Hepatoprotective action of including (<i>Euterpe oleracea</i> Mart.) in the diet of Koi carp (<i>Cyprinus carpio</i>)
Bibliographic record
Abstract
This study evaluated the hepatoprotective effect of açaí inclusion in the diets of juvenile Koi carp ( Cyprinus carpio ). For the experimental trial, 240 fish were distributed across 20 tanks (n = 12), using a completely randomized design that involved four treatments and one control group. The tested diets were: control (DC0.0%) with no açaí; 0.5% açaí (DA0.5%); 1.0% açaí (DA1.0%); 1.5% açaí (DA1.5%); and 2.0% açaí (DA2.0%) inclusion. The açaí-supplemented diets showed higher concentrations of phenolic compounds, tannins, and flavonoids, as well as superior antioxidant potential compared to the control group (p<0.05). After 30 days of feeding, four specimens from each tank were collected for histological analysis. The analysis of variance at 5% significance revealed a significant difference in the loss of the hepatic cord arrangement, with a reduction of 62.50 ± 13.06% in the control group (DC0.0%) compared to the other treatments. The DA2.0% diet exhibited greater congestion in the sinusoids (54.17 ± 20.87%) compared to the control (33.33 ± 11.68%). The control group also showed a higher number of mononuclear inflammatory infiltrates (72.92 ± 7.54%). Necrotic areas were more intense in the control group (64.58 ± 12.87%) and less pronounced in the DA1.5% diet (43.75 ± 24.13%). The results suggest that diets with intermediate levels of açaí can exert a hepatoprotective effect on Koi carp, indicating that diets with the inclusion of açaí for carp can help in growth and nutrient assimilation, since the liver tissue metabolizes a large amount of the substance, but additional studies are needed to determine the ideal dose and explore its application in other fish species.
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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) | 0.001 | 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".