Mismatched pre- and postnatal nutrition leads to cardiovascular dysfunction and altered renal function in adulthood
Bibliographic record
Abstract
The early life environment has long-term implications for the risk of developing cardiovascular (CV) disease in adulthood. Fetal responses to changes in maternal nutrition may be of immediate benefit to the fetus, but the long-term effects of these adaptations may prove detrimental if nutrition in postnatal life does not match that predicted by the fetus on the basis of its prenatal environment. We tested this predictive adaptive response hypothesis with respect to CV function in sheep. We observed that a mismatch between pre- and postnatal nutrient environments induced an altered CV function in adult male sheep that was not seen when environments were similar. Sheep that received postnatal undernutrition alone had altered growth, CV function, and basal hypothalamo-pituitary-adrenal axis activity in adulthood. Prenatal undernutrition induced greater weight gain by weaning compared with the prenatal control diet, which may provide a reserve in the face of a predicted poor diet in later life. In an adequate postnatal nutrient environment (i.e., relatively mismatched), these offspring exhibited cardiac hypertrophy and altered CV function in adulthood. These data support the concept that adult CV function can be determined by developmental responses to intrauterine nutrition made in expectation of the postnatal nutritional environment, and that if these predictions are not met, the adult may be maladapted and at greater risk of CV disease. Our findings have substantial implications for devising strategies to reduce the impact of a mismatch in nutrition levels in humans undergoing rapid socio-economic transitions in both developing and developed societies.
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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) | 0.001 | 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".