N-Acetylcysteine prevents congenital heart defects induced by pregestational diabetes
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Bibliographic record
Abstract
BACKGROUND: Pregestational diabetes is a major risk factor of congenital heart defects (CHDs). Glutathione is depleted and reactive oxygen species (ROS) production is elevated in diabetes. In the present study, we aimed to examine whether treatment with N-acetylcysteine (NAC), which increases glutathione synthesis and inhibits ROS production, prevents CHDs induced by pregestational diabetes. METHODS: Female mice were treated with streptozotocin (STZ) to induce pregestational diabetes prior to breeding with normal males to produce offspring. Some diabetic mice were treated with N-acetylcysteine (NAC) in drinking water from E0.5 to the end of gestation or harvesting of the embryos. CHDs were identified by histology. ROS levels, cell proliferation and gene expression in the fetal heart were analyzed. RESULTS: Our data show that pregestational diabetes resulted in CHDs in 58% of the offspring, including ventricular septal defect (VSD), atrial septal defect (ASD), atrioventricular septal defects (AVSD), transposition of great arteries (TGA), double outlet right ventricle (DORV) and tetralogy of Fallot (TOF). Treatment with NAC in drinking water in pregestational diabetic mice completely eliminated the incidence of AVSD, TGA, TOF and significantly diminished the incidence of ASD and VSD. Furthermore, pregestational diabetes increased ROS, impaired cell proliferation, and altered Gata4, Gata5 and Vegf-a expression in the fetal heart of diabetic offspring, which were all prevented by NAC treatment. CONCLUSIONS: Treatment with NAC increases GSH levels, decreases ROS levels in the fetal heart and prevents the development of CHDs in the offspring of pregestational diabetes. Our study suggests that NAC may have therapeutic potential in the prevention of CHDs induced by pregestational diabetes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 it