Estrogen and sympathetic modulation of hindlimb blood flow variability in rats
Bibliographic record
Abstract
Recent evidence suggests that males and females rely on different physiologic mechanisms to maintain blood flow and vasculature conductance. To test the hypothesis that sympathetic inputs affect hindlimb flow variability, the coefficient of variation (CV = standard deviation/mean) of hindlimb flow and conductance were measured in male and female animals of various rat strains (Sprague Dawley, Spontaneously Hypertensive and Wistar‐Kyoto). One thousand consecutive heart beats at baseline and during sympathectomy (25mg/kg Hexamethonium; Hex) were used to assess each CV. Female rats (any strain) exhibited greater CV in hindlimb conductance at baseline compared to males (grouped gender averages: 35±19AU vs. 12±11AU, respectively; P<0.05 ). A subgroup of female hypertensive animals that were ovariectomized (OVX) exhibited lower CV (25±21AU) compared to their intact counterparts (41±14AU; P<0.05 ), and OVX animals given estrogen (51±22AU; P<0.05) . The variability in female animals was driven by changes in hindlimb flow, and was blunted (i.e. not different from males) following Hex (19±13AU vs. 10±6AU, n.s. between female and male animals respectively). Therefore, blood flow variability was greater in the hindlimb of female rats of various strains and this variability was related to both estrogen and sympathetic mechanisms. Supported by CIHR.
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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) | 0.000 | 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".