Altered oxidative stress and antioxidant biomarkers concentrations in pregnant individuals exposed to oil and gas sites in Northeastern British Columbia
Bibliographic record
Abstract
Northeastern British Columbia is a region of prolific unconventional oil and gas (UOG) activity. UOG activity can release volatile organic compounds (VOCs) which can elevate oxidative stress and disrupt antioxidant activity in exposed pregnant individuals, potentially increasing the risk of adverse pregnancy outcomes. This study measured biomarkers of oxidative stress and antioxidant activity in pooled urine samples of 85 pregnant individuals living in Northeastern British Columbia, to analyze associations between indoor air VOCs, oil and gas well density and proximity metrics, and biomarker concentrations. Concentrations of catalase, superoxide dismutase (SOD), glutathione S-transferase, total antioxidant capacity, 6-hydroxymelatonin sulfate (aMT6s), malondialdehyde (MDA), 8-hydroxy-2'-deoxyguanosine (8-OHdG), and 8-isoprostane were measured using assay kits. Associations between exposure metrics and biomarker concentrations were determined using multiple linear regression models adjusted for biomarker-specific covariables. UOG proximity was associated with decreased SOD and 8-OHdG. Decreased 8-OHdG was associated with increased proximity to all wells. Decreased aMT6s were observed with increased indoor air hexanal concentrations. MDA was negatively associated with indoor air 1,4-dioxane concentrations. No statistically significant associations were found between other biomarkers and exposure metrics. Although some associations linked oil and gas activity to altered oxidative stress and antioxidant activity, the possibility of chance findings due to the large number of tests cannot be discounted. This study shows that living near UOG wells may alter oxidative stress and antioxidant activity in pregnant individuals. More research is needed to elucidate underlying mechanisms and to what degree UOG activity affects oxidative stress and antioxidant activity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".