The implementation of a dedicated education unit in a public health setting.

INTRODUCTION: The dedicated education unit (DEU) is an innovative clinical model that prepares preceptors for success in clinical settings with nursing students. Though the DEU is mostly used in acute-care settings, this project explores the implementation of a DEU in a public health setting. OBJECTIVES: Better preparation of public health nurses and social workers as clinical preceptors for nursing students with the implementation of a DEU in a public health setting. DESIGN: IRB approved, pre/post survey with participant comments. MEASUREMENTS: Clinical Nurse Teacher Survey was assessed pre/post intervention with registered nurses and social work staff (n = 13). Paired t-tests analysis was used to determine significance. The Clinical Learning Environment and Nurse Teacher (CLES+T) scale completed postimplementation by nursing students (n = 8) after the clinical rotation. RESULTS: Clinical Nurse Teacher Survey mean scores preintervention was 4.56 and increased postintervention to 4.89, though not statistically significant (p-value .11). CLES+T showing 100% fully agree or agree that the Public Health DEU is an effective learning environment. CONCLUSIONS: The DEU model in a public health setting is an opportunity to improve lived clinical experiences of preceptors and nursing students, which may increase nursing students' positive perceptions of, and increase interest in serving as a public health nurse after graduation.

Individual-level concentrations of fine particulate matter chemical components and subclinical atherosclerosis: a cross-sectional analysis based on 2 advanced exposure prediction models in the multi-ethnic study of atherosclerosis.

Long-term exposure to outdoor particulate matter with an aerodynamic diameter less than or equal to 2.5 µm (PM2.5) has been associated with cardiovascular morbidity and mortality. The chemical composition of PM2.5 that may be most responsible for producing these associations has not been identified. We assessed cross-sectional associations between long-term concentrations of PM2.5 and 4 of its chemical components (sulfur, silicon, elemental carbon, and organic carbon (OC)) and subclinical atherosclerosis, measured as carotid intima-media thickness (CIMT) and coronary artery calcium, between 2000 and 2002 among 5,488 Multi-Ethnic Study of Atherosclerosis participants residing in 6 US metropolitan areas. Long-term concentrations of PM2.5 components at participants' homes were predicted using both city-specific spatiotemporal models and a national spatial model. The estimated differences in CIMT associated with interquartile-range increases in sulfur, silicon, and OC predictions from the spatiotemporal model were 0.022 mm (95% confidence interval (CI): 0.014, 0.031), 0.006 mm (95% CI: 0.000, 0.012), and 0.026 mm (95% CI: 0.019, 0.034), respectively. Findings were generally similar using the national spatial model predictions but were often sensitive to adjustment for city. We did not find strong evidence of associations with coronary artery calcium. Long-term concentrations of sulfur and OC, and possibly silicon, were associated with CIMT using 2 distinct exposure prediction modeling approaches.

Applying morphometrics to early land plant systematics: a new Leclercqia (Lycopsida) species from Washington State, USA.

PREMISE OF THE STUDY: Early land plant fossils can be challenging to interpret due to their morphological simplicity and often fragmentary nature. Morphometric techniques using commonly preserved characters might increase diagnostic value of such material. To evaluate the utility of morphometrics in assessing morphospecies boundaries in the Devonian, we compared degrees of variation within the cosmopolitan lycopsid genus Leclercqia with that of living relatives (Lycopodium-Spinulum spp.) Of particular interest was determining whether a new morphotype of Leclercqia from the Middle Devonian Chilliwack flora of Washington State fell within or outside the range of variation of previously described species. METHODS: Morphological variation of Leclercqia was assessed across the geographic range of the genus using six vegetative and three reproductive characters. The new morphotype and two previously described species (L. complexa, L. andrewsii) were compared using linear discriminant analysis (LDA). Extant Lycopodium-Spinulum species and variants were similarly analyzed to assess inter- vs. intraspecific variation in living lycopsids. KEY RESULTS: The LDA comparisons of Lycopodium-Spinulum yielded notable morphological disparity between species but substantial overlap between intraspecific variants. Among the fossils, LDA separates the new morphotype, Leclercqia complexa, and L. andrewsii to a similar degree as Lycopodium and Spinulum species. Based on these results and further study, we describe a new species of Leclercqia: Leclercqia scolopendra Benca et Strömberg sp. nov. CONCLUSIONS: Morphometric analyses can aid in informing taxonomic assignment of fragmentary early land plant fossils using readily preserved features, even in the absence of reproductive structures. Applications of this approach to the Chilliwack flora suggest Leclercqia displayed greater morphological variation, taxonomic diversity, and biogeographic extent than previously thought.

Comparison of Yamuna (India) and Mississippi River (United States of America) bacterial communities reveals greater diversity below the Yamunotri Glacier.

The Yamuna River in India and the Mississippi River in the United States hold significant commercial, cultural, and ecological importance. This preliminary survey compares the bacterial communities sampled in surface waters at 11 sites (Yamuna headwaters, Mississippi headwaters, Yamuna River Yamunotri Town, Mississippi River at Winona, Tons River, Yamuna River at Paonta Sahib, Yamuna River Delhi-1, Yamuna River Delhi-2, Yamuna River before Sangam, Sangam, Ganga River before Sangam). Bacterial 16S rDNA analyses demonstrate dominance of Proteobacteria and Bacteroidetes phyla. Actinobacteria were also dominant at sites near Sangam in India and sites in Minnesota. A dominance of Epsilonbacteraeota were found in Delhi, India. Principal component analysis (PCA) using unique operational taxonomic units (OTUs) resulted in the identification of 3 groups that included the Yamuna River locations in Delhi (Delhi locations), Yamuna headwaters and Yamuna River at Yamunotri (Yamuna River locations below the Glacier) and Mississippi, Ganga, Tons, and other Yamuna River locations. Diversity indices were significantly higher at the Yamuna River locations below the Glacier (Simpson D = 0.986 and Shannon H = 5.06) as compared (p value <0.001) to the Delhi locations (D = 0.951 and H = 4.23) and as compared (p value < 0.001) to Mississippi, Ganga, Tons, and other Yamuna River locations (D = 0.943 and H = 3.96). To our knowledge, this is the first survey to compare Mississippi and Yamuna River bacterial communities. We demonstrate higher diversity in the bacterial communities below the Yamunotri glacier in India.

A More Comfortable Method for Hydrostatic Weighing: Head above Water at Total Lung Capacity.

Hydrostatic weighing (HW) requires full submersion with the lungs at residual volume (RV) which is uncomfortable. Therefore, the purpose of this study was to find a more comfortable way to complete HW. A HW system was used to complete three comparisons: comparison 1: change in head position (head above water vs. head below water (HAW vs. HBW)), comparison 2: change in lung volume (total lung capacity (TLC) vs. RV), and comparison 3: change in head and lung volume changes. Participants were separated by males (n = 64) and females (n = 58). Comparison 1: HAW resulted in higher mean percent body fat (PBF) than HBW (4.5% overall, 3.8% in males, 5.4% in females, p < 0.05). Comparison 2: TLC resulted in lower mean PBF than RV (5.1% overall, 5.3% in males, 4.8% in females, p < 0.05). Comparison 3: HAW@TLC resulted in significantly lower (1.5% lower, p = 0.003) mean PBF for males but was not significantly lower for females or overall (0.6% higher, p = 0.39, 0.6% lower, p = 0.18, respectively) compared to HBW@RV. In conclusion, keeping the head above water and taking a deep inhale makes HW a more enjoyable, and accessible experience for everyone while still producing accurate PBF results.

A regionalized national universal kriging model using Partial Least Squares regression for estimating annual PM2.5 concentrations in epidemiology.

Many cohort studies in environmental epidemiology require accurate modeling and prediction of fine scale spatial variation in ambient air quality across the U.S. This modeling requires the use of small spatial scale geographic or "land use" regression covariates and some degree of spatial smoothing. Furthermore, the details of the prediction of air quality by land use regression and the spatial variation in ambient air quality not explained by this regression should be allowed to vary across the continent due to the large scale heterogeneity in topography, climate, and sources of air pollution. This paper introduces a regionalized national universal kriging model for annual average fine particulate matter (PM2.5) monitoring data across the U.S. To take full advantage of an extensive database of land use covariates we chose to use the method of Partial Least Squares, rather than variable selection, for the regression component of the model (the "universal" in "universal kriging") with regression coefficients and residual variogram models allowed to vary across three regions defined as West Coast, Mountain West, and East. We demonstrate a very high level of cross-validated accuracy of prediction with an overall R2 of 0.88 and well-calibrated predictive intervals. In accord with the spatially varying characteristics of PM2.5 on a national scale and differing kriging smoothness parameters, the accuracy of the prediction varies by region with predictive intervals being notably wider in the West Coast and Mountain West in contrast to the East.

Classifying behavior from short-interval biologging data: An example with GPS tracking of birds.

Recent advances in digital data collection have spurred accumulation of immense quantities of data that have potential to lead to remarkable ecological insight, but that also present analytic challenges. In the case of biologging data from birds, common analytical approaches to classifying movement behaviors are largely inappropriate for these massive data sets.We apply a framework for using K-means clustering to classify bird behavior using points from short time interval GPS tracks. K-means clustering is a well-known and computationally efficient statistical tool that has been used in animal movement studies primarily for clustering segments of consecutive points. To illustrate the utility of our approach, we apply K-means clustering to six focal variables derived from GPS data collected at 1-11 s intervals from free-flying bald eagles (Haliaeetus leucocephalus) throughout the state of Iowa, USA. We illustrate how these data can be used to identify behaviors and life-stage- and age-related variation in behavior.After filtering for data quality, the K-means algorithm identified four clusters in >2 million GPS telemetry data points. These four clusters corresponded to three movement states: ascending, flapping, and gliding flight; and one non-moving state: perching. Mapping these states illustrated how they corresponded tightly to expectations derived from natural history observations; for example, long periods of ascending flight were often followed by long gliding descents, birds alternated between flapping and gliding flight.The K-means clustering approach we applied is both an efficient and effective mechanism to classify and interpret short-interval biologging data to understand movement behaviors. Furthermore, because it can apply to an abundance of very short, irregular, and high-dimensional movement data, it provides insight into small-scale variation in behavior that would not be possible with many other analytical approaches.

Implementation of a Dedicated Education Unit Model for ADN Students in a Rural Primary Care Setting.

BACKGROUND: Dedicated education unit (DEU) clinical education models are an innovative, evidence-based approach to create effective learning environments for students. These models have been implemented primarily in acute care settings. PROBLEM: The gap between nursing education and clinical practice in rural health care settings is a growing concern, compounded by a nursing faculty shortage and decreased availability of clinical sites. APPROACH: A descriptive study design was used to assess the outcomes of a DEU model of clinical practice with associate degree nursing students in a rural primary care clinic, using registered nurses (RNs) who were prepared as clinical nurse teachers. OUTCOMES: Associate degree nursing students experienced the RN role in primary care, worked with nurses who wanted to teach them, and improved their nursing skills. CONCLUSIONS: The DEU model is a positive clinical teaching pedagogy for students and staff nurses.

Individual neuronal subtypes control initial myelin sheath growth and stabilization.

BACKGROUND: In the developing central nervous system, pre-myelinating oligodendrocytes sample candidate nerve axons by extending and retracting process extensions. Some contacts stabilize, leading to the initiation of axon wrapping, nascent myelin sheath formation, concentric wrapping and sheath elongation, and sheath stabilization or pruning by oligodendrocytes. Although axonal signals influence the overall process of myelination, the precise oligodendrocyte behaviors that require signaling from axons are not completely understood. In this study, we investigated whether oligodendrocyte behaviors during the early events of myelination are mediated by an oligodendrocyte-intrinsic myelination program or are over-ridden by axonal factors. METHODS: To address this, we utilized in vivo time-lapse imaging in embryonic and larval zebrafish spinal cord during the initial hours and days of axon wrapping and myelination. Transgenic reporter lines marked individual axon subtypes or oligodendrocyte membranes. RESULTS: In the larval zebrafish spinal cord, individual axon subtypes supported distinct nascent sheath growth rates and stabilization frequencies. Oligodendrocytes ensheathed individual axon subtypes at different rates during a two-day period after initial axon wrapping. When descending reticulospinal axons were ablated, local spinal axons supported a constant ensheathment rate despite the increased ratio of oligodendrocytes to target axons. CONCLUSION: We conclude that properties of individual axon subtypes instruct oligodendrocyte behaviors during initial stages of myelination by differentially controlling nascent sheath growth and stabilization.

Multipollutant measurement error in air pollution epidemiology studies arising from predicting exposures with penalized regression splines.

Air pollution epidemiology studies are trending towards a multi-pollutant approach. In these studies, exposures at subject locations are unobserved and must be predicted using observed exposures at misaligned monitoring locations. This induces measurement error, which can bias the estimated health effects and affect standard error estimates. We characterize this measurement error and develop an analytic bias correction when using penalized regression splines to predict exposure. Our simulations show bias from multi-pollutant measurement error can be severe, and in opposite directions or simultaneously positive or negative. Our analytic bias correction combined with a non-parametric bootstrap yields accurate coverage of 95% confidence intervals. We apply our methodology to analyze the association of systolic blood pressure with PM2.5 and NO2 in the NIEHS Sister Study. We find that NO2 confounds the association of systolic blood pressure with PM2.5 and vice versa. Elevated systolic blood pressure was significantly associated with increased PM2.5 and decreased NO2. Correcting for measurement error bias strengthened these associations and widened 95% confidence intervals.

Prediction of fine particulate matter chemical components with a spatio-temporal model for the Multi-Ethnic Study of Atherosclerosis cohort.

Although cohort studies of the health effects of PM2.5 have developed exposure prediction models to represent spatial variability across participant residences, few models exist for PM2.5 components. We aimed to develop a city-specific spatio-temporal prediction approach to estimate long-term average concentrations of four PM2.5 components including sulfur, silicon, and elemental and organic carbon for the Multi-Ethnic Study of Atherosclerosis cohort, and to compare predictions to those from a national spatial model. Using 2-week average measurements from a cohort-focused monitoring campaign, the spatio-temporal model employed selected geographic covariates in a universal kriging framework with the data-driven temporal trend. Relying on long-term means of daily measurements from regulatory monitoring networks, the national spatial model employed dimension-reduced predictors using universal kriging. For the spatio-temporal model, the cross-validated and temporally-adjusted R(2) was relatively higher for EC and OC, and in the Los Angeles and Baltimore areas. The cross-validated R(2)s for both models across the six areas were reasonably high for all components except silicon. Predicted long-term concentrations at participant homes from the two models were generally highly correlated across cities but poorly correlated within cities. The spatio-temporal model may be preferred for city-specific health analyses, whereas both models could be used for multi-city studies.

Long-Term Air Pollution Exposure and Blood Pressure in the Sister Study.

BACKGROUND: Exposure to air pollution has been consistently associated with cardiovascular morbidity and mortality, but mechanisms remain uncertain. Associations with blood pressure (BP) may help to explain the cardiovascular effects of air pollution. OBJECTIVE: We examined the cross-sectional relationship between long-term (annual average) residential air pollution exposure and BP in the National Institute of Environmental Health Sciences' Sister Study, a large U.S. cohort study investigating risk factors for breast cancer and other outcomes. METHODS: This analysis included 43,629 women 35-76 years of age, enrolled 2003-2009, who had a sister with breast cancer. Geographic information systems contributed to satellite-based nitrogen dioxide (NO2) and fine particulate matter (≤ 2.5 µm; PM2.5) predictions at participant residences at study entry. Generalized additive models were used to examine the relationship between pollutants and measured BP at study entry, adjusting for cardiovascular disease risk factors and including thin plate splines for potential spatial confounding. RESULTS: A 10-µg/m(3) increase in PM2.5 was associated with 1.4-mmHg higher systolic BP (95% CI: 0.6, 2.3; p < 0.001), 1.0-mmHg higher pulse pressure (95% CI: 0.4, 1.7; p = 0.001), 0.8-mmHg higher mean arterial pressure (95% CI: 0.2, 1.4; p = 0.01), and no significant association with diastolic BP. A 10-ppb increase in NO2 was associated with a 0.4-mmHg (95% CI: 0.2, 0.6; p < 0.001) higher pulse pressure. CONCLUSIONS: Long-term PM2.5 and NO2 exposures were associated with higher blood pressure. On a population scale, such air pollution-related increases in blood pressure could, in part, account for the increases in cardiovascular disease morbidity and mortality seen in prior studies.

A national prediction model for PM2.5 component exposures and measurement error-corrected health effect inference.

BACKGROUND: Studies estimating health effects of long-term air pollution exposure often use a two-stage approach: building exposure models to assign individual-level exposures, which are then used in regression analyses. This requires accurate exposure modeling and careful treatment of exposure measurement error. OBJECTIVE: To illustrate the importance of accounting for exposure model characteristics in two-stage air pollution studies, we considered a case study based on data from the Multi-Ethnic Study of Atherosclerosis (MESA). METHODS: We built national spatial exposure models that used partial least squares and universal kriging to estimate annual average concentrations of four PM2.5 components: elemental carbon (EC), organic carbon (OC), silicon (Si), and sulfur (S). We predicted PM2.5 component exposures for the MESA cohort and estimated cross-sectional associations with carotid intima-media thickness (CIMT), adjusting for subject-specific covariates. We corrected for measurement error using recently developed methods that account for the spatial structure of predicted exposures. RESULTS: Our models performed well, with cross-validated R2 values ranging from 0.62 to 0.95. Naïve analyses that did not account for measurement error indicated statistically significant associations between CIMT and exposure to OC, Si, and S. EC and OC exhibited little spatial correlation, and the corrected inference was unchanged from the naïve analysis. The Si and S exposure surfaces displayed notable spatial correlation, resulting in corrected confidence intervals (CIs) that were 50% wider than the naïve CIs, but that were still statistically significant. CONCLUSION: The impact of correcting for measurement error on health effect inference is concordant with the degree of spatial correlation in the exposure surfaces. Exposure model characteristics must be considered when performing two-stage air pollution epidemiologic analyses because naïve health effect inference may be inappropriate.

Quantifying protein function specificity in the gene ontology.

Quantitative or numerical metrics of protein function specificity made possible by the Gene Ontology are useful in that they enable development of distance or similarity measures between protein functions. Here we describe how to calculate four measures of function specificity for GO terms: 1) number of ancestor terms; 2) number of offspring terms; 3) proportion of terms; and 4) Information Content (IC). We discuss the relationship between the metrics and the strengths and weaknesses of each.