Prenatal exposure to maternal undernutrition induces adult cardiac dysfunction
Bibliographic record
Abstract
An adverse environmental experience of the growing fetus may lead to permanent changes in the structure and function of organs that may predispose the individual to chronic diseases in later life; however, nothing is known about the occurrence and mechanisms of heart failure. We employed a rat model in which pregnant dams were fed diets containing either 180 g (normal) or 90 g (low) casein/kg for 2 weeks before mating and throughout pregnancy. The ejection fraction (EF) of the pups exposed to the low-protein (LP) diet was severely depressed in the first 2 weeks of life and was associated with an increase in cardiomyocyte apoptosis. This early depressed cardiac function was followed by progressive recovery and normalization of the EF of the offspring in the LP group. The left ventricular (LV) internal diameters were increased between 24 h and 84 d (12 weeks) of age in the LP-exposed group. Although between 3 d and 2 weeks of age the LV wall of the heart in the LP group was thinner, a progressive increase in LV wall thickness was seen. At 40 weeks of age, although the EF was normal, a two-fold elevation in LV end-diastolic pressure, reduced cardiac output, decreased maximum rates of contraction and relaxation, and reduced mean arterial pressure were observed. Our findings demonstrate that exposure of the developing fetus to a maternal LP diet programs cardiac dysfunction in the offspring in later life.
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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".