PCB Related Effects Thresholds As Derived through Gene Transcript Profiles in Locally Contaminated Ringed Seals (<i>Pusa hispida</i>)
Bibliographic record
Abstract
Causal evidence linking toxic injury to polychlorinated biphenyl (PCB) exposure is typically confounded by the complexity of real-world contaminant mixtures to which aquatic wildlife are exposed. A local PCB "hotspot" on the Labrador coast provided a rare opportunity to evaluate the effects of PCBs on the health of a marine mammal as this chemical dominated their persistent organic pollutant (POP) burdens. The release of approximately 260 kg of PCBs by a military radar facility over a 30 year period (1970-2000) contaminated some local marine biota, including the ringed seal (Pusa hispida). The abundance profiles of eight health-related gene transcripts were evaluated in liver samples collected from 43 ringed seals in the affected area. The mRNA transcript levels of five gene targets, including aryl hydrocarbon receptor (Ahr), interleukin-1 β (Il1b), estrogen receptor α (Esr1), insulin like growth factor receptor 1 (Igf1), and glucocorticoid receptor α (Nr3c1) correlated with increasing levels of blubber PCBs. PCB threshold values calculated using best-fit hockey-stick regression models for these five genes averaged 1,680±206 ng/g lw, with the lowest, most conservative, being 1,370 ng/g lw for Il1b. Approximately 14% of the seals in the region exceeded this threshold. The dominance of PCBs in the seals studied enabled an assessment of the effects of this chemical on gene transcripts involved in regulating the health of a highly mobile predator, something that is rarely possible in the world of complex mixtures.
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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".