Co-administration of a Rhododendron tomentosum extract does not affect mercury tissue concentrations and excretion rate in methylmercury-treated adult male rats
Bibliographic record
Abstract
Abstract Objectives Consumption of fish/seafood is clearly linked to higher mercury levels in human tissue samples. However, correlations between methylmercury (MeHg) intakes calculated from dietary surveys and mercury body burdens are usually weak and can vary across populations. Different factors may affect MeHg absorption, distribution, metabolism and excretion, including co-exposures to phytochemicals and antibiotics, which were shown to affect mercury body burdens in rodents. Based on the observation that rat pups developmentally exposed to MeHg and a Rhododendron tomentosum extract (Labrador Tea) presented significantly higher blood mercury levels at weaning compared to pups exposed to MeHg alone, the modulation of MeHg toxicokinetics by Labrador Tea was further investigated in adult rats. Results Total mercury levels were quantified in the blood, liver, kidney and feces of adult male rats exposed to MeHg (1.2 mg/kg bodyweight/day, for 3 weeks) administered either alone or in combination with Labrador Tea (100 mg/kg bodyweight/day) or with an antibiotics cocktail (to inhibit MeHg demethylation by gut bacteria). While the reduced fecal excretion and higher blood mercury levels expected from antibiotics-treated rats were observed, mercury levels in samples from Labrador Tea-treated rats were not significantly different from those measured in samples from rats exposed to MeHg alone.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".