Combination of (M)DSC and surface analysis to study the phase behaviour and drug distribution of ternary solid dispersions

Purpose: Miscibility of the different compounds that make up a solid dispersion based formulation play a crucial role in the drug release profile and physical stability of the solid dispersion as it defines the phase behaviour of the dispersion. The standard technique to obtain information on phase behaviour of a sample is (modulated) differential scanning calorimetry ((M)DSC). However, for ternary mixtures (M)DSC alone is not sufficient to characterize their phase behaviour and to gain insight into the distribution of the active pharmaceutical ingredient (API) in a two-phased polymeric matrix. Methods: MDSC was combined with complementary surface analysis techniques, specifically time-of-flight secondary ion mass spectrometry (ToF-SIMS) and atomic force microscopy (AFM). Three spray-dried model formulations with varying API/PLGA/PVP ratios were analyzed. Results: The distribution of the API in the ternary solid dispersions depended on formulation parameters. The extent of API surface coverage and therefore the distribution of the API over both polymeric phases differed significantly for the three formulations. Conclusions: Combining (M)DSC and surface analysis rendered additional insights in the composition of mixed phases in complex systems, like ternary solid dispersions

Family physicians' perceptions of academic detailing: a quantitative and qualitative study

<p>Abstract</p> <p>Background</p> <p>The efficacy of academic detailing in changing physicians' knowledge and practice has been the subject of many primary research publications and systematic reviews. However, there is little written about the features of academic detailing that physicians find valuable or that affect their use of it. The goal of our project was to explore family physicians' (FPs) perceptions of academic detailing and the factors that affect their use of it.</p> <p>Methods</p> <p>We used 2 methods to collect data, a questionnaire and semi-structured telephone interviews. We mailed questionnaires to all FPs in the Dalhousie Office of Continuing Medical Education database and analyzed responses of non-users and users of academic detailing. After a preliminary analysis of questionnaire data, we conducted semi-structured interviews with 7 FPs who did not use academic detailing and 17 who did use it.</p> <p>Results</p> <p>Overall response rate to the questionnaire was 33% (289/869). Response rate of non-users of academic detailing was 15% (60/393), of users was 48% (229/476). The 3 factors that most encouraged use of academic detailing were the topics selected, the evidence-based approach adopted, and the handout material. The 3 factors that most discouraged the use of academic detailing were spending office time doing CME, scheduling time to see the academic detailer, and having CME provided by a non-physician. Users of academic detailing rated it as being more valuable than other forms of CME. Generally, interview data confirmed questionnaire data with the exception that interview informants did not view having CME provided by a non-physician as a barrier. Interview informants mentioned that the evidence-based approach adopted by academic detailing had led them to more critically evaluate information from other CME programs, pharmaceutical representatives, and journal articles, but not advice from specialists.</p> <p>Conclusion</p> <p>Users of academic detailing highly value its educational value and tend to view information from other sources more critically because of its evidence-based approach. Non-users are unlikely to adopt academic detailing despite its high educational value because they find using office time for CME too much of a barrier. To reach these physicians with academic detailing messages, we will have to find other CME formats.</p

Six years beyond pediatric trauma: child and parental ratings of children’s health-related quality of life in relation to parental mental health

Purpose: To examine the relationship between child self-report and parent proxy report of health-related quality of life (HRQL) and how parents’ mental health status relates to the HRQL ratings 6 years after minor to severe injury of the child. Materials and methods: This cross-sectional cohort study was performed at a regional pediatric trauma center in Stockholm, Sweden. The PedsQL 4.0 versions for ages 5–7, 8–12, and 13–18 years were completed by 177 child–parent dyads 6 years after injury to the child. The parents also rated their own mental health through the mental health domain (MH) in the SF-36 Health Survey. Results: The children’s median age was 13 years (IQR 10–16 years), 54 % were males, and the median ISS was 5 (IQR 2–9). Most of the parents were female (77 %), born in Sweden (79 %), and half had university degrees. There was no statistically significant difference between child self-report and parent proxy report in any of the PedsQL 4.0 scales or summary scales. The levels of agreement between child self-report and parent proxy reports were excellent (ICC ≥ 0.80) for all scales with the exception of emotional functioning (ICC 0.53) which also was the scale with the lowest internal consistency in child self-report (α 0.60). Multiple regression analyses showed that worse parental mental health status correlated with worse child self-report and parent proxy report of children’s HRQL. Conclusions: Children and their parents’ reports on child’s HRQL were in agreement. Decreased mental health in parents was associated with lower scores on parent proxy reports and child self-reports of HRQL after injury. The current investigation highlights the possible relationship between parent’s mental health status and children’s HRQL long after an injury, which should be considered in future investigations and in clinical care

Roles for Treg expansion and HMGB1 signaling through the TLR1-2-6 axis in determining the magnitude of the antigen-specific immune response to MVA85A

© 2013 Matsumiya et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are creditedA better understanding of the relationships between vaccine, immunogenicity and protection from disease would greatly facilitate vaccine development. Modified vaccinia virus Ankara expressing antigen 85A (MVA85A) is a novel tuberculosis vaccine candidate designed to enhance responses induced by BCG. Antigen-specific interferon-γ (IFN-γ) production is greatly enhanced by MVA85A, however the variability between healthy individuals is extensive. In this study we have sought to characterize the early changes in gene expression in humans following vaccination with MVA85A and relate these to long-term immunogenicity. Two days post-vaccination, MVA85A induces a strong interferon and inflammatory response. Separating volunteers into high and low responders on the basis of T cell responses to 85A peptides measured during the trial, an expansion of circulating CD4+ CD25+ Foxp3+ cells is seen in low but not high responders. Additionally, high levels of Toll-like Receptor (TLR) 1 on day of vaccination are associated with an increased response to antigen 85A. In a classification model, combined expression levels of TLR1, TICAM2 and CD14 on day of vaccination and CTLA4 and IL2Rα two days post-vaccination can classify high and low responders with over 80% accuracy. Furthermore, administering MVA85A in mice with anti-TLR2 antibodies may abrogate high responses, and neutralising antibodies to TLRs 1, 2 or 6 or HMGB1 decrease CXCL2 production during in vitro stimulation with MVA85A. HMGB1 is released into the supernatant following atimulation with MVA85A and we propose this signal may be the trigger activating the TLR pathway. This study suggests an important role for an endogenous ligand in innate sensing of MVA and demonstrates the importance of pattern recognition receptors and regulatory T cell responses in determining the magnitude of the antigen specific immune response to vaccination with MVA85A in humans.This work was funded by the Wellcome Trust. MM has a Wellcome Trust PhD studentship and HM is a Wellcome Trust Senior Fello

Age-dependent alterations in the inflammatory response to pulmonary challenge

The aging lung is increasingly susceptible to infectious disease. Changes in pulmonary physiology and function are common in older populations, and in those older than 60 years, pneumonia is the major cause of infectious death. Understanding age-related changes in the innate and adaptive immune systems, and how they affect both pulmonary and systemic responses to pulmonary challenge are critical to the development of novel therapeutic strategies for the treatment of the elderly patient. In this observational study, we examined age-associated differences in inflammatory responses to pulmonary challenge with cell wall components from Gram-positive bacteria. Thus, male Sprague-Dawley rats, aged 6 months or greater than 18 months (approximating humans of 20 and 55-65 years), were challenged, intratracheally, with lipoteichoic acid and peptidoglycan. Cellular and cytokine evaluations were performed on both bronchoalveolar lavage fluid (BAL) and plasma, 24 h post-challenge. The plasma concentration of free thyroxine, a marker of severity in non-thyroidal illness, was also evaluated. The older animals had an increased chemotactic gradient in favor of the airspaces, which was associated with a greater accumulation of neutrophils and protein. Furthermore, macrophage migration inhibitory factor (MIF), an inflammatory mediator and putative biomarker in acute lung injury, was increased in both the plasma and BAL of the older, but not young animals. Conversely, plasma free thyroxine, a natural inhibitor of MIF, was decreased in the older animals. These findings identify age-associated inflammatory/metabolic changes following pulmonary challenge that it may be possible to manipulate to improve outcome in the older, critically ill patient

The contribution of the environment (especially diet) to breast cancer risk

Environmental factors play an important role in breast carcinogenesis. Opportunities for prevention are limited, however, because most of the known or suspected risk factors are not targets for modification. Dietary factors have generally not emerged as crucial contributors to mammary tumor causation. We still appear to be missing a critical piece of the breast cancer puzzle because we can only explain a moderate proportion of international and national variation in breast cancer rates. Research needs to pursue new avenues, focusing on exposure windows that have not yet been sufficiently explored, such as events between conception and adolescence, and on modifiable risk factors that show large variation within or between populations

<Book Reviews> Ingemar Fagerlind and Lawrence J Saha Education and National Development : A Comparative Perspective

textabstractVarious modeling methods have been proposed to estimate the potential predictive ability of polygenic risk variants that predispose to various common diseases. However, it is unknown whether differences between them affect their conclusions on predictive ability. We reviewed input parameters, assumptions and output of the five most common methods and compared their estimates of the area under the receiver operating characteristic (ROC) curve (AUC) using hypothetical data representing effect sizes and frequencies of genetic variants, population disease risk and number of variants. To assess the accuracy of the estimated AUCs, we aimed to reproduce the AUCs of published empirical studies. All methods assumed that the combined effect of genetic variants on disease risk followed a multiplicative risk model of independent genetic effects, but they either assumed per allele, per genotype or dominant/recessive effects for the genetic variants. Modeling strategy and input parameters differed. Methods used simulation analysis or analytical formulas with effect sizes quantified by odds ratios (ORs) or relative risks. Estimated AUC values were similar for lower ORs (0.7) due to variants with strong effects, differences in estimated AUCs between methods increased. The simulation methods accurately reproduced the AUC values of empirical studies, but the analytical methods did not. We conclude that despite differences in input parameters, the modeling methods estimate similar AUC for realistic values of the ORs. When one or more variants have stronger effects and AUC values are higher, the simulation methods tend to be more accurate

A systematic review of studies measuring health-related quality of life of general injury populations

Background. It is important to obtain greater insight into health-related quality of life (HRQL) of injury patients in order to document people's pathways to recovery and to quantify the impact of injury on population health over time. We performed a systematic review of studies measuring HRQL in general injury populations with a generic health state measure to summarize existing knowledge. Methods. Injury studies (1995-2009) were identified with main inclusion criteri

The Genetic Interpretation of Area under the ROC Curve in Genomic Profiling

Genome-wide association studies in human populations have facilitated the creation of genomic profiles which combine the effects of many associated genetic variants to predict risk of disease. The area under the receiver operator characteristic (ROC) curve is a well established measure for determining the efficacy of tests in correctly classifying diseased and non-diseased individuals. We use quantitative genetics theory to provide insight into the genetic interpretation of the area under the ROC curve (AUC) when the test classifier is a predictor of genetic risk. Even when the proportion of genetic variance explained by the test is 100%, there is a maximum value for AUC that depends on the genetic epidemiology of the disease, i.e. either the sibling recurrence risk or heritability and disease prevalence. We derive an equation relating maximum AUC to heritability and disease prevalence. The expression can be reversed to calculate the proportion of genetic variance explained given AUC, disease prevalence, and heritability. We use published estimates of disease prevalence and sibling recurrence risk for 17 complex genetic diseases to calculate the proportion of genetic variance that a test must explain to achieve AUC = 0.75; this varied from 0.10 to 0.74. We provide a genetic interpretation of AUC for use with predictors of genetic risk based on genomic profiles. We provide a strategy to estimate proportion of genetic variance explained on the liability scale from estimates of AUC, disease prevalence, and heritability (or sibling recurrence risk) available as an online calculator