Chemical and Cellular Formation of Reactive Oxygen Species from Secondary Organic Aerosols in Epithelial Lining Fluid.
Bibliographic record
Abstract
INTRODUCTION: inhalation and deposition into the respiratory tract causes the formation of ROS by chemical reactions and phagocytosis of macrophages in the epithelial lining fluid (ELF), but their relative contributions are not well quantified and their link to oxidative stress remains uncertain. The specific aims of this project were (1) elucidating the chemical mechanism and quantifying the formation kinetics of ROS in the ELF by SOA; (2) quantifying the relative importance of ROS formation by chemical reactions and macrophages in the ELF. METHODS: ). We collected size-segregated PM at two highway sites in Anaheim, CA, and Long Beach, CA, and at an urban site in Irvine, CA, during two wildfire events. The collected particles were extracted into water or surrogate ELF that contained lung antioxidants. ROS generation was quantified using electron paramagnetic resonance (EPR) spectroscopy with a spin-trapping technique. PM oxidative potential (OP) was also quantified using the dithiothreitol assay. In addition, kinetic modeling was applied for analysis and interpretation of experimental data. Finally, we quantified cellular superoxide release by RAW264.7 macrophage cells upon exposure to quinones and isoprene SOA using a chemiluminescence assay as calibrated with an EPR spin-probing technique. We also applied cellular imaging techniques to study the cellular mechanism of superoxide release and oxidative damage on cell membranes. RESULTS: was the dominant species generated by all types of SOA. At neutral pH, α-terpineol SOA exhibited a substantial yield of carbon-centered organic radicals (R·), while no radical formation was observed by aromatic SOA. . ·OH and superoxide were found to be efficiently scavenged by antioxidants. production were governed by Fe and Cu ions, ·OH radicals were mainly generated by organic compounds and Fenton-like reactions of metal ions. We obtained mixed results for correlations between PM OP and ROS formation, providing rationale and limitations of the use of oxidative potential as an indicator for PM toxicity in epidemiological and toxicological studies. Quinones and isoprene SOA activated nicotinamide adenine dinucleotide phosphate (NADPH) oxidase in macrophages, releasing massive amounts of superoxide via respiratory burst and overwhelming the superoxide formation by aqueous chemical reactions in the ELF. The threshold dose for macrophage activation was much smaller for quinones compared with isoprene SOA. The released ROS caused lipid peroxidation to increase cell membrane fluidity, inducing oxidative damage and stress. Further increases of doses led to the activation of antioxidant response elements, reducing the net cellular superoxide production. At very high doses and long exposure times, chemical production became comparably important or dominant if the escalation of oxidative stress led to cell death. CONCLUSIONS: . For a comprehensive assessment of PM toxicity and health effects via oxidative stress, it is important to consider both chemical reactions and cellular processes for the formation of ROS in the ELF. Chemical composition of PM strongly influences ROS formation; further investigations are required to study ROS formation from various PM sources. Such research will provide critical information to environmental agencies and policymakers for the development of air quality policy and regulation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".