Coronary artery formation in the offspring of female mice with pregestational diabetes
Bibliographic record
Abstract
Women with pregestational diabetes have a 5-fold increased risk of congenital heart defects in their offspring. Major congenital heart diseases involving malformation of ventricles, atria and great arteries have been reported in humans and diabetic animal models. Whether the coronary artery formation is affected by maternal diabetes remains elusive. We investigated coronary artery formation in the offspring of mice with pregestational diabetes. Adult C57BL/6 female mice were treated with streptozotocin to induce diabetes. One week later, they were bred with C57BL/6 males and their offspring was harvested at E9.5, E12.5 and P1. Hearts were evaluated for coronary artery morphology and immunostained for Wilm's tumor-1 protein to study changes in proepicardium organ (PEO) and the epicardium. Our results showed that coronary arteries total volume was significantly decreased in the offspring of diabetic mice at P1. PEO at E9.5 was similar in size between the offspring of diabetic and non-diabetic mice. However, a significant reduction in the number of epicardial cells was observed in the diabetic offspring at E12.5. We conclude that pregeatational diabetes induces coronary artery malformation possibly by disrupting epicardial development, which is critical for formation of coronary arteries through epithelial to mesenchymal transformation. This research is supported by HSFO.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".