compounds (VOC) and PM mass concentration, elemental composition and nitrate content. The exhaust composition depends on load condition because of its effect on fuel consumption, engine wear and combustion temperature. Higher load conditions result in lower PM concentration and sharper edged particles with larger aerodynamic diameters. A positive correlation with load condition was found for K, Ca, Sr, Mn, Cu, Zn and Pb adsorbed on PM, elements that originate from lubricating oil or engine corrosion. The nitrate concentration decreases at higher load conditions, due to enhanced nitrate dissociation to gaseous NO at higher engine temperatures. Dilution on the other hand decreases PM and nitrate concentration and increases gaseous VOC and adsorbed metal content. In conclusion, these data show that operating and sampling conditions have a major effect on the exhaust gas composition of small-scale diesel generators. Therefore, care must be taken when designing new experiments or comparing literature results

    Efficient representation of uncertainty in multiple sequence alignments using directed acyclic graphs

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    Background A standard procedure in many areas of bioinformatics is to use a single multiple sequence alignment (MSA) as the basis for various types of analysis. However, downstream results may be highly sensitive to the alignment used, and neglecting the uncertainty in the alignment can lead to significant bias in the resulting inference. In recent years, a number of approaches have been developed for probabilistic sampling of alignments, rather than simply generating a single optimum. However, this type of probabilistic information is currently not widely used in the context of downstream inference, since most existing algorithms are set up to make use of a single alignment. Results In this work we present a framework for representing a set of sampled alignments as a directed acyclic graph (DAG) whose nodes are alignment columns; each path through this DAG then represents a valid alignment. Since the probabilities of individual columns can be estimated from empirical frequencies, this approach enables sample-based estimation of posterior alignment probabilities. Moreover, due to conditional independencies between columns, the graph structure encodes a much larger set of alignments than the original set of sampled MSAs, such that the effective sample size is greatly increased. Conclusions The alignment DAG provides a natural way to represent a distribution in the space of MSAs, and allows for existing algorithms to be efficiently scaled up to operate on large sets of alignments. As an example, we show how this can be used to compute marginal probabilities for tree topologies, averaging over a very large number of MSAs. This framework can also be used to generate a statistically meaningful summary alignment; example applications show that this summary alignment is consistently more accurate than the majority of the alignment samples, leading to improvements in downstream tree inference. Implementations of the methods described in this article are available at http://statalign.github.io/WeaveAlign webcite

    Re-examining the Unified Theory of Acceptance and Use of Technology (UTAUT): Towards a Revised Theoretical Model

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    YesBased on a critical review of the Unified Theory of Acceptance and Use of Technology (UTAUT), this study first formalized an alternative theoretical model for explaining the acceptance and use of information system (IS) and information technology (IT) innovations. The revised theoretical model was then empirically examined using a combination of meta-analysis and structural equation modelling (MASEM) techniques. The meta-analysis was based on 1600 observations on 21 relationships coded from 162 prior studies on IS/IT acceptance and use. The SEM analysis showed that attitude: was central to behavioural intentions and usage behaviours, partially mediated the effects of exogenous constructs on behavioural intentions, and had a direct influence on usage behaviours. A number of implications for theory and practice are derived based on the findings

    Transcriptomics in Interferon-α-Treated Patients Identifies Inflammation-, Neuroplasticity- and Oxidative Stress-Related Signatures as Predictors and Correlates of Depression

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    Owing to the unique opportunity to assess individuals before and after they develop depression within a short timeframe, interferon-α (IFN-α) treatment for chronic hepatitis C virus (HCV) infection is an ideal model to identify molecular mechanisms relevant to major depression, especially in the context of enhanced inflammation. Fifty-eight patients were assessed prospectively, at baseline and monthly over 24 weeks of IFN-α treatment. New-onset cases of depression were determined using the Mini International Neuropsychiatric Interview (MINI). Whole-blood transcriptomic analyses were conducted to investigate the following: (1) baseline gene expression differences associated with future development of IFN-α-induced depression, before IFN-α, and (2) longitudinal gene expression changes from baseline to weeks 4 or 24 of IFN-α treatment, separately in those who did and did not develop depression. Transcriptomics data were analyzed using Partek Genomics Suite (1.4-fold, FDR adjusted pless than or equal to0.05) and Ingenuity Pathway Analysis Software. Twenty patients (34%) developed IFN-α-induced depression. At baseline, 73 genes were differentially expressed in patients who later developed depression compared with those who did not. After 4 weeks of IFN-α treatment, 592 genes were modulated in the whole sample, representing primarily IFN-α-responsive genes. Substantially more genes were modulated only in patients who developed depression (n=506, compared with n=70 in patients who did not), with enrichment in inflammation-, neuroplasticity- and oxidative stress-related pathways. A similar picture was observed at week 24. Our data indicate that patients who develop IFN-α-induced depression have an increased biological sensitivity to IFN-α, as shown by larger gene expression changes, and specific signatures both as predictors and as correlates
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