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Effects of Ethinyl Estradiol, Estradiol, and Testosterone on Hindlimb Endothelial Function In Vivo

2002· article· en· W2018647123 on OpenAlexaff
Rabelais Tatchum‐Talom, Céline Martel, André Marette

Bibliographic record

VenueJournal of Cardiovascular Pharmacology · 2002
Typearticle
Languageen
FieldMedicine
TopicMenopause: Health Impacts and Treatments
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsOvariectomized ratHindlimbEndocrinologyInternal medicineTestosterone (patch)VasodilationEstrogenSodium nitroprussideHemodynamicsBlood pressureChemistryVasomotorNitric oxideMedicine

Abstract

fetched live from OpenAlex

SUMMARY: This study was designed to evaluate the effects of chronic treatment with estrogen and testosterone on hindlimb vascular function. Spontaneously hypertensive rats (SHR) were sham-operated (SHAM) or ovariectomized and treated with vehicle (OVX), ethinyl estradiol (OVX-EE2), estradiol (OVX-E2), or testosterone (OVX-TESTO) for 3 weeks. Anesthetized SHR were instrumented for the measurement of arterial blood pressure and hindlimb blood flow. Ovariectomy had no significant effect on hindlimb resistance. Resting blood pressure (mm Hg) and hindlimb resistance (mm Hg/ml/min/kg) were higher in OVX-TESTO (158 +/- 4 and 4.7 +/- 0.3) than SHAM control (130 +/- 6 and 3.3 +/- 0.4), OVX (139 +/- 6 and 3.4 +/- 0.3), OVX-EE2 (130 +/- 4 and 3.0 +/- 0.3), and OVX-E2 (120 +/- 4 and 3.3 +/- 0.4). The hemodynamic responses to the endothelium-dependent vasodilator acetylcholine (ACh) were similar in SHAM, OVX, OVX-EE2, and OVX-E2. The hindlimb vasodilatory effects of ACh were consistently greater in OVX-TESTO compared with OVX, OVX-EE2, OVX-E2, and SHAM control rats. The hemodynamic responses to the nitric oxide donor, sodium nitroprusside, were similar in all groups. Our results provide evidence of modulatory influence of testosterone on vasomotor function. It is suggested that the enhanced hindlimb endothelial function represents a compensatory mechanism for testosterone-induced hypertension.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.397
Threshold uncertainty score0.624

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.289
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations16
Published2002
Admission routes1
Has abstractyes

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