Effects of estradiol on measurements of conduit artery endothelial function after ischemia and reperfusion in premenopausal women
Bibliographic record
Abstract
In premenopausal women, ovarian steroids are felt to play a role in the prevention of cardiovascular disease. We aimed to assess whether menstrual cycle variations in estrogen can modify the response to ischemia–reperfusion (IR) injury in humans. In an investigator-blinded crossover study, 10 healthy premenopausal women with regular menstrual cycles were studied. They had flow-mediated dilatation (FMD) measured by ultrasound in the radial artery before and after IR (15 min of brachial artery ischemia, 15 min of reperfusion) during both the early and late follicular phases of the menstrual cycle. The order of these visits was not randomized. IR significantly blunted FMD in the early follicular phase (pre-IR: 7.1% ± 1.0%; post-IR: 3.6% ± 1.0%, P = 0.01) when estradiol levels were low (148.4 ± 19.8 pmol/L). Conversely, FMD was preserved after IR during the late follicular phase (pre-IR: 7.2% ± 0.9%; post-IR: 7.0% ± 0.8%, P = NS, P = 0.03 compared with early follicular) when estradiol levels were high (825.7 ± 85.8 pmol/L, P < 0.001 compared with early follicular). There was a significant inverse relationship between estradiol concentration and IR-induced endothelial dysfunction (i.e., change in FMD after IR) (r = 0.59, r 2 = 0.36, P < 0.01). These findings demonstrate, for the first time in humans, a clear relationship between the cyclical changes in serum concentrations of estradiol and the endothelium’s response to IR.
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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 | 0.001 | 0.002 |
| 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".