Inflammatory Bowel Disease Prevalence: Surveillance data from the U.S. National Health and Nutrition Examination Survey.

Determining the overall US prevalence of Inflammatory Bowel Disease (IBD) is essential to national level prevention programs and population risk assessment; however currently US IBD prevalence remains uncertain. We used US National Health and Nutrition Examination Survey (NHANES) data to estimate the population-based prevalence of a self-reported history of medically diagnosed IBD, comparing to prior reports. Lifetime IBD prevalence for adults aged 20 + years was estimated in the independently conducted NHANES II (1976-80) and NHANES 2009-10 surveys. Participants were considered to have IBD if they reported being told by a physician they had Crohn's Disease (CD) or ulcerative colitis (UC). Clinically relevant NHANES data were analyzed to assess the self-reports. Survey design variables and sample weights were used to account for the complex survey design. The NHANES 2009-10 US IBD diagnosed prevalence was 1.2% (95% CI 0.8,1.6%), or an estimated 2.3 million persons. UC prevalence was 1.0% (95% CI 0.5,1.4%; 1.9 million persons) and CD prevalence was 0.3% (95% CI 0.1,0.4%; 578,000 persons). NHANES II UC prevalence was 1.0 (95% CI 0.8,1.2%), similar to 2009-10. UC prevalence was higher for ages ≥ 50 years in both surveys. NHANES 2009-10 data showed no UC sex differences, but women had higher UC prevalence in NHANES II. Remarkably, UC prevalence was similar between the two NHANES surveys fielded 30 years apart. The NHANES data are consistent with IBD prevalences reported in previous US nationally representative surveys, indicating that diagnosed IBD may affect approximately 1% of the US adult population.

Evapotranspiration and water yield of a pine-broadleaf forest are not altered by long-term atmospheric [CO2 ] enrichment under native or enhanced soil fertility.

Changes in evapotranspiration (ET) from terrestrial ecosystems affect their water yield (WY), with considerable ecological and economic consequences. Increases in surface runoff observed over the past century have been attributed to increasing atmospheric CO2 concentrations resulting in reduced ET by terrestrial ecosystems. Here, we evaluate the water balance of a Pinus taeda (L.) forest with a broadleaf component that was exposed to atmospheric [CO2 ] enrichment (ECO2 ; +200 ppm) for over 17 years and fertilization for 6 years, monitored with hundreds of environmental and sap flux sensors on a half-hourly basis. These measurements were synthesized using a one-dimensional Richard's equation model to evaluate treatment differences in transpiration (T), evaporation (E), ET, and WY. We found that ECO2 did not create significant differences in stand T, ET, or WY under either native or enhanced soil fertility, despite a 20% and 13% increase in leaf area index, respectively. While T, ET, and WY responded to fertilization, this response was weak (<3% of mean annual precipitation). Likewise, while E responded to ECO2 in the first 7 years of the study, this effect was of negligible magnitude (<1% mean annual precipitation). Given the global range of conifers similar to P. taeda, our results imply that recent observations of increased global streamflow cannot be attributed to decreases in ET across all ecosystems, demonstrating a great need for model-data synthesis activities to incorporate our current understanding of terrestrial vegetation in global water cycle models.

Computational discovery of pathway-level genetic vulnerabilities in non-small-cell lung cancer.

MOTIVATION: Novel approaches are needed for discovery of targeted therapies for non-small-cell lung cancer (NSCLC) that are specific to certain patients. Whole genome RNAi screening of lung cancer cell lines provides an ideal source for determining candidate drug targets. RESULTS: Unsupervised learning algorithms uncovered patterns of differential vulnerability across lung cancer cell lines to loss of functionally related genes. Such genetic vulnerabilities represent candidate targets for therapy and are found to be involved in splicing, translation and protein folding. In particular, many NSCLC cell lines were especially sensitive to the loss of components of the LSm2-8 protein complex or the CCT/TRiC chaperonin. Different vulnerabilities were also found for different cell line subgroups. Furthermore, the predicted vulnerability of a single adenocarcinoma cell line to loss of the Wnt pathway was experimentally validated with screening of small-molecule Wnt inhibitors against an extensive cell line panel. AVAILABILITY AND IMPLEMENTATION: The clustering algorithm is implemented in Python and is freely available at https://bitbucket.org/youngjh/nsclc_paper CONTACT: marcotte@icmb.utexas.edu or jon.young@utexas.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Forest water use and water use efficiency at elevated CO2 : a model-data intercomparison at two contrasting temperate forest FACE sites.

Predicted responses of transpiration to elevated atmospheric CO2 concentration (eCO2 ) are highly variable amongst process-based models. To better understand and constrain this variability amongst models, we conducted an intercomparison of 11 ecosystem models applied to data from two forest free-air CO2 enrichment (FACE) experiments at Duke University and Oak Ridge National Laboratory. We analysed model structures to identify the key underlying assumptions causing differences in model predictions of transpiration and canopy water use efficiency. We then compared the models against data to identify model assumptions that are incorrect or are large sources of uncertainty. We found that model-to-model and model-to-observations differences resulted from four key sets of assumptions, namely (i) the nature of the stomatal response to elevated CO2 (coupling between photosynthesis and stomata was supported by the data); (ii) the roles of the leaf and atmospheric boundary layer (models which assumed multiple conductance terms in series predicted more decoupled fluxes than observed at the broadleaf site); (iii) the treatment of canopy interception (large intermodel variability, 2-15%); and (iv) the impact of soil moisture stress (process uncertainty in how models limit carbon and water fluxes during moisture stress). Overall, model predictions of the CO2 effect on WUE were reasonable (intermodel µ = approximately 28% ± 10%) compared to the observations (µ = approximately 30% ± 13%) at the well-coupled coniferous site (Duke), but poor (intermodel µ = approximately 24% ± 6%; observations µ = approximately 38% ± 7%) at the broadleaf site (Oak Ridge). The study yields a framework for analysing and interpreting model predictions of transpiration responses to eCO2 , and highlights key improvements to these types of models.