Development of an antioxidant assay to study oxidative potential of airborne particulate matter
Bibliographic record
Abstract
Oxidative potential is a measure of redox activity of airborne particulate matter (PM) and is often used as a surrogate to estimate one form of PM toxicity. The evaluation of oxidative potential in a physiologically relevant environment is always challenging. In this work, we developed a chromatographic method, employing an ultra-high-performance liquid chromatograph coupled to a triple–quadruple mass spectrometer, to determine the oxidative potential of PM from different sources. To this purpose, we measured the PM-induced oxidation of glutathione, cysteine, and ascorbic acid, and formation of glutathione disulfide and cystine, following PM addition to simulated epithelial lining fluids, which, in addition to the antioxidants, contained inorganic salts, a phospholipid, and proteins. The new method showed high precision and, when applied to standard reference PM, the oxidative potential was found to increase with the reaction time and PM concentration in the lung fluid. The antioxidant depletion rates were considerably higher than the rates found with the conventional dithiothreitol assay, indicating the higher sensitivity of the new method. The presence of the lung fluid inorganic species increased the oxidative potential determined through glutathione and cysteine, but showed an opposite effect with ascorbic acid, whereas the presence of proteins resulted in a moderate decrease in the oxidative potential. In the presence of PM 2.5 , glutathione and cysteine demonstrated similar depletion patterns, which were noticeably different from that of ascorbic acid, suggesting that cysteine could be used as an alternative to glutathione for probing oxidative potential.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".