Dietary probiotic <i>Pediococcus acidilactici</i> MA18/5M modulates the intestinal microbiota and stimulates intestinal immunity in rainbow trout (<i>Oncorhynchus mykiss</i>)
Bibliographic record
Abstract
Abstract A study was conducted to evaluate the probiotic effect of Pediococcus acidilactici MA18/5M on rainbow trout, Oncorhynchus mykiss. Fish (310 ± 9 g) were fed a control diet or a P. acidilactici‐supplemented diet (at 2.4 × 106 CFU/g) for 4 weeks. The probiotic was observed to populate the intestine with levels ranging from log 3.7 to 5.4 CFU/g. Furthermore, these populations were able to persist for at least 24 hr after the cessation of probiotic feeding. High‐throughput sequencing analysis of bacterial 16S rRNA libraries demonstrated that P. acidilactici was able to modulate the gut microbiome of rainbow trout and that the probiotic was detected as a common taxon on the mucosa and in the digesta of the probiotic fish (p < .05). Real‐time polymerase chain reaction demonstrated that feeding the probiotic upregulated pro‐inflammatory cytokines, interleukin‐1β, and interleukin‐8 and downregulated anti‐inflammatory interleukin‐10 compared to the control‐fed fish. Furthermore, the mRNA levels for the mucosal antibody immunoglobulin T was also elevated in probiotic‐fed fish. These findings help to explain some of the mechanisms behind the previously reported observed benefits of using this probiotic in the intestinal morphology and immunity of rainbow trout.
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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 | 0.000 |
| 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".