Effects on Biotransformation, Oxidative Stress, and Endocrine Disruption in Rainbow Trout (<i>Oncorhynchus mykiss</i>) Exposed to Hydraulic Fracturing Flowback and Produced Water
Bibliographic record
Abstract
The effects of hydraulic fracturing (HF) flowback and produced water (HF-FPW), a complex saline mixture of injected HF fluids and deep formation water that return to the surface, was examined in rainbow trout (Oncorhynchus mykiss). Exposure to HF-FPWs resulted in significant induction of ethoxyresorufin-O-deethylase (EROD) activity in both liver and gill tissues. Increased lipid peroxidation via oxidative stress was also detected by thiobarbituric acid reactive substances (TBARS) assay. The mRNA expressions of a battery of genes related to biotransformation, oxidative stress, and endocrine disruption were also measured using quantitative real-time polymerase chain reaction (Q-RT-PCR). The increased expression of cyp1a (2.49 ± 0.28-fold), udpgt (2.01 ± 0.31-fold), sod (1.67 ± 0.09-fold), and gpx (1.58 ± 0.10-fold) in raw sample exposure group (7.5%) indicated elevated metabolic enzyme activity, likely through the aryl hydrocarbon receptor pathway, and generation of reactive oxygen species. In addition, the elevated vtg and era2 expression demonstrated endocrine disrupting potential exerted by HF-FPW in rainbow trout. The overall results suggested HF-FPW could cause significant adverse effects on fish, and the organic contents might play the major role in its toxicity. Future studies are needed to help fully determine the toxic mechanism(s) of HF-FPW on freshwater fish, and aid in establishing monitoring, treatment, and remediation protocols for HF-FPW.
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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".