Impact of Dietary Fructose on the Lipid Profile in Six Macaws
Bibliographic record
Abstract
Atherosclerosis is frequently diagnosed in captive parrots. Recent studies have highlighted the potential role of high fructose intake in the development of human cardiovascular disease. The objective of this study was to investigate the effects of dietary fructose on the lipid profile in psittacine birds. Six macaws, composed of 3 green-winged macaws (Ara chloropterus, 2 females, 1 male), and 3 blue-and-gold macaws (Ara ararauna, 1 female, 2 males), ranging from 15 to 26 years of age, were used as subject animals for this dietary investigation. Initially, fruits were removed from the diet and replaced with vegetables lower in fructose for a month. Then, with a crossover study design, each bird was randomly selected to receive either 34 kcal of a fructose solution daily for 5 days then an equivalent volume of water for 5 days, or water in the first 5 days followed by the 34 kcal fructose solution. Lipid profiles were repeatedly performed over the course of the study at specific intervals. Serum cholesterol (3.01–5.55 mmol/L), triglycerides (0.27–2.70 mmol/L), high-density lipoprotein–cholesterol (1.43–4.79 mmol/L), low-density lipoprotein–cholesterol (0.02–0.85 mmol/L), and very low density lipoprotein–cholesterol (0.12–1.22 mmol/L) levels were not statistically significantly different over time and treatment. Although no significant effect could be demonstrated in this study, further studies are needed to investigate the effect of a high fructose intake in psittacine birds, because it could have a deleterious influence on their cardiovascular health if proven to be linked with dyslipidemia as reported in humans. Higher amounts of fructose and longer periods of administration should be considered for future studies.
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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 | 0.001 | 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".