Potential Impact of Metabolic and Gut Microbial Response to Pregnancy and Lactation in Lean and Diet‐Induced Obese Rats on Offspring Obesity Risk
Bibliographic record
Abstract
SCOPE: Maternal obesity programs metabolic dysfunction in offspring, increasing their susceptibility to obesity and metabolic diseases in later life. Moreover, pregnancy and lactation are associated with many metabolic adaptations, yet it is unclear how diet-induced maternal obesity may interrupt these processes. METHODS AND RESULTS: H NMR serum metabolomics analysis was performed on samples collected pre-pregnancy and in pregnant and lactating lean and high fat/sucrose (HFS) diet-induced obese Sprague-Dawley rats to identify maternal metabolic pathways associated with developmental programming of offspring obesity. Gut microbial composition was assessed using qPCR. Offspring of HFS dams had nearly 40% higher adiposity at weaning compared to offspring of lean dams. While pregnancy and lactation were associated with distinct maternal metabolic changes common to both lean and obese dams, we identified several metabolic differences, potentially implicating dysregulated one-carbon and mammary gland metabolism in the metabolic programming of obesity. Gut microbial composition was significantly altered with obesity, and both gestation and lactation were accompanied by changes in gut microbiota. CONCLUSION: Diet-induced maternal obesity and consumption of an obesogenic maternal diet results in differential metabolic and gut microbial adaptations to pregnancy and lactation; these maladaptations may be directly involved in maternal programming of offspring susceptibility to obesity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".