Macronutrient Ratio Modification in a Semi-Purified Diet Composition: Effects on Growth and Body Composition of Juvenile Zebrafish <i>Danio rerio</i>
Bibliographic record
Abstract
Abstract The interaction of dietary macronutrients in the control of growth, body composition, health, and longevity has received renewed attention. The protein leverage hypothesis proposes an inverse relationship between dietary protein levels and obesity development (low protein promoting high obesity), although the majority of laboratory studies have utilized a design modulating the protein amount within a single dietary protein source composition. We investigated whether varying the levels of dietary protein amount and sources would have impacts on growth and body composition using the Zebrafish Danio rerio model. At 28 d postfertilization, Zebrafish were fed 1 of 12 dietary treatments for 12 weeks. Diets contained different protein sources (fish protein hydrolysate [FPH], soy protein isolate [SOY], casein [CAS], or a mixture of all three sources including wheat gluten [MIX]). Sources were formulated at three protein concentrations (18, 33, or 48% as fed, substituted with wheat starch for caloric balance). Body length, height, and weight were measured over time and at termination. Contributions of macronutrients to growth and body fat outcomes were estimated by LASSO (least absolute shrinkage and selection operator) regression. Male and female length, height, and weight increased significantly in response to increasing dietary protein. Male and female fish fed SOY or FPH had the highest amount of body lipid at all protein concentrations relative to those fed CAS or MIX. Relative body lipid was highest in fish that were fed the lowest protein concentration. These data suggest an important role of macronutrient balances, including dietary protein amount and source, in relation to the protein: energy (carbohydrate and lipid) ratio on growth and body composition outcomes. These outcomes may ultimately reflect metabolic alterations that can lead to confounding interpretations of health and disease status. Furthermore, these data reinforce the need to consider and report dietary composition in establishing rigorous and reproducible nutritional guidelines for Zebrafish.
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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 | 0.001 |
| 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".