We investigated the role of interferon (IFN)- gamma , interleukin (IL)-1 beta , IL-2, IL-4, IL-5, IL-6, IL-10, IL-12, tumor necrosis factor (TNF)- alpha , and transforming growth factor (TGF)- beta in clinically well-defined groups of Plasmodium falciparum-infected patients manifesting mild malaria (MM), severe noncerebral malaria (SM), or cerebral malaria (CM) and in control subjects from Gondia, a malaria-endemic site in India, as well as in healthy subjects from non-malaria-endemic areas. Two-way coupled cluster analysis revealed 2 clusters of cytokines relevant to clinical subgroups of disease. The first cluster was composed of IFN- gamma , IL-2, IL-5, IL-6, and IL-12, the levels of which were significantly increased during infection but were predominant in patients with MM and allowed us to distinguish them from patients with SM or CM. The second cluster was composed of TGF- beta , TNF- alpha , IL-10, and IL-1 beta , the levels of which were highly correlated with each other in the different clinical groups of patients and significantly increased with disease severity, particularly in CM. Discriminant analyses allowed us to propose a minimal model. Levels of cytokines such as IL-5, IL-1 beta , IL-10, and IL-2 increase with infection. Levels of IL-12, IL-5, and IL-6 discriminate severe forms of malaria from MM. Finally, levels of IL-1 beta , IL-12, and IFN- gamma are relevant for the discrimination of CM from SM: high IL-1 beta levels are associated with CM, and high IL-12 and IFN- gamma levels are associated with SM.

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The CREATE-ECLA Randomized Controlled TrialThe CREATE-ECLA Trial Group Investigators* See also pp 427 and 489.

The strategy of using an antiviral initially to decrease HBV DNA levels before adding an immunomodulatory agent leads to improved sustained virological response as compared with using immunomodulator from the start.

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BackgroundThe main processes in the pathogenesis of cerebral malaria caused by Plasmodium falciparum involved sequestration of parasitized red blood cells and immunopathological responses. Among immune factors, IgG autoantibodies to brain antigens are increased in P. falciparum infected patients and correlate with disease severity in African children. Nevertheless, their role in the pathophysiology of cerebral malaria (CM) is not fully defined. We extended our analysis to an Indian population with genetic backgrounds and endemic and environmental status different from Africa to determine if these autoantibodies could be either a biomarker or a risk factor of developing CM.Methods/Principal FindingsWe investigated the significance of these self-reactive antibodies in clinically well-defined groups of P. falciparum infected patients manifesting mild malaria (MM), severe non-cerebral malaria (SM), or cerebral malaria (CM) and in control subjects from Gondia, a malaria epidemic site in central India using quantitative immunoprinting and multivariate statistical analyses. A two-fold complete-linkage hierarchical clustering allows classifying the different patient groups and to distinguish the CM from the others on the basis of their profile of IgG reactivity to brain proteins defined by PANAMA Blot. We identified beta tubulin III (TBB3) as a novel discriminant brain antigen in the prevalence of CM. In addition, circulating IgG from CM patients highly react with recombinant TBB3. Overall, correspondence analyses based on singular value decomposition show a strong correlation between IgG anti-TBB3 and elevated concentration of cluster-II cytokine (IFNγ, IL1β, TNFα, TGFβ) previously demonstrated to be a predictor of CM in the same population.Conclusions/SignificanceCollectively, these findings validate the relationship between antibody response to brain induced by P. falciparum infection and plasma cytokine patterns with clinical outcome of malaria. They also provide significant insight into the immune mechanisms associated to CM by the identification of TBB3 as a new disease-specific marker and potential therapeutic target.

In this first systematic review of CAD in India, prevalence of risk factors is high, treatments delayed and use of evidence based treatments variable.