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Record W2342686466 · doi:10.1152/ajpregu.00491.2015

Role of aortic arch vascular mechanics in cardiovagal baroreflex sensitivity

2016· article· en· W2342686466 on OpenAlexaff
Stephen A. Klassen, Daniele Chirico, Kylie S. Dempster, J. Kevin Shoemaker, Deborah D. O’Leary

Bibliographic record

VenueAmerican Journal of Physiology-Regulatory, Integrative and Comparative Physiology · 2016
Typearticle
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsWestern UniversityBrock University
Fundersnot available
KeywordsBaroreflexBaroreceptorCardiologyMedicineInternal medicineBlood pressurePulse pressureHeart rateAortic archPeripheralAortaAnesthesia

Abstract

fetched live from OpenAlex

Cardiovagal baroreflex sensitivity (cvBRS) measures the efficiency of the cardiovagal baroreflex to modulate heart rate in response to increases or decreases in systolic blood pressure (SBP). Given that baroreceptors are located in the walls of the carotid sinuses (CS) and aortic arch (AA), the arterial mechanics of these sites are important contributors to cvBRS. However, the relative contribution of CS and AA mechanics to cvBRS remains unclear. This study employed sex differences as a model to test the hypothesis that differences in cvBRS between groups would be explained by the vascular mechanics of the AA but not the CS. Thirty-six young, healthy, normotensive individuals (18 females; 24 ± 2 yr) were recruited. cvBRS was measured using transfer function analysis of the low-frequency region (0.04-0.15 Hz). Ultrasonography was performed at the CS and AA to obtain arterial diameters for the measurement of distensibility. Local pulse pressure (PP) was taken at the CS using a hand-held tonometer, whereas AA PP was estimated using a transfer function of brachial PP. Both cvBRS (25 ± 11 vs. 19 ± 7 ms/mmHg, P = 0.04) and AA distensibility (16.5 ± 6.0 vs. 10.5 ± 3.8 mmHg(-1) × 10(-3), P = 0.02) were greater in females than males. Sex differences in cvBRS were eliminated after controlling for AA distensibility (P = 0.19). There were no sex differences in CS distensibility (5.32 ± 2.3 vs. 4.63 ± 1.3 mmHg(-1) × 10(-3), P = 0.32). The present data demonstrate that AA mechanics are an important contributor to differences in cvBRS.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.788
Threshold uncertainty score0.779

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.016
GPT teacher head0.278
Teacher spread0.262 · 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

Citations22
Published2016
Admission routes1
Has abstractyes

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