Aryl hydrocarbon bioaccessibility to small mammals from arctic plants using in vitro techniques
Bibliographic record
Abstract
Through their diet, herbivores inhabiting contaminated sites may be chronically exposed to a variety of aryl hydrocarbons (e.g., dioxins and polycyclic aromatic hydrocarbons [PAHs]). However, little is known about how differences in morphology and physiology among plant species alter the environmental accumulation of aryl hydrocarbons or their release and subsequent activity in the gastrointestinal tract of herbivores after ingestion. In the present study, the activity of aryl hydrocarbons during digestion was examined using six Arctic plant species growing in impacted and reference sites near Inuvik, Northwest Territories, Canada. The plant species studied were black spruce (Picea mariana), labrador tea (Ledum groenlandicum), bog birch (Betula glandulosa), green alder (Alnus crispa), water sedge (Carex aquatilis), and little-tree willow (Salix arbusculoides). Plants were digested using a simulator of the upper digestive tract, and aryl hydrocarbon release was evaluated using an aryl hydrocarbon-receptor assay. Bioaccessible aryl hydrocarbon activity varied among the plant species tested. The species with the greatest activity was green alder, and the species with the least activity was black spruce. Further investigation revealed that digested plant extracts may antagonize the aryl hydrocarbon receptor and prevent bioactivation of the aryl compound benzo[a]pyrene. Thus, PAH risk from the ingestion of vegetation varies among plant species and may depend on antagonists present in the vegetation.
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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) | 0.001 | 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".