Down selecting adjuvanted vaccine formulations: a comparative method for harmonized evaluation.

The need for rapid and accurate comparison of panels of adjuvanted vaccine formulations and subsequent rational down selection, presents several challenges for modern vaccine development. Here we describe a method which may enable vaccine and adjuvant developers to compare antigen/adjuvant combinations in a harmonized fashion. Three reference antigens: Plasmodium falciparum apical membrane antigen 1 (AMA1), hepatitis B virus surface antigen (HBsAg), and Mycobacterium tuberculosis antigen 85A (Ag85A), were selected as model antigens and were each formulated with three adjuvants: aluminium oxyhydroxide, squalene-in-water emulsion, and a liposome formulation mixed with the purified saponin fraction QS21. The nine antigen/adjuvant formulations were assessed for stability and immunogenicity in mice in order to provide benchmarks against which other formulations could be compared, in order to assist subsequent down selection of adjuvanted vaccines. Furthermore, mouse cellular immune responses were analyzed by measuring IFN-γ and IL-5 production in splenocytes by ELISPOT, and humoral responses were determined by antigen-specific ELISA, where levels of total IgG, IgG1, IgG2b and IgG2c in serum samples were determined. The reference antigens and adjuvants described in this study, which span a spectrum of immune responses, are of potential use as tools to act as points of reference in vaccine development studies. The harmonized methodology described herein may be used as a tool for adjuvant/antigen comparison studies

A Research and Development (R&D) roadmap for influenza vaccines: Looking toward the future

Improved influenza vaccines are urgently needed to reduce the burden of seasonal influenza and to ensure a rapid and effective public-health response to future influenza pandemics. The Influenza Vaccines Research and Development (R&D) Roadmap (IVR) was created, through an extensive international stakeholder engagement process, to promote influenza vaccine R&D. The roadmap covers a 10-year timeframe and is organized into six sections: virology; immunology; vaccinology for seasonal influenza vaccines; vaccinology for universal influenza vaccines; animal and human influenza virus infection models; and policy, finance, and regulation. Each section identifies barriers, gaps, strategic goals, milestones, and additional R&D priorities germane to that area. The roadmap includes 113 specific R&D milestones, 37 of which have been designated high priority by the IVR expert taskforce. This report summarizes the major issues and priority areas of research outlined in the IVR. By identifying the key issues and steps to address them, the roadmap not only encourages research aimed at new solutions, but also provides guidance on the use of innovative tools to drive breakthroughs in influenza vaccine R&D.publishedVersio

Integrin-mediated axoglial interactions initiate myelination in the central nervous system

All but the smallest-diameter axons in the central nervous system are myelinated, but the signals that initiate myelination are unknown. Our prior work has shown that integrin signaling forms part of the cell–cell interactions that ensure only those oligodendrocytes contacting axons survive. Here, therefore, we have asked whether integrins regulate the interactions that lead to myelination. Using homologous recombination to insert a single-copy transgene into the hypoxanthine phosphoribosyl transferase (hprt) locus, we find that mice expressing a dominant-negative β1 integrin in myelinating oligodendrocytes require a larger axon diameter to initiate timely myelination. Mice with a conditional deletion of focal adhesion kinase (a signaling molecule activated by integrins) exhibit a similar phenotype. Conversely, transgenic mice expressing dominant-negative β3 integrin in oligodendrocytes display no myelination abnormalities. We conclude that β1 integrin plays a key role in the axoglial interactions that sense axon size and initiate myelination, such that loss of integrin signaling leads to a delay in myelination of small-diameter axons

Development and Characterization of Synthetic Glucopyranosyl Lipid Adjuvant System as a Vaccine Adjuvant

Innate immune responses to vaccine adjuvants based on lipopolysaccharide (LPS), a component of Gram-negative bacterial cell walls, are driven by Toll-like receptor (TLR) 4 and adaptor proteins including MyD88 and TRIF, leading to the production of inflammatory cytokines, type I interferons, and chemokines. We report here on the characterization of a synthetic hexaacylated lipid A derivative, denoted as glucopyranosyl lipid adjuvant (GLA). We assessed the effects of GLA on murine and human dendritic cells (DC) by combining microarray, mRNA and protein multiplex assays and flow cytometry analyses. We demonstrate that GLA has multifunctional immunomodulatory activity similar to naturally-derived monophosphory lipid A (MPL) on murine DC, including the production of inflammatory cytokines, chemokines, DC maturation and antigen-presenting functions. In contrast, hexaacylated GLA was overall more potent on a molar basis than heterogeneous MPL when tested on human DC and peripheral blood mononuclear cells (PBMC). When administered in vivo, GLA enhanced the immunogenicity of co-administered recombinant antigens, producing strong cell-mediated immunity and a qualitative TH1 response. We conclude that the GLA adjuvant stimulates and directs innate and adaptive immune responses by inducing DC maturation and the concomitant release of pro-inflammatory cytokines and chemokines associated with immune cell trafficking, activities which have important implications for the development of future vaccine adjuvants

Correction: Study protocol: Improving patient choice in treating Low back pain (IMPACT - LBP): A randomised controlled trial of a decision support package for use in physical therapy

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.After publication of this protocol a change in study design was needed [1]. Due to changes in the service configuration in the host physiotherapy department individual randomisation as originally planned could not be implemented. It was necessary to change to cluster randomisation with the unit of randomisation being the treating physiotherapist. Potential participants are given outpatient appointments by booking staff unaware of the physiotherapist’s randomisation. Trial recruitment is also done blind to physiotherapist allocation. In this manner we have ensured allocation concealment prior to participants joining the study. Cluster randomised trials need to inflate their sample size to account for clustering. Typically primary care trials use an intra-cluster correlation coefficient (ICC) of 0.05 in this calculation [2]. Our past experience is that clustering effects by therapist in trials of this nature may be very small [3]. To account for this we developed a provisional revised sample size using an ICC of 0.05 and did an interim analysis of pooled data, just for ICC of the primary outcome, after the first 40 participants had completed the three month follow-up questionnaire. The ICC was close to zero, suggesting that using an ICC of 0.05 was too conservative. We therefore assumed an ICC of 0.01 to estimate the design effect due to clustering. Based on an average cluster size of nine this results in a revised final sample size of 158

Methods for identification and confirmation of targeted subgroups in clinical trials: A systematic review.

Important objectives in the development of stratified medicines include the identification and confirmation of subgroups of patients with a beneficial treatment effect and a positive benefit-risk balance. We report the results of a literature review on methodological approaches to the design and analysis of clinical trials investigating a potential heterogeneity of treatment effects across subgroups. The identified approaches are classified based on certain characteristics of the proposed trial designs and analysis methods. We distinguish between exploratory and confirmatory subgroup analysis, frequentist, Bayesian and decision-theoretic approaches and, last, fixed-sample, group-sequential, and adaptive designs and illustrate the available trial designs and analysis strategies with published case studies.peerReviewe

Cellular scaling rules for primate brains

Primates are usually found to have richer behavioral repertoires and better cognitive abilities than rodents of similar brain size. This finding raises the possibility that primate brains differ from rodent brains in their cellular composition. Here we examine the cellular scaling rules for primate brains and show that brain size increases approximately isometrically as a function of cell numbers, such that an 11× larger brain is built with 10× more neurons and ≈12× more nonneuronal cells of relatively constant average size. This isometric function is in contrast to rodent brains, which increase faster in size than in numbers of neurons. As a consequence of the linear cellular scaling rules, primate brains have a larger number of neurons than rodent brains of similar size, presumably endowing them with greater computational power and cognitive abilities

Parents’ age at birth of their offspring and child survival

This study presents some new results on parental age as a risk factor for child survival. The study is based on individual registration forms for live births and infant deaths collected in Hungary from 1984 to 1988. Logistic regression models have been fitted for early neonatal and neonatal mortality on the one hand, and post-neonatal mortality on the other hand. Children of older males and females have significantly higher early neonatal and neonatal mortality rates compared to those of younger males and females. The impact of age of both parents remains, however, slighter than that of other biological characteristics such as previous number of fetal deaths, induced abortions, or live births. The authors discuss possible biological explanations