Role of p85α in neutrophil extra- and intracellular reactive oxygen species generation

Drug resistance is a growing problem that necessitates new strategies to combat pathogens. Neutrophil phagocytosis and production of intracellular ROS, in particular, has been shown to cooperate with antibiotics in the killing of microbes. This study tested the hypothesis that p85α, the regulatory subunit of PI3K, regulates production of intracellular ROS. Genetic knockout of p85α in mice caused decreased expression of catalytic subunits p110α, p110β, and p110δ, but did not change expression levels of the NADPH oxidase complex subunits p67phox, p47phox, and p40phox. When p85α, p55α, and p50α (all encoded by Pik3r1) were deleted, there was an increase in intracellular ROS with no change in phagocytosis in response to both Fcγ receptor and complement receptor stimulation. Furthermore, the increased intracellular ROS correlated with significantly improved neutrophil killing of both methicillin-susceptible and methicillin-resistant S. aureus. Our findings suggest inhibition of p85α as novel approach to improving the clearance of resistant pathogens

A Tribute to the Mind, Methodology and Mentoring of Wayne Velicer

Wayne Velicer is remembered for a mind where mathematical concepts and calculations intrigued him, behavioral science beckoned him, and people fascinated him. Born in Green Bay, Wisconsin on March 4, 1944, he was raised on a farm, although early influences extended far beyond that beginning. His Mathematics BS and Psychology minor at Wisconsin State University in Oshkosh, and his PhD in Quantitative Psychology from Purdue led him to a fruitful and far-reaching career. He was honored several times as a high-impact author, was a renowned scholar in quantitative and health psychology, and had more than 300 scholarly publications and 54,000+ citations of his work, advancing the arenas of quantitative methodology and behavioral health. In his methodological work, Velicer sought out ways to measure, synthesize, categorize, and assess people and constructs across behaviors and time, largely through principal components analysis, time series, and cluster analysis. Further, he and several colleagues developed a method called Testing Theory-based Quantitative Predictions, successfully applied to predicting outcomes and effect sizes in smoking cessation, diet behavior, and sun protection, with the potential for wider applications. With $60,000,000 in external funding, Velicer also helped engage a large cadre of students and other colleagues to study methodological models for a myriad of health behaviors in a widely applied Transtheoretical Model of Change. Unwittingly, he has engendered indelible memories and gratitude to all who crossed his path. Although Wayne Velicer left this world on October 15, 2017 after battling an aggressive cancer, he is still very present among us

Essential Content for Teaching Implementation Practice in Healthcare: A Mixed-Methods Study of Teams Offering Capacity-Building Initiatives

Background Applying the knowledge gained through implementation science can support the uptake of research evidence into practice; however, those doing and supporting implementation (implementation practitioners) may face barriers to applying implementation science in their work. One strategy to enhance individuals’ and teams’ ability to apply implementation science in practice is through training and professional development opportunities (capacity-building initiatives). Although there is an increasing demand for and offerings of implementation practice capacity-building initiatives, there is no universal agreement on what content should be included. In this study we aimed to explore what capacity-building developers and deliverers identify as essential training content for teaching implementation practice. Methods We conducted a convergent mixed-methods study with participants who had developed and/or delivered a capacity-building initiative focused on teaching implementation practice. Participants completed an online questionnaire to provide details on their capacity-building initiatives; took part in an interview or focus group to explore their questionnaire responses in depth; and offered course materials for review. We analyzed a subset of data that focused on the capacity-building initiatives’ content and curriculum. We used descriptive statistics for quantitative data and conventional content analysis for qualitative data, with the data sets merged during the analytic phase. We presented frequency counts for each category to highlight commonalities and differences across capacity-building initiatives. Results Thirty-three individuals representing 20 capacity-building initiatives participated. Study participants identified several core content areas included in their capacity-building initiatives: (1) taking a process approach to implementation; (2) identifying and applying implementation theories, models, frameworks, and approaches; (3) learning implementation steps and skills; (4) developing relational skills. In addition, study participants described offering applied and pragmatic content (e.g., tools and resources), and tailoring and evolving the capacity-building initiative content to address emerging trends in implementation science. Study participants highlighted some challenges learners face when acquiring and applying implementation practice knowledge and skills. Conclusions This study synthesized what experienced capacity-building initiative developers and deliverers identify as essential content for teaching implementation practice. These findings can inform the development, refinement, and delivery of capacity-building initiatives, as well as future research directions, to enhance the translation of implementation science into practice

Rethinking Research Ethics for Latinos: The Policy Paradox of Health Reform and the Role of Social Justice

http://dx.doi.org/10.1080/10508422.2012.72999

Undergraduate Biology Education Research Gordon Research Conference: A Meeting Report

The 2019 Undergraduate Biology Education Research Gordon Research Conference (UBER GRC), titled “Achieving Widespread Improvement in Undergraduate Education,” brought together a diverse group of researchers and practitioners working to identify, promote, and understand widespread adoption of evidence-based teaching, learning, and success strategies in undergraduate biology. Graduate students and postdocs had the additional opportunity to present and discuss research during a Gordon Research Seminar (GRS) that preceded the GRC. This report provides a broad overview of the UBER GRC and GRS and highlights major themes that cut across invited talks, poster presentations, and informal discussions. Such themes include the importance of working in teams at multiple levels to achieve instructional improvement, the potential to use big data and analytics to inform instructional change, the need to customize change initiatives, and the importance of psychosocial supports in improving undergraduate student well-being and academic success. The report also discusses the future of the UBER GRC as an established meeting and describes aspects of the conference that make it unique, both in terms of facilitating dissemination of research and providing a welcoming environment for conferees

Statistical practices of educational researchers: An analysis of their ANOVA, MANOVA, and ANCOVA analyses

Articles published in several prominent educational journals were examined to investigate the use of data-analysis tools by researchers in four research paradigms: between-subjects univariate designs, between-subjects multivariate designs, repeated measures designs, and covariance designs. In addition to examining specific details pertaining to the research design (e.g., sample size, group size equality/inequality) and methods employed for data analysis, we also catalogued whether: (a) validity assumptions were examined, (b) effect size indices were reported, (c) sample sizes were selected based on power considerations, and (d) appropriate textbooks and/or articles were cited to communicate the nature of the analyses that were performed. Our analyses imply that researchers rarely verify that validity assumptions are satisfied and accordingly typically use analyses that are nonrobust to assumption violations. In addition, researchers rarely report effect size statistics, nor do they routinely perform power analyses to determine sample size requirements. We offer many recommendations to rectify these shortcomings.Social Sciences and Humanities Research Counci

A comparison of low-dose risperidone to paroxetine in the treatment of panic attacks: a randomized, single-blind study

<p>Abstract</p> <p>Background</p> <p>Because a large proportion of patients with panic attacks receiving approved pharmacotherapy do not respond or respond poorly to medication, it is important to identify additional therapeutic strategies for the management of panic symptoms. This article describes a randomized, rater-blind study comparing low-dose risperidone to standard-of-care paroxetine for the treatment of panic attacks.</p> <p>Methods</p> <p>Fifty six subjects with a history of panic attacks were randomized to receive either risperidone or paroxetine. The subjects were then followed for eight weeks. Outcome measures included the Panic Disorder Severity Scale (PDSS), the Hamilton Anxiety Scale (Ham-A), the Hamilton Depression Rating Scale (Ham-D), the Sheehan Panic Anxiety Scale-Patient (SPAS-P), and the Clinical Global Impression scale (CGI).</p> <p>Results</p> <p>All subjects demonstrated a reduction in both the frequency and severity of panic attacks regardless of treatment received. Statistically significant improvements in rating scale scores for both groups were identified for the PDSS, the Ham-A, the Ham-D, and the CGI. There was no difference between treatment groups in the improvement in scores on the measures PDSS, Ham-A, Ham-D, and CGI. Post hoc tests suggest that subjects receiving risperidone may have a quicker clinical response than subjects receiving paroxetine.</p> <p>Conclusion</p> <p>We can identify no difference in the efficacy of paroxetine and low-dose risperidone in the treatment of panic attacks. Low-dose risperidone appears to be tolerated equally well as paroxetine. Low-dose risperidone may be an effective treatment for anxiety disorders in which panic attacks are a significant component.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov Identifier: NCT100457106</p

Association and interaction of PPAR-complex gene variants with latent traits of left ventricular diastolic function

<p>Abstract</p> <p>Background</p> <p>Abnormalities in myocardial metabolism and/or regulatory genes have been implicated in left ventricular systolic dysfunction. However, the extent to which these modulate left ventricular diastolic function (LVDF) is uncertain.</p> <p>Methods</p> <p>Independent component analysis was applied to extract latent LVDF traits from 14 measured echocardiography-derived endophenotypes of LVDF in 403 Caucasians. Genetic association was assessed between measured and latent LVDF traits and 64 single nucleotide polymorphisms (SNPs) in three peroxisome proliferator-activated receptor <it>(PPAR)</it>-complex genes involved in the transcriptional regulation of fatty acid metabolism.</p> <p>Results</p> <p>By linear regression analysis, 7 SNPs (4 in <it>PPARA</it>, 2 in <it>PPARGC1A</it>, 1 in <it>PPARG</it>) were significantly associated with the latent LVDF trait, whereas a range of 0-4 SNPs were associated with each of the 14 measured echocardiography-derived endophenotypes. Frequency distribution of <it>P </it>values showed a greater proportion of significant associations with the latent LVDF trait than for the measured endophenotypes, suggesting that analyses of the latent trait improved detection of the genetic underpinnings of LVDF. Ridge regression was applied to investigate within-gene and gene-gene interactions. In the within-gene analysis, there were five significant pair-wise interactions in <it>PPARGC1A </it>and none in <it>PPARA </it>or <it>PPARG</it>. In the gene-gene analysis, significant interactions were found between rs4253655 in <it>PPARA </it>and rs1873532 (p = 0.02) and rs7672915 (p = 0.02), both in <it>PPARGC1A</it>, and between rs1151996 in <it>PPARG </it>and rs4697046 in <it>PPARGC1A </it>(p = 0.01).</p> <p>Conclusions</p> <p>Myocardial metabolism <it>PPAR</it>-complex genes, including within and between genes interactions, may play an important role modulating left ventricular diastolic function.</p

Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK): Explanation and Elaboration

The REMARK “elaboration and explanation” guideline, by Doug Altman and colleagues, provides a detailed reference for authors on important issues to consider when designing, conducting, and analyzing tumor marker prognostic studies