A diet-change modulates the previously established bacterial gut community in juvenile brown trout (Salmo trutta)
Bibliographic record
Abstract
The aim of the present study was to investigate the impact of dietary plant proteins on the gut microbiome of first feeding brown trout (Salmo trutta) reproduced from wild stocks and to evaluate whether the initial microbiome of brown trout fry can be permanently manipulated by the first feeding diet. Therefore, brown trout fry was fed diets based on either 0%, 50% or 90% plant-derived proteins from first feeding onwards and via 16S rRNA gene sequencing a strong dietary influence on the bacterial gut community on phylum and order level was detected. Proteobacteria and Fusobacteria were significantly enhanced when fishmeal was integrated into the experimental diet, whereas plant-derived proteins significantly promoted Firmicutes and Bacteroidetes. In order to evaluate whether the first feeding diet had a permanent effect on the initially established microbial gut community of juvenile brown trout, a cross-over diet-change was applied 61 days post first feeding. 48 days after the diet-change, the gut microbiome of all dietary groups was significantly different from the one initially established after first feeding. Moreover, the first feeding diet had no statistically significant influence on the gut microbiome after the diet-change, demonstrating no permanent effect on the gut microbiome formation.
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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".