Paternal Methyl Donor Supplementation in Rats Improves Fertility, Physiological Outcomes, Gut Microbial Signatures and Epigenetic Markers Altered by High Fat/High Sucrose Diet
Bibliographic record
Abstract
Increased consumption of high fat/sucrose (HF/S) diets has contributed to rising rates of obesity and its co-morbidities globally, while also negatively impacting male reproductive health. Our objective was to examine whether adding a methyl donor cocktail to paternal HF/S diet (HF/S+M) improves health status in fathers and offspring. From 3–12 weeks of age, male Sprague Dawley rats consumed a HF/S or HF/S+M diet. Offspring were followed until 16 weeks of age. Body composition, metabolic markers, gut microbiota, DNA methyltransferase (DNMT) and microRNA expression were measured in fathers and offspring. Compared to HF/S, paternal HF/S+M diet reduced fat mass in offspring (p < 0.005). HF/S+M fathers consumed 16% fewer kcal/day, which persisted in HF/S+M female offspring and was explained in part by changes in serum glucagon-like peptide-1 (GLP-1) and peptide tyrosine tyrosine (PYY) levels. Compared to HF/S, HF/S+M fathers had a 33% improvement in days until conception and 300% fewer stillbirths. In fathers, adipose tissue DNMT3a and hepatic miR-34a expression were reduced with HF/S+M. Adult male offspring showed upregulated miR-24, -33, -122a and -143 expression while females exhibited downregulated miR-33 expression. Fathers and offspring presented differences in gut microbial signatures. Supplementing a paternal HF/S diet with methyl-donors improved fertility, physiological outcomes, epigenetic and gut microbial signatures intergenerationally.
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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) | 0.002 | 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".