Effect of Exercise on Vascular Superoxide Dismutase Expression in High-Risk Pregnancy
Bibliographic record
Abstract
Endothelial dysfunction of the maternal vasculature induced by pro-oxidants may contribute to the development of preeclampsia. Obesity results in vascular inflammation and oxidative stress and is therefore a risk factor for preeclampsia. Regular exercise is known to induce antioxidants. We recently demonstrated that stretchers (subjects who performed low-intensity exercises) had a lower incidence of preeclampsia as opposed to walkers (moderate-intensity exercise; 2.6% versus 14.6%). We now seek to determine the possible protective mechanisms. We hypothesized that stretchers will have higher vascular levels of the antioxidant superoxide dismutase (SOD) and plasma transferrin levels, an antioxidant marker. We conducted immunohistochemical analyses of blood vessels embedded in fat biopsy samples obtained during cesarean sections from women who were randomized to either stretching ( N = 6) or walking ( N = 5) exercises. In addition, levels of plasma transferrin were measured. SOD expression was increased ( P < 0.05) in stretchers [106.3 (interquartile range 84.2 to 127.8 arbitrary units (AU)] when compared with that of walkers [56.92 (interquartile range 46.35 to 82.32 AU)]. Transferrin levels continued to increase throughout gestation only among the stretchers. There appears to be a higher antioxidant protective effect in subjects who performed low-intensity exercise during pregnancy.
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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 | 0.001 |
| 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".