Previous gestational diabetes impairs long-term endothelial function in a mouse model of complicated pregnancy
Bibliographic record
Abstract
Women who develop gestational diabetes mellitis (GDM) display endothelial dysfunction up to 1 yr after pregnancy, despite a return to normoglycemia. It is unknown whether this dysfunction was preexisting or whether GDM pregnancy leads to long-term endothelial dysfunction. A mouse model that spontaneously develops GDM (Lepr(db/+)) was used to determine whether the endothelial dysfunction that develops during GDM is evident in later life. Heterozygous and wild-type (WT) controls were allowed to litter once, then age to 9-10 mo, and were compared with virgin controls. Vascular function of small mesenteric arteries was assessed using wire myography. Concentration response curves to the thromboxane A(2)mimetic U46619 and the endothelium-dependent vasodilator methacholine were constructed. Superoxide production and peroxynitrite formation was also measured. Mice with previous GDM displayed blood glucose concentrations similar to previously pregnant WT mice (8.0 +/- 0.1 vs. 7.1 +/- 0.3 mmol/l, P > 0.05). Arteries from mice with previous GDM displayed increased sensitivity to U46619 (EC(50) 5.2 +/- 0.7 vs. 45.2 +/- 1.0 nmol/l, P < 0.01) and impaired endothelium-dependent relaxation compared with WT controls (29 +/- 8 vs. 58 +/- 16 percent relaxation, P < 0.05). This was associated with increased superoxide production (93.3 +/- 2.3 vs. 64.6 +/- 1.6 mean fluorescence intensity, P < 0.001) and increased peroxynitrite formation (173.5 +/- 11.0 vs. 57.4 +/- 16.2 mean fluorescence intensity, P < 0.01) compared with virgin controls. In summary, endothelial dysfunction was evident in mice with previous GDM compared with previously healthy pregnant mice or virgin controls. These data suggest that GDM affects endothelial function and may contribute to an increased risk of cardiovascular disease.
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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 | 0.001 |
| 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 | 0.001 |
| 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".