Methylmercury accumulation and elimination in mink (<i>Neovison vison</i>) hair and blood: Results of a controlled feeding experiment using stable isotope tracers
Bibliographic record
Abstract
Concentrations of metals in hair are used often to develop pharmacokinetic models for both animals and humans. Although data on uptake are available, elimination kinetics are less well understood; stable isotope tracers provide an excellent tool for measuring uptake and elimination kinetics. In the present study, methylmercury concentrations through time were measured in the hair and blood of mink (Neovison vison) during a controlled 60-d feeding experiment. Thirty-four mink were fed a standard fish-based diet for 14 d, at the end of which (day 0), 4 mink were sacrificed to determine baseline methylmercury (MeHg) concentrations. From day 0 to day 10, the remaining mink were fed a diet consisting of the base diet supplemented with 0.513 ± 0.013 µg Me(199) Hg/g and 0.163 ± 0.003 µg Me(201) Hg/g. From day 10 to day 60, mink were fed the base diet supplemented with 0.175 ± 0.024 µg Me(201) Hg/g. Animals were sacrificed periodically to determine accumulation of Me(201) Hg in blood and hair over the entire 60-d period and the elimination of Me(199) Hg over the last 50 d. Hair samples, collected from each mink and cut into 2.0-mm lengths, indicate that both isotopes of MeHg appeared in the hair closest to the skin at approximately day 10, with concentrations in the hair reaching steady state from day 39 onward. The elimination rate of Me(199) Hg from the blood was 0.05/d, and the ratio of MeHg in the hair to blood was 119. A large fraction of MeHg (22% to >100%) was stored in the hair, suggesting that in fur-bearing mammals the hair is a major route of elimination of MeHg from the body.
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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 | 0.001 |
| 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".