Elise Hickman, Victoria Carberry, Celeste Carberry
et al.
Growing evidence supports the importance of extracellular vesicle (EV) as mediators of communication in pathological processes, including those underlying respiratory disease. However, establishing methods for isolating and characterizing EVs remains challenging, particularly for respiratory samples. This study set out to address this challenge by comparing different EV isolation methods and evaluating their impacts on EV yield, markers of purity, and proteomic signatures, utilizing equine/horse bronchoalveolar lavage samples. Horses can serve as effective translational animal models for respiratory studies due to similarities with human immune responses, shared environmental exposures, and naturally occurring respiratory diseases including asthma. Further, horses are long-lived large animals that allow for longitudinal sample collection, and provide large sample volume and cell yield, which are particularly useful since EV research is commonly limited by low sample yields. Here, EVs were isolated from horse bronchoalveolar lavage fluid (BALF) using four different methods (ultracentrifugation, microcentrifugation, and two sizes of size exclusion chromatography columns) and characterized by measuring particle counts, EV purity, total protein yield, and proteomic cargo, with a specific focus on vesicle surface marker expression potentially informing cell type of origin. We found that size exclusion chromatography yielded the highest particle counts, greatest EV purity markers and elevated vesicle surface marker expression. Overall proteomic profiles differed across isolation methods, with size exclusion chromatography clustering separately from centrifugation. Taken together, our results demonstrate that different isolation methods impact characteristics of EVs, notably that size exclusion chromatography, compared to centrifugation methods, resulted in higher EV purity and better characterized proteomic diversity, including information on EV cell-of-origin. This is the first study to characterize proteomic profiles of EVs following different isolation methods using equine BALF. The results of this study will pave the way for future studies using equine and human samples to characterize respiratory tract EVs.
Linda Smail, David Santandreu Calonge, Firuz Kamalov
et al.
This research investigates the potential of Artificial Intelligence (AI) models to bridge the knowledge gap in environmental education among university students. By focusing on prominent large language models (LLMs) such as GPT-3.5, GPT-4, GPT-4o, Gemini, Claude Sonnet, and Llama 2, the study assesses their effectiveness in conveying environmental concepts and, consequently, facilitating environmental education. The investigation employs a standardized tool, the Environmental Knowledge Test (EKT-19), supplemented by targeted questions, to evaluate the environmental knowledge of university students in comparison to the responses generated by the AI models. The results of this study suggest that while AI models possess a vast, readily accessible, and valid knowledge base with the potential to empower both students and academic staff, a human discipline specialist in environmental sciences may still be necessary to validate the accuracy of the information provided.
Devojyoti Kansabanik, Marcel Gouws, Deepan Patra
et al.
Solar radio emissions offer unique diagnostic insights into the solar corona. However, their dynamic and multiscale nature, along with several orders of magnitude variations in intensity, pose significant observational challenges. To date, at gigahertz frequencies, MeerKAT stands out globally with high potential of producing high-fidelity, spectroscopic snapshot images of the Sun, enabled by its dense core, high sensitivity, and broad frequency coverage. Yet, as a telescope originally designed for observing faint galactic and extragalactic sources, observing the Sun at the boresight of the telescope requires customized observing strategies and calibration methods. This work demonstrates the technical readiness of MeerKAT for solar observations at the boresight of the telescope in the UHF (580-1015 MHz) and L-band (900-1670 MHz) frequency ranges, including optimized modes, a dedicated calibration scheme, and a tailored, entirely automated calibration and imaging pipeline. The quality of solar images is validated through morphological comparisons with the solar images at other wavelengths. Several unique early science results showcase the potential of this new capability of MeerKAT. Once fully commissioned and operational, this will unlock novel solar studies, significantly expand the scientific portfolio of MeerKAT, and lay the groundwork for solar observations with the mid-frequency telescope of the upcoming Square Kilometre Array Observatory, for which MeerKAT serves as a precursor.
Sonia Bujok, Tomasz Pańczyk, Kosma Szutkowski
et al.
To clean or not to clean? The solution to this dilemma is related to understanding the plasticiser migration which has a few practical implications for the state of museum artefacts made of plasticised poly(vinyl chloride) - PVC and objects stored in their vicinity. The consequences of this process encompass aesthetic changes due to the presence of exudates and dust deposition, an increase in air pollution and the development of mechanical stresses. Therefore, this paper discusses the plasticiser migration in PVC to provide evidence and support the development of recommendations and guidelines for conservators, collection managers and heritage scientists. Particularly, the investigation is focused on the migration of the ortho-phthalates representing the group of the most abundant plasticisers in PVC collections. The predominance of inner diffusion or surface emission (evaporation) determining the rate-limiting step of the overall migration process is considered a fundament for understanding the potential environmental and mechanical risk. According to this concept, general correlations for various ortho-phthalates are proposed depending on their molar mass with the support of molecular dynamics simulations and NMR diffusometry. The study reveals that for the majority of the PVC objects in collections, the risk of accelerated migration upon mild removal of surface plasticiser exudate is low. Thus, surface cleaning would allow for diminishing dust deposition and air pollution by phthalate-emitting objects in a museum environment. Bearing in mind simplicity and the need for fast decision-supporting solutions, the step-by-step protocol for non-destructive identification and quantification of plasticisers in objects made of or containing plasticised PVC, determination of the physical state of investigated artefacts and rate-limiting process of plasticiser migration is proposed.
<p>This study investigates simulated glacial lake outburst floods (GLOFs) at five glacial lakes in the Everest region of Nepal using the three-dimensional model OpenFOAM. It presents the evolution of GLOF characteristics in the 21st century considering different moraine breach scenarios and two Shared Socioeconomic Pathways scenarios. The results demonstrate that in low-magnitude scenarios, the five lakes generate GLOFs that inundate between 0.35 and 2.23 km<span class="inline-formula"><sup>2</sup></span> of agricultural land with an average water depth of 0.9 to 3.58 m. These GLOFs reach distances of 59 to 84 km, affect 30 to 88 km of roads or trails, and inundate 183 to 1699 buildings with 1.2 to 4.9 m of water. In higher scenarios, GLOFs can extend over 100 km and also affect larger settlements in the foothills. Between 80 and 100 km of roads, 735 to 1989 houses and 0.85 to 3.52 km<span class="inline-formula"><sup>2</sup></span> of agricultural land could be inundated, with average water depths of up to 10 m. The high precision of the 3D flood modeling, with detailed simulations of turbulence and viscosity, provides valuable insights into 21st-century GLOF evolution, supporting more accurate risk assessments and effective adaptation strategies.</p>
Jordan R Kuiper, Shelley H Liu, Bruce P Lanphear
et al.
Abstract Few methods have been used to characterize repeatedly measured biomarkers of chemical mixtures. We applied latent profile analysis (LPA) to serum concentrations of 4 perfluoroalkyl and polyfluoroalkyl substances (PFAS) measured at 4 time points from gestation to age 12 years. We evaluated the relationships between profiles and z scores of height, body mass index, fat mass index, and lean body mass index at age 12 years (n = 218). We compared LPA findings with an alternative approach for cumulative PFAS mixtures using g-computation to estimate the effect of simultaneously increasing the area under the receiver operating characteristic curve (AUC) for all PFAS. We identified 2 profiles: a higher PFAS profile (35% of sample) and a lower PFAS profile (relative to each other), based on their average PFAS concentrations at all time points. The higher PFAS profile had generally lower z scores for all outcomes, with somewhat larger effects for males, though all 95% CIs crossed the null. For example, the higher PFAS profile was associated with a 0.50-unit lower (β = −0.50; 95% CI, −1.07 to 0.08) BMI z score among males but not among females (β = 0.04; 95% CI, −0.45 to 0.54). We observed similar patterns with AUCs. We found that a higher childhood PFAS profile and higher cumulative PFAS mixtures may be associated with altered growth in early adolescence. This article is part of a Special Collection on Environmental Epidemiology.
Alexander Wieser, Johannes Lachner, Martin Martschini
et al.
The detection of low abundances of $^{135}$Cs in environmental samples is of significant interest in different fields of environmental sciences, especially in combination with its shorter-lived sister isotope $^{137}$Cs. The method of Ion-Laser InterAction Mass Spectrometry (ILIAMS) for barium separation at the Vienna Environmental Research Accelerator (VERA) was investigated and further improved for low abundance cesium detection. The difluorides BaF$_2^-$ and CsF$_2^-$ differ in their electron detachment energies and make isobar suppression with ILIAMS by more than 7 orders of magnitude possible. By this method, samples with ratios down to the order of $^{135,137}$Cs/$^{133}$Cs $\approx 10^{-11}$ are measurable and the $^{135}$Cs/$^{137}$Cs ratios of first environmental samples were determined by AMS.
Matrix completion is one of the crucial tools in modern data science research. Recently, a novel sampling model for matrix completion coined cross-concentrated sampling (CCS) has caught much attention. However, the robustness of the CCS model against sparse outliers remains unclear in the existing studies. In this paper, we aim to answer this question by exploring a novel Robust CCS Completion problem. A highly efficient non-convex iterative algorithm, dubbed Robust CUR Completion (RCURC), is proposed. The empirical performance of the proposed algorithm, in terms of both efficiency and robustness, is verified in synthetic and real datasets.
Hydrogen internal combustion engines (H2-ICEs) have advantages such as clean combustion and zero carbon emissions, and have become one of the important technical routes for decarbonization in the internal combustion engine industry. In this paper, several key factors affecting the performance and emissions of hydrogen internal combustion engines, such as ignition timing, excess air coefficient, and hydrogen injection timing, were systematically studied on a spark ignition multi-point injection (MPI) hydrogen internal combustion engine bench. The experimental results indicate that the ignition timing controls the combustion phase of hydrogen. Moderate early ignition can improve the brake thermal efficiency (BTE) while having little impact on the NOX emissions. Excess air coefficient(λ) can significantly affect the performance and emissions of H2-ICE. Along with the increase of the λ, the NOX emissions first increases and then continues to decline. When the λ reaching 2.1 or above, near zero emissions of NOX can be achieved. The advance of hydrogen injection timing will slightly increase the peak of cylinder pressure and instantaneous heat release rate. However, overall, the impact of hydrogen injection timing on BTE and NOX emissions is not significant on MPI H2-ICE.
Background: Studies about the combined effects of gaseous air pollutants and particulate matters are still rare. Objectives: This study was performed based on baseline survey of the Diverse Life-Course Cohort in the Beijing-Tianjin-Hebei (BTH) Region of North China to evaluate the association of long-term air pollutants with blood pressure and the combined effect of the air pollutants mixture among 32821 natural han population aged 20 years or above. Methods: Three-year average exposure to air pollutants (PM10, PM2.5, PM1, O3, SO2, NO2, and CO) and PM2.5 components [black carbon (BC), ammonium (NH4+), nitrate (NO3−), sulfate (SO42−), and organic matter (OM)] of residential areas were calculated based on well-validated models. Generalized linear mixed models (GLMMs) were used to estimate the associations of air pollutants exposure with the systolic blood pressure (SBP), diastolic blood pressure (DBP), Mean arterial pressure (MAP), pulse pressure (PP) and prevalent hypertension. Quantile g-Computation and Bayesian Kernel Machine Regression (BKMR) were employed to assess the combined effect of the air pollutant mixture. Results: We found that long-term exposures of O3, PM2.5, and PM2.5 components were stably and strongly associated with elevated SBP, DBP, and MAP and prevalent hypertension. O3 increased SBP, DBP, and MAP at a similar extent, but with greater effects; while, PM2.5 and PM2.5 components had a greater impact on SBP than DBP, which increased PP simultaneously. In multi-pollutant models, the combined effects of the air pollutant mixture on blood pressure and prevalent hypertension was predominantly influenced by O3, PM2.5, and O3, OM in different models, respectively. For example, O3, PM2.5 contributed 57.25 %, 39.22 % of the positive combined effect of the air pollutant mixture on SBP; and O3, OM positively contributed 70.00 %, 30.00 % on prevalent hypertension, respectively. There were interactions between O3, CO, SO2 and PM2.5 components on hbp, SBP and PP. Conclusions: The results showed positive associations of air pollutant mixtures with blood pressure, where O3 and PM2.5 (especially OM) might be primary contributors. There were interactions between gaseous air pollutants and PM2.5 components on blood pressure and prevalent hypertension.
Sinead A. Keogh, Jessica H. Leibler, Caryn M. Sennett Decker
et al.
Abstract Background Mortality from chronic kidney disease of unknown etiology (CKDu) is extremely high along the Pacific coast of Central America, particularly among sugarcane workers. The Mesoamerican Nephropathy Occupational Study (MANOS) is a prospective cohort study of CKDu among agricultural and non-agricultural workers in El Salvador and Nicaragua. The objective of this manuscript is to describe the MANOS cohort recruitment, baseline data collection, and CKDu prevalence after two rounds. Methods Workers with no known diabetes, hypertension, or CKD were recruited from sugarcane, corn, plantain, brickmaking, and road construction industries (n = 569). Investigators administered questionnaires, collected biological samples, and observed workers for three consecutive workdays at the worksite. Serum specimens were analyzed for kidney function parameters, and used to calculate estimated glomerular filtration rate (eGFR). At six months, serum was collected again prior to the work shift. CKD at baseline is defined as eGFR ≤ 60 ml/min/1.73m2 at both timepoints. Age-standardized prevalence was calculated by industry, country, and demographic measures. Kidney function parameters were compared by CKD status. Results Prevalence of CKD at baseline was 7.4% (n = 42). Age-standardized prevalence was highest in Salvadoran sugarcane (14.1%), followed by Salvadoran corn (11.6%), and Nicaraguan brickmaking (8.1%). Nicaraguan sugarcane had the lowest prevalence, likely due to kidney function screenings prior to employment. Conclusion Despite efforts to enroll participants without CKD, our identification of prevalent CKD among agricultural and non-agricultural workers in the MANOS cohort indicates notable kidney disease in the region, particularly among sugarcane workers.
Word embeddings are an essential instrument in many NLP tasks. Most available resources are trained on general language from Web corpora or Wikipedia dumps. However, word embeddings for domain-specific language are rare, in particular for the social science domain. Therefore, in this work, we describe the creation and evaluation of word embedding models based on 37,604 open-access social science research papers. In the evaluation, we compare domain-specific and general language models for (i) language coverage, (ii) diversity, and (iii) semantic relationships. We found that the created domain-specific model, even with a relatively small vocabulary size, covers a large part of social science concepts, their neighborhoods are diverse in comparison to more general models. Across all relation types, we found a more extensive coverage of semantic relationships.
Over the past decade, there have been increasing recognition and concern of the toxicological impacts of microplastics (MPs) in the environment, which have been widely found in various marine environments from estuary to deep oceans. Numerous toxicological studies have been conducted on the impacts of MPs on various marine organisms, especially phytoplankton, zooplankton, bivalves, and fish of different trophic levels. These studies mainly focused on the measurements of MPs bioaccumulation and their resulting biological impacts at molecular, metabolic, biochemical, physiological, and organismic levels. This review examines the various studies conducted over the recent years on the toxicology of MPs in different marine organisms, particularly on the bioaccumulation and toxicity of MPs. The impacts of MPs on marine organisms are diverse, and the complexity of organism physiology as well as MPs physical and chemical properties need to be considered. Future studies should consider the environmental relevance of toxicological research and the development of quantitative tools to model the transport, bioaccumulation, and toxicity of MPs. These are important for the real environmental risk assessments of MPs in the marine environments.
AbstractDespite substantial strides in diagnosis and treatment, cardiovascular diseases (CVDs) continue to represent the leading cause of death in the USA and around the world, resulting in significant morbidity and loss of productive years of life. It is increasingly evident that environmental exposures during early development can influence CVD risk across the life course. CVDs exhibit marked sexual dimorphism, but how sex interacts with environmental exposures to affect cardiovascular health is a critical and understudied area of environmental health. Emerging evidence suggests that developmental exposures may have multi- and transgenerational effects on cardiovascular health, with potential sex differences; however, further research in this important area is urgently needed. Lead (Pb), phthalate plasticizers, and perfluoroalkyl substances (PFAS) are ubiquitous environmental contaminants with numerous adverse human health effects. Notably, recent evidence suggests that developmental exposure to each of these toxicants has sex-specific effects on cardiovascular outcomes, but the underlying mechanisms, and their effects on future generations, require further investigation. This review article will highlight the role for the developmental environment in influencing cardiovascular health across generations, with a particular emphasis on sex differences and epigenetic mechanisms. In particular, we will focus on the current evidence for adverse multi and transgenerational effects of developmental exposures to Pb, phthalates, and PFAS and highlight areas where further research is needed.
Rebecca D. Kehm, E. Jane Walter, Sabine Oskar
et al.
Abstract Background Polycyclic aromatic hydrocarbons (PAH), which are found in air pollution, have carcinogenic and endocrine disrupting properties that might increase breast cancer risk. PAH exposure might be particularly detrimental during pregnancy, as this is a time when the breast tissue of both the mother and daughter is undergoing structural and functional changes. In this study, we tested the hypothesis that ambient PAH exposure during pregnancy is associated with breast tissue composition, measured one to two decades later, in adolescent daughters and their mothers. Methods We conducted a prospective analysis using data from a New York City cohort of non-Hispanic Black and Hispanic mother–daughter dyads (recruited 1998–2006). During the third trimester of pregnancy, women wore backpacks containing a continuously operating air sampling pump for two consecutive days that measured ambient exposure to eight carcinogenic higher molecular weight nonvolatile PAH compounds (Σ8 PAH) and pyrene. When daughters (n = 186) and mothers (n = 175) reached ages 11–20 and 29–55 years, respectively, optical spectroscopy (OS) was used to evaluate measures of breast tissue composition (BTC) that positively (water content, collagen content, optical index) and negatively (lipid content) correlate with mammographic breast density, a recognized risk factor for breast cancer. Multivariable linear regression was used to evaluate associations between ambient PAH exposure and BTC, overall and by exposure to household tobacco smoke during pregnancy (yes/no). Models were adjusted for race/ethnicity, age, and percent body fat at OS. Results No overall associations were found between ambient PAH exposure (Σ8 PAH or pyrene) and BTC, but statistically significant additive interactions between Σ8 PAH and household tobacco smoke exposure were identified for water content and optical index in both daughters and mothers (interaction p values < 0.05). Σ8 PAH exposure was associated with higher water content (βdaughters = 0.42, 95% CI = 0.15–0.68; βmothers = 0.32, 95% CI = 0.05–0.61) and higher optical index (βdaughters = 0.38, 95% CI = 0.12–0.64; βmothers = 0.38, 95% CI = 0.12–0.65) in those exposed to household tobacco smoke during pregnancy; no associations were found in non-smoking households (interaction p values < 0.05). Conclusions Exposure to ambient Σ8 PAH and tobacco smoke during pregnancy might interact synergistically to impact BTC in mothers and daughters. If replicated in other cohorts, these findings might have important implications for breast cancer risk across generations.