Chemical and Cellular Formation of Reactive Oxygen Species from Secondary Organic Aerosols in Epithelial Lining Fluid.
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».