Circulating small extracellular vesicles increase after an acute bout of moderate-intensity exercise in pregnant compared to non-pregnant women
Bibliographic record
Abstract
The physiological and molecular mechanisms linking prenatal physical activity and improvements in maternal-fetal health are unknown. It is hypothesized that small extracellular vesicles (EVs, ~ 10-120 nm) are involved in tissue cross-talk during exercise. We aimed to characterize the circulating small EV profile of pregnant versus non-pregnant women after an acute bout of moderate-intensity exercise. Pregnant (N = 10) and non-pregnant control (N = 9) women performed a single session of moderate-intensity treadmill walking for 30 min. Plasma was collected immediately pre- and post-exercise, and small EVs were isolated by differential ultracentrifugation. EV presence was confirmed by western blotting for the small EV proteins TSG-101 and flottilin-1. Small EVs were quantified by size and concentration using nanoparticle tracking analysis and transmission electron microscopy. All EV fractions were positive for TSG-101 and flotillin-1, and negative for calnexin. Mean vesicle size at baseline and percent change in size post-exercise were not different between groups. At baseline, pregnant women had higher levels of small EVs compared to controls (1.83E+10 ± 1.25E+10 particles/mL vs. 8.11E+09 ± 4.04E+09 particles/mL, respectively; p = 0.032). Post-exercise, small EVs increased significantly in the circulation of pregnant compared to non-pregnant women after correcting for baseline values (64.7 ± 24.6% vs. - 23.3 ± 26.1%, respectively; F = 5.305, p = 0.035). Further research is needed to assess the functional roles of exercise-induced small EVs in 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".