Teacher workshops chip away at economic illiteracy

Workshops put on for teachers by the Atlanta and St. Louis Feds are having the desired results, a recent assessment shows. Teachers are learning about the economy and personal finance, and they are passing this information on to a student body that desperately needs it.Education - Economic aspects ; Economics - Study and teaching

Effects of flexible fiberoptic endoscopy on pharyngeal swallow physiology

OBJECTIVE: The purpose of this study was to determine if the presence of a flexible fiberoptic endoscope in the pharynx affects swallow physiology. STUDY DESIGN: This was a prospective cohort study. SUBJECTS AND METHODS: Fourteen individuals with normal swallow function, 23 to 83 years of age, completed a videofluoroscopic swallow study with and without a 3.5 mm flexible fiberoptic endoscope maintained in the high position, ie, below the velopharyngeal port and above the epiglottis. Each study was analyzed for three swallow duration measures, number of swallows necessary to clear the bolus, and penetration-aspiration scale scores. RESULTS: No significant (P \u3e 0.05) main effects for condition were found for swallow duration, penetration-aspiration scale scores and number of swallows to clear the bolus. CONCLUSION: The presence of a flexible fiberoptic endoscope in the pharynx during swallowing did not significantly affect pharyngeal swallow physiology in the patients studied, but we cannot exclude a false-negative conclusion because of low statistical power

Gaps in Data and Modeling Tools for Understanding Fire and Fire Effects in Tundra Ecosystems

As the ecosystem science community learns more about tundra ecosystems and disturbance in tundra, a review of base data sets and ecological field data for the region shows there are many gaps that need to be filled. In this paper we will review efforts to improve our knowledge of the occurrence and impacts of fire in the North American tundra region completed under a NASA Terrestrial Ecology grant. Our main source of information is remote sensing data from satellite sensors and ecological data from past and recent field data collections by our team, collaborators, and others. Past fire occurrence is not well known for this region compared with other North American biomes. In this presentation we review an effort to use a semi-automated detection algorithm to identify past fire occurrence using the Landsat TM/ETM+ archives, pointing out some of the still-unaddressed issues for a full understanding of fire regime for the region. For this task, fires in Landsat scenes were mapped using the Random Forest classifier (Breiman 2001) to automatically detect potential burn scars. Random Forests is an ensemble classifier that employs machine learning to build a large collection of decision trees that are grown from a random selection of user supplied training data. A pixel\u27s classification is then determined by which class receives the most \u27votes\u27 from each tree. We also review the use fire location records and existing modeling methods to quantify emissions from these fires. Based on existing maps of vegetation fuels, we used the approach developed for the Wildland Fire Emissions Information System (WFEIS; French et al. 2011) to estimate emissions across the tundra region. WFEIS employs the Consume model (http://www.fs.fed.us/pnw/fera/research/smoke/consume/index.shtml) to estimate emissions by applying empirically developed relationships between fuels, fire conditions (weather-based fire indexes), and emissions. Here again, we will review the gaps in data and modeling capability for accurate estimation of fire emissions in this region. Initial evaluation of Landsat for tundra fire characterization (Loboda et al. 2013) and successful use of the rich archive of Synthetic Aperture Radar imagery for many fire-disturbed sites in the region will be additional topics covered in this poster presentation. References: Breiman, L. 2001. Random forests. Machine Learning, 45:5-32. French, N.H.F., W.J. de Groot, L.K. Jenkins, B.. Rogers, et al. 2011. Model comparisons for estimating carbon emissions from North American wildland fire. J. Geophys. Res. 116:G00K05, doi:10.1029/2010JG001469. Loboda, T L, N H F French, C. Hight-Harf, L. Jenkins, M.E. Miller. 2013. Mapping fire extent and burn severity in Alaskan tussock tundra: An analysis of the spectral response of tundra vegetation to wildland fire. Remote Sens. Enviro. 134:194-209

Massively parallel variant characterization identifies NUDT15 alleles associated with thiopurine toxicity

As a prototype of genomics-guided precision medicine, individualized thiopurine dosing based on pharmacogenetics is a highly effective way to mitigate hematopoietic toxicity of this class of drugs. Recently, NUDT15 deficiency was identified as a genetic cause of thiopurine toxicity, and NUDT15-informed preemptive dose reduction was quickly adopted in clinical settings. To exhaustively identify pharmacogenetic variants in this gene, we developed massively parallel NUDT15 function assays to determine the variants' effect on protein abundance and thiopurine cytotoxicity. Of the 3,097 possible missense variants, we characterized the abundance of 2,922 variants and found 54 hotspot residues at which variants resulted in complete loss of protein stability. Analyzing 2,935 variants in the thiopurine cytotoxicity-based assay, we identified 17 additional residues where variants altered NUDT15 activity without affecting protein stability. We identified structural elements key to NUDT15 stability and/or catalytical activity with single amino acid resolution. Functional effects for NUDT15 variants accurately predicted toxicity risk alleles in patients treated with thiopurines with far superior sensitivity and specificity compared to bioinformatic prediction algorithms. In conclusion, our massively parallel variant function assays identified 1,152 deleterious NUDT15 variants, providing a comprehensive reference of variant function and vastly improving the ability to implement pharmacogenetics-guided thiopurine treatment individualization.This article is available to RD&E staff via NHS OpenAthens. Click on the Publisher URL, and log in with NHS OpenAthens if prompted.R01 CA096670/CA/NCI NIH HHS/United States R25 CA023944/CA/NCI NIH HHS/United States P30 CA021765/CA/NCI NIH HHS/United States U10 CA098543/CA/NCI NIH HHS/United States U10 CA180899/CA/NCI NIH HHS/United States R01 GM118578/GM/NIGMS NIH HHS/United States U10 CA180886/CA/NCI NIH HHS/United States P50 GM115279/GM/NIGMS NIH HHS/United States U10 CA098413/CA/NCI NIH HHS/United States U10 CA095861/CA/NCI NIH HHS/United Statespublished version, accepted version (6 month embargo)