937 research outputs found
Host markers in Quantiferon supernatants differentiate active TB from latent TB infection: preliminary report
<p>Abstract</p> <p>Background</p> <p>Interferon gamma release assays, including the QuantiFERON<sup>® </sup>TB Gold In Tube (QFT) have been shown to be accurate in diagnosing <it>Mycobacterium tuberculosis </it>infection. These assays however, do not discriminate between latent TB infection (LTBI) and active TB disease.</p> <p>Methods</p> <p>We recruited twenty-three pulmonary TB patients and 34 household contacts from Cape Town, South Africa and performed the QFT test. To investigate the ability of new host markers to differentiate between LTBI and active TB, levels of 29 biomarkers in QFT supernatants were evaluated using a Luminex multiplex cytokine assay.</p> <p>Results</p> <p>Eight out of 29 biomarkers distinguished active TB from LTBI in a pilot study. Baseline levels of epidermal growth factor (EGF) soluble CD40 ligand (sCD40L), antigen stimulated levels of EGF, and the background corrected antigen stimulated levels of EGF and macrophage inflammatory protein (MIP)-1β were the most informative single markers for differentiation between TB disease and LTBI, with AUCs of 0.88, 0.84, 0.87, 0.90 and 0.79 respectively. The combination of EGF and MIP-1β predicted 96% of active TB cases and 92% of LTBIs. Combinations between EGF, sCD40L, VEGF, TGF-α and IL-1α also showed potential to differentiate between TB infection states. EGF, VEGF, TGF-α and sCD40L levels were higher in TB patients.</p> <p>Conclusion</p> <p>These preliminary data suggest that active TB may be accurately differentiated from LTBI utilizing adaptations of the commercial QFT test that includes measurement of EGF, sCD40L, MIP-1β, VEGF, TGF-α or IL-1α in supernatants from QFT assays. This approach holds promise for development as a rapid diagnostic test for active TB.</p
Public and community engagement in health science research: Openings and obstacles for listening and responding in the majority world
Editoria
Editorial: Public and community engagement in health science research: Openings and obstacles for listening and responding in the majority world
Cohabitants’ rights in conflict:The Family Law (Scotland) Act 2006 vs unjustified enrichment in Courtney’s Executors v Campbell
BDNF Val66Met and DRD2 Taq1A polymorphisms interact to influence PTSD symptom severity: A preliminary investigation in a South African population
BACKGROUND: We evaluated the role that selected variants in serotonin transporter (5-HTT), dopamine receptor 2 (DRD2) and brain-derived neurotrophic factor (BDNF) genes play in PTSD symptom severity in an at-risk population. We also investigated the interaction between the genetic variants to determine whether these variables and the interactions between the variables influenced the severity of PTSD symptoms.
METHODS: PTSD symptoms were quantitatively assessed using the Davidson Trauma Scale (DTS) in 150 participants from an at-risk South African population. All participants were genotyped for the 5-HTTLPR, DRD2 Taq1A and BDNF Val66Met polymorphisms. Gene–gene interactions were investigated using various linear models. All analyses were adjusted for age, gender, major depressive disorder diagnosis, level of resilience, level of social support and alcohol dependence.
RESULTS: A significant interaction effect between DRD2 Taq1A and BDNF Val66Met variants on DTS score was observed. On the background of the BDNF Val66Val genotype, DTS score increased significantly with the addition of a DRD2 Taq1A A1 allele. However, on the BDNF Met66 allele background, the addition of an A1 allele was found to reduce total DTS score.
CONCLUSIONS: This study provides preliminary evidence for an epistatic interaction between BDNF Val66Met and DRD2 Taq1A polymorphisms on the severity of PTSD symptoms, where both too little and too much dopamine can result in increased PTSD symptom severity.Web of Scienc
Analysis of host responses to Mycobacterium tuberculosis antigens in a multi-site study of subjects with different TB and HIV infection states in sub-Saharan Africa.
BACKGROUND: Tuberculosis (TB) remains a global health threat with 9 million new cases and 1.4 million deaths per year. In order to develop a protective vaccine, we need to define the antigens expressed by Mycobacterium tuberculosis (Mtb), which are relevant to protective immunity in high-endemic areas. METHODS: We analysed responses to 23 Mtb antigens in a total of 1247 subjects with different HIV and TB status across 5 geographically diverse sites in Africa (South Africa, The Gambia, Ethiopia, Malawi and Uganda). We used a 7-day whole blood assay followed by IFN-γ ELISA on the supernatants. Antigens included PPD, ESAT-6 and Ag85B (dominant antigens) together with novel resuscitation-promoting factors (rpf), reactivation proteins, latency (Mtb DosR regulon-encoded) antigens, starvation-induced antigens and secreted antigens. RESULTS: There was variation between sites in responses to the antigens, presumably due to underlying genetic and environmental differences. When results from all sites were combined, HIV- subjects with active TB showed significantly lower responses compared to both TST(-) and TST(+) contacts to latency antigens (Rv0569, Rv1733, Rv1735, Rv1737) and the rpf Rv0867; whilst responses to ESAT-6/CFP-10 fusion protein (EC), PPD, Rv2029, TB10.3, and TB10.4 were significantly higher in TST(+) contacts (LTBI) compared to TB and TST(-) contacts fewer differences were seen in subjects with HIV co-infection, with responses to the mitogen PHA significantly lower in subjects with active TB compared to those with LTBI and no difference with any antigen. CONCLUSIONS: Our multi-site study design for testing novel Mtb antigens revealed promising antigens for future vaccine development. The IFN-γ ELISA is a cheap and useful tool for screening potential antigenicity in subjects with different ethnic backgrounds and across a spectrum of TB and HIV infection states. Analysis of cytokines other than IFN-γ is currently on-going to determine correlates of protection, which may be useful for vaccine efficacy trials
Flux of particulate elements in the North Atlantic Ocean constrained by multiple radionuclides
Author Posting. © American Geophysical Union, 2019. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Global Biogeochemical Cycles 32(12), (2019): 1738-1758, doi:10.1029/2018GB005994.Sinking particles strongly regulate the distribution of reactive chemical substances in the ocean, including particulate organic carbon and other elements (e.g., P, Cd, Mn, Cu, Co, Fe, Al, and 232Th). Yet, the sinking fluxes of trace elements have not been well described in the global ocean. The U.S. GEOTRACES campaign in the North Atlantic (GA03) offers the first data set in which the sinking flux of carbon and trace elements can be derived using four different radionuclide pairs (238U:234Th ;210Pb:210Po; 228Ra:228Th; and 234U:230Th) at stations co‐located with sediment trap fluxes for comparison. Particulate organic carbon, particulate P, and particulate Cd fluxes all decrease sharply with depth below the euphotic zone. Particulate Mn, Cu, and Co flux profiles display mixed behavior, some cases reflecting biotic remineralization, and other cases showing increased flux with depth. The latter may be related to either lateral input of lithogenic material or increased scavenging onto particles. Lastly, particulate Fe fluxes resemble fluxes of Al and 232Th, which all have increasing flux with depth, indicating a dominance of lithogenic flux at depth by resuspended sediment transported laterally to the study site. In comparing flux estimates derived using different isotope pairs, differences result from different timescales of integration and particle size fractionation effects. The range in flux estimates produced by different methods provides a robust constraint on the true removal fluxes, taking into consideration the independent uncertainties associated with each method. These estimates will be valuable targets for biogeochemical modeling and may also offer insight into particle sinking processes.This study grew out of a synthesis workshop at the Lamont‐Doherty Earth Observatory of Columbia University in August 2016. This workshop was sponsored by the U.S. GEOTRACES Project Office (NSF 1536294) and the Ocean Carbon and Biogeochemistry (OCP) Project Office (NSF 1558412 and NASA NNX17AB17G). The U.S. National Science Foundation supported all of the analytical work on GA03. Kuanbo Zhou measured 228Th in the large size class particles (NSF 0925158 to WHOI). NSF 1061128 to Stony Brook University supported the BaRFlux project, for which Chistina Heilbrun is acknowledged for laboratory and field work. The lead author acknowledges support from a start‐up grant from the University of Southern Mississippi. Two anonymous reviewers are thanked for their constructive comments. All GEOTRACES GA03 data used in this study are accessible through the Biological and Chemical Oceanography Data Management Office (http://data.bco‐dmo.org/jg/dir/BCO/GEOTRACES/NorthAtlanticTransect/), and derived parameters are reported in the supporting information.2019-05-2
Before and after study of bar workers' perceptions of the impact of smoke-free workplace legislation in the Republic of Ireland
<p>Abstract</p> <p>Background</p> <p><it>Objectives</it>: To compare support for, and perceptions of, the impacts of smoke-free workplace legislation among bar workers in the Republic of Ireland (ROI) pre- and post-implementation, and to identify predictors of support for the legislation.</p> <p>Methods</p> <p><it>Setting</it>: Public houses (pubs) in three areas of the ROI.</p> <p><it>Design</it>: Comparisons pre- and post-implementation of smoke-free workplace legislation.</p> <p><it>Participants</it>: From a largely non-random selection, 288 bar workers volunteered for the baseline survey; 220 were followed up one year later (76.4%).</p> <p><it>Outcome measures: </it>Level of support for the legislation, attitude statements concerning potential impacts of the law and modelled predictors of support for the legislation.</p> <p>Results</p> <p>Pre-implementation 59.5% of participants supported the legislation, increasing to 76.8% post-implementation. Support increased among smokers by 27.3 percentage points from 39.4% to 66.7% (p < 0.001) and among non-smokers by 12.4% percentage points from 68.8% to 81.2% (p = 0.003).</p> <p>Pre-legislation three-quarters of participants agreed that the legislation would make bars more comfortable and was needed to protect workers' health. Post-legislation these proportions increased to over 90% (p < 0.001). However, negative perceptions also increased, particularly for perceptions that the legislation has a negative impact on business (from 50.9% to 62.7%, p = 0.008) and that fewer people would visit pubs (41.8% to 62.7%, p < 0.001). After adjusting for relevant covariates, including responses to the attitude statements, support for the ban increased two to three-fold post-implementation. Regardless of their views on the economic impact, most participants agreed, both pre- and post-implementation, that the legislation was needed to protect bar workers' health.</p> <p>Conclusion</p> <p>Smoke-free legislation had the support of three-quarters of a large sample of bar workers in the ROI. However, this group holds complex sets of both positive and negative perspectives on the legislation. Of particular importance is that negative economic perceptions did not diminish the widely held perception that the ban is needed to protect workers' health.</p
Medroxyprogesterone Acetate Alters Mycobacterium Bovis BCG-Induced Cytokine Production in Peripheral Blood Mononuclear Cells of Contraceptive Users
Most individuals latently infected with Mycobacterium tuberculosis (M.tb) contain the infection by a balance of effector and regulatory immune responses. This balance can be influenced by steroid hormones such as glucocorticoids. The widely used contraceptive medroxyprogesterone acetate (MPA) possesses glucocorticoid activity. We investigated the effect of this hormone on immune responses to BCG in household contacts of active TB patients. Multiplex bead array analysis revealed that MPA demonstrated both glucocorticoid and progestogenic properties at saturating and pharmacological concentrations in peripheral blood mononuclear cells (PBMCs) and suppressed antigen specific cytokine production. Furthermore we showed that PBMCs from women using MPA produced significantly lower levels of IL-1α, IL-12p40, IL-10, IL-13 and G-CSF in response to BCG which corresponded with lower numbers of circulating monocytes observed in these women. Our research study is the first to show that MPA impacts on infections outside the genital tract due to a systemic effect on immune function. Therefore MPA use could alter susceptibility to TB, TB disease severity as well as change the efficacy of new BCG-based vaccines, especially prime-boost vaccine strategies which may be administered to adult or adolescent women in the future
Biomarker discovery in heterogeneous tissue samples -taking the in-silico deconfounding approach
<p>Abstract</p> <p>Background</p> <p>For heterogeneous tissues, such as blood, measurements of gene expression are confounded by relative proportions of cell types involved. Conclusions have to rely on estimation of gene expression signals for homogeneous cell populations, e.g. by applying micro-dissection, fluorescence activated cell sorting, or <it>in-silico </it>deconfounding. We studied feasibility and validity of a non-negative matrix decomposition algorithm using experimental gene expression data for blood and sorted cells from the same donor samples. Our objective was to optimize the algorithm regarding detection of differentially expressed genes and to enable its use for classification in the difficult scenario of reversely regulated genes. This would be of importance for the identification of candidate biomarkers in heterogeneous tissues.</p> <p>Results</p> <p>Experimental data and simulation studies involving noise parameters estimated from these data revealed that for valid detection of differential gene expression, quantile normalization and use of non-log data are optimal. We demonstrate the feasibility of predicting proportions of constituting cell types from gene expression data of single samples, as a prerequisite for a deconfounding-based classification approach.</p> <p>Classification cross-validation errors with and without using deconfounding results are reported as well as sample-size dependencies. Implementation of the algorithm, simulation and analysis scripts are available.</p> <p>Conclusions</p> <p>The deconfounding algorithm without decorrelation using quantile normalization on non-log data is proposed for biomarkers that are difficult to detect, and for cases where confounding by varying proportions of cell types is the suspected reason. In this case, a deconfounding ranking approach can be used as a powerful alternative to, or complement of, other statistical learning approaches to define candidate biomarkers for molecular diagnosis and prediction in biomedicine, in realistically noisy conditions and with moderate sample sizes.</p
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