The intercellular communications mediating radiation-induced bystander effects and their relevance to environmental, occupational, and therapeutic exposures
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Silicone elastomers have advantageous physical properties and are widely used in various applications. Additive manufacturing (AM) of silicones provides additional utility by enabling tunable mechanical and functional properties. However, the performance of these elastomers deteriorates over time with exposure to environmental stressors. Organic solvents and volatile organic compounds (VOCs) are stressors that can cause dimensional changes to silicones with exposure and impact the overall function. Yet, the effects of such exposure on mechanical performance, including load response (LR), are not well understood. Here, in this study, we investigated the impact of a nonpolar solvent, toluene, on AM silicone material properties and compressive load. We observed that AM silicones rapidly absorbed toluene and swelled, leading to an increase in relative LR. Toluene concentration and compression did not affect uptake or swelling rates. In contrast, outgassing rates were slower for compressed coupons compared to uncompressed specimens, attributed to geometric constraints and polymer network changes impacting toluene diffusion outward. Compression also pinned the AM silicones at an enlarged state, significantly reducing relative LR after outgassing. Depending on toluene concentrations and compression, AM silicones can remain robust against toluene exposure and recover their initial printing geometry and mechanical performance after toluene outgassing and polymer relaxation.
The environments where galaxies reside crucially shape their star formation histories. We investigate a large sample of 1626 cluster galaxies located within 105 galaxy clusters spanning a large range in redshift (0.26 < z < 1.13). The galaxy clusters are massive (M 500 ≳ 2 × 10 14 M ⊙ ) and uniformly selected from the SPT and ACT Sunyaev–Zel'dovich surveys. With spectra in hand for thousands of cluster members, we use the galaxies' position in projected phase space as a proxy for their infall times, which provides a more robust measurement of environment than quantities such as projected clustercentric radius. We find clear evidence for a gradual age increase of the galaxy's mean stellar populations (~0.71 ± 0.4 Gyr based on a 4000 Å break, D n 4000) with the time spent in the cluster environment. This environmental quenching effect is found regardless of galaxy luminosity (faint or bright) and redshift (low or high-z), although the exact stellar age of galaxies depends on both parameters at fixed environmental effects. Such a systematic increase of D n 4000 with infall proxy would suggest that galaxies that were accreted into hosts earlier were quenched earlier due to longer exposure to environmental effects such as ram pressure stripping and starvation. Compared to the typical dynamical timescales of 1–3 Gyr of cluster galaxies, the relatively small age increase (~0.71 ± 0.4 Gyr) found in our sample galaxies seems to suggest that a slow environmental process such as starvation is the dominant quenching pathway. Our results provide new insights into environmental quenching effects spanning a large range in cosmic time (~5.2 Gyr, z = 0.26–1.13) and demonstrate the power of using a kinematically derived infall time proxy.
An integrated modeling approach has been developed to better understand the relative impacts of different expiratory and environmental factors on airborne pathogen transport and transmission, motivated by the recent COVID-19 pandemic. Computational fluid dynamics (CFD) modeling was used to simulate spatial-temporal aerosol concentrations and quantified risks of exposure as a function of separation distance, exposure duration, environmental conditions (e.g., airflow/ventilation), and face coverings. The CFD results were combined with infectivity models to determine probability of infection, which is a function of the spatial-temporal aerosol concentrations, viral load, infectivity rate, viral viability, lung-deposition probability, and inhalation rate. Uncertainty distributions were determined for these parameters from the literature. Probabilistic analyses were performed to determine cumulative distributions of infection probabilities and to determine the most important parameters impacting transmission. This modeling approach has relevance to both pathogen and pollutant dispersion from expelled aerosol plumes.
Abstract One of the challenges associated with understanding environmental impacts on cancer risk and outcomes is estimating potential exposures of individuals diagnosed with cancer to adverse environmental conditions over the life course. Historically, this has been partly due to the lack of reliable measures of cancer patients’ potential environmental exposures before a cancer diagnosis. The emerging sources of cancer-related spatiotemporal environmental data and residential history information, coupled with novel technologies for data extraction and linkage, present an opportunity to integrate these data into the existing cancer surveillance data infrastructure, thereby facilitating more comprehensive assessment of cancer risk and outcomes. In this paper, we performed a landscape analysis of the available environmental data sources that could be linked to historical residential address information of cancer patients’ records collected by the National Cancer Institute’s Surveillance, Epidemiology, and End Results Program. The objective is to enable researchers to use these data to assess potential exposures at the time of cancer initiation through the time of diagnosis and even after diagnosis. The paper addresses the challenges associated with data collection and completeness at various spatial and temporal scales, as well as opportunities and directions for future research.
Background Selenium (Se) is an essential trace element for the human body. Serum Se and urinary Se are also biomarkers to assess Se exposure status. However, studies focusing on the association between urinary Se and the risk of gestational diabetes mellitus (GDM) are rare. Objective To investigate the association between urinary Se and the risk of GDM. Methods A nested case–control study based on a prospective birth cohort in Wuhan, China, which focuses on the effects of prenatal environmental factors exposure on pregnant women and children’s health was conducted. Two hundred and twenty-six cases and 452 controls were included. Maternal urine samples were collected before GDM diagnosis, and the urinary Se levels were determined. We assessed the association of urinary Se with GDM by conditional logistic regression with maternal urinary Se level as a categorical variable, and estimated the association between Se and glucose levels by multiple linear regression. The potential modifier roles of maternal age and fetal sex have also been assessed. Results Lower urinary level of Se was significantly associated with a higher risk of GDM (OR = 2.35 for the tertile 1, 95% CI:1.36-4.06; adjusted OR = 1.79 for the tertile 2, 95%CI:1.09-2.95; p for trend = 0.01). Fetal sex had an interaction with Se in the association with GDM. The association was more pronounced among pregnant women with female fetuses than with male fetuses. Discussion Our study suggested a significant negative association between urinary Se and the risk of GDM, and this association may vary depending on the fetal sex.
Radiation dosimetry is central to virtually all radiation safety applications, optimization, and research. It relates to various individuals and population groups and to miscellaneous exposure situations—including planned, existing, and emergency situations. The International Commission on Radiological Protection (ICRP) has developed a new computational framework for internal dose estimations. Important components are more detailed and improved anatomical models and more realistic biokinetic models than before. The ICRP is currently producing new organ dose and effective dose coefficients for occupational intakes of radionuclides (OIR) and environmental intakes of radionuclides (EIR), which supersede the earlier dose coefficients in Publication 68 and the Publication 72 series, respectively. However, the ICRP only publishes dose coefficients for a single acute intake of a radionuclide and for an integration period of 50 years for intake by adults and to age 70 years for intakes by pre-adults. The new software, IDAC-Bio, performs committed absorbed dose and effective dose calculations for a selectable intake scenario, e.g., for a continuous intake or an intake during x hours per day and y days per week, and for any selected integration time. The software uses the primary data and models of the ICRP biokinetic models and numerically solves the biokinetic model and calculates the absorbed doses to organs and tissues in the ICRP reference human phantoms. The software calculates absorbed dose using the nuclear decay data in ICRP publication 107. IDAC-Bio is a further development and an important addition to the internal dosimetry program IDAC-Dose2.1. Here, the results generated by the software were validated against published ICRP dose coefficients. The potential of the software is illustrated by dose calculations for a nuclear power plant worker who had been exposed to varying levels of 60 Co and who had undergone repeated whole-body measurements, and for a hypothetical member of the public subject to future releases of 148 Gd from neutron spallation in tungsten at the European Spallation Source.
Mercury (Hg) is a major global pollutant arising from both natural and anthropogenic sources. Its widespread use in medicinal and industrial applications makes it a common chemical exposure and environmental pollutant. It can exist in several forms which include: Metallic mercury (Hg{sup 0}), mercurous (Hg{sub 2}{sup 2+}), mercuric salts (Hg{sup 2+}), and organic mercury (e.g. CH{sub 3}Hg{sup +}), with the latter being the most toxic of all the species. Due to mercury's high toxicity, new approaches towards its detection has received significant attention in the scientific community. Mercury exposure at the Savannah River Site (SRS) has been a recent concern especially with increasing amounts of organic mercury in the saltstone. It originates mainly from its use as an acidic dissolution catalyst of aluminum cladding from target fuels within the uranium and plutonium processing operations [1]. It is present to an amount of about 60 metric tons in the high-level waste (HLW) tanks. Organic Mercury species have been found in low activity waste (LAW) at the site that eventually ends up in the saltstone. Therefore, there is a need for: i) Converting organic mercury to other less toxic forms and ii) Complexation and removal of Hg prior of disposal of LAW in saltstone. Various methods have been developed for selective sensing of mercury in the presence of other toxic metals. These methods include using ligands that can form organo-soluble metal complexes with different optical and spectroscopic properties that can be used for toxic metal sensing. In 2005, our group pioneered an ion-exchange extraction method, in which o-phenylenediamine-derived disulfonamides were used to complex and selectively extract and sense Pb{sup 2+} from aqueous solutions into an organic phase [2,3]. Herein, a disulfonamide and a bis-dansylamide have been shown to extract, complex and sense Hg(II). Ligand 1: The crystal structure of the disulfonamide-Hg complex confirms the complexation of Hg(II) with the ligand. Complexation was corroborated by the {sup 1}H-NMR spectra obtained after contacting solutions of various concentrations of Hg{sup 2+} with 2 mM ligand in chloroform. Distinct resonances are observed at Hg/L ratio of 0.5 that are also observed for the isolated 1:2 complex. In the presence of excess mercury, new resonances, as well as the movement of Et{sub 3}N resonances indicate the formation of a different Hg-sulfonamide-triethylamine complex, presumably having 1:1 Hg:L stoichiometry. The electronic spectra of aqueous phases after extraction show that there was no free ligand absorption at 0.5 eq of Hg, indicating a complete complexation. Complexation was also confirmed by the UV-visible titrations with Hg{sup 2+} at constant ligand concentration. pH-dependent extraction carried out shows that extraction of Hg(II) by ligand 1 was over 90% for most alkaline pHs. Ligand 2: The crystal structure of the Ligand 2 complex formed with Hg(OAc){sub 2} shows a remarkable coordination pattern with 4:2 metal:ligand stoichiometry. The fluorescent bis-dansyl disulfonamide derivative was found to complex and sense HgCl{sub 2} and Hg(OAc){sub 2} by demonstrating fluorescence quenching upon Hg(II) addition in comparison with other metals (Zn(II), Cd(II), Pb(II)). No were observed for Cu(II), Ag(I) and Co(II). We have shown the complexation of Hg(II) by a disulfonamide and a bis-dansyl disulfonamide ligand using several spectroscopic methods. Ligand 1 was able to extract mercury into chloroform and form a complex in the presence of excess mercury by synergistic complexation with triethylamine acting as a co-ligand. X-ray and NMR both confirm a 1:2 HgL{sub 2} stoichiometry. Ligand 2 can be used for sensing of Hg(II) as fluorescence quenching was observed after addition of Hg(II)
Solid amine sorbents have shown promise in the removal of ultradilute CO 2 from the atmosphere. Despite being a promising candidate material type for this application, these sorbents are prone to degradation during long-term exposure to environmental components such as CO 2 , O 2 , and H 2 O, with amine oxidation being a particularly challenging problem. In this study, we investigate the potency of different radical scavengers and additives in mitigating the degradation of a model poly- (ethylenimine) (PEI)/Al 2 O 3 sorbent under direct air capture (DAC)-relevant conditions. The results reveal that a 4,4′-bis(α,α- dimethylbenzyl)diphenylamine (BDDPA)-incorporated PEI/Al 2 O 3 sorbent showed the most resistance toward oxidative degradation at varying exposure times and BDDPA loadings under CO 2 -free air (21% O 2 /balance N 2 ) at 120 °C. Interestingly, under humid (∼43% relative humidity (RH) at 26 °C) and dry 0.04% CO 2 -air, the BDDPA/PEI/Al 2 O 3 sorbent showed enhanced sorbent stability both at 70 and 120 °C after 4.5 h of exposure. Under humid CO 2 -free air, at 120 °C, the antioxidant performance slightly declined (in comparison to the dry CO 2 -free air condition) but displayed a much higher stability than the pristine sorbent. Overall, the ability of BDDPA to inhibit sorbent degradation under dry and humid, CO 2 -free and CO 2 -containing (0.04%) air at intermediate (70 °C) and elevated (120 °C) temperatures is promising in prolonging sorbent stability and underscores the importance of performing accelerated oxidation studies in the presence of all species that are expected to be present in DAC processes to identify suitable stabilization treatments for sorbent materials.
Plastics in all shapes and sizes have become widespread across ecosystems due to intense anthropogenic use. As such, they can interact with other contaminants that accumulate in the terrestrial environment, such as pharmaceuticals, metals or nanomaterials (NMs). These interactions can potentiate combined toxic effects in the exposed soil organisms, with hazardous long-term consequences to the full ecosystem. In the present study, a terrestrial model species, Enchytraeus crypticus (oligochaeta), was exposed through contaminated soil with nanopolystyrene (representative of nanoplastics (NPls)), alone and in combination with diphenhydramine (DPH, representative of pharmaceuticals), silver nitrate (AgNO3, representative of metals) and vanadium nanoparticles (VNPs, representative of NMs). AgNO3 and VNPs decreased E. crypticus reproduction at 50 mg/kg, regardless of the presence of NPls. Moreover, at the same concentration, both single and combined VNP exposures decreased the E. crypticus survival. On the other hand, DPH and NPls individually caused no effect on organisms’ survival and reproduction. However, the combination of DPH (10 and 50 mg/kg) with 300 mg NPls/kg induced a decrease in reproduction, showing a relevant interaction between the two contaminants (synergism). Our findings indicate that the NPls can play a role as vectors for other contaminants and can potentiate the effects of pharmaceuticals, such as DPH, even at low and sub-lethal concentrations, highlighting the negative impact of mixtures of contaminants (including NPls) on soil systems.
Abstract The gut microbiome produces vitamins, nutrients, and neurotransmitters, and helps to modulate the host immune system—and also plays a major role in the metabolism of many exogenous compounds, including drugs and chemical toxicants. However, the extent to which specific microbial species or communities modulate hazard upon exposure to chemicals remains largely opaque. Focusing on the effects of collateral dietary exposure to the widely used herbicide atrazine, we applied integrated omics and phenotypic screening to assess the role of the gut microbiome in modulating host resilience in Drosophila melanogaster . Transcriptional and metabolic responses to these compounds are sex-specific and depend strongly on the presence of the commensal microbiome. Sequencing the genomes of all abundant microbes in the fly gut revealed an enzymatic pathway responsible for atrazine detoxification unique to Acetobacter tropicalis . We find that Acetobacter tropicalis alone, in gnotobiotic animals, is sufficient to rescue increased atrazine toxicity to wild-type, conventionally reared levels. This work points toward the derivation of biotic strategies to improve host resilience to environmental chemical exposures, and illustrates the power of integrative omics to identify pathways responsible for adverse health outcomes.
Lithium-ion batteries degrade due to usage and exposure to environmental conditions, which affects their capability to store energy and supply power. Accurately predicting the capacity and power fade of lithium-ion battery cells is challenging due to intrinsic manufacturing variances and coupled nonlinear ageing mechanisms. In this paper, we propose a data-driven prognostics framework to predict both capacity and power fade simultaneously with multi-task learning. The model is able to predict the degradation trajectory of both capacity and internal resistance together with knee-points and end-of-life points accurately at early-life stage. The validation shows an average percentage error of 2.37% and 1.24% for the prediction of capacity fade and resistance rise, respectively. The model's ability to accurately predict the degradation, facing capacity and resistance estimation errors, further demonstrates the model's robustness and generalizability. Compared with single-task learning models for forecasting capacity and power degradation, the model shows a significant prediction accuracy improvement and computational cost reduction. This work presents the highlights of multi-task learning in the degradation prognostics for lithium-ion batteries.
Body fat depots are heterogeneous concerning their embryonic origin, structure, exposure to environmental stressors, and availability. Thus, investigating adipose-derived mesenchymal stromal cells (ASCs) from different sources is essential to standardization for future therapies. In vitro amplification is also critical because it may predispose cell senescence and mutations, reducing regenerative properties and safety. Here, we evaluated long-term culture of human facial ASCs (fASCs) and abdominal ASCs (aASCs) and showed that both met the criteria for MSCs characterization but presented differences in their immunophenotypic profile, and differentiation and clonogenic potentials. The abdominal tissue yielded more ASCs, and these had higher proliferative potential, but facial cells displayed fewer mitotic errors at higher passages. However, both cell types reduced clonal efficiency over time and entered replicative senescence around P12, as evaluated by progressive morphological alterations, reduced proliferative capacity, and SA-β-galactosidase expression. Loss of genetic integrity was detected by a higher proportion of cells showing nuclear alterations and γ-H2AX expression. Our findings indicate that the source of ASCs can substantially influence their phenotype and therefore should be carefully considered in future cell therapies, avoiding, however, long-term culture to ensure genetic stability.
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Exposure to environmental arsenic is associated with serious of health issues such as cancer, diabetes and developmental delays in infants and children. In human liver, As(III) S-adenosylmethionine methyl transferase (hAS3MT) (EC 2.1.1.137) was proposed to be an detoxification process by methylation of inorganic arsenite into pentavalent methyl MAs(V) and dimethyl arsenite DMAs(V). More recently the first product was shown to be highly toxic and potentially carcinogenic trivalent methylarsenite (MAs(III)). Our studies are designed to elucidate the mechanism of AS3MT and its contribution to arsenic-related diseases. Here, in this paper, we report the first crystallization and preliminary X-ray diffraction analysis of the human AS3MT enzyme. The crystals belong to the monoclinic P12 1 1 space group with unit cell parameters of a = 135.03 Å, b = 260.44 Å, c = 279.03 Å, α = 90.00°, β = 93.36°, γ = 90.00°.
Federal Guidance Report No. 16 will provide risk coefficients for use in projecting the probability of cancer morbidity or mortality from exposure to environmental radionuclides. The derivation of nuclide-specific risk coefficients involves multiple steps, with each step relying on the accuracy of the previous step as well as the numerical data utilized within each step. Thus, to ensure the quality of the derived risk coefficients, it is necessary to evaluate and confirm the quality and proper implementation of input data at each step of the derivation. The Oak Ridge National Laboratory (ORNL) dosimetry research team currently has two largely independent software codes for deriving radiation dose estimates, dose coefficients, and cancer risk coefficients for internally deposited radionuclides: DCAL and QCAL. The agreement of derived values based on alternate codes is an important step in quality assurance (QA) of the risk coefficients produced in this project. DCAL is an integration of the dosimetric software and numerical databases developed at ORNL over the past 25 years for the EPA’s Office of Radiation and Indoor Air (ORIA). QCAL was developed in 2015 to serve as a substitute for DCAL while DCAL was undergoing revision and to provide QA for the updated version of DCAL. The complex methodology employed in the derivation of cancer risk coefficients presents a challenge for QA, and as such, this report describes the QA steps used by the ORNL dosimetry team in this process as implemented in DCAL and QCAL for Federal Guidance Report No. 16.
This overview discusses the role of imprinting in the development of an organism, and how exposure to environmental chemicals during fetal development leads to the physiological and biochemical changes that can have adverse lifelong effects on the health of the offspring. There has been a recent upsurge in the use of chemical products in everyday life. These chemicals include industrial byproducts, pesticides, dietary supplements, and pharmaceutical products. They mimic the natural estrogens and bind to estradiol receptors. Consequently, they reduce the number of receptors available for ligand binding. This leads to a faulty signaling in the neuroendocrine system during the critical developmental process of ‘imprinting’. Imprinting causes structural and organizational differentiation in male and female reproductive organs, sexual behavior, bone mineral density, and the metabolism of exogenous and endogenous chemical substances. Several studies conducted on animal models and epidemiological studies provide profound evidence that altered imprinting causes various developmental and reproductive abnormalities and other diseases in humans. Altered metabolism can be measured by various endpoints such as the profile of cytochrome P-450 enzymes (CYP450’s), xenobiotic metabolite levels, and DNA adducts. The importance of imprinting in the potentiation or attenuation of toxic chemicals is discussed.
One of the most significant challenges in human health risk assessment is to evaluate hazards from exposure to environmental chemical mixtures. Polycyclic aromatic hydrocarbons (PAHs) are a class of ubiquitous contaminants typically found as mixtures in gaseous and particulate phases in ambient air pollution associated with petrochemicals from Superfund sites and the burning of fossil fuels. However, little is understood about how PAHs in mixtures contribute to toxicity in lung cells. To investigate mixture interactions and component additivity from environmentally relevant PAHs, two synthetic mixtures were created from PAHs identified in passive air samplers at a legacy creosote site impacted by wildfires. The primary human bronchial epithelial cells differentiated at the air–liquid interface were treated with PAH mixtures at environmentally relevant proportions and evaluated for the differential expression of transcriptional biomarkers related to xenobiotic metabolism, oxidative stress response, barrier integrity, and DNA damage response. Component additivity was evaluated across all endpoints using two independent action (IA) models with and without the scaling of components by toxic equivalence factors. Both IA models exhibited trends that were unlike the observed mixture response and generally underestimated the toxicity across dose suggesting the potential for non-additive interactions of components. Overall, this study provides an example of the usefulness of mixture toxicity assessment with the currently available methods while demonstrating the need for more complex yet interpretable mixture response evaluation methods for environmental samples.