Availability of Recreation Facilities and Parks In Relation to Adolescent Participation in Organized Sports and Activity Programs.

Most adolescents do not meet physical activity guidelines, so understanding facilitators and barriers is important. This study used surveys and geocoded location data to examine associations of availability of parks and recreation facilities with adolescent-reported participation in organized team sports and physical activity classes. The study was conducted with 928 adolescents aged 12-17 years, plus one parent/caretaker, recruited from two regions of the US. Adolescents' participation in teams and classes was positively associated with parents' perceptions of multiple available recreation environments, but not with objectively-measured availability. Having multiple nearby parks and recreation facilities may provide adolescents with more options for participating in preferred organized team sports and activity classes.

International evaluation of the Microscale Audit of Pedestrian Streetscapes (MAPS) Global instrument: comparative assessment between local and remote online observers.

OBJECTIVES: The use of online imagery by non-local observers to conduct remote, centralized collection of streetscape audit data in international studies has the potential to enhance efficiency of collection and comparability of such data for research on built environments and health. The objectives of the study were to measure (1) the consistency in responses between local in-field observers and non-local remote online observers and (2) the reliability between in-country online observers and non-local remote online observers using the Microscale Audit of Pedestrian Streetscapes Global tool to characterize pedestrian-related features along streets in five countries. METHODS: Consistency and inter-rater reliability were analyzed between local and non-local observers on a pooled database of 200 routes in five study regions (Melbourne, Australia; Ghent, Belgium; Curitiba, Brazil; Hong Kong, China; and Valencia, Spain) for microscale environmental feature subscales and item-level variables using the intraclass correlation coefficient (ICC). RESULTS: A local in-field versus remote online comparison had an ICC of 0.75 (95 % CI: 0.68-0.80) for the grand total score. An ICC of 0.91 (95 % CI: 0.88-0.93) was found for the local online versus remote online comparison. Positive subscales yielded stronger results in comparison to negative subscales, except for the similarly poor-performing positive aesthetics/social characteristics. CONCLUSIONS: This study demonstrated remote audits of microscale built environments using online imagery had good reliability with local in-field audits and excellent reliability with local online audits. Results generally supported remote online environmental audits as comparable to local online audits. This identification of low-cost and efficient data acquisition methods is important for expanding research on microscale built environments and physical activity globally.

Heterozygous loss-of-function variants significantly expand the phenotypes associated with loss of GDF11.

PURPOSE: Growth differentiation factor 11 (GDF11) is a key signaling protein required for proper development of many organ systems. Only one prior study has associated an inherited GDF11 variant with a dominant human disease in a family with variable craniofacial and vertebral abnormalities. Here, we expand the phenotypic spectrum associated with GDF11 variants and document the nature of the variants. METHODS: We present a cohort of six probands with de novo and inherited nonsense/frameshift (4/6 patients) and missense (2/6) variants in GDF11. We generated gdf11 mutant zebrafish to model loss of gdf11 phenotypes and used an overexpression screen in Drosophila to test variant functionality. RESULTS: Patients with variants in GDF11 presented with craniofacial (5/6), vertebral (5/6), neurological (6/6), visual (4/6), cardiac (3/6), auditory (3/6), and connective tissue abnormalities (3/6). gdf11 mutant zebrafish show craniofacial abnormalities and body segmentation defects that match some patient phenotypes. Expression of the patients' variants in the fly showed that one nonsense variant in GDF11 is a severe loss-of-function (LOF) allele whereas the missense variants in our cohort are partial LOF variants. CONCLUSION: GDF11 is needed for human development, particularly neuronal development, and LOF GDF11 alleles can affect the development of numerous organs and tissues.

Active travel and social justice: Addressing disparities and promoting health equity through a novel approach to Regional Transportation Planning.

Public health impacts of transportation policies and infrastructure investment are becoming better understood, particularly for those associated with physical activity. Yet health impacts are not routinely evaluated within the context of the development of a Regional Transportation Plan (RTP) and subsequent programming and investment processes. This is particularly concerning because the spatial distribution of planned transportation infrastructure potentially has significant health equity implications for vulnerable populations at greater risk of chronic disease. This study discusses the application of the National Public Health Assessment Model (NPHAM) - a new approach that expands several scenario planning tools to include health - for the San Joaquin Council of Governments 2018 RTP. It demonstrates how quantifying health impacts at a finer spatial scale (census block groups) helps assess the extent to which RTP strategies are likely to benefit or harm health. It further enables a spatial form of health equity analysis that can help planners understand where infrastructure is most needed to meet social equity goals. To the knowledge of the authors, this is the first example of a quantified, health equity analysis of transport physical activity and a health outcome - body mass index - associated with an RTP; it demonstrates significant advancement in transportation planning practice and policy.

Comparing spatial regression to random forests for large environmental data sets.

Environmental data may be "large" due to number of records, number of covariates, or both. Random forests has a reputation for good predictive performance when using many covariates with nonlinear relationships, whereas spatial regression, when using reduced rank methods, has a reputation for good predictive performance when using many records that are spatially autocorrelated. In this study, we compare these two techniques using a data set containing the macroinvertebrate multimetric index (MMI) at 1859 stream sites with over 200 landscape covariates. A primary application is mapping MMI predictions and prediction errors at 1.1 million perennial stream reaches across the conterminous United States. For the spatial regression model, we develop a novel transformation procedure that estimates Box-Cox transformations to linearize covariate relationships and handles possibly zero-inflated covariates. We find that the spatial regression model with transformations, and a subsequent selection of significant covariates, has cross-validation performance comparable to random forests. We also find that prediction interval coverage is close to nominal for each method, but that spatial regression prediction intervals tend to be narrower and have less variability than quantile regression forest prediction intervals. A simulation study is used to generalize results and clarify advantages of each modeling approach.

Estimating the Distribution of Harvested Estuarine Bivalves with Natural-History-Based Habitat Suitability Models.

Habitat suitability models are useful to estimate the potential distribution of a species of interest, particularly in the case of infaunal bivalves. Sampling for these bivalves is time- and cost-intensive, which is increasingly difficult for organizations or agencies that are limited by personnel and funds. Consequently, we developed a framework to identify suitable bivalve habitat in estuaries (FISBHE) - a habitat suitability index (HSI) modeling framework for NE Pacific estuaries that was parameterized with published natural-hi story information and existing habitat datasets, without requiring extensive field sampling of bivalves. Spatially explicit, rule-based habitat suitability models were constructed in a GIS for five species of bay-clams (Clinocardium nuttallii, My a arenaria, Tresus capax, Saxidomus gigantea, and Leukoma staminea) that are popular targets for recreational and commercial harvest in estuaries of the U.S. Pacific Northwest. Habitat rasters were produced for Yaquina and Tillamook estuaries (Oregon, USA) using environmental data (bathymetric depth, sediment % silt-clay, wet-season salinity, and burrowing shrimp presence/absence) from multiple studies (1953-2015). These habitat rasters then served as inputs in the final model which produced HSI classes ranging from 0-4 (lowest to highest suitability), dependent upon the number of habitat variables that fell within the sensitivity limits for each species of bay-clam. The models were tested with validation analyses and bay-clam occurrence data (reported in benthic community studies, 1996-2012) within each HSI class; logistic regression and Kendall's correlation coefficient both showed correspondence between predicted HSI classes and bay-clam presence/absence. Results also showed that the greatest presence probabilities occurred within habitats of highest predicted suitability, with the exception of M. arenaria in Tillamook Bay. The advantage of FISBHE is that disparate, independent sets of existing data are sufficient to parameterize the models, as well as produce and validate maps of habitat suitability. This approach can be transferred to data-poor systems with modest investment, which can be useful for prioritizing estuarine land-use decisions and could be used to estimate the vulnerability of this valued ecosystem good to changes in habitat quality and distribution.

The Health and economic effects of light rail lines: design, methods, and protocol for a natural experiment.

BACKGROUND: The health impacts of community design have been studied extensively over the past two decades. In particular, public transportation use is associated with more walking between transit stops and shops, work, home and other destinations. Change in transit access has been linked with physical activity and obesity but seldom to health outcomes and associated costs, especially within a causal framework. Health related fiscal impacts of transit investment should be a key consideration in major transit investment decisions. METHODS: The Rails & Health study is a natural experiment evaluating changes in clinical measures, health care utilization and health care costs among Kaiser Permanente Northwest (KPNW) members following the opening of a new light rail transit (LRT) line in Portland, Oregon. The study is prospectively following 3036 adults exposed to the new LRT line and a similar cohort of 4386 adults who do not live close to the new line. Individual-level outcomes and covariates are extracted from the electronic medical record at KPNW, including member demographics and comorbidities, blood pressure, body mass index, lipids, glycosylated hemoglobin, and health care utilization and costs. In addition, participants are surveyed about additional demographics, travel patterns, physical activity (PA), and perceived neighborhood walkability. In a subsample of the study population, we are collecting direct measures of travel-related behavior-physical activity (accelerometry), global positioning system (GPS) tracking, and travel diaries-to document mechanisms responsible for observed changes in health outcomes and cost. Comprehensive measures of the built environment at baseline and after rail construction are also collected. Statistical analyses will (1) examine the effects of opening a new LRT line on chronic disease indicators, health care utilization, and health care costs and (2) evaluate the degree to which observed effects of the LRT line on health measures and costs are mediated by changes in total and transportation-associated PA. DISCUSSION: The results of the Rails & Health study will provide urban planners, transportation engineers, health practitioners, developers, and decision makers with critical information needed to document how transit investments impact population health and related costs.

Perioperative and Anesthetic Management of Coarctation of the Aorta.

Isolated coarctation of the aorta is a relatively common form of congenital heart disease that is characterized by variable degrees of obstruction to aortic outflow. The clinical presentation varies from asymptomatic arterial hypertension to cardiogenic shock. The treatment options include surgical repair or interventional therapy with aortic balloon dilation and stent placement. This article will summarize the pathophysiology as well as describe the surgical and interventional procedures. The anesthetic management for those interventions will be reviewed.

Indoximod: An Immunometabolic Adjuvant That Empowers T Cell Activity in Cancer.

Exploding interest in immunometabolism as a source of new cancer therapeutics has been driven in large part by studies of tryptophan catabolism mediated by IDO/TDO enzymes. A chief focus in the field is IDO1, a pro-inflammatory modifier that is widely overexpressed in cancers where it blunts immunosurveillance and enables neovascularization and metastasis. The simple racemic compound 1-methyl-D,L-tryptophan (1MT) is an extensively used probe of IDO/TDO pathways that exerts a variety of complex inhibitory effects. The L isomer of 1MT is a weak substrate for IDO1 and is ascribed the weak inhibitory activity of the racemate on the enzyme. In contrast, the D isomer neither binds nor inhibits the purified IDO1 enzyme. However, clinical development focused on D-1MT (now termed indoximod) due to preclinical cues of its greater anticancer activity and its distinct mechanisms of action. In contrast to direct enzymatic inhibitors of IDO1, indoximod acts downstream of IDO1 to stimulate mTORC1, a convergent effector signaling molecule for all IDO/TDO enzymes, thus possibly lowering risks of drug resistance by IDO1 bypass. In this review, we survey the unique biological and mechanistic features of indoximod as an IDO/TDO pathway inhibitor, including recent clinical findings of its ability to safely enhance various types of cancer therapy, including chemotherapy, chemo-radiotherapy, vaccines, and immune checkpoint therapy. We also review the potential advantages indoximod offers compared to selective IDO1-specific blockade, which preclinical studies and the clinical study ECHO-301 suggest may be bypassed readily by tumors. Indoximod lies at a leading edge of broad-spectrum immunometabolic agents that may act to improve responses to many anticancer modalities, in a manner analogous to vaccine adjuvants that act to boost immunity in settings of infectious disease.

Linking green space to neighborhood social capital in older adults: The role of perceived safety.

This study examines the moderating effect of perceived safety on the association of green space with neighborhood social capital in older adults. Green space may play an important role for promoting neighborhood social capital and health for older adults; however, safety remains a significant challenge in maximizing the benefits of green space. Data were drawn from 647 independent-living seniors who participated in the Senior Neighborhood Quality of Life Study in the Seattle/King County and Baltimore/Washington DC region. The results suggest that certain green space elements, such as natural sights, may be beneficial to neighborhood social capital of older adults. However, other types of green space, such as parks and street trees, may be less advantageous to older adults who perceive their neighborhoods as unsafe for pedestrians. Findings highlight the importance of pedestrian safety in examining associations of green space with neighborhood social capital in older adults. Further studies using a longitudinal design are warranted to confirm the causality of the findings.

Development and reliability of a streetscape observation instrument for international use: MAPS-global.

BACKGROUND: Relationships between several built environment factors and physical activity and walking behavior are well established, but internationally-comparable built environment measures are lacking. The Microscale Audit of Pedestrian Streetscapes (MAPS)-Global is an observational measure of detailed streetscape features relevant to physical activity that was developed for international use. This study examined the inter-observer reliability of the instrument in five countries. METHODS: MAPS-Global was developed by compiling concepts and items from eight environmental measures relevant to walking and bicycling. Inter-rater reliability data were collected in neighborhoods selected to vary on geographic information system (GIS)-derived macro-level walkability in five countries (Australia, Belgium, Brazil, Hong Kong-China, and Spain). MAPS-Global assessments (n = 325) were completed in person along a ≥ 0.25 mile route from a residence toward a non-residential destination, and a commercial block was also rated for each residence (n = 82). Two raters in each country rated each route independently. A tiered scoring system was created that summarized items at multiple levels of aggregation, and positive and negative valence scores were created based on the expected effect on physical activity. The intraclass correlation coefficient (ICC) was computed for scales and selected items using one-way random models. RESULTS: Overall, 86.6% of individual items and single item indicators showed excellent agreement (ICC ≥ 0.75), and 13.4% showed good agreement (ICC = 0.60-0.74). All subscales and overall summary scores showed excellent agreement. Six of 123 items were too rare to compute the ICC. The median ICC for items and scales was 0.92 with a range of 0.50-1.0. Aesthetics and social characteristics showed lower ICCs than other sub-scales, but reliabilities were still in the excellent range (ICC ≥ 0.75). CONCLUSION: Evaluation of inter-observer reliability of MAPS-Global across five countries indicated all items and scales had "good" or "excellent" reliability. The results demonstrate that trained observers from multiple countries were able to reliably conduct observations of both residential and commercial areas with the new MAPS-Global instrument. Next steps are to evaluate construct validity in relation to physical activity in multiple countries and gain experience with using MAPS-Global for research and practice applications.

Bringing health into transportation and land use scenario planning: Creating a National Public Health Assessment Model (N-PHAM).

There is mounting evidence linking land development and transportation investments to physical activity with resulting implications for chronic disease prevention. Links between the physical environment and health have traditionally focused on harmful exposures such as air pollution, noise, and traffic injury. Given limited funds and competition for how and where investments are made, there is a need to prioritize and target resources to maximize health benefits that can include activity related chronic disease prevention. The ability to apply this evidence to decision making has been limited by the complexity and inconsistency of research methods, and lack of a direct connection with the planning contexts in which decisions are made. Scenario planning tools provide a method to apply evidence with spatial planning decisions at a range of geographic scales. The US Environmental Protection Agency commissioned the development of a National Public Health Assessment Model (N-PHAM). This project utilized built and natural environment data at the block-group level and large population surveys to model the relationships of the environment with several health outcomes for a range of age and income groups. N-PHAM is the first health assessment tool that can connect to multiple existing scenario planning platforms utilizing nationally available data and can be consistently applied nationally. Such tools can empower communities to choose investments that have the greatest potential to improve public health and quality of life, reduce health care costs, and address environmental justice related disparities.

Predictive mapping of the biotic condition of conterminous U.S. rivers and streams.

Understanding and mapping the spatial variation in stream biological condition could provide an important tool for conservation, assessment, and restoration of stream ecosystems. The USEPA's 2008-2009 National Rivers and Streams Assessment (NRSA) summarizes the percentage of stream lengths within the conterminous United States that are in good, fair, or poor biological condition based on a multimetric index of benthic invertebrate assemblages. However, condition is usually summarized at regional or national scales, and these assessments do not provide substantial insight into the spatial distribution of conditions at unsampled locations. We used random forests to model and predict the probable condition of several million kilometers of streams across the conterminous United States based on nearby and upstream landscape features, including human-related alterations to watersheds. To do so, we linked NRSA sample sites to the USEPA's StreamCat Dataset; a database of several hundred landscape metrics for all 1:100,000-scale streams and their associated watersheds within the conterminous United States. The StreamCat data provided geospatial indicators of nearby and upstream land use, land cover, climate, and other landscape features for modeling. Nationally, the model correctly predicted the biological condition class of 75% of NRSA sites. Although model evaluations suggested good discrimination among condition classes, we present maps as predicted probabilities of good condition, given upstream and nearby landscape settings. Inversely, the maps can be interpreted as the probability of a stream being in poor condition, given human-related watershed alterations. These predictions are available for download from the USEPA's StreamCat website. Finally, we illustrate how these predictions could be used to prioritize streams for conservation or restoration.

Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology.

Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological data sets, there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected set of predictor variables are used or stepwise procedures are employed which iteratively remove variables according to their importance measures. This paper investigates the application of variable selection methods to RF models for predicting probable biological stream condition. Our motivating data set consists of the good/poor condition of n = 1365 stream survey sites from the 2008/2009 National Rivers and Stream Assessment, and a large set (p = 212) of landscape features from the StreamCat data set as potential predictors. We compare two types of RF models: a full variable set model with all 212 predictors and a reduced variable set model selected using a backward elimination approach. We assess model accuracy using RF's internal out-of-bag estimate, and a cross-validation procedure with validation folds external to the variable selection process. We also assess the stability of the spatial predictions generated by the RF models to changes in the number of predictors and argue that model selection needs to consider both accuracy and stability. The results suggest that RF modeling is robust to the inclusion of many variables of moderate to low importance. We found no substantial improvement in cross-validated accuracy as a result of variable reduction. Moreover, the backward elimination procedure tended to select too few variables and exhibited numerous issues such as upwardly biased out-of-bag accuracy estimates and instabilities in the spatial predictions. We use simulations to further support and generalize results from the analysis of real data. A main purpose of this work is to elucidate issues of model selection bias and instability to ecologists interested in using RF to develop predictive models with large environmental data sets.

International comparison of observation-specific spatial buffers: maximizing the ability to estimate physical activity.

BACKGROUND: Advancements in geographic information systems over the past two decades have increased the specificity by which an individual's neighborhood environment may be spatially defined for physical activity and health research. This study investigated how different types of street network buffering methods compared in measuring a set of commonly used built environment measures (BEMs) and tested their performance on associations with physical activity outcomes. METHODS: An internationally-developed set of objective BEMs using three different spatial buffering techniques were used to evaluate the relative differences in resulting explanatory power on self-reported physical activity outcomes. BEMs were developed in five countries using 'sausage,' 'detailed-trimmed,' and 'detailed,' network buffers at a distance of 1 km around participant household addresses (n = 5883). RESULTS: BEM values were significantly different (p < 0.05) for 96% of sausage versus detailed-trimmed buffer comparisons and 89% of sausage versus detailed network buffer comparisons. Results showed that BEM coefficients in physical activity models did not differ significantly across buffering methods, and in most cases BEM associations with physical activity outcomes had the same level of statistical significance across buffer types. However, BEM coefficients differed in significance for 9% of the sausage versus detailed models, which may warrant further investigation. CONCLUSIONS: Results of this study inform the selection of spatial buffering methods to estimate physical activity outcomes using an internationally consistent set of BEMs. Using three different network-based buffering methods, the findings indicate significant variation among BEM values, however associations with physical activity outcomes were similar across each buffering technique. The study advances knowledge by presenting consistently assessed relationships between three different network buffer types and utilitarian travel, sedentary behavior, and leisure-oriented physical activity outcomes.

Influence of solvent on ion aggregation and transport in PY15TFSI ionic liquid-aprotic solvent mixtures.

Molecular dynamics (MD) simulations using a many-body polarizable APPLE&P force field have been performed on mixtures of the N-methyl-N-pentylpyrrolidinium bis(trifluoromethanesulfonyl)imide (PY15TFSI) ionic liquid (IL) with three molecular solvents: propylene carbonate (PC), dimethyl carbonate (DMC), and acetonitrile (AN). The MD simulations predict density, viscosity, and ionic conductivity values that agree well with the experimental results. In the solvent-rich regime, the ionic conductivity of the PY15TFSI-AN mixtures was found to be significantly higher than the conductivity of the corresponding -PC and -DMC mixtures, despite the similar viscosity values obtained from both the MD simulations and experiments for the -DMC and -AN mixtures. The significantly lower conductivity of the PY15TFSI-DMC mixtures, as compared to those for PY15TFSI-AN, in the solvent-rich regime was attributed to the more extensive ion aggregation observed for the -DMC mixtures. The PY15TFSI-DMC mixtures present an interesting case where the addition of the organic solvent to the IL results in an increase in the cation-anion correlations, in contrast to what is found for the mixtures with PC and AN, where ion motion became increasingly uncorrelated with addition of solvent. A combination of pfg-NMR and conductivity measurements confirmed the MD simulation predictions. Further insight into the molecular interactions and properties was also obtained using the MD simulations by examining the solvent distribution in the IL-solvent mixtures and the mixture excess properties.

Ionic liquids behave as dilute electrolyte solutions.

We combine direct surface force measurements with thermodynamic arguments to demonstrate that pure ionic liquids are expected to behave as dilute weak electrolyte solutions, with typical effective dissociated ion concentrations of less than 0.1% at room temperature. We performed equilibrium force-distance measurements across the common ionic liquid 1-butyl-3-methylimidazolium bis(trifluoromethanesulfonyl)imide ([C4mim][NTf2]) using a surface forces apparatus with in situ electrochemical control and quantitatively modeled these measurements using the van der Waals and electrostatic double-layer forces of the Derjaguin-Landau-Verwey-Overbeek theory with an additive repulsive steric (entropic) ion-surface binding force. Our results indicate that ionic liquids screen charged surfaces through the formation of both bound (Stern) and diffuse electric double layers, where the diffuse double layer is comprised of effectively dissociated ionic liquid ions. Additionally, we used the energetics of thermally dissociating ions in a dielectric medium to quantitatively predict the equilibrium for the effective dissociation reaction of [C4mim][NTf2] ions, in excellent agreement with the measured Debye length. Our results clearly demonstrate that, outside of the bound double layer, most of the ions in [C4mim][NTf2] are not effectively dissociated and thus do not contribute to electrostatic screening. We also provide a general, molecular-scale framework for designing ionic liquids with significantly increased dissociated charge densities via judiciously balancing ion pair interactions with bulk dielectric properties. Our results clear up several inconsistencies that have hampered scientific progress in this important area and guide the rational design of unique, high-free-ion density ionic liquids and ionic liquid blends.

Diffusion Coefficients from (13)C PGSE NMR Measurements-Fluorine-Free Ionic Liquids with the DCTA(-) Anion.

Pulsed-field gradient spin-echo (PGSE) NMR is a widely used method for the determination of molecular and ionic self-diffusion coefficients. The analysis has thus far been limited largely to (1)H, (7)Li, (19)F, and (31)P nuclei. This limitation handicaps the analysis of materials without these nuclei or for which these nuclei are insufficient for complete characterization. This is demonstrated with a class of ionic liquids (or ILs) based on the nonfluorinated anion 4,5-dicarbonitrile-1,2,3-triazole (DCTA(-)). It is demonstrated here that (13)C-PGSE NMR can be used to both verify the diffusion coefficients obtained from other nuclei, as well as characterize materials that lack commonly scrutinized nuclei - all without the need for specialized NMR methods.