Maternal high fat diet alters lactation-specific miRNA expression and programs the DNA methylome in the amygdala of female offspring
Bibliographic record
Abstract
Abstract Adverse maternal diets high in saturated fats are associated with impaired neurodevelopment and epigenetic modifications in offspring. Maternal milk, the primary source of early life nutrition in mammals, contains lactation-specific microRNAs (miRNAs). Lactation-specific miRNAs have been found in various offspring tissues in early life, including the brain. We examined the effects of maternal high saturated fat diet (mHFD) on lactation-specific miRNAs that inhibit DNA methyltransferases (DNMTs), enzymes that catalyze DNA methylation modifications, in the amygdala of female offspring during early life and adulthood. Offspring exposed to mHFD showed reduced miR-148/152 and miR-21 transcripts in stomach milk and amygdala in the first week of life. This was associated with increased DNMT1 expression, DNMT activity, and global DNA methylation in the amygdala. In addition, persistent DNA methylation modifications from early life to adulthood were observed in pathways involved in neurodevelopment as well as genes regulating the DNMT machinery and protein function in mHFD offspring. The findings indicate a novel link between exogenous, lactation-specific miRNAs and developmental programming of the neural DNA methylome in offspring.
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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) | 0.002 | 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".