Regulation of feed intake, digestive enzyme activity, and growth in response to live feed and prepared diet during early rearing of <i>Labeo rohita</i>
Bibliographic record
Abstract
A 35 day feeding trial in a replicate of five was conducted to evaluate the impact of partial and total replacement of live feed (LF) with nanoparticulate-prepared diet (ND) on early rearing of rohu ( Labeo rohita (Hamilton, 1822)). Larvae 3 days after hatching (DAH) were evenly distributed into three groups; T1 was reared exclusively on LF, T2 was on ND, and T3 was co-fed both LF and ND (1:1). All groups showed a feed-dependent increase in growth and the expression of genes involved in feed intake and growth with age DAH. The T3 group showed significantly higher weight gain, specific growth rate, and expression of insulin-like growth factor-1 followed by the T2 group, while the highest expression of ghrelin and growth hormone secretagogue receptor was observed in T3 followed by T1. Furthermore, leptin showed the highest expression in the T2 followed by the T1 group. The intestinal enzymes showed variable trends, with the highest activity of cellulase, amylase, and protease in the T1, T2, and T3 groups, respectively. Moreover, in all groups, cellulase increased continuously with age DAH, while amylase and protease showed a positive correlation up to 30 DAH and then declined. The results of this study could be helpful in larval nutrition programming.
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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) | 0.001 | 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".