Evidence for an interaction between linoleic acid intake and skin barrier properties in healthy dogs – a pilot study
Bibliographic record
Abstract
Abstract Dogs suffer from skin associated issues with a disproportionate frequency, with consequent interest in providing nutrition to optimize their skin's natural defences. Linoleic acid (LA) is known as an essential nutrient in dogs and plays a critical part in the lipid component of skin barrier formation. Minimum requirements have been defined, primarily based on eliminating signs of deficiencies such as dry, flaky skin and inflammation. Zn has been shown as an important nutrient for maintaining epidermal health. This pilot study investigated whether there are skin barrier benefits from feeding both linoleic acid and Zn at levels significantly in excess of published minimum requirements. Eight Labrador retrievers were fed a diet containing 3.8 g/Mcal LA, 21 mg/Mcal Zn for 12 weeks to establish baseline conditions for all dogs (basal diet). After this period, for a further 12 weeks, the dogs were switched onto a diet containing 7.9 g/Mcal LA and 50 mg/Mcal Zn (test diet). Transepidermal water loss (TEWL measurements) were used as a measure of skin quality and integrity and were taken at the end of the initial feeding period, and at 6 and 12 weeks of the test feeding period. TEWL was reduced by 8.11 g/m2/h (P < 0.001) six weeks after instigation of the test diet, and by 7.52 g/m2/h (P < 0.005) at 12 weeks, compared to the levels (14.73 g/m2/h) at the end of the basal feeding trial period. The results showed evidence of improved barrier properties as TEWL when feeding higher levels of LA and Zn for six and 12 weeks.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".