Effects of estrogen and progesterone on cerebrovascular responses to euoxic hypercapnia in women
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVES: To determine the cerebral blood flow response to step changes in end-tidal Pco(2) in premenopausal women (n = 10; mean age±standard deviation 27.0±6.4 years) during the follicular (FP), mid-cycle (MC) and luteal (LP) phases of the menstrual cycle. METHODS: Transcranial Doppler ultrasound was used to measure beat-by-beat averaged peak blood flow velocity (V(p)) in the middle cerebral artery in response to 20 min of euoxic hypercapnia (end-tidal PO(2) = 88 Torr; end-tidal PCO(2) = 7.0 Torr above resting values). The V(p) responses to euoxic hypercapnia were fitted to a simple mathematical model that included gain terms for the on (G(on)) and off (G(off)) responses, time constants for the on (τ(on)) and off (τ(off)) responses, baseline terms and a time delay (T(d)). RESULTS: Serum progesterone levels were significantly greater for LP compared to FP and MC (40.6±13.2 vs. 32.6±1.4 nmol/l (p < 0.001) and 8.8±3.8 nmol/l (p < 0.001), respectively). Serum estrogen concentrations were significantly lower in FP compared to MC and LP (150.9±51.2 vs. 506.5±220.5 pmol/l (p = 0.002) and 589.1±222.8 pmol/l (p < 0.001), respectively). Arterial PCO(2) was significantly greater in MC compared to LP (35.0±2.1 and 32.6±1.4 Torr, respectively; p = 0.02). There was a significant increase in G(off) during LP compared with FP and MC (3.38±0.68 vs. 2.79±0.82 cm s(-1) Torr(-1) (p = 0.021) and 2.74±0.90 (p = 0.018) cm s(-1) Torr2(1), respectively). Progesterone and the estrogen/progesterone ratio contributed to the observed differences in G(off). CONCLUSION: There is an increase in G(off) during LP that is explained, at least in part, by increases in serum progesterone and estrogen and a decrease in arterial PCO(2).
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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