Poor association between 13-valent pneumococcal conjugate vaccine-induced serum and mucosal antibody responses with experimental Streptococcus pneumoniae serotype 6B colonisation.

BACKGROUND: Pneumococcal carriage is the primary reservoir for transmissionand a prerequisite for invasive pneumococcal disease. Pneumococcal Conjugate Vaccine 13 (PCV13) showed a 62% efficacy in protection against experimental Streptococcus pneumoniae serotype 6B (Spn6B) carriage in a controlled human infection model (CHIM) of healthy Malawian adults. We, therefore, measured humoral responses to experimental challenge and PCV-13 vaccination and determined the association with protection against pneumococcal carriage. METHODS: We vaccinated 204 young, healthy Malawian adults with PCV13 or placebo and nasally inoculated them with Spn6B at least four weeks post-vaccination to establish carriage. We collected peripheral blood and nasal lining fluid at baseline, 4 weeks post-vaccination (7 days pre-inoculation), 2, 7, 14 and > 1 year post-inoculation. We measured the concentration of anti-serotype 6B Capsular Polysaccharide (CPS) Immunoglobulin G (IgG) and IgA antibodies in serum and nasal lining fluid using the World Health Organization (WHO) standardised enzyme-linked immunosorbent assay (ELISA). RESULTS: PCV13-vaccinated adults had higher serum IgG and nasal IgG/IgA anti-Spn6B CPS-specific binding antibodies than placebo recipients 4 to 6 weeks post-vaccination, which persisted for at least a year after vaccination. Nasal challenge with Spn6B did not significantly alter serum or nasal anti-CPS IgG binding antibody titers with or without experimental pneumococcal carriage. Pre-challenge titers of PCV13-induced serum IgG and nasal IgG/IgA anti-Spn6B CPS binding antibodies did not significantly differ between those that got experimentally colonised by Spn6B compared to those that did not. CONCLUSION: This study demonstrates that despite high PCV13 efficacy against experimental Spn6B carriage in young, healthy Malawian adults, robust vaccine-induced systemic and mucosal anti-Spn6B CPS binding antibodies did not directly relate to protection.

Clofazimine for Treatment of Cryptosporidiosis in Human Immunodeficiency Virus Infected Adults: An Experimental Medicine, Randomized, Double-blind, Placebo-controlled Phase 2a Trial.

BACKGROUND: We evaluated the efficacy, pharmacokinetics (PK), and safety of clofazimine (CFZ) in patients living with human immunodeficiency virus (HIV) with cryptosporidiosis. METHODS: We performed a randomized, double-blind, placebo-controlled study. Primary outcomes in part A were reduction in Cryptosporidium shedding, safety, and PK. Primary analysis was according to protocol (ATP). Part B of the study compared CFZ PK in matched individuals living with HIV without cryptosporidiosis. RESULTS: Twenty part A and 10 part B participants completed the study ATP. Almost all part A participants had high viral loads and low CD4 counts, consistent with failure of antiretroviral (ARV) therapy. At study entry, the part A CFZ group had higher Cryptosporidium shedding, total stool weight, and more diarrheal episodes compared with the placebo group. Over the inpatient period, compared with those who received placebo, the CFZ group Cryptosporidium shedding increased by 2.17 log2 Cryptosporidium per gram stool (95% upper confidence limit, 3.82), total stool weight decreased by 45.3 g (P = .37), and number of diarrheal episodes increased by 2.32 (P = .87). The most frequent solicited adverse effects were diarrhea, abdominal pain, and malaise. One placebo and 3 CFZ participants died during the study. Plasma levels of CFZ in participants with cryptosporidiosis were 2-fold lower than in part B controls. CONCLUSIONS: Our findings do not support the efficacy of CFZ for the treatment of cryptosporidiosis in a severely immunocompromised HIV population. However, this trial demonstrates a pathway to assess the therapeutic potential of drugs for cryptosporidiosis treatment. Screening persons living with HIV for diarrhea, and especially Cryptosporidium infection, may identify those failing ARV therapy. CLINICAL TRIALS REGISTRATION: NCT03341767.

A genome-wide association study identifies risk loci for childhood acute lymphoblastic leukemia at 10q26.13 and 12q23.1.

Genome-wide association studies (GWASs) have shown that common genetic variation contributes to the heritable risk of childhood acute lymphoblastic leukemia (ALL). To identify new susceptibility loci for the largest subtype of ALL, B-cell precursor ALL (BCP-ALL), we conducted a meta-analysis of two GWASs with imputation using 1000 Genomes and UK10K Project data as reference (totaling 1658 cases and 7224 controls). After genotyping an additional 2525 cases and 3575 controls, we identify new susceptibility loci for BCP-ALL mapping to 10q26.13 (rs35837782, LHPP, P=1.38 × 10-11) and 12q23.1 (rs4762284, ELK3, P=8.41 × 10-9). We also provide confirmatory evidence for the existence of independent risk loci at 9p21.3, but show that the association marked by rs77728904 can be accounted for by linkage disequilibrium with the rare high-impact CDKN2A p.Ala148Thr variant rs3731249. Our data provide further insights into genetic susceptibility to ALL and its biology.

Joint application of an empirical and mechanistic model for regional lake acidification.

The empirical direct distribution model for lake acidification is calibrated for use in an integrated assessment model which predicts the regional impact of an acid deposition control strategy. The calibration is based on the mechanistic Model of Acidification of Groundwater in Catchments (MAGIC). The models are applied jointly to a set of 33 statistically-selected lakes in the Adirondack region of New York. Calibration of the direct distribution model is based on a step-function application of acid deposition to MAGIC. Comparative evaluations of the resulting model predictions are made using historic deposition estimates and two alternative future deposition scenarios. The predictions of the direct distribution model match well the shapes and patterns of change of the regional distributions of ANC and pH predicted by MAGIC, the short- and medium-term dynamics of these changes, and the effect of including organic acids. However, small, long-term decreases in the fraction of incoming acid deposition neutralized by lakes and their watersheds predicted by MAGIC are not reproduced.

Experimental analysis of large belief networks for medical diagnosis.

We present an experimental analysis of two parameters that are important in knowledge engineering for large belief networks. We conducted the experiments on a network derived from the Internist-1 medical knowledge base. In this network, a generalization of the noisy-OR gate is used to model causal independence for the multivalued variables, and leak probabilities are used to represent the nonspecified causes of intermediate states and findings. We study two network parameters, (1) the parameter governing the assignment of probability values to the network, and (2) the parameter denoting whether the network nodes represent variables with two or more than two values. The experimental results demonstrate that the binary simplification computes diagnoses with similar accuracy to the full multivalued network. We discuss the implications of these parameters, as well other network parameters, for knowledge engineering for medical applications.

Probabilistic diagnosis using a reformulation of the INTERNIST-1/QMR knowledge base. I. The probabilistic model and inference algorithms.

In Part I of this two-part series, we report the design of a probabilistic reformulation of the Quick Medical Reference (QMR) diagnostic decision-support tool. We describe a two-level multiply connected belief-network representation of the QMR knowledge base of internal medicine. In the belief-network representation of the QMR knowledge base, we use probabilities derived from the QMR disease profiles, from QMR imports of findings, and from National Center for Health Statistics hospital-discharge statistics. We use a stochastic simulation algorithm for inference on the belief network. This algorithm computes estimates of the posterior marginal probabilities of diseases given a set of findings. In Part II of the series, we compare the performance of QMR to that of our probabilistic system on cases abstracted from continuing medical education materials from Scientific American Medicine. In addition, we analyze empirically several components of the probabilistic model and simulation algorithm.

Probabilistic diagnosis using a reformulation of the INTERNIST-1/QMR knowledge base. II. Evaluation of diagnostic performance.

We have developed a probabilistic reformulation of the Quick Medical Reference (QMR) system. In Part I of this two-part series, we described a two-level, multiply connected belief-network representation of the QMR knowledge base and a simulation algorithm to perform probabilistic inference on the reformulated knowledge base. In Part II of this series, we report on an evaluation of the probabilistic QMR, in which we compare the performance of QMR to that of our probabilistic system on cases abstracted from continuing medical education materials from Scientific American Medicine. In addition, we analyze empirically several components of the probabilistic model and simulation algorithm.