Dietary lipid content reorganizes gut microbiota and probiotic L. rhamnosus attenuates obesity and enhances catabolic hormonal milieu in zebrafish
Bibliographic record
Abstract
In the present study, we explored whether dietary lipid content influences the gut microbiome in adult zebrafish. Diets containing three different lipid levels (high [HFD], medium [MFD], and low [LFD]) were administered with or without the supplementation of Lactobacillus rhamnosus (P) to zebrafish in order to explore how the dietary lipid content may influence the gut microbiome. Dietary lipid content shifted the gut microbiome structure. The addition of L. rhamnosus in the diets, induced transcriptional reduction of orexigenic genes, upregulation of anorexigenic genes, and transcriptional decrease of genes involved in cholesterol and triglyceride (TAG) metabolism, concomitantly with lower content of cholesterol and TAG. Probiotic feeding also decreased nesfatin-1 peptide in HFD-P and attenuated weight gain in HFD-P and MFD-P fed zebrafish, but not in LFD-P group. Intestinal ultrastructure was not affected by dietary fat level or probiotic inclusion. In conclusion, these findings underline the role of fat content in the diet in altering gut microbiota community by shifting phylotype composition and highlight the potential of probiotics to attenuate high-fat diet-related metabolic disorder.
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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".