Development and testing of the Measure of Innovation-Specific Implementation Intentions (MISII) using Rasch measurement theory

© 2018 The Author(s). Background: Implementation is proposed to be a multiphase, multilevel process. After a period of exploration, an adoption decision is made, typically at the upper management or policy level. Nevertheless, movement through each of the subsequent phases of the implementation process involves clinicians or providers at the individual level to adopt the innovation and then change their behavior to use/deliver the innovation. Multiple behavioral change theories propose that intentions are a critical determinant of implementation behavior. However, there is a need for the development and testing of pragmatic measures of providers' intentions to use a specific innovation or evidence-based practice (EBP). Methods: Nine items were developed to assess providers' intentions to use a specific innovation or EBP. Motivational interviewing was the EBP in the study. Items were administered, as part of larger survey, to 179 providers across 38 substance use disorder treatment (SUDT) programs within five agencies in California, USA. Rasch analysis was conducted using RUMM2030 software to assess the items, their overall fit to the Rasch model, the response scale used, individual item fit, differential item functioning (DIF), and person separation. Results: Following a stepwise process, the scale was reduced from nine items to three items to increase the feasibility and acceptability of the scale while maintaining suitable psychometric properties. The three-item unidimensional scale showed good person separation (PSI =.872), no disordering of thresholds, and no evidence of uniform or non-uniform DIF. Rasch analysis supported the viability of the scale as a measure of implementation intentions. Conclusions: The Measure of Innovation-Specific Implementation Intentions (MISII) is a sound measure of providers' intentions to use a specific innovation or EBP. Future evaluation of convergent, divergent, and predictive validity are needed. The study also demonstrates the value of Rasch analysis for testing the psychometric properties of pragmatic implementation measures

Genetic and metabolic predictors of chemosensitivity in oligodendroglial neoplasms

The −1p/−19q genotype predicts chemosensitivity in oligodendroglial neoplasms, but some with intact 1p/19q also respond and not all with 1p/19q loss derive durable benefit from chemotherapy. We have evaluated the predictive and prognostic significance of pretherapy 201Tl and 18F-FDG SPECT and genotype in 38 primary and 10 recurrent oligodendroglial neoplasms following PCV chemotherapy. 1p/19q loss was seen in 8/15 OII, 6/15 OAII, 7/7 OIII, 3/11 OAIII and was associated with response (Fisher-Exact: P=0.000) and prolonged progression-free (log-rank: P=0.002) and overall survival (OS) (log-rank: P=0.0048). Response was unrelated to metabolism, with tumours with high or low metabolism showing response. Increased 18F-FDG or 201Tl uptake predicted shorter progression-free survival (PFS) in the series (log-rank: 201Tl P=0.0097, 18F-FDG P=0.0170) and in cases with or without the −1p/−19q genotype. Elevated metabolism was associated with shorter OS in cases with intact 1p/19q (log-rank: 18F-FDG P=0.0077; 201Tl P=0.0004) and shorter PFS in responders (log-rank: 18F-FDG P=0.005; 201Tl P=0.0132). 201Tl uptake and 1p/19q loss were independent predictors of survival in multivariate analysis. In this initial study, 201Tl and 18F-FDG uptake did not predict response to PCV, but may be associated with poor survival following therapy irrespective of genotype. This may be clinically useful warranting further study

Towards Universal Structure-Based Prediction of Class II MHC Epitopes for Diverse Allotypes

The binding of peptide fragments of antigens to class II MHC proteins is a crucial step in initiating a helper T cell immune response. The discovery of these peptide epitopes is important for understanding the normal immune response and its misregulation in autoimmunity and allergies and also for vaccine design. In spite of their biomedical importance, the high diversity of class II MHC proteins combined with the large number of possible peptide sequences make comprehensive experimental determination of epitopes for all MHC allotypes infeasible. Computational methods can address this need by predicting epitopes for a particular MHC allotype. We present a structure-based method for predicting class II epitopes that combines molecular mechanics docking of a fully flexible peptide into the MHC binding cleft followed by binding affinity prediction using a machine learning classifier trained on interaction energy components calculated from the docking solution. Although the primary advantage of structure-based prediction methods over the commonly employed sequence-based methods is their applicability to essentially any MHC allotype, this has not yet been convincingly demonstrated. In order to test the transferability of the prediction method to different MHC proteins, we trained the scoring method on binding data for DRB1*0101 and used it to make predictions for multiple MHC allotypes with distinct peptide binding specificities including representatives from the other human class II MHC loci, HLA-DP and HLA-DQ, as well as for two murine allotypes. The results showed that the prediction method was able to achieve significant discrimination between epitope and non-epitope peptides for all MHC allotypes examined, based on AUC values in the range 0.632–0.821. We also discuss how accounting for peptide binding in multiple registers to class II MHC largely explains the systematically worse performance of prediction methods for class II MHC compared with those for class I MHC based on quantitative prediction performance estimates for peptide binding to class II MHC in a fixed register

Evolutionarily Conserved Protein Sequences of Influenza A Viruses, Avian and Human, as Vaccine Targets

10.1371/journal.pone.0001190PLoS ONE21

Averages of b-hadron, c-hadron, and tau-lepton properties as of 2018 Heavy Flavor Averaging Group (HFLAV)

This paper reports world averages of measurements of b-hadron, c-hadron, and τ -lepton properties obtained by the Heavy Flavour Averaging Group using results available through September 2018. In rare cases, significant results obtained several months later are also used. For the averaging, common input parameters used in the various analyses are adjusted (rescaled) to common values, and known correlations are taken into account. The averages include branching fractions, lifetimes, neutral meson mixing parameters, C P violation parameters, parameters of semileptonic decays, and Cabibbo–Kobayashi–Maskawa matrix elements

Influenza vaccination for immunocompromised patients: systematic review and meta-analysis from a public health policy perspective.

Immunocompromised patients are vulnerable to severe or complicated influenza infection. Vaccination is widely recommended for this group. This systematic review and meta-analysis assesses influenza vaccination for immunocompromised patients in terms of preventing influenza-like illness and laboratory confirmed influenza, serological response and adverse events