Impact of Chronic Infection on Resistance and Tolerance to Secondary Infection in Drosophila melanogaster.

Prior exposure to a pathogen can greatly influence the outcome of a secondary infection, and although invertebrates lack classically defined adaptive immunity, their immune response is still influenced by prior immune challenges. While the strength and specificity of such immune priming depends highly on the host organism and infecting microbe, chronic bacterial infection of the fruit fly Drosophila melanogaster with species isolated from wild-caught fruit flies provides broad nonspecific protection against a later secondary bacterial infection. To determine how chronic infection influences progression of secondary infection, we specifically tested how chronic infection with Serratia marcescens and Enterococcus faecalis impacted both resistance and tolerance to a secondary infection with an unrelated bacterium, Providencia rettgeri, by simultaneously tracking survival and bacterial load postinfection across a range of infectious doses. We found that these chronic infections increased both tolerance and resistance to P. rettgeri. Further investigation of S. marcescens chronic infection also revealed robust protection against the highly virulent Providencia sneebia, and that protection was dependent on the initial infectious dose for S. marcescens with protective doses corresponding with significantly increased diptericin expression. While the increased expression of this antimicrobial peptide gene likely explains the increased resistance, increased tolerance is likely due to other alterations in organismal physiology, such as increased negative regulation of immunity or tolerance of ER stress. These findings provide a foundation for future studies on how chronic infection influences tolerance to secondary infection.

Evaluating clinical and demographic influences on health perception: A translation of the SF-12 for use with NHANES.

Improving public health depends on an intricate understanding of the factors that influence how individuals perceive and self-report their personal health. Self-perceived health is an independent predictor of future health-related outcomes, but capturing self-perception of health is complex due to the intricate relationship between clinical and perceived health. A commonly used measure of self-perceived health is the Short Form 12 (SF-12), developed in the 1990s. In this study, we aim to evaluate clinical and demographic influences on self-perceived health among American adults using the National Health and Nutrition Examination Survey (NHANES). While NHANES captures information on a number of domains of health, including clinical assessments, it does not include SF-12 items necessary to measure self-perceived health. Therefore, to assess self-perceived health for our study, we constructed and validated a novel SF-12-equivalent measure for use with NHANES using analogous items from the 2015-2016 NHANES interview questionnaires. The developed measure reflects established knowledge of population health patterns and closely parallels the behavior of the original SF-12. An analysis of the clinical and demographic influences on this novel measure of health perception revealed that both clinical and demographic factors, such as depression status and race, influence how healthy individuals perceive themselves to be. Importantly, our analysis indicated that among American adults, while controlling for clinical and demographic covariates, an increase in low-density lipoprotein (i.e., "bad") cholesterol level was associated with an improvement in self-perceived health. This study contributes significantly in two domains: it provides a novel measure of self-perceived health compatible for use with the widely used NHANES data (as well as details on how the process was developed), and it identifies a critical area in need of improved clinical education regarding the apparent confusion around cholesterol health.

Patient-Centered Medical Home Exposure and Its Impact on PA Career Intentions.

BACKGROUND AND OBJECTIVES: The transformation of primary care (PC) training sites into patient-centered medical homes (PCMH) has implications for the education of health professionals. This study investigates the extent to which physician assistant (PA) students report learning about the PCMH model and how clinical exposure to PCMH might impact their interest in a primary care career. METHODS: An electronic survey was distributed to second-year PA students who had recently completed their PC rotation from 12 PA programs. Descriptive statistics and ordered logistic regression analyses were used to characterize the results. RESULTS: A total of 202 second-year PA students completed the survey. When asked about their knowledge of the new health care delivery models, 30% of the students responded they had received instruction about the PCMH. Twenty- five percent of respondents stated they were oriented to new payment structures proposed in the Affordable Care Act and quality improvement principles. Based on their experiences in the primary care clerkship, 64% stated they were likely to pursue a career in primary care, 13% were not likely, and 23% were unsure. Predictors of interest in a primary care career included: (1) age greater than 35 years, (2) being a recipient of a NHSC scholarship, (3) clerkship site setting in an urban cluster of 2,500 to 50,000 people, (4) number of PCMH elements offered at site, and (4) positive impression of team-based care. CONCLUSIONS: PA students lack adequate instruction related to the new health care delivery models. Students whose clerkship sites offered greater number of PCMH elements were more interested in pursuing a career in primary care.

Non-stationary spatio-temporal modeling of traffic-related pollutants in near-road environments.

A problem often encountered in environmental epidemiological studies assessing the health effects associated with ambient exposure to air pollution is the spatial misalignment between monitors' locations and subjects' actual residential locations. Several strategies have been adopted to circumvent this problem and estimate pollutants concentrations at unsampled sites, including spatial statistical or geostatistical models that rely on the assumption of stationarity to model the spatial dependence in pollution levels. Although computationally convenient, the assumption of stationarity is often untenable for pollutants concentration, particularly in the near-road environment. Building upon the work of Fuentes (2001) and Schmidt et al. (2011), in this paper we present a non-stationary spatio-temporal model for three traffic-related pollutants in a localized near-road environment. Modeling each pollutant separately and independently, we express each pollutant's concentration as a mixture of two independent spatial processes, each equipped with a non-stationary covariance function with covariates driving the non-stationarity and the mixture weights.

Spatiotemporal calibration and resolution refinement of output from deterministic models.

Spatiotemporal calibration of output from deterministic models is an increasingly popular tool to more accurately and efficiently estimate the true distribution of spatial and temporal processes. Current calibration techniques have focused on a single source of data on observed measurements of the process of interest that are both temporally and spatially dense. Additionally, these methods often calibrate deterministic models available in grid-cell format with pixel sizes small enough that the centroid of the pixel closely approximates the measurement for other points within the pixel. We develop a modeling strategy that allows us to simultaneously incorporate information from two sources of data on observed measurements of the process (that differ in their spatial and temporal resolutions) to calibrate estimates from a deterministic model available on a regular grid. This method not only improves estimates of the pollutant at the grid centroids but also refines the spatial resolution of the grid data. The modeling strategy is illustrated by calibrating and spatially refining daily estimates of ambient nitrogen dioxide concentration over Connecticut for 1994 from the Community Multiscale Air Quality model (temporally dense grid-cell estimates on a large pixel size) using observations from an epidemiologic study (spatially dense and temporally sparse) and Environmental Protection Agency monitoring stations (temporally dense and spatially sparse). Copyright © 2016 John Wiley & Sons, Ltd.

Primary Care Teams, Composition, Roles, and Satisfaction of PA Students During Primary Care Rotations.

PURPOSE: The goal of t his study was to describe the characteristics of primary care teams, activities, and ro les of physician assistant (PA) students as they encounter various primary care sites. METHODS: An electronic survey was distributed to second year PA students in 12 programs who had completed at least 4 weeks in a primary care rotation. RESULTS: Of the 179 students who responded (response rate 41 %), 88% had completed their primary care rotations in urban settings, mostly in private practices (53%). Physician assistant students reported encountering many types of health care providers on their teams, and the 2 most favored features of the rotations were the interactions with their supervising clinicians and clinical responsibilities. About 68% interacted with other health profession students during their rotation(interprofessional experiential learning). Almost all students completed histories, physical examinations, and treatment plans, but less than 30% reported involvement in billing or care coordination and less than 10% participated in quality improvement projects. More than 60% were satisfied with team-based and interprofessional practices encountered during their primary care rotations, and 39% were more than likely to pursue primary care careers. CONCLUSIONS: Team-based prima ry ca re had a positive impact on students, but more exposure to underserved clinical settings, care coordination, quality improvement, and billing is needed to prepare PA students for the practice of the future. This study is t he first of its kind to explore the relationship between primary care sites and PA training in the era of health care reform.

Are thromboembolic and bleeding complications a drawback for composite aortic root replacement?

BACKGROUND: Valve-preserving aortic root reconstruction is being performed with increasing frequency. Independent of durability concerns, enthusiasm for retaining the native valve is often championed on the presumption that composite graft replacement of the aorta will be complicated by thromboembolism and bleeding. Our goal in this late follow-up study is to determine if thromboembolism or bleeding, or both, are indeed problematic after composite aortic root replacement. METHODS: Between 1995 and 2011, 306 patients (mean age, 56±14 years) underwent composite graft replacement of the aorta. St. Jude mechanical valve conduits (St. Jude Medical, St Paul, MN) were used in 242 patients, and 64 received a biologic conduit. Long-term postoperative follow-up (mean, 56 months; range, 1 to 97 months) was performed through our Aortic Database, supplemented by patient interviews and use of the Social Security Death Index. RESULTS: Hospital mortality was 2.9% overall and 1.4% in the last 8 years. Kaplan-Meier curves showed freedom (±standard deviation) from bleeding, stroke, and distal embolism as 94.3%±1.7% at 5 years and 91.3%±2.4% at 10 years. Survival was 93.5%±1.8% at 5 years and 80.9%±4.6% at 10 years, which was not statistically different from that for an age- and sex-matched population in Connecticut. Freedom from reoperation of the aortic root was 99% at 10 years. CONCLUSIONS: Patients had excellent survival and few thromboembolic and bleeding complications after composite aortic root replacement. These data supporting minimal morbidity in the setting of well-established durability should be used to put alternative procedures, such as valve-preserving aortic root reconstruction, into context.