Effect of dietary zeaxanthin on tissue distribution of zeaxanthin and lutein in quail.
Bibliographic record
Abstract
PURPOSE: The xanthophyll carotenoids (lutein and zeaxanthin) are hypothesized to delay progression of age-related macular degeneration. The quail has a cone-dominant retina that accumulates carotenoids. The purpose of these experiments was to characterize the carotenoid composition of retina, serum, liver, and fat in quail and to determine whether dietary enrichment with zeaxanthin alters zeaxanthin or lutein concentrations in these tissues. METHODS: Quail were fed for 6 months with a commercial turkey diet (T group; n = 8), carotenoid-deficient diet (C- group; n = 8), or a carotenoid-deficient diet supplemented with 35 mg 3R,3'R-zeaxanthin per kilogram of food, (Z+ group; n = 8). Zeaxanthin was derived from Sphingobacterium multivorum (basonym Flavobacterium). Carotenoids in serum, retina, liver, and fat were analyzed by HPLC. RESULTS: As in the primate fovea, the retina accumulated zeaxanthin, lutein, and cryptoxanthin, and preferentially absorbed zeaxanthin (P < 0.005). In contrast, lutein was preferentially absorbed by liver (P < 0.01) and fat (P < 0.0001). In supplemented females, zeaxanthin increased approximately 4-fold in retina, and 74-, 63- and 22-fold in serum, liver, and fat, respectively. In males, zeaxanthin was elevated approximately 3-fold in retina, and 42-, 17-, and 12-fold in serum, liver, and fat, respectively. Birds fed the Z+ diet absorbed a higher fraction of dietary lutein into serum, but lutein was reduced in the retina (P < 0.05). CONCLUSIONS: Xanthophyll profiles in quail mimic those in primates. Dietary supplements of zeaxanthin effectively increased zeaxanthin concentrations in serum, retina, liver, and fat. The robust response to zeaxanthin supplementation identifies the quail as an animal model for exploration of factors regulating delivery of dietary carotenoids to the retina.
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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".