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Unlocking Hidden Histories: Enhancing Information Accessibility Through Org Chart Metadata Structures
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Global organic and inorganic aerosol hygroscopicity and its effect on radiative forcing
The climate effects of atmospheric aerosol particles serving as cloud condensation nuclei (CCN) depend on chemical composition and hygroscopicity, which are highly variable on spatial and temporal scales. Here we present global CCN measurements, covering diverse environments from pristine to highly polluted conditions. We show that the effective aerosol hygroscopicity, κ, can be derived accurately from the fine aerosol mass fractions of organic particulate matter (ϵ org ) and inorganic ions (ϵ inorg ) through a linear combination, κ = ϵ org · κ org + ϵ inorg · κ inorg . In spite of the chemical complexity of organic matter, its hygroscopicity is well captured and represented by a global average value of κ org = 0.12 ± 0.02 with κinorg = 0.63 ± 0.01 as the corresponding value for inorganic ions. By showing that the sensitivity of global climate forcing to changes in κ org and κ inorg is small, we constrain a critically important aspect of global climate modelling.
Regional-Scale Modeling Parameterizations for Secondary Organic Aerosol Formation from Isoprene Epoxydiols: Experimentally Based Evaluation and Optimization
Isoprene is an abundant volatile organic compound emitted from broadleaf forests. Under low nitric oxide concentrations, isoprene is photochemically oxidized to form gas-phase isoprene epoxydiols (IEPOX). In the presence of acidified sulfate aerosols, IEPOX enhances the secondary organic aerosol (SOA) formation. Predictions of IEPOX-SOA in regional-scale models, e.g., the Community Multiscale Air Quality Model (CMAQ), are uncertain due to homogeneous aerosol assumptions, underpredictions of water uptake (hygroscopicity), and aerosol surface area. Here, we used experimental measurements of IEPOX-SOA tracers, 2-methyltetrols (2-MT) and 2-methyltetrol sulfates (2-MTS), formed at initial IEPOX-to-inorganic sulfate ratios ranging from 1–10.5, at ∼50% relative humidity to constrain key IEPOX-SOA parameters: phase separation, organic shell diffusivity (D org ), acidity, hygroscopic growth, mass accommodation, and kinetics. The base CMAQ parametrization overpredicted experimental IEPOX-SOA with an average normalized mean bias (NMB average ) of 1.63. CMAQ with phase separation underpredicted IEPOX-SOA (NMB average = −0.71). Using the phase-separated model, CMAQ model performance was optimized (NMB average = 0.077) with an increased D org = 2 × 10 –16 m 2 s –1 and increased rate constants (k 2-MT = 1 × 10 –3 M 2 s –1 , k 2-MTS = 8.83 × 10 –3 M 2 s –1 ). The optimized model explicitly accounted for hygroscopic growth by utilizing experimentally derived growth rates, improving aerosol surface area predictions. Our model highlights the importance of the aerosol mixing state (homogeneous versus phase-separated), aerosol size dynamics, and hygroscopic growth in modeling heterogeneous reactive uptake of IEPOX.
Tonian Carbonates Record Phosphate-Rich Shallow Seas
The early-middle Neoproterozoic is thought to have witnessed significant perturbations to marine P cycling, in turn facilitating the rise of eukaryote-dominated primary production. However, with few robust constraints on aqueous P concentrations, current understanding of Neoproterozoic P cycling is generally model-dependent. To provide new geochemical constraints, we combined microanalytical data sets with solid-state Nuclear Magnetic Resonance, synchrotron-based X-ray Absorption Near Edge Structure spectroscopy, and micro-X-ray Fluorescence imaging to characterize the speciation and distribution of P in Tonian shallow-water carbonate rocks. These data reflect shallow water phosphate concentrations 10–100× higher than modern systems, supporting the hypothesis that tectonically-driven influxes in P periodically initiated kinetically-controlled CaCO 3 deposition, in turn destabilizing marine carbonate chemistry, climate, and nutrient inventories. Alongside these observations, a new compilation and statistical analysis of mudstone geochemistry data indicates that, in parallel, C org and P burial increased across later Tonian continental margins until becoming decoupled at the close of the Tonian, implicating widespread N-limitation triggered by increasing atmospheric O 2 .
Residual stress of controlled atmosphere plasma spray blended metal deposits measured via in-situ substrate curvature method
The preliminary use of the in-situ curvature measurement technique for analyzing the planar stress evolution of controlled atmosphere plasma spray (CAPS) refractory metal deposits was performed with SNL-NM org. 1834’s CAPS system. A porous refractory metal exemplar of Ta-Nb was sprayed onto Ni-200, Ti-6Al-4V, and Al 7075-T6 substrates using a constant plasma torch parameter setting and deposition toolpath. Residual stresses of the deposits were found to be largely influenced by the substrate coefficient of thermal expansion and were calculated to be 49, 90, and -136 MPa for Ni 200, Ti-6Al-4V, and Al 7075-T6, respectively. The “Evolving stress” of the Ta-Nb deposits, which more accurately describes the mean intrinsic splat quenching stress of the spray material during deposition, was calculated to be 67, 92, and 129 MPa for Ni-200, Ti-6Al-4V, and Al 7075-T6, respectively. Notable difference in curvature measurement for the 1st coating pass for the Al 7075- T6 substrate was observed, with interface micrograph evidence suggesting potential softening and/or melting of the Al 7075-T6 substrate surface during deposition. Substrate temperature measurements prior to Ta-Nb deposition were used to calculate thermal energy absorbed from the hot gas plume by the different substrates and were found to correlate to the substrate’s thermal effusively. These calculated thermal energies were also found to be ~10 to 15% of the calculated energy output from the plasma torch’s nozzle exit for these experimental conditions.
RCSB Protein Data Bank: visualizing groups of experimentally determined PDB structures alongside computed structure models of proteins
Recent advances in Artificial Intelligence and Machine Learning (e.g., AlphaFold, RosettaFold, and ESMFold) enable prediction of three-dimensional (3D) protein structures from amino acid sequences alone at accuracies comparable to lower-resolution experimental methods. These tools have been employed to predict structures across entire proteomes and the results of large-scale metagenomic sequence studies, yielding an exponential increase in available biomolecular 3D structural information. Given the enormous volume of this newly computed biostructure data, there is an urgent need for robust tools to manage, search, cluster, and visualize large collections of structures. Equally important is the capability to efficiently summarize and visualize metadata, biological/biochemical annotations, and structural features, particularly when working with vast numbers of protein structures of both experimental origin from the Protein Data Bank (PDB) and computationally-predicted models. Moreover, researchers require advanced visualization techniques that support interactive exploration of multiple sequences and structural alignments. This paper introduces a suite of tools provided on the RCSB PDB research-focused web portal RCSB. org, tailor-made for efficient management, search, organization, and visualization of this burgeoning corpus of 3D macromolecular structure data.
Mortality of older construction and craft workers employed at Department of Energy (DOE) nuclear sites: Follow‐up through 2021
Background To determine if construction and trades workers formerly employed at US Department of Energy (DOE) nuclear weapons sites are at significant risk for occupational diseases, we studied the mortality experience of participants in the Building Trades National Medical Screening Program (BTMed). Methods The cohort included 26,922 participants enrolled between 1998 and 2021 and 8367 deaths. Standardized mortality ratios were calculated based on US death rates. Cox models compared construction workers (n = 22,747; 7487 deaths) to two nonconstruction subpopulations: administrative, scientific and security workers (n = 1894; 330 deaths), and all other nonconstruction workers (n = 2218; 550 deaths). Results Mortality was elevated for all causes, all cancers, cancers of the trachea, bronchus, lung, kidneys, and lymphatic and hematopoietic system, mesothelioma, chronic obstructive pulmonary disease (COPD), asbestosis, transportation injuries, and other injuries, particularly accidental poisonings. There were 167 deaths from coronavirus disease 2019 (COVID-19), which was lower than expected using US death rates. Overall cause-specific mortality was significantly higher among construction workers than for internal comparison groups. Conclusions Construction workers employed at DOE sites have a significantly increased risk for occupational illnesses. Apart from COVID-19 deaths, this update: (1) found that mortality among construction workers is significantly elevated compared to the US population and significantly higher than in the internal comparison populations, and (2) confirmed excess risk for these workers for first employment after 1990. Cancer mortality risks are similar to the cancers identified for DOE compensation from radiation exposures. In conclusion, the high lung cancer risk supports the value of early lung cancer detection. Continued medical surveillance is important.
Connecting suborganismal data to bioenergetic processes: killifish embryos exposed to a dioxin-like compound
A core challenge for ecological risk assessment is to integrate molecular responses into a chain of causality to organismal or population level outcomes. Bioenergetic theory may be a useful approach for integrating suborganismal responses to predict organismal level responses that influence population dynamics. In this work, we describe a novel application of Dynamic Energy Budget (DEB), theory in the context of a toxicity framework (Adverse Outcome Pathways, AOP) to make quantitative predictions of chemical exposures to individuals, starting from suborganismal data. We use early life stage exposure of Fundulus heteroclitus to dioxin-like chemicals (DLCs) and connect AOP Key Events (KEs) to DEB processes through “damage” that is produced at a rate proportional to the internal toxicant concentration. We use transcriptomic data of fish embryos exposed to DLCs to translate molecular indicators of damage into changes in DEB parameters (damage increases somatic maintenance costs) and use DEB models to predict sublethal and lethal effects of young fish. By changing a small subset of model parameters, we predict the evolved tolerance to DLCs in some wild F. heteroclitus populations, a data set not used in model parameterization. The differences in model parameters points to reduced sensitivity and altered damage repair dynamics as contributing to this evolved resistance. Our methodology has potential extrapolation to untested chemicals of ecological concern.
Detection and Mitigation of Radionuclides in the Environment: Toward a Clean Ecosystem
This research describes a straightforward approach to producing surface-engineered nanomaterials for the detection and mitigation of radionuclides generated in nuclear facilities. Here, a micelle forming surfactant ligand, namely cetyltrimethylammonium bromide (CTAB), was engineered on the surface of iron oxide nanoparticles and explored for the removal of radioactive materials, such as pertechnetate (TcO 4 – ), from aqueous environments. A series of analytical tools were employed to characterize the nanocomposite materials, such as SEM, EDS, UV-Vis spectroscopy, DLS, and PALS, and evaluated for their ability to capture a model analyte, perrhenate (ReO 4 – ) ions. The iron oxide magnetic nanoparticles retain their magnetic properties after surface functionalization and can be easily manipulated and collected with a magnet. Therefore, these nanocomposite materials can be used to remotely remediate environments by scavenging and collecting radionuclide species at the desired location.
Concepts of association between cancer and ionising radiation: accounting for specific biological mechanisms
The probability that an observed cancer was caused by radiation exposure is usually estimated using cancer rates and risk models from radioepidemiological cohorts and is called assigned share (AS). This definition implicitly assumes that an ongoing carcinogenic process is unaffected by the studied radiation exposure. However, there is strong evidence that radiation can also accelerate an existing clonal development towards cancer. In this work, we define different association measures that an observed cancer was newly induced, accelerated, or retarded. The measures were quantified exemplarily by Monte Carlo simulations that track the development of individual cells. Three biologically based two-stage clonal expansion (TSCE) models were applied. In the first model, radiation initiates cancer development, while in the other two, radiation has a promoting effect, i.e. radiation accelerates the clonal expansion of pre-cancerous cells. The parameters of the TSCE models were derived from breast cancer data from the atomic bomb survivors of Hiroshima and Nagasaki. For exposure at age 30, all three models resulted in similar estimates of AS at age 60. For the initiation model, estimates of association were nearly identical to AS. However, for the promotion models, the cancerous clonal development was frequently accelerated towards younger ages, resulting in associations substantially higher than AS. This work shows that the association between a given cancer and exposure in an affected person depends on the underlying biological mechanism and can be substantially larger than the AS derived from classic radioepidemiology.
Comparison and multi-model inference of excess risks models for radiation-related solid cancer
In assessments of detrimental health risks from exposures to ionising radiation, many forms of risk to dose–response models are available in the literature. The usual practice is to base risk assessment on one specific model and ignore model uncertainty. The analysis illustrated here considers model uncertainty for the outcome all solid cancer incidence, when modelled as a function of colon organ dose, using the most recent publicly available data from the Life Span Study on atomic bomb survivors of Japan. Seven recent publications reporting all solid cancer risk models currently deemed plausible by the scientific community have been included in a model averaging procedure so that the main conclusions do not depend on just one type of model. The models have been estimated with different baselines and presented for males and females at various attained ages and ages at exposure, to obtain specially computed model-averaged Excess Relative Risks (ERR) and Excess Absolute Risks (EAR). Monte Carlo simulated estimation of uncertainty on excess risks was accounted for by applying realisations including correlations in the risk model parameters. Three models were found to weight the model-averaged risks most strongly depending on the baseline and information criteria used for the weighting. Fitting all excess risk models with the same baseline, one model dominates for both information criteria considered in this study. Based on the analysis presented here, it is generally recommended to take model uncertainty into account in future risk analyses.
Mercury bioaccumulation and Hepatozoon spp. infections in two syntopic watersnakes in South Carolina
Mercury (Hg) is a ubiquitous environmental contaminant known to bioaccumulate in biota and biomagnify in food webs. Parasites occur in nearly every ecosystem and often interact in complex ways with other stressors that their hosts experience. Hepatozoon spp. are intraerythrocytic parasites common in snakes. The Florida green watersnake (Nerodia floridana) and the banded watersnake (Nerodia fasciata) occur syntopically in certain aquatic habitats in the Southeastern United States. The purpose of this study was to investigate relationships among total mercury (THg) concentrations, body size, species,habitat type and prevalence and parasitemia of Hepatozoon spp. infections in snakes. In the present study, we sampled N. floridana and N. fasciata from former nuclear cooling reservoirs and isolated wetlands of the Savannah River Site in South Carolina. We used snake tail clips to quantify THg and collected blood samples for hemoparasite counts. Our results indicate a significant, positive relationship between THg and snake body size in N. floridana and N. fasciata in both habitats. Average THg was significantly higher for N. fasciata compared to N. floridana in bays (0.22 ± 0.02 and 0.08 ± 0.006 mg/kg, respectively; p < 0.01), but not in reservoirs (0.17 ± 0.02 and 0.17 ± 0.03 mg/kg, respectively; p = 0.29). Sex did not appear to be related to THg concentration or Hepatozoon spp. infections in either species. In conclusion, we found no association between Hg and Hepatozoon spp. prevalence or parasitemia; however, our results suggest that species and habitat type play a role in susceptibility to Hepatozoon spp. infection.
Evaluating county-level lung cancer incidence from environmental radiation exposure, PM 2.5 , and other exposures with regression and machine learning models
Characterizing the interplay between exposures shaping the human exposome is vital for uncovering the etiology of complex diseases. For example, cancer risk is modified by a range of multifactorial external environmental exposures. Environmental, socioeconomic, and lifestyle factors all shape lung cancer risk. However, epidemiological studies of radon aimed at identifying populations at high risk for lung cancer often fail to consider multiple exposures simultaneously. For example, moderating factors, such as PM 2.5 , may affect the transport of radon progeny to lung tissue. This ecological analysis leveraged a population-level dataset from the National Cancer Institute’s Surveillance, Epidemiology, and End-Results data (2013–17) to simultaneously investigate the effect of multiple sources of low-dose radiation (gross γ activity and indoor radon) and PM 2.5 on lung cancer incidence rates in the USA. County-level factors (environmental, sociodemographic, lifestyle) were controlled for, and Poisson regression and random forest models were used to assess the association between radon exposure and lung and bronchus cancer incidence rates. Tree-based machine learning (ML) method perform better than traditional regression: Poisson regression: 6.29/7.13 (mean absolute percentage error, MAPE), 12.70/12.77 (root mean square error, RMSE); Poisson random forest regression: 1.22/1.16 (MAPE), 8.01/8.15 (RMSE). The effect of PM 2.5 increased with the concentration of environmental radon, thereby confirming findings from previous studies that investigated the possible synergistic effect of radon and PM 2.5 on health outcomes. In summary, the results demonstrated (1) a need to consider multiple environmental exposures when assessing radon exposure’s association with lung cancer risk, thereby highlighting (1) the importance of an exposomics framework and (2) that employing ML models may capture the complex interplay between environmental exposures and health, as in the case of indoor radon exposure and lung cancer incidence.
Trace elements and heavy metals in black vultures ( Coragyps atratus ) and turkey vultures ( Cathartes aura ) in the southeastern United States
Many vulture species worldwide are declining at alarming rates due to a variety of anthropogenic causes, including exposure to pollutants and pharmaceuticals through consumption of contaminated carrion. However, little is known about the extent to which vultures are exposed to various contaminants as well as toxicity thresholds for trace elements and heavy metals. Our objective was to quantify levels of trace elements and heavy metals within black vulture (Coragyps atratus) and turkey vulture (Cathartes aura) tissues to determine the extent to which populations in the southeastern United States are exposed to carrion that contains high levels of contaminants. We collected black vulture liver samples and examined differences in trace element and heavy metal concentrations between sexes and age classes (adult and juvenile). Further, we collected 81 blood and 42 feather samples from additional black and turkey vultures and compared differences between species and age classes. We found similar element concentrations between juvenile and adult black vultures with the exception of Cu, where levels 40 were higher in juveniles compared to adults. However, we did observe substantial differences in element concentrations between species for both blood and feather samples, with black vultures generally having higher concentrations of most elements. Our data revealed higher element levels in both species compared to toxicity thresholds found in other bird of prey species, such as blood and liver toxicity threshold suggestions for Pb poisoning in Falconiformes. Further, while average contaminant levels were generally low, extreme outliers were observed for some elements, including Pb, suggesting some individuals were exposed to high levels of potentially toxic elements. In conclusion, more research is needed to better understand contaminant exposure in black and turkey vultures across a broader geographic region, as well as elucidate toxicity thresholds and non-lethal impacts of contaminant exposure in these species.
Comparison of mercury (Hg) bioaccumulation with mono- and mixed Lemna minor and Spirodela polyrhiza cultures
Mercury (Hg) is a prevalent and harmful contaminant that persists in the environment. For phytoremediation, it is important to discover which plants can bioaccumulate meaningful amounts of Hg while also tolerating its toxicity. Additionally, increasing biodiversity could create a more resilient and self-sustaining system for remediation. This study explores whether mixed populations of Lemna minor and Spirodela polyrhiza can better bioaccumulate and tolerate Hg than monocultures. Mono- and mixed cultures of L. minor and S. polyrhiza were grown in mesocosms of 0.5 μg/L or 100 μg/L Hg ( HgCl2) spiked water for 96 h. Change in weight of duckweed was used to assess Hg tolerance. Diffusive gradients in thin-films (DGTs) were used as surrogate monitoring devices for bioavailable levels of Hg. For biomass growth, the mixed culture of the L. minor was greater than the monoculture at the high dose. The L. minor accumulated more Hg in the mixed culture at the low dose while the S. polyrhiza was higher in the mixed at the high dose. Hg speciation in water was modeled using Windermere Humic Aqueous Model 7 (WHAM7) to compare the bioavailable species indicated by the DGTs. Potentially due to the controlled conditions, the WHAM7 output of bioavailable Hg was almost 1:1 to that estimated by the DGTs, indicating good predictive capability of geochemical modeling and passive sampler DGT on metal bioavailability. Altogether, the mixed cultures statistically performed as well as or better than the monocultures when tolerating and bioaccumulating Hg. However, there needs to be further work to see if the significant differences translate into practical differences worth the extra resources to maintain multiple species.
Eddy covariance towers as sentinels of abnormal radioactive material releases
Ensuring accurate detection and attribution of abnormal releases of radioactive material is critical for protecting human health and safety. Most commonly, such detection is accomplished via active monitoring approaches involving the collection of physical samples. Further, this is labor intensive and limits the temporal and spatial resolution of any detected events to a relatively coarse level. As an alternative first step towards passive monitoring, we developed an approach using eddy flux tower data records to identify signals from a known abnormal release and quantify the extent to which that signal also occurs at other times in the data record. Through two case studies, one of which targeted the Fukushima nuclear disaster and the other targeting an abnormal release event at a radioisotope production facility in Fleurus, Belgium, we tested our approach and identified several potential heretofore unidentified abnormal events that were consistent with atmospheric circulation patterns and/or wind direction from known release sites. Because our approach is relatively simple and is resistant to systematic errors in the observational record, it has broad applicability beyond specific constituents and ecosystem types to identify a wide variety of limited-duration anomalies in flux tower data to ensure human health and industrial safety.
Potential reductions in fine particulate matter and premature mortality following implementation of air pollution controls on coal-fired power plants in India
Coal-fired power plants (CFPPs) account for > 70% of electricity generation in India, but < 5% of facilities have installed technologies for sulfur dioxide (SO 2 ) and nitrogen oxide (NO X ) removal. Emissions of these pollutants lead to the formation of fine particulate matter (PM 2.5 ) and an increased risk of premature mortality for exposed populations. Here, we use a nested version of the GEOS-Chem global chemical transport model (0.5° × 0.625° resolution) for India to estimate reductions in PM 2.5 concentrations that could have been achieved by implementing existing emission control technologies like flue-gas desulfurization (FGD) and/or selective catalytic reduction (SCR). We quantify the associated burden of disease using the integrated exposure response (IER) and global exposure mortality model (GEMM) functions and compare the costs of premature mortality to those for FGD installation. Model simulations for 2010 suggest installation of FGD would have reduced mean annual PM 2.5 concentrations across India by 8%, compared to 3% with SCR installation, and 11% with both FGD and SCR. A 7–28% reduction in PM 2.5 was simulated for local communities closest to CFPPs (same model grid cell), leading to up to 17% reduction in annual premature mortality. Overall, more than 0.21–0.48 million premature deaths would have been avoided over a 10-year period if FGD had been implemented on all CFPPs, compared to 0.09–0.21 million with SCR and 0.22–0.72 million with both FGD and SCR. Benefits associated with such actions are approximately $\$18.1$–$\$604$ billion USD per year, which is equivalent to ~ 0.44 to 10% of India’s GDP. These results suggest that monetary benefits from avoided premature mortality far outweigh the capital and operational costs of FGD and/or SCR installation of $\$19.5$ billion and/or $\$32.8$ billion per year, respectively. This information is essential because the high costs of installation and operation are often given as reasons for delaying installation and commissioning. Finally, we conclude that policy actions to control air pollution from CFPPs are economically justifiable.