Particle-bound reactive oxygen species in cooking emissions: Aging effects and cytotoxicity
Bibliographic record
Abstract
Oil-based cooking (such as stir- and deep-frying) are large sources of particulate unsaturated fatty acids that can be further oxidized to form peroxidic products, a group of reactive oxygen species (ROS). Deposition of ROS on respiratory system can lead to adverse health impacts. In this work, we quantified the particle-bound ROS (PB-ROS), primarily peroxide species, in aqueous extracts of real cooking emissions at food stalls in Singapore. Stir-frying has the highest potential to emit PB-ROS as compared to other cooking methods being investigated in this work. The PB-ROS contents in stir-frying emission can be comparable to those in secondary organic aerosol (SOA), which has been recognized as a potential large source of ambient PB-ROS. This work also demonstrates the complex effects of atmospheric processing. The PB-ROS contents in some stir- and deep-frying emissions with low initial values could increase by a factor of 2 or higher after dark ozonolysis at ∼100 ppb for 3 days, whereas substantial reduction of PB-ROS were observed for stir-frying emissions with high initial values regardless of ozone concentrations. The observations from the aging of laboratory-generated heated cooking oil droplets suggest that the bulk oil compositions, in particularly the fraction contribution of polyunsaturated fatty acids in cooking oils, and heating temperature can play an important role in affecting the degree of unsaturation (DoU) of fresh oil droplets and the subsequent production of PB-ROS during the aging process. The changes in cell viability and cellular ROS concentrations due to exposure of heated cooking oil droplet extracts indicate the possible relationship between the observed cytotoxicity and PB-ROS content, highlighting the potential impacts of inhaling cooking fumes on cellular ROS production and interconversion.
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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 | 0.000 |
| 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".