Vitamin A physiology in the precocious harbour seal (<i>Phoca vitulina</i>): a tissue-based biomarker approach
Bibliographic record
Abstract
Vitamin A is a nutrient essential to all mammals for growth and development, as well as for the maintenance of reproductive, endocrine, and immune systems. Environmental contaminant-related disruption of vitamin A has been observed in many wildlife species and can therefore be used as a biomarker of toxic effects. However, the natural processes regulating vitamin A uptake, storage, and distribution among compartments are poorly understood in marine mammals. In this study, 20 young healthy harbour seals (Phoca vitulina) were captured to establish a compartment-based model providing a foundation for a mechanistic understanding of vitamin A physiology and disruption. Vitamin A (retinol, retinyl palmitate, and (or) retinoic acid) was quantified in blood plasma and in biopsy samples of liver, blubber, and skin. Although the highest concentrations of vitamin A were found in liver, blubber represents a more important storage depot, with an estimated 66% of the total retinoid content of the compartments measured. We suggest that vitamin A physiology in the precocious harbour seal has evolved to deal with high vitamin A availability during a short nursing period and to sustain growth during the postweaning fast. Positive correlations in vitamin A concentrations among liver, blubber, and skin support the use of less invasive biopsy sampling of just blubber or skin, which can provide physiologically relevant information in biomarker studies of free-ranging marine mammals.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".