99 research outputs found

    GIS Modeling of Air Toxics Releases from TRI-Reporting and Non-TRI-Reporting Facilities: Impacts for Environmental Justice

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    The Toxics Release Inventory (TRI) requires facilities with 10 or more full-time employees that process > 25,000 pounds in aggregate or use > 10,000 pounds of any one TRI chemical to report releases annually. However, little is known about releases from non-TRI-reporting facilities, nor has attention been given to the very localized equity impacts associated with air toxics releases. Using geographic information systems and industrial source complex dispersion modeling, we developed methods for characterizing air releases from TRI-reporting as well as non-TRI-reporting facilities at four levels of geographic resolution. We characterized the spatial distribution and concentration of air releases from one representative industry in Durham County, North Carolina (USA). Inclusive modeling of all facilities rather than modeling of TRI sites alone significantly alters the magnitude and spatial distribution of modeled air concentrations. Modeling exposure receptors at more refined levels of geographic resolution reveals localized, neighborhood-level exposure hot spots that are not apparent at coarser geographic scales. Multivariate analysis indicates that inclusive facility modeling at fine levels of geographic resolution reveals exposure disparities by income and race. These new methods significantly enhance the ability to model air toxics, perform equity analysis, and clarify conflicts in the literature regarding environmental justice findings. This work has substantial implications for how to structure TRI reporting requirements, as well as methods and types of analysis that will successfully elucidate the spatial distribution of exposure potentials across geographic, income, and racial lines

    Labeling poststorm coastal imagery for machine learning: measurement of interrater agreement

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    © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Goldstein, E. B., Buscombe, D., Lazarus, E. D., Mohanty, S. D., Rafique, S. N., Anarde, K. A., Ashton, A. D., Beuzen, T., Castagno, K. A., Cohn, N., Conlin, M. P., Ellenson, A., Gillen, M., Hovenga, P. A., Over, J.-S. R., Palermo, R., Ratliff, K. M., Reeves, I. R. B., Sanborn, L. H., Straub, J. A., Taylor, L. A., Wallace E. J., Warrick, J., Wernette, P., Williams, H. E. Labeling poststorm coastal imagery for machine learning: measurement of interrater agreement. Earth and Space Science, 8(9), (2021): e2021EA001896, https://doi.org/10.1029/2021EA001896.Classifying images using supervised machine learning (ML) relies on labeled training data—classes or text descriptions, for example, associated with each image. Data-driven models are only as good as the data used for training, and this points to the importance of high-quality labeled data for developing a ML model that has predictive skill. Labeling data is typically a time-consuming, manual process. Here, we investigate the process of labeling data, with a specific focus on coastal aerial imagery captured in the wake of hurricanes that affected the Atlantic and Gulf Coasts of the United States. The imagery data set is a rich observational record of storm impacts and coastal change, but the imagery requires labeling to render that information accessible. We created an online interface that served labelers a stream of images and a fixed set of questions. A total of 1,600 images were labeled by at least two or as many as seven coastal scientists. We used the resulting data set to investigate interrater agreement: the extent to which labelers labeled each image similarly. Interrater agreement scores, assessed with percent agreement and Krippendorff's alpha, are higher when the questions posed to labelers are relatively simple, when the labelers are provided with a user manual, and when images are smaller. Experiments in interrater agreement point toward the benefit of multiple labelers for understanding the uncertainty in labeling data for machine learning research.The authors gratefully acknowledge support from the U.S. Geological Survey (G20AC00403 to EBG and SDM), NSF (1953412 to EBG and SDM; 1939954 to EBG), Microsoft AI for Earth (to EBG and SDM), The Leverhulme Trust (RPG-2018-282 to EDL and EBG), and an Early Career Research Fellowship from the Gulf Research Program of the National Academies of Sciences, Engineering, and Medicine (to EBG). U.S. Geological Survey researchers (DB, J-SRO, JW, and PW) were supported by the U.S. Geological Survey Coastal and Marine Hazards and Resources Program as part of the response and recovery efforts under congressional appropriations through the Additional Supplemental Appropriations for Disaster Relief Act, 2019 (Public Law 116-20; 133 Stat. 871)

    Epidemiologic evidence for asthma and exposure to air toxics: linkages between occupational, indoor, and community air pollution research.

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    Outdoor ambient air pollutant exposures in communities are relevant to the acute exacerbation and possibly the onset of asthma. However, the complexity of pollutant mixtures and etiologic heterogeneity of asthma has made it difficult to identify causal components in those mixtures. Occupational exposures associated with asthma may yield clues to causal components in ambient air pollution because such exposures are often identifiable as single-chemical agents (e.g., metal compounds). However, translating occupational to community exposure-response relationships is limited. Of the air toxics found to cause occupational asthma, only formaldehyde has been frequently investigated in epidemiologic studies of allergic respiratory responses to indoor air, where general consistency can be shown despite lower ambient exposures. The specific volatile organic compounds (VOCs) identified in association with occupational asthma are generally not the same as those in studies showing respiratory effects of VOC mixtures on nonoccupational adult and pediatric asthma. In addition, experimental evidence indicates that airborne polycyclic aromatic hydrocarbon (PAH) exposures linked to diesel exhaust particles (DEPs) have proinflammatory effects on airways, but there is insufficient supporting evidence from the occupational literature of effects of DEPs on asthma or lung function. In contrast, nonoccupational epidemiologic studies have frequently shown associations between allergic responses or asthma with exposures to ambient air pollutant mixtures with PAH components, including black smoke, high home or school traffic density (particularly truck traffic), and environmental tobacco smoke. Other particle-phase and gaseous co-pollutants are likely causal in these associations as well. Epidemiologic research on the relationship of both asthma onset and exacerbation to air pollution is needed to disentangle effects of air toxics from monitored criteria air pollutants such as particle mass. Community studies should focus on air toxics expected to have adverse respiratory effects based on biological mechanisms, particularly irritant and immunological pathways to asthma onset and exacerbation

    Retrotransposons Are the Major Contributors to the Expansion of the \u3ci\u3eDrosophila ananassae\u3c/i\u3e Muller F Element

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    The discordance between genome size and the complexity of eukaryotes can partly be attributed to differences in repeat density. The Muller F element (∼5.2 Mb) is the smallest chromosome in Drosophila melanogaster, but it is substantially larger (\u3e18.7 Mb) in D. ananassae. To identify the major contributors to the expansion of the F element and to assess their impact, we improved the genome sequence and annotated the genes in a 1.4-Mb region of the D. ananassae F element, and a 1.7-Mb region from the D element for comparison. We find that transposons (particularly LTR and LINE retrotransposons) are major contributors to this expansion (78.6%), while Wolbachia sequences integrated into the D. ananassae genome are minor contributors (0.02%). Both D. melanogaster and D. ananassae F-element genes exhibit distinct characteristics compared to D-element genes (e.g., larger coding spans, larger introns, more coding exons, and lower codon bias), but these differences are exaggerated in D. ananassae. Compared to D. melanogaster, the codon bias observed in D. ananassae F-element genes can primarily be attributed to mutational biases instead of selection. The 5′ ends of F-element genes in both species are enriched in dimethylation of lysine 4 on histone 3 (H3K4me2), while the coding spans are enriched in H3K9me2. Despite differences in repeat density and gene characteristics, D. ananassae F-element genes show a similar range of expression levels compared to genes in euchromatic domains. This study improves our understanding of how transposons can affect genome size and how genes can function within highly repetitive domains

    Functional Roles of the N- and C-Terminal Regions of the Human Mitochondrial Single-Stranded DNA-Binding Protein

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    Biochemical studies of the mitochondrial DNA (mtDNA) replisome demonstrate that the mtDNA polymerase and the mtDNA helicase are stimulated by the mitochondrial single-stranded DNA-binding protein (mtSSB). Unlike Escherichia coli SSB, bacteriophage T7 gp2.5 and bacteriophage T4 gp32, mtSSBs lack a long, negatively charged C-terminal tail. Furthermore, additional residues at the N-terminus (notwithstanding the mitochondrial presequence) are present in the sequence of species across the animal kingdom. We sought to analyze the functional importance of the N- and C-terminal regions of the human mtSSB in the context of mtDNA replication. We produced the mature wild-type human mtSSB and three terminal deletion variants, and examined their physical and biochemical properties. We demonstrate that the recombinant proteins adopt a tetrameric form, and bind single-stranded DNA with similar affinities. They also stimulate similarly the DNA unwinding activity of the human mtDNA helicase (up to 8-fold). Notably, we find that unlike the high level of stimulation that we observed previously in the Drosophila system, stimulation of DNA synthesis catalyzed by human mtDNA polymerase is only moderate, and occurs over a narrow range of salt concentrations. Interestingly, each of the deletion variants of human mtSSB stimulates DNA synthesis at a higher level than the wild-type protein, indicating that the termini modulate negatively functional interactions with the mitochondrial replicase. We discuss our findings in the context of species-specific components of the mtDNA replisome, and in comparison with various prokaryotic DNA replication machineries

    Human Flt3L Generates Dendritic Cells from Canine Peripheral Blood Precursors: Implications for a Dog Glioma Clinical Trial

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    Glioblastoma multiforme (GBM) is the most common primary brain tumor in adults and carries a dismal prognosis. We have developed a conditional cytotoxic/immunotherapeutic approach using adenoviral vectors (Ads) encoding the immunostimulatory cytokine, human soluble fms-like tyrosine kinase 3 ligand (hsFlt3L) and the conditional cytotoxic molecule, i.e., Herpes Simplex Type 1- thymide kinase (TK). This therapy triggers an anti-tumor immune response that leads to tumor regression and anti-tumor immunological memory in intracranial rodent cancer models. We aim to test the efficacy of this immunotherapy in dogs bearing spontaneous GBM. In view of the controversy regarding the effect of human cytokines on dog immune cells, and considering that the efficacy of this treatment depends on hsFlt3L-stimulated dendritic cells (DCs), in the present work we tested the ability of Ad-encoded hsFlt3L to generate DCs from dog peripheral blood and compared its effects with canine IL-4 and GM-CSF.Our results demonstrate that hsFlT3L expressed form an Ad vector, generated DCs from peripheral blood cultures with very similar morphological and phenotypic characteristics to canine IL-4 and GM-CSF-cultured DCs. These include phagocytic activity and expression of CD11c, MHCII, CD80 and CD14. Maturation of DCs cultured under both conditions resulted in increased secretion of IL-6, TNF-alpha and IFN-gamma. Importantly, hsFlt3L-derived antigen presenting cells showed allostimulatory potential highlighting their ability to present antigen to T cells and elicit their proliferation.These results demonstrate that hsFlt3L induces the proliferation of canine DCs and support its use in upcoming clinical trials for canine GBM. Our data further support the translation of hsFlt3L to be used for dendritic cells' vaccination and gene therapeutic approaches from rodent models to canine patients and its future implementation in human clinical trials