Microbiota Changes in Fathers Consuming a High Prebiotic Fiber Diet Have Minimal Effects on Male and Female Offspring in Rats
Bibliographic record
Abstract
Background: Consuming a diet high in prebiotic fiber has been associated with improved metabolic and gut microbial parameters intergenerationally, although studies have been limited to maternal intake with no studies examining this effect in a paternal model. Method: Male Sprague Dawley rats were allocated to either (1) control or (2) oligofructose-supplemented diet for nine weeks and then mated. Offspring consumed control diet until 16 weeks of age. Bodyweight, body composition, glycemia, hepatic triglycerides, gastrointestinal hormones, and gut microbiota composition were measured in fathers and offspring. Results: Paternal energy intake was reduced, while satiety inducing peptide tyrosine tyrosine (PYY) gut hormone was increased in prebiotic versus control fathers. Increased serum PYY persisted in female prebiotic adult offspring. Hepatic triglycerides were decreased in prebiotic fathers with a similar trend (p = 0.07) seen in female offspring. Gut microbial composition showed significantly reduced alpha diversity in prebiotic fathers at 9 and 12 weeks of age (p < 0.001), as well as concurrent differences in beta diversity (p < 0.001), characterized by differences in Bifidobacteriaceae, Lactobacillaceae and Erysipelotrichaceae, and particularly Bifidobacterium animalis. Female prebiotic offspring had higher alpha diversity at 3 and 9 weeks of age (p < 0.002) and differences in beta diversity at 15 weeks of age (p = 0.04). Increases in Bacteroidetes in female offspring and Christensenellaceae in male offspring were seen at nine weeks of age. Conclusions: Although paternal prebiotic intake before conception improves metabolic and microbiota outcomes in fathers, effects on offspring were limited with increased serum satiety hormone levels and changes to only select gut bacteria.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".