Biochemical and Transcriptomic Effects of Herring Gull Egg Extracts from Variably Contaminated Colonies of the Laurentian Great Lakes in Chicken Hepatocytes
Bibliographic record
Abstract
Determining the effects of complex mixtures of environmental contaminants poses many challenges within the field of ecotoxicology. In this study, graded concentrations of herring gull egg extracts, collected from five Great Lakes breeding colonies with variable burdens of organohalogen contaminants (OHCs), were administered to chicken embryonic hepatocytes to determine effects on 7-ethoxyresorufin-O-deethylase (EROD) activity, porphyrin accumulation, and mRNA expression. EROD activity and porphyrin accumulation permitted the ranking of colonies based on the efficacy of eliciting an aryl hydrocarbon receptor-mediated response. An avian ToxChip polymerase chain reaction (PCR) array provided more exhaustive coverage in terms of potential toxicity pathways being affected, including xenobiotic and lipid metabolism and the thyroid hormone pathway. Herring gull eggs from Channel Shelter Island (CHSH, Lake Huron) and Gull Island (GULL, Lake Michigan) had among the highest OHC burdens, and extracts elicited a biochemical and transcriptomic response greater than that of extracts from the other three, less polluted colonies. For example, EROD EC50 values and porphyrin ECthreshold values were lower for CHSH and GULL extracts than for the other colonies. Extracts from CHSH and GULL altered 15 and 13 of 27 genes on the PCR array compared to no more than eight genes for the less contaminated sites. The combination of a well-established avian in vitro assay, two well-characterized biochemical assays, and the avian ToxChip PCR array permitted the geographical discrimination of variably contaminated herring gull eggs from the Great Lakes. Such high-throughput assays show potential promise as cost-effective tools for determining toxic potencies of complex mixtures in the environment.
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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".