Meteorological data source comparison-a case study in geospatial modeling of potential environmental exposure to abandoned uranium mine sites in the Navajo Nation.

Meteorological (MET) data is a crucial input for environmental exposure models. While modeling exposure potential using geospatial technology is a common practice, existing studies infrequently evaluate the impact of input MET data on the level of uncertainty on output results. The objective of this study is to determine the effect of various MET data sources on the potential exposure susceptibility predictions. Three sources of wind data are compared: The North American Regional Reanalysis (NARR) database, meteorological aerodrome reports (METARs) from regional airports, and data from local MET weather stations. These data sources are used as inputs into a machine learning (ML) driven GIS Multi-Criteria Decision Analysis (GIS-MCDA) geospatial model to predict potential exposure to abandoned uranium mine sites in the Navajo Nation. Results indicate significant variations in results derived from different wind data sources. After validating the results from each source using the National Uranium Resource Evaluation (NURE) database in a geographically weighted regression (GWR), METARs data combined with the local MET weather station data showed the highest accuracy, with an average R2 of 0.74. We conclude that local direct measurement-based data (METARs and MET data) produce a more accurate prediction than the other sources evaluated in the study. This study has the potential to inform future data collection methods, leading to more accurate predictions and better-informed policy decisions surrounding environmental exposure susceptibility and risk assessment.

Environmental risk mapping of potential abandoned uranium mine contamination on the Navajo Nation, USA, using a GIS-based multi-criteria decision analysis approach.

The Navajo Nation (NN), a sovereign indigenous tribal nation in the Southwestern United States, is home to 523 abandoned uranium mines (AUMs). Previous health studies have articulated numerous human health hazards associated with AUMs and multiple environmental mechanisms/pathways (e.g., air, water, and soil) for contaminant transport. Despite this evidence, the limited modeling of AUM contamination that exists relies solely on proximity to mines and only considers single rather than combined pathways from which the contamination is a product. In order to better understand the spatial dynamics of contaminant exposure across the NN, we adopted the following established geospatial and computational methods to develop a more sophisticated environmental risk map illustrating the potential for AUM contamination: GIS-based multi-criteria decision analysis (GIS-MCDA), fuzzy logic, and analytic hierarchy process (AHP). Eight criteria layers were selected for the GIS-MCDA model: proximity to AUMs, roadway proximity, drainage proximity, topographic landforms, wind index, topographic wind exposure, vegetation index, and groundwater contamination. Model sensitivity was evaluated using the one-at-a-time method, and statistical validation analysis was conducted using two separate environmental datasets. The sensitivity analysis indicated consistency and reliability of the model. Model results were strongly associated with environmental uranium concentrations. The model classifies 20.2% of the NN as high potential for AUM contamination while 65.7% and 14.1% of the region are at medium and low risk, respectively. This study is entirely a novel application and a crucial first step toward informing future epidemiologic studies and ongoing remediation efforts to reduce human exposure to AUM waste.

Regulation of mammalian siderophore 2,5-DHBA in the innate immune response to infection.

Competition for iron influences host-pathogen interactions. Pathogens secrete small iron-binding moieties, siderophores, to acquire host iron. In response, the host secretes siderophore-binding proteins, such as lipocalin 24p3, which limit siderophore-mediated iron import into bacteria. Mammals produce 2,5-dihydroxy benzoic acid, a compound that resembles a bacterial siderophore. Our data suggest that bacteria use both mammalian and bacterial siderophores. In support of this idea, supplementation with mammalian siderophore enhances bacterial growth in vitro. In addition, mice lacking the mammalian siderophore resist E. coli infection. Finally, we show that the host responds to infection by suppressing siderophore synthesis while up-regulating lipocalin 24p3 expression via TLR signaling. Thus, reciprocal regulation of 24p3 and mammalian siderophore is a protective mechanism limiting microbial access to iron.

Endogenous siderophore 2,5-dihydroxybenzoic acid deficiency promotes anemia and splenic iron overload in mice.

Eukaryotes produce a siderophore-like molecule via a remarkably conserved biosynthetic pathway. 3-OH butyrate dehydrogenase (BDH2), a member of the short-chain dehydrogenase (SDR) family of reductases, catalyzes a rate-limiting step in the biogenesis of the mammalian siderophore 2,5-dihydroxybenzoic acid (2,5-DHBA). Depletion of the mammalian siderophore by inhibiting expression of bdh2 results in abnormal accumulation of intracellular iron and mitochondrial iron deficiency in cultured mammalian cells, as well as in yeast cells and zebrafish embryos We disrupted murine bdh2 by homologous recombination to analyze the effect of bdh2 deletion on erythropoiesis and iron metabolism. bdh2 null mice developed microcytic anemia and tissue iron overload, especially in the spleen. Exogenous supplementation with 2,5-DHBA alleviates splenic iron overload in bdh2 null mice. Additionally, bdh2 null mice exhibit reduced serum iron. Although BDH2 has been proposed to oxidize ketone bodies, we found that BDH2 deficiency did not alter ketone body metabolism in vivo. In sum, our findings demonstrate a key role for BDH2 in erythropoiesis.