Two thermodynamic equilibrium models were applied to estimate changes in mean airborne fine particle (PM2.5) mass concentrations that could result from changes in ambient concentrations of sulfate, nitric acid, or ammonia in the southeastern United States, the midwestern United States, and central California. Pronounced regional differences were found. Southeastern sites exhibited the lowest current mean concentrations of nitrate, and the smallest predicted responses of PM2.5 nitrate and mass concentrations to reductions of nitric acid, which is the principal reaction product of the oxidation of nitrogen dioxide (NO2) and the primary gas-phase precursor of fine particulate nitrate. Weak responses of PM2.5 nitrate and mass concentrations to changes in nitric acid levels occurred even if sulfate concentrations were half of current levels. The midwestern sites showed higher levels of fine particulate nitrate, characterized by cold-season maxima, and were projected to show decreases in overall PM levels following decreases of either sulfate or nitric acid. For some midwestern sites, predicted PM2.5 nitrate concentrations increased as modeled sulfate levels declined, but sulfate reductions always reduced the predicted fine PM mass concentrations; PM2.5 nitrate concentrations became more sensitive to reductions of nitric acid as modeled sulfate concentrations were decreased. The California sites currently have the highest mean concentrations of fine PM nitrate and the lowest mean concentrations of fine PM sulfate. Both the estimated PM2.5 nitrate and fine mass concentrations decreased in response to modeled reductions of nitric acid at all California sites. The results indicate important regional differences in expected PM2.5 mass concentration responses to changes in sulfate and nitrate precursors. Analyses of ambient data, such as described here, can be a key part of weight of evidence (WOE) demonstrations for PM2.5 attainment plans. Acquisition of the data may require special sampling efforts, especially for PM2.5 precursor concentration data.
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http://dx.doi.org/10.3155/1047-3289.57.11.1337 | DOI Listing |
BMC Pregnancy Childbirth
January 2025
Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetrics and Gynecology, Peking University Third Hospital, Peking University Third Hospital), National Center for Healthcare Quality Management in Obstetrics, Beijing, 100191, China.
Background: Postpartum hemorrhage (PPH) is the leading cause of maternal mortality worldwide, with uterine atony accounting for approximately 70% of PPH cases. However, there is currently no effective prediction method to promote early management of PPH. In this study, we aimed to screen for potential predictive biomarkers for atonic PPH using combined omics approaches.
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January 2025
Archaea Physiology & Biotechnology Group, Department of Functional and Evolutionary Ecology, University of Vienna, Wien, Austria.
Methanogenic archaea (methanogens) possess fascinating metabolic characteristics, such as the ability to fix molecular nitrogen (N). Methanogens are of biotechnological importance due to the ability to produce methane (CH) from molecular hydrogen (H) and carbon dioxide (CO) and to excrete proteinogenic amino acids. This study focuses on analyzing the link between biological methanogenesis and amino acid excretion under N-fixing conditions.
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January 2025
Student Research Committee, Kermanshah University of Medical Sciences, Kermanshah, Iran.
There is limited understanding of socioeconomic inequality in multimorbidity in Iran. This study aims to investigate socioeconomic inequality in multimorbidity among adults in western Iran. Data from the Ravansar Non-Communicable Disease (RaNCD) cohort study were used in this cross-sectional study.
View Article and Find Full Text PDFNat Commun
January 2025
School of Safety Science, Tsinghua University, Beijing, China.
Ultrafine particles (UFPs) under 100 nm pose significant health risks inadequately addressed by traditional mass-based metrics. The WHO emphasizes particle number concentration (PNC) for assessing UFP exposure, but large-scale evaluations remain scarce. In this study, we developed a stacking-based machine learning framework integrating data-driven and physical-chemical models for a national-scale UFP exposure assessment at 1 km spatial and 1-hour temporal resolutions, leveraging long-term standardized PNC measurements in Switzerland.
View Article and Find Full Text PDFNPJ Vaccines
January 2025
Department of Biochemistry, University of Oxford, OX1 3QU, Oxford, UK.
The rapid development and worldwide distribution of COVID-19 vaccines is a remarkable achievement of biomedical research and logistical implementation. However, these developments are associated with the risk of a surge of substandard and falsified (SF) vaccines, as illustrated by the 184 incidents with SF and diverted COVID-19 vaccines which have been reported during the pandemic in 48 countries, with a paucity of methods for their detection in supply chains. In this context, matrix-assisted laser desorption ionisation-time of flight (MALDI-ToF) mass spectrometry (MS) is globally available for fast and accurate analysis of bacteria in patient samples, offering a potentially accessible solution to identify SF vaccines.
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