59 research outputs found

    Multiplexed measurements of immunomodulator levels in peripheral blood of healthy subjects: Effects of analytical variables based on anticoagulants, age, and gender

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    Multiplex microbead immunoassay (MMIA) is a powerful technology for a wide range of biomedical and clinical applications. It is important to study the normal concentration ranges of immunomodulators under different sample preparation conditions and age groups of subjects in order to more precisely determine their reference values for use in assessing alterations of their levels in disease. The aim of this study was to determine the plasma concentrations of immunomodulators (cytokines, chemokines, and growth factors) in the peripheral blood from healthy subjects by the use of a large multiplex panel, and to determine the effects of different anticoagulants, age, and gender on the immunomodulator levels. In addition, the assay precision for these biomarker analytes was determined. Plasma samples from 107 healthy subjects, aged 18 to 85 years, were collected in three different anticoagulants (sodium citrate, EDTA, Heparin); corresponding serum samples were also obtained. Multiplex microbead immunoassays were performed for measuring a total of 23 analytes including chemokines, cytokines, and growth factors (IL-1β, IL-1ra, IL-2, IL-6, IL-7, IL-8, IL-12 p70, IL-17, IFN-γ, IP-10, MCP-1, PDGF-BB, RANTES, TNF-α, IL-1a, IL-16, HGF, MIG, TNF-β, PDGF-ABBB, EGF, Flt-3 Ligand, VEGF). For these analytes, our results showed that the anticoagulant affected the concentration measurements and the coefficients of variation. However, the relative levels of the analytes (profiles) of samples collected in a particular anticoagulant are consistent. The analytes IL-1β, IL-7, Flt-3 Ligand, and IL-12p70 show the largest variation (up to fourfold) between the age groups. In addition, no statistically significant differences in the level of the analytes were found between the sexes

    A Recombinant Attenuated Mycobacterium tuberculosis Vaccine Strain Is Safe in Immunosuppressed Simian Immunodeficiency Virus-Infected Infant Macaques

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    ABSTRACT Many resource-poor countries are faced with concurrent epidemics of AIDS and tuberculosis (TB) caused by human immunodeficiency virus (HIV) and Mycobacterium tuberculosis , respectively. Dual infections with HIV and M. tuberculosis are especially severe in infants. There is, however, no effective HIV vaccine, and the only licensed TB vaccine, the Mycobacterium bovis bacillus Calmette-Guérin (BCG) vaccine, can cause disseminated mycobacterial disease in HIV-infected children. Thus, a pediatric vaccine to prevent HIV and M. tuberculosis infections is urgently needed. We hypothesized that a highly attenuated M. tuberculosis strain containing HIV antigens could be safely administered at birth and induce mucosal and systemic immune responses to protect against HIV and TB infections, and we rationalized that vaccine safety could be most rigorously assessed in immunocompromised hosts. Of three vaccine candidates tested, the recombinant attenuated M. tuberculosis strain mc 2 6435 carrying a simian immunodeficiency virus (SIV) Gag expression plasmid and harboring attenuations of genes critical for replication ( panCD and leuCD ) and immune evasion ( secA2 ), was found to be safe for oral or intradermal administration to non-SIV-infected and SIV-infected infant macaques. Safety was defined as the absence of clinical symptoms, a lack of histopathological changes indicative of M. tuberculosis infection, and a lack of mycobacterial dissemination. These data represent an important step in the development of novel TB vaccines and suggest that a combination recombinant attenuated M. tuberculosis -HIV vaccine could be a safe alternative to BCG for the pediatric population as a whole and, more importantly, for the extreme at-risk group of HIV-infected infants

    Automated machine learning for endemic active tuberculosis prediction from multiplex serological data

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    Serological diagnosis of active tuberculosis (TB) is enhanced by detection of multiple antibodies due to variable immune responses among patients. Clinical interpretation of these complex datasets requires development of suitable algorithms, a time consuming and tedious undertaking addressed by the automated machine learning platform MILO (Machine Intelligence Learning Optimizer). MILO seamlessly integrates data processing, feature selection, model training, and model validation to simultaneously generate and evaluate thousands of models. These models were then further tested for generalizability on out-of-sample secondary and tertiary datasets. Out of 31 antigens evaluated, a 23-antigen model was the most robust on both the secondary dataset (TB vs healthy) and the tertiary dataset (TB vs COPD) with sensitivity of 90.5% and respective specificities of 100.0% and 74.6%. MILO represents a user-friendly, end-to-end solution for automated generation and deployment of optimized models, ideal for applications where rapid clinical implementation is critical such as emerging infectious diseases
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