Montana Department of Environmental Quality

Trait datasets play a crucial role in advancing ecological, biogeographical and evolutionary studies and in prioritizing global conservation efforts. Birds are the best-known major group of organisms and comprise excellent environmental indicators. With their diverse traits, birds offer valuable insights into the provisioning of critical ecological functions and how animals adapt to global change. BIRDBASE is a global avian trait dataset that provides an up-to-date compilation of ecological traits for all birds. With 78 traits from 11,589 bird species in 254 families, and data on 6%-16% more species than the previous avian trait datasets, BIRDBASE includes all the bird species recognized by the four major avian taxonomies. BIRDBASE is also the first avian trait dataset that covers all the species in AviList, the new unified global avian checklist. As the most comprehensive avian trait dataset, BIRDBASE will enable new meta-analyses in ornithology, conservation biology and macroecology, expand our ability to understand the origins and maintenance of biodiversity, help quantify avian responses to global change, and inform international conservation efforts.

(1) The beach areas of Galveston, Texas, USA are heavily used for recreational activities and often experience elevated fecal indicator bacteria levels, representing a potential threat to ecosystem services, human health, and tourism-based economies that rely on suitable water quality. (2) During the span of 15 months (March 2022–May 2023), water samples that exceeded the U.S. Environmental Protection Agency-accepted alternative Beach Action Value (BAV) for enterococci of 104 MPN/100 mL were analyzed via microbial source tracking (MST) through quantitative polymerase chain reaction (qPCR) assays. The Bacteroides HF183 and DogBact as well as the Catellicoccus LeeSeaGull markers were used to detect human, dog, and gull fecal sources, respectively. The qPCR MST data were then utilized in a quantitative microbial risk assessment (QMRA) to assess human health risks. Additionally, samples collected in July and August 2022 were sequenced for 16S rRNA and matched with fecal sources through the Bayesian SourceTracker2 program. (3) Overall, 26% of the 110 samples with enterococci exceedances were positive for at least one of the MST markers. Gull was revealed to be the primary source of identified fecal contamination through qPCR and SourceTracker2. Human contamination was detected at very low levels (<1%), whereas dog contamination was found to co-occur with human contamination through qPCR. QMRA identified Campylobacter from canine sources as being the primary driver for human health risks for contact recreation for both adults and children. (4) These MST results coupled with QMRA provide important insight into water quality in Galveston that can inform future water quality and beach management decisions that prioritize public health risks.

Per- and polyfluoroalkyl substances (PFAS) are a class of long-lasting chemicals with widespread use and environmental persistence that have been increasingly studied for their detrimental impacts to human and animal health. Several major PFAS species are linked to neurodevelopmental toxicity. For example, epidemiological studies have associated prenatal exposure to perfluorooctanoate (PFOA) and perfluorononanoate (PFNA) with autism risk. However, the neurodevelopmental toxicities of major PFAS species have not been systematically evaluated in an animal model, and the molecular mechanisms underlying these toxicities have remained elusive. Using a high-throughput zebrafish social behavioral model, we screened six major PFAS species currently under regulation by the Environmental Protection Agency (EPA), including PFOA, PFNA, perfluorooctane sulfonate (PFOS), perfluorohexanesulfonic acid (PFHxS), perfluorobutane sulfonate (PFBS), and hexafluoropropylene oxide dimer acid ammonium salt (GenX). We found that embryonic exposure to PFNA, PFOA, and PFOS induced social deficits in zebrafish, recapitulating one of the hallmark behavioral deficits in autistic individuals. To uncover protein targets of the six EPA-regulated PFAS, we screened a virtual library containing predicted binding pockets of over 80% of the 3D human proteome through reverse molecular docking. We found that folate receptor beta (FR-β, encoded by the gene FOLR2) interacts strongly with PFNA, PFOA, and PFOS but to a lesser degree with PFHxS, PFBS, and GenX, correlating positively with their in vivo toxicity. Embryonic co-exposure to folic acid rescued social deficits induced by PFAS. The folic acid pathway has been implicated in autism, indicating a novel molecular mechanism for PFAS in autism etiology.

Soil microbial communities, including biological soil crust microbiomes, play key roles in water, carbon and nitrogen cycling, biological weathering, and other nutrient releasing processes of desert ecosystems. However, our knowledge of microbial distribution patterns and ecological drivers is still poor, especially so for the Chihuahuan Desert. This project investigated the effects of trampling disturbance on surface soil microbiomes, explored community composition and structure, and related patterns to abiotic and biotic landscape characteristics within the Chihuahuan Desert biome. Composite soil samples were collected in disturbed and undisturbed areas of 15 long-term ecological research plots in the Jornada Basin, New Mexico. Microbial diversity of cross-domain microbial groups (total Bacteria, Cyanobacteria, Archaea, and Fungi) was obtained via DNA amplicon metabarcode sequencing. Sequence data were related to landscape characteristics including vegetation type, landforms, ecological site and state as well as soil properties including gravel content, soil texture, pH, and electrical conductivity. Filamentous Cyanobacteria dominated the photoautotrophic community while Proteobacteria and Actinobacteria dominated among the heterotrophic bacteria. Thaumarchaeota were the most abundant Archaea and drought adapted taxa in Dothideomycetes and Agaricomycetes were most abundant fungi in the soil surface microbiomes. Apart from richness within Archaea (p = 0.0124), disturbed samples did not differ from undisturbed samples with respect to alpha diversity and community composition (p ≥ 0.05), possibly due to a lack of frequent or impactful disturbance. Vegetation type and landform showed differences in richness of Bacteria, Archaea, and Cyanobacteria but not in Fungi. Richness lacked strong relationships with soil variables. Landscape features including parent material, vegetation type, landform type, and ecological sites and states, exhibited stronger influence on relative abundances and microbial community composition than on alpha diversity, especially for Cyanobacteria and Fungi. Soil texture, moisture, pH, electrical conductivity, lichen cover, and perennial plant biomass correlated strongly with microbial community gradients detected in NMDS ordinations. Our study provides first comprehensive insights into the relationships between landscape characteristics, associated soil properties, and cross-domain soil microbiomes in the Chihuahuan Desert. Our findings will inform land management and restoration efforts and aid in the understanding of processes such as desertification and state transitioning, which represent urgent ecological and economical challenges in drylands around the world.

Radiomics and machine learning applied to the isolated cartilaginous bone lesion on magnetic resonance imaging (MRI) is increasingly useful to distinguish malignant versus benign bone lesions, to determine whether repetitive imaging over time, to determine dynamic expansion, or immediate excisional biopsy are indicated.

Many experimental studies have demonstrated that titanium dioxide nanoparticles (TiO2 NPs) could induce adverse health effects in vivo and in vitro. But epidemiological evidence and biomarkers related to early health effects are still lacking. This study aimed to explore biomarkers in the urine samples of workers occupationally exposed to a relatively low concentration of TiO2 NPs. A cross-sectional study was conducted in Jinan, China, involving 132 employees of a TiO2 NP manufacturing plant, among which the exposed group and control group were 1 : 1 matched by confounding factors such as gender, age, BMI, smoking and drinking. Untargeted metabolomics was performed in urine samples using high performance liquid chromatography-mass spectrometry (HPLC-MS) technology. The differential metabolites between the TiO2 NP exposed group and the control group were analyzed and then screened for potential biomarkers using bioinformatics methods. Metabolomics found a total of 1760 differentially expressed metabolites in the TiO2 NP exposed group, of which 60 differential metabolites were simultaneously confirmed by one-dimensional and multi-dimensional statistical analysis. Among these 60 differential metabolites, the relative expression of 27 metabolites increased, and the remaining 33 decreased. Pathway enrichment analysis further found that the metabolic pathway of long chain acyl-coa dehydrogenase deficiency (Lcad) was significantly enriched. Ten differential metabolites were selected as potential biomarkers of occupational exposure to TiO2 NPs using machine learning methods, including dibenzyl ether, quassimarin, tryptophan, etc. The receiver operating characteristic curves (ROCs) of these potential biomarkers showed good sensitivity and specificity. These potential biomarkers also had biological basis for occupational exposure to TiO2 NPs. Therefore, urine metabolites represented by dibenzyl ether are considered as good biomarkers of early health effects for occupational exposure to TiO2 NPs.

ObjectiveHigh-risk opioid prescribing practices in workers’ compensation (WC) settings are associated with excess opioid-related morbidity, longer work disability and higher costs. This study characterises the burden of prescription opioid-related hospitalisations among injured workers.MethodsHospital discharge data for eight states (Arizona, Colorado, Michigan, New Jersey, New York, South Carolina, Utah and Washington) were obtained from the State Inpatient Databases, Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality. We calculated 5-year (2010–2014) average annual rates of prescription opioid overdose/adverse effect (AE) hospitalisations. Injured workers were identified using payer (WC) and external cause codes.ResultsState-level average annual prescription opioid overdose/AE hospitalisation rates ranged from 0.3 to 1.2 per 100 000 employed workers. Rates for workers aged ≥65 years old were two to six times the overall rates. Among those hospitalised with prescription opioid overdose/AEs, injured workers were more likely than other inpatients to have a low back disorder diagnosis, and less likely to have an opioid dependence/abuse or cancer diagnosis, or a fatal outcome. Averaged across states, WC was the primary expected payer for <1% of prescription opioid overdose/AE hospitalisations vs 6% of injury hospitalisations.ConclusionsPopulation-based estimates of prescription opioid morbidity are almost nonexistent for injured workers; this study begins to fill that gap. Rates for injured workers increased markedly with age but were low relative to inpatients overall. Research is needed to assess whether WC as payer adequately identifies work-related opioid morbidity for surveillance purposes, and to further quantify the burden of prescription opioid-related morbidity.

In recent years, the ultrasound-guided adductor canal block (US-ACB) has increasingly become a point of reference for postoperative knee analgesia, especially after total knee arthroplasty (TKA).[1][1] Pain following TKA is often severe and may compromise patients’ rehabilitation and functional