An acute bout of aerobic exercise elicits a sustained post-exercise vasodilatation that is mediated by histamine H
1
and H
2
receptor activation. However, the upstream signaling pathway that leads to ...post-exercise histamine receptor activation is unknown. We tested the hypothesis that the potent antioxidant ascorbate would inhibit this histaminergic vasodilatation following exercise. Subjects performed 1 hr unilateral dynamic knee extension at 60% of peak power in three conditions: 1) control; 2) intravenous ascorbate infusion; and, 3) ascorbate infusion plus oral H
1
/H
2
histamine receptor blockade. Femoral artery blood flow (Doppler ultrasound) was measured before exercise and for 2 hr post-exercise. Femoral vascular conductance was calculated as flow/pressure. Post-exercise vascular conductance was greater for control condition (3.4 ± 0.1 ml min
−1
mmHg
−1
) compared with ascorbate (2.7 ± 0.1 ml min
−1
mmHg
−1
,
P
< 0.05) and ascorbate plus H
1
/H
2
blockade (2.8 ± 0.1 ml min
−1
mmHg
−1
,
P
< 0.05), which did not differ from one another (
P
= 0.9). Because ascorbate may catalyze the degradation of histamine
in vivo
, we conducted a follow-up study where subjects performed exercise in two conditions: 1) control and 2) intravenous N-acetylcysteine infusion. Post-exercise vascular conductance was similar for control (4.0 ± 0.1 ml min
−1
mmHg
−1
) and N-acetylcysteine conditions (4.0 ± 0.1 ml min
−1
mmHg
−1
;
P
= 0.8). Thus, the results in study 1 were due to the degradation of histamine in skeletal muscle by ascorbate, since the histaminergic vasodilatation was unaffected by N-acetylcysteine. Taken together, exercise-induced oxidative stress does not appear to contribute to sustained post-exercise vasodilatation.
The application of Bayesian methods is increasing in modern epidemiology. Although parametric Bayesian analysis has penetrated the population health sciences, flexible nonparametric Bayesian methods ...have received less attention. A goal in nonparametric Bayesian analysis is to estimate unknown functions (e.g., density or distribution functions) rather than scalar parameters (e.g., means or proportions). For instance, ROC curves are obtained from the distribution functions corresponding to continuous biomarker data taken from healthy and diseased populations. Standard parametric approaches to Bayesian analysis involve distributions with a small number of parameters, where the prior specification is relatively straight forward. In the nonparametric Bayesian case, the prior is placed on an infinite dimensional space of all distributions, which requires special methods. A popular approach to nonparametric Bayesian analysis that involves Polya tree prior distributions is described. We provide example code to illustrate how models that contain Polya tree priors can be fit using SAS software. The methods are used to evaluate the covariate-specific accuracy of the biomarker, soluble epidermal growth factor receptor, for discerning lung cancer cases from controls using a flexible ROC regression modeling framework. The application highlights the usefulness of flexible models over a standard parametric method for estimating ROC curves.
We develop a novel semiparametric modeling framework involving mixtures of Polya trees for screening data with the dual purpose of diagnosing infection or disease status and of assessing the accuracy ...of continuous diagnostic measures. In this framework, we obtain (i) predictive probabilities of 'disease' based on continuous diagnostic test outcomes in conjunction with other information, including relevant covariates and results from one or more independent binary diagnostic tests. An example would be the modeling of a serum enzyme-linked immunosorbent assay (ELISA) procedure for detecting antibodies to an infectious agent when used in conjunction with culture for antigen detection. Our second goal is to (ii) characterize measures of diagnostic performance of continuous tests by estimating receiver-operating characteristic curves and area under the curve, primarily when such extra information is available. When true disease status is unknown, parametric and nonparametric analyses require sufficient separation between the distributions of outcome values for the diseased and nondiseased populations. However, this overlap becomes less problematic when additional information in the form of either an informative 'prior' that is based on real (preferably data-based) scientific input, or when additional information, or both, are available. The additional information can be used to distinguish 'diseased' from 'nondiseased' individuals. We present an example using simulated data that illustrates this point. We also present an example involving data from an animal-health survey for Johne's disease, where the performance of a serum ELISA is evaluated using additional information obtained from fecal culture. Issues related to identifiability and partial identifiability are also discussed. PUBLICATION ABSTRACT
Research examining built environment (BE) characteristics and walking/cycling behaviors has been conducted primarily in high-income countries and conclusions cannot be applied directly to low- and ...middle-income countries. We evaluated perceived BE characteristics and walking/cycling behaviors across 355 urban communities in 21 low-, middle-, and high- income countries using individual data for 39,908 adults in the Prospective Urban and Rural Epidemiology study. The 1-week long-form International Physical Activity Questionnaire was used to measure walking/cycling behaviors. Perceived BE characteristics were measured using the Neighborhood Environment Walkability Scale. Mixed effects logistic regression models examined associations between BE measures and walking for transport (≥150 min/wk), walking for leisure (≥150 min/wk), and any cycling for transport, controlling for individual, household, and community factors. Land-use mix diversity, land-use mix access, and street connectivity were associated with higher odds of walking for transport. Land-use mix diversity, land-use mix access, safety from traffic and safety from crime were associated with higher odds of walking for leisure. Land-use mix diversity, land-use mix access, and aesthetics were associated with higher odds of cycling. Differences in associations were observed by country-income status. Our findings can help guide policy makers globally to implement BE design to encourage walking and cycling behaviors.
•Wide variation in the prevalence of walking/cycling behaviors across country development levels.•Specific built environment measures associated with increased odds of walking/cycling.•Different built environment characteristics support cycling and walking differently.•Many associations differed by country income status.
Urbanization may influence physical activity (PA) levels, although little evidence is available for low- and middle- income countries where urbanization is occurring fastest. We evaluated ...associations between urbanization and total PA, as well as work-, leisure-, home-, and transport-specific PA, for 138,206 adults living in 698 communities across 22 countries within the Prospective Urban and Rural Epidemiology (PURE) study. The 1-week long-form International PA Questionnaire was administered at baseline (2003-2015). We used satellite-derived population density and impervious surface area estimates to quantify baseline urbanization levels for study communities, as well as change measures for 5- and 10-years prior to PA surveys. We used generalized linear mixed effects models to examine associations between urbanization measures and PA levels, controlling for individual, household and community factors. Higher community baseline levels of population density (- 12.4% per IQR, 95% CI - 16.0, - 8.7) and impervious surface area (- 29.2% per IQR, 95% CI - 37.5, - 19.7), as well as the rate of change in 5-year population density (- 17.2% per IQR, 95% CI - 25.7, - 7.7), were associated with lower total PA levels. Important differences in the associations between urbanization and PA were observed between PA domains, country-income levels, urban/rural status, and sex. These findings provide new information on the complex associations between urbanization and PA.
Emerging evidence suggests that the tumor microenvironment plays a critical role in regulating cancer stem cells (CSCs) and tumor progression through both autocrine and paracrine signaling. Elevated ...production of bone morphogenetic proteins (BMPs) from human ovarian cancer cells and stroma has been shown to increase CSC proliferation and tumor growth. Here, we report that Lin28, a stem cell factor, binds to BMP4 mRNA in epithelial ovarian carcinoma cells, thereby promoting BMP4 expression at the post-transcriptional level. As co-expression of Lin28 and Oct4 (another stem cell factor) has been implicated in ovarian cancer CSCs, we also determined that high levels of Lin28 are associated with an unfavorable prognosis when co-expressed with high levels of Oct4. Together, these findings uncover a new level of regulation of BMP4 expression and imply a novel Lin28/Oct4/BMP4-mediated mechanism of regulating ovarian tumor cell growth, thus holding potential for the development of new strategies for the diagnosis and treatment of ovarian cancer.
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