Building capacity for dissemination and implementation research: One university’s experience

Abstract Background While dissemination and implementation (D&I) science has grown rapidly, there is an ongoing need to understand how to build and sustain capacity in individuals and institutions conducting research. There are three inter-related domains for capacity building: people, settings, and activities. Since 2008, Washington University in St. Louis has dedicated significant attention and resources toward building D&I research capacity. This paper describes our process, challenges, and lessons with the goal of informing others who may have similar aims at their own institution. Activities An informal collaborative, the Washington University Network for Dissemination and Implementation Research (WUNDIR), began with a small group and now has 49 regular members. Attendees represent a wide variety of settings and content areas and meet every 6 weeks for half-day sessions. A logic model organizes WUNDIR inputs, activities, and outcomes. A mixed-methods evaluation showed that the network has led to new professional connections and enhanced skills (e.g., grant and publication development). As one of four, ongoing, formal programs, the Dissemination and Implementation Research Core (DIRC) was our first major component of D&I infrastructure. DIRC’s mission is to accelerate the public health impact of clinical and health services research by increasing the engagement of investigators in later stages of translational research. The aims of DIRC are to advance D&I science and to develop and equip researchers with tools for D&I research. As a second formal component, the Washington University Institute for Public Health has provided significant support for D&I research through pilot projects and a small grants program. In a third set of formal programs, two R25 training grants (one in mental health and one in cancer) support post-doctoral scholars for intensive training and mentoring in D&I science. Finally, our team coordinates closely with D&I functions within research centers across the university. We share a series of challenges and potential solutions. Conclusion Our experience in developing D&I research at Washington University in St. Louis shows how significant capacity can be built in a relatively short period of time. Many of our ideas and ingredients for success can be replicated, tailored, and improved upon by others

Knowledge and Perceptions of HPV Vaccine Acceptance among African-American College Women

Human papillomavirus (HPV) is the most prevalent sexually transmitted disease in the United States. Prevalence rates among sexually active young women are approximately 50%. An HPV vaccine has been created that has high efficacy in preventing persistent HPV infection, cervical cancer precursor lesions, and genital warts caused by four HPV subtypes. The purpose of this study was to assess African-American college women’s knowledge and perceptions of HPV, and their association with the acceptance of HPV vaccination. Variable selection was guided by the Health Belief Model and the Theory of Planned Behavior. Written surveys were administered to 122 African-American women between the ages of 18 and 26 who were enrolled as undergraduates at Florida Agricultural and Mechanical University (FAMU). Statistically significant associations were found between planning to get vaccinated against HPV and several perception variables. Health education efforts aimed at African-American women in college should be renewed, given the high percentage of misconceptions about HPV among members of the study population. Interventions should appeal to social networks of the young women, as their opinions regarding the vaccine weighs in their decision to plan to get vaccinated. This study underscores the need for continuous and consistent health education interventions directed at African-American women of college age

Rapid Multiplexed Data Acquisition: Application To Three-Dimensional Magnetic Field Measurements In A Turbulent Laboratory Plasma

Multiplexing electronics have been constructed to reduce the cost of high-speed data acquisition at the Swarthmore Spheromak Experiment (SSX) and Redmond Plasma Physics Laboratory. An application of the system is described for a three-dimensional magnetic probe array designed to resolve magnetohydrodynamic time scale and ion inertial spatial scale structure of magnetic reconnection in a laboratory plasma at SSX. Multiplexing at 10 MHz compresses 600 pick-up coil signals in the magnetic probe array into 75 digitizer channels. An external master timing system maintains synchronization of the multiplexers and digitizers. The complete system, calibrated and tested with Helmholtz, line current, and magnetofluid fields, reads out the entire 5 x 5 x 8 probe array every 800 ns with an absolute accuracy of approximately 20 G, limited mainly by bit error. (C) 2003 American Institute of Physics

Sex Hormone-Binding Globulin Levels Are Inversely Associated With Nonalcoholic Fatty Liver Disease in HIV-Infected and -Uninfected Men.

BackgroundNonalcoholic fatty liver disease (NAFLD) is a leading cause of liver disease worldwide. Elevated sex hormone-binding globulin (SHBG) levels have been observed in the setting of HIV and may protect against some metabolic disorders. We aimed to investigate whether higher SHBG levels may protect against NAFLD in men with/without HIV.MethodsNAFLD was assessed using noncontrast computed tomography in 530 men in the Multicenter AIDS Cohort Study (MACS) who drank <3 alcoholic drinks/d and were uninfected with chronic hepatitis C or B (340HIV+, 190HIV-). Morning serum samples were tested for SHBG, total testosterone (TT), and adiponectin. Multivariable logistic regression was used to assess associations between HIV, SHBG, TT, adiponectin, and NAFLD.ResultsMedian SHBG was highest among HIV+/NAFLD- men and lowest among HIV-/NAFLD+ men. Adjusted for demographics, HIV, visceral adiposity, HOMA-IR, TT, and PNPLA3 genotype, higher SHBG was associated with lower odds of NAFLD (odds ratio [OR], 0.52 per doubling; 95% confidence interval [CI], 0.34-0.80). In separate multivariable models without SHBG, HIV (OR, 0.46; 95% CI, 0.26-0.79) and higher adiponectin (OR, 0.66 per doubling; 95% CI, 0.49-0.89) were associated with lower NAFLD odds, whereas TT was not significantly associated (OR, 0.74 per doubling; 95% CI, 0.53-1.04). Adjusting for SHBG attenuated the associations of HIV (OR, 0.61; 95% CI, 0.34-1.08) and adiponectin (OR, 0.74; 95% CI, 0.54-1.02) with NAFLD.ConclusionsSHBG levels were higher among HIV+ men, were independently associated with lower NAFLD, and could partially explain the associations of HIV and higher adiponectin with lower NAFLD in our cohort. These findings suggest that SHBG may protect against NAFLD, supporting further prospective and mechanistic studies

Evaluation of Rapid Syphilis Testing Using the Syphilis Health Check in Florida, 2015–2016

The Syphilis Health Check (SHC) had low estimated specificity (91.5%) in one Florida county. We investigated use of SHC by a range of Florida publicly-funded programs between 2015 and 2016 to estimate specificity, positive predictive value (PPV), field staff acceptance, and impacts on programmatic outcomes. All reported SHC results were extracted from routinely collected program data. Field staff were surveyed about SHC’s utility. Analyses investigated differences between SHC and traditional syphilis testing outcomes. Of 3,630 SHC results reported, 442 were reactive; 92 (20.8%) had prior diagnoses of syphilis; 7 (1.6%) had no further testing. Of the remaining 343; 158 (46.0%) were confirmed cases, 168 (49.0%) were considered false-positive, and 17 (5.0%) were not cases but not clearly false-positive. Estimated specificity of SHC was 95.0%. Overall, 48.5% of positives became confirmed cases (PPV). PPV varied according to prevalence of syphilis in populations tested. Staff (90%) thought SHC helped identify new cases but expressed concern regarding discordance between reactive SHC and lab-based testing. Programmatic outcomes assessment showed shorter time to treatment and increased numbers of partners tested for the SHC group; these enhanced outcomes may better mitigate the spread of syphilis compared to traditional syphilis testing alone, but more research is needed

The Clustering of Extremely Red Objects

We measure the clustering of Extremely Red Objects (EROs) in ~8 deg^2 of the NOAO Deep Wide Field Survey Bo\"otes field in order to establish robust links between ERO z~1.2 and local galaxy z<0.1 populations. Three different color selection criteria from the literature are analyzed to assess the consequences of using different criteria for selecting EROs. Specifically, our samples are (R-K_s)>5.0 (28,724 galaxies), (I-K_s)>4.0 (22,451 galaxies) and (I-[3.6])>5.0 (64,370 galaxies). Magnitude-limited samples show the correlation length (r_0) to increase for more luminous EROs, implying a correlation with stellar mass. We can separate star-forming and passive ERO populations using the (K_s-[24]) and ([3.6]-[24]) colors to K_s=18.4 and [3.6]=17.5, respectively. Star-forming and passive EROs in magnitude limited samples have different clustering properties and host dark halo masses, and cannot be simply understood as a single population. Based on the clustering, we find that bright passive EROs are the likely progenitors of >4L^* elliptical galaxies. Bright EROs with ongoing star formation were found to occupy denser environments than star-forming galaxies in the local Universe, making these the likely progenitors of >L^* local ellipticals. This suggests that the progenitors of massive >4L^* local ellipticals had stopped forming stars by z>1.2, but that the progenitors of less massive ellipticals (down to L^*) can still show significant star formation at this epoch.Comment: 19 pages, 16 figures, 4 tables, Accepted to ApJ 27th November 201

Application of machine learning constructs to predict post-operative complications and adverse events following shoulder hemiarthroplasty

Background: Artificial intelligence (AI) constructs and machine learning (ML) algorithms have demonstrated utility in predicting various clinical, surgical, and financial outcomes. In this study, we applied AI to shoulder hemiarthroplasty (HA) to predict various post-operative complications. Methods: The sample was queried from the American college of surgeons-national surgical quality improvement program (ACS-NSQIP) database for all shoulder HA cases from 2008-2018. Six ML algorithms-random forest classifier, gradient boosting classifier, decision tree classifier, SVM classifier-tuned model, Gaussian Naïve Bayes classifier, multi-layer perception-analyzed the sample dataset. Postoperative complications included extended length of stay, non-home discharge destination, transfusion, and any adverse event. Each ML model was compared to logistic regression (LR), and model strength was evaluated. Results: We identified a total of 1585 shoulder HA cases. Mean age, BMI, operative time, and length of stay were 66±12 years, 31±8 kg/m2, 114±61 minutes, and 2.93±6.61 days. Preop hematocrit, longer operative time, and older age were most predictive of extended length of stay. Preop hematocrit, operative time, and ASA class had the highest importance in any adverse events (AAE) prediction. ML models outperformed traditional comorbidity indices, LR, for predicting extended length of stay (79% vs. 66%), non-home discharge destination (79% vs. 65%), any adverse event (78% vs. 66%), and transfusion requirement (82% vs. 63%).  Conclusions: ML algorithms predicted post-surgical outcomes of interest following shoulder HA at a higher rate to conventional LR and can assist orthopedic surgeons in decision making.

py4DSTEM: a software package for multimodal analysis of four-dimensional scanning transmission electron microscopy datasets

Scanning transmission electron microscopy (STEM) allows for imaging, diffraction, and spectroscopy of materials on length scales ranging from microns to atoms. By using a high-speed, direct electron detector, it is now possible to record a full 2D image of the diffracted electron beam at each probe position, typically a 2D grid of probe positions. These 4D-STEM datasets are rich in information, including signatures of the local structure, orientation, deformation, electromagnetic fields and other sample-dependent properties. However, extracting this information requires complex analysis pipelines, from data wrangling to calibration to analysis to visualization, all while maintaining robustness against imaging distortions and artifacts. In this paper, we present py4DSTEM, an analysis toolkit for measuring material properties from 4D-STEM datasets, written in the Python language and released with an open source license. We describe the algorithmic steps for dataset calibration and various 4D-STEM property measurements in detail, and present results from several experimental datasets. We have also implemented a simple and universal file format appropriate for electron microscopy data in py4DSTEM, which uses the open source HDF5 standard. We hope this tool will benefit the research community, helps to move the developing standards for data and computational methods in electron microscopy, and invite the community to contribute to this ongoing, fully open-source project

Islands of linkage in an ocean of pervasive recombination reveals two-speed evolution of human cytomegalovirus genomes

Human cytomegalovirus (HCMV) infects most of the population worldwide, persisting throughout the host's life in a latent state with periodic episodes of reactivation. While typically asymptomatic, HCMV can cause fatal disease among congenitally infected infants and immunocompromised patients. These clinical issues are compounded by the emergence of antiviral resistance and the absence of an effective vaccine, the development of which is likely complicated by the numerous immune evasins encoded by HCMV to counter the host's adaptive immune responses, a feature that facilitates frequent super-infections. Understanding the evolutionary dynamics of HCMV is essential for the development of effective new drugs and vaccines. By comparing viral genomes from uncultivated or low-passaged clinical samples of diverse origins, we observe evidence of frequent homologous recombination events, both recent and ancient, and no structure of HCMV genetic diversity at the whole-genome scale. Analysis of individual gene-scale loci reveals a striking dichotomy: while most of the genome is highly conserved, recombines essentially freely and has evolved under purifying selection, 21 genes display extreme diversity, structured into distinct genotypes that do not recombine with each other. Most of these hyper-variable genes encode glycoproteins involved in cell entry or escape of host immunity. Evidence that half of them have diverged through episodes of intense positive selection suggests that rapid evolution of hyper-variable loci is likely driven by interactions with host immunity. It appears that this process is enabled by recombination unlinking hyper-variable loci from strongly constrained neighboring sites. It is conceivable that viral mechanisms facilitating super-infection have evolved to promote recombination between diverged genotypes, allowing the virus to continuously diversify at key loci to escape immune detection, while maintaining a genome optimally adapted to its asymptomatic infectious lifecycle

Drug-Driven AMPA Receptor Redistribution Mimicked by Selective Dopamine Neuron Stimulation

Addictive drugs have in common that they cause surges in dopamine (DA) concentration in the mesolimbic reward system and elicit synaptic plasticity in DA neurons of the ventral tegmental area (VTA). Cocaine for example drives insertion of GluA2-lacking AMPA receptors (AMPARs) at glutamatergic synapes in DA neurons. However it remains elusive which molecular target of cocaine drives such AMPAR redistribution and whether other addictive drugs (morphine and nicotine) cause similar changes through their effects on the mesolimbic DA system