Dietary enzyme-hydrolyzed marine proteins supplementation promotes appetite, enhances lipid and protein metabolism in Litopenaeus vannamei fed reduced fish meal diets
Bibliographic record
Abstract
An 8-weeks feeding trial was conducted to evaluate the effect of dietary enzyme-hydrolyzed marine protein (EMP) supplementation on appetite, protein and lipid metabolism of Litopenaeus vannamei fed reduced fishmeal diets. The control group was supplemented with 30 % fishmeal, in the experimental group, 28 % fish meal was supplemented with 1 % EMP (1 % EMP), and 26 % fish meal with 2 % EMP (2 % EMP). The results showed that there were no significant differences in growth performance in each group ( P > 0.05). Shrimp in control group exhibited higher total cholesterol, triglyceride and low-density lipoprotein cholesterol in hemolymph than those in the other groups ( P < 0.05). The results of intestinal histology showed that shrimp fed with 1 % EMP diet exhibited higher fold height and fold width than those fed the other diets ( P < 0.001). Compared with control group, the lipid catabolism genes and regulatory factors ( atgl, hsl, ampkα , ampkγ , acox1 ) was significantly enhanced in 1 % EMP group ( P < 0.05). Moreover, the neurotransmitter and appetite related-genes expressions (such as oa-ta , tdc , tbh and ghs-r1 ) in 1 % EMP group of cerebral ganglion were significantly up-regulated than those in other group ( P < 0.05). Dietary 1 % EMP supplementation activated expressions of TORC1 pathway-related genes ( tor , rheb , slc3a2 , 4e-bp ) in the hepatopancreas than those feed the control diet ( P < 0.05). In conclusion, the results revealed that reducing 2 % fish meal and adding 1 % EMP in the diet could improve the appetite, lipid and protein metabolism, intestinal and hepatopancreas health of juvenile Pacific white shrimp.
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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".