Information Preserving Component Analysis: Data Projections for Flow Cytometry Analysis

Flow cytometry is often used to characterize the malignant cells in leukemia and lymphoma patients, traced to the level of the individual cell. Typically, flow cytometric data analysis is performed through a series of 2-dimensional projections onto the axes of the data set. Through the years, clinicians have determined combinations of different fluorescent markers which generate relatively known expression patterns for specific subtypes of leukemia and lymphoma -- cancers of the hematopoietic system. By only viewing a series of 2-dimensional projections, the high-dimensional nature of the data is rarely exploited. In this paper we present a means of determining a low-dimensional projection which maintains the high-dimensional relationships (i.e. information) between differing oncological data sets. By using machine learning techniques, we allow clinicians to visualize data in a low dimension defined by a linear combination of all of the available markers, rather than just 2 at a time. This provides an aid in diagnosing similar forms of cancer, as well as a means for variable selection in exploratory flow cytometric research. We refer to our method as Information Preserving Component Analysis (IPCA).Comment: 26 page

Valuing Children's Fatality Risk Reductions

The estimates used by U.S. Federal agencies and others to value reductions in fatality risks generally reflect adults’ willingness to trade income for changes in their own risks. Several studies have now been completed that address the value of risk reductions to children. We review these studies for quality and applicability based on selection and evaluation criteria derived from recent discussions of best practices. To limit the effects of between-study variability, we searched for studies that estimate values for both adults and children using a consistent approach. We find seven studies that meet our selection criteria. The studies suggest that the value for children exceeds the value for adults by a factor of 1.2 to 3.0, with a midpoint of 2.1. Studies that estimate the value of reductions in nonfatal risks lead to similar results. Although some studies suggest that the divergence between child and adult values may decrease as the child ages, more work is needed to determine the extent to which these multipliers vary across age groups

Valuing Children's Fatality Risk Reductions

The estimates used by U.S. Federal agencies and others to value reductions in fatality risks generally reflect adults’ willingness to trade income for changes in their own risks. Several studies have now been completed that address the value of risk reductions to children. We review these studies for quality and applicability based on selection and evaluation criteria derived from recent discussions of best practices. To limit the effects of between-study variability, we searched for studies that estimate values for both adults and children using a consistent approach. We find seven studies that meet our selection criteria. The studies suggest that the value for children exceeds the value for adults by a factor of 1.2 to 3.0, with a midpoint of 2.1. Studies that estimate the value of reductions in nonfatal risks lead to similar results. Although some studies suggest that the divergence between child and adult values may decrease as the child ages, more work is needed to determine the extent to which these multipliers vary across age groups

Evaluating the Sensitivity of Mortality Attributable to Pollution to Modeling Choices: A Case Study for Colorado

We evaluated the sensitivity of estimated PM2.5 and NO2 health impacts to varying key input parameters and assumptions including: 1) the spatial scale at which impacts are estimated, 2) using either a single concentration-response function (CRF) or using racial/ethnic group specific CRFs from the same epidemiologic study, 3) assigning exposure to residents based on home, instead of home and work locations. This analysis was carried out for the state of Colorado. We found that the spatial scale of the analysis influences the magnitude of NO2, but not PM2.5, attributable deaths. Using county-level predictions instead of 1 km2 predictions of NO2 resulted in a lower estimate of mortality attributable to NO2 by ~ 50% for all of Colorado for each year between 2000-2020. Using an all-population CRF instead of racial/ethnic group specific CRFs results in a higher estimate of annual mortality attributable to PM2.5 by a factor 1.3 for the white population and a lower estimate of mortality attributable to PM2.5 by factors of 0.4 and 0.8 for Black and Hispanic residents, respectively. Using racial/ethnic group specific CRFs did not result in a different estimation of NO2 attributable mortality for white residents, but led to lower estimates of mortality by a factor of ~ 0.5 for Black residents, and by a factor of 2.9 for to Hispanic residents. Using NO2 based on home instead of home and workplace locations results in a smaller estimate of annual mortality attributable to NO2 for all of Colorado by ~0.980 each year and 0.997 for PM2.5.Comment: 24 pages, 6 figures, 2 table

Estimates of the global burden of ambient PM2.5, ozone, and NO2 on asthma incidence and emergency room visits

Abstract Background: Asthma is the most prevalent chronic respiratory disease worldwide, affecting 358 million people in 2015. Ambient air pollution exacerbates asthma among populations around the world and may also contribute to new-onset asthma. Objectives: We aimed to estimate the number of asthma emergency room visits and new onset asthma cases globally attributable to fine particulate matter (PM2.5), ozone, and nitrogen dioxide (NO2) concentrations. Methods: We used epidemiological health impact functions combined with data describing population, baseline asthma incidence and prevalence, and pollutant concentrations. We constructed a new dataset of national and regional emergency room visit rates among people with asthma using published survey data. Results: We estimated that 9–23 million and 5–10 million annual asthma emergency room visits globally in 2015 could be attributable to ozone and PM2.5, respectively, representing 8–20% and 4–9% of the annual number of global visits, respectively. The range reflects the application of central risk estimates from different epidemiological meta-analyses. Anthropogenic emissions were responsible for ∼37% and 73% of ozone and PM2.5 impacts, respectively. Remaining impacts were attributable to naturally occurring ozone precursor emissions (e.g., from vegetation, lightning) and PM2.5 (e.g., dust, sea salt), though several of these sources are also influenced by humans. The largest impacts were estimated in China and India. Conclusions: These findings estimate the magnitude of the global asthma burden that could be avoided by reducing ambient air pollution. We also identified key uncertainties and data limitations to be addressed to enable refined estimation. https://doi.org/10.1289/EHP376

Large-scale patterns of turnover and basal area change in Andean forests

General patterns of forest dynamics and productivity in the Andes Mountains are poorly characterized. Here we present the first large-scale study of Andean forest dynamics using a set of 63 permanent forest plots assembled over the past two decades. In the North-Central Andes tree turnover (mortality and recruitment) and tree growth declined with increasing elevation and decreasing temperature. In addition, basal area increased in Lower Montane Moist Forests but did not change in Higher Montane Humid Forests. However, at higher elevations the lack of net basal area change and excess of mortality over recruitment suggests negative environmental impacts. In North-Western Argentina, forest dynamics appear to be influenced by land use history in addition to environmental variation. Taken together, our results indicate that combinations of abiotic and biotic factors that vary across elevation gradients are important determinants of tree turnover and productivity in the Andes. More extensive and longer-term monitoring and analyses of forest dynamics in permanent plots will be necessary to understand how demographic processes and woody biomass are responding to changing environmental conditions along elevation gradients through this century