Increased dietary intake of tyrosine upregulates melanin deposition in the hair of adult black-coated dogs
Bibliographic record
Abstract
The principle determinant of melanin derived hair colour and patterning in mammals is genetic, but environmental factors are now thought to play a role. It has been shown that the concentration of melanins in cat hair is influenced by the amino acid composition of their diets. Also, puppies were found to require tyrosine (Tyr) intake significantly greater than that recommended for normal growth and development in order to optimize melanin expression in their coats. Much of the work to date has been conducted in growing animals. Less is known about the relationship between nutrition and hair melanin deposition in healthy adult animals. In this study, we fed 2 groups of adult black Labrador retrievers (12 dogs/group) different concentrations of Phe + Tyr (5.6 vs. 3.5 g/Mcal) for 24 weeks and used spectrophotometric measurements every 8 weeks to detect any associated changes in the dogs’ hair colour. The higher intake dogs showed reduced dilution of their black coat pigment compared with the lower intake dogs. Specifically, following 16 weeks at the higher intake, the dogs showed less yellow pigmentation to their coats (P = 0.0032), and after 24 weeks at the higher intake, the dogs showed less red (P < 0.0001) and yellow (P< 0.0001), as well as greater overall dark pigmentation (P < 0.0001). In conclusion, we have demonstrated for the first time that colour expression in the hair-coat of adult dogs is dependent on dietary intake of Tyr, and that the requirement appears to be in excess of the minimum level recommended to maintain health.
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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".