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Muscle Sympathetic Activity Kinetics during One‐leg Cycling in Men and Women with and without Heart Failure: Evidence for Preserved Cardiopulmonary Baroreflex Sympathoinhibition

2019· article· en· W2928268661 on OpenAlexaffabout
Philip J. Millar, Catherine F. Notarius, Peter Picton, Nobuhiko Haruki, John S. Floras

Bibliographic record

VenueThe FASEB Journal · 2019
Typearticle
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsUniversity of TorontoUniversity of GuelphUniversity Health NetworkMount Sinai Hospital
Fundersnot available
KeywordsCardiologyMedicineBaroreflexHeart failureInternal medicineCyclingHeart rateIntensity (physics)MicroneurographyEjection fractionBlood pressurePhysics

Abstract

fetched live from OpenAlex

Microneurographic recordings of muscle sympathetic nerve activity (MSNA) are generally analyzed over discrete epochs, usually in minutes. This is sufficient for determining resting sympathetic outflow but may obscure physiologically relevant information regarding temporal changes during an acute stress, such as exercise. To address this limitation, we applied a moving average to examine continuously the effects of one‐leg cycling on MSNA in 22 participants with (n=11) and without (n=11) heart failure with reduced ejection fraction (HFrEF). MSNA burst frequency and incidence were acquired over an 8 minute period: 2 minutes of baseline, zeroload cycling, moderate intensity cycling (50% of VO 2 peak), and recovery. MSNA was analyzed in 30 second epochs, advancing in five‐second increments to create a 91 point overlapping moving average plot. Area under the curve analysis demonstrated that both MSNA burst frequency and incidence were higher in HFrEF than controls during zeroload and moderate intensity cycling (both, p<0.05). To estimate the reflex sympathoinhibitory consequences of skeletal muscle‐pump induced increases in cardiopulmonary blood volume at the start of exercise, we calculated the nadir reduction in MSNA burst frequency and incidence during the first 30 seconds of zeroload (HFrEF vs. controls: −6±7 vs. −7±4 bursts/min; −12±11 vs. −15±5 bursts/100 heartbeats) and moderate intensity (HFrEF vs. controls: −7±5 vs. −6±7 bursts/min; −11±7 vs. −8±9 bursts/100 heartbeats) cycling; no differences were observed between HFrEF and controls (all, p>0.05). Such initial reductions in MSNA burst frequency were observed in 9/11 HFrEF and 11/11 controls with zeroload cycling; reductions occurred in 11/11 HFrEF and 7/11 controls with moderate intensity cycling (both, p>0.05). These similar group‐mean magnitude reductions in MSNA at the onset of exercise are consistent with preserved cardiopulmonary‐reflex mediated sympathoinhibition in HFrEF; the subsequent increase in MSNA is consistent with an exaggerated muscle metaboreflex contribution. As peripheral neurogenic vasoconstriction contributes to exercise intolerance in HFrEF, exercise regimens with shorter durations (e.g. high intensity interval training) may be better tolerated and more efficacious elements of conditioning protocols for such patients. Support or Funding Information This study was supported by Grants‐in‐Aid from the Heart and Stroke Foundation of Ontario (T4938, NA6298). P.J.M. was supported by a Canadian Institutes of Health Research Postdoctoral Fellowship. J.S.F. was supported by the Canada Research Chair Program. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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

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 head0.026
GPT teacher head0.268
Teacher spread0.241 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2019
Admission routes2
Has abstractyes

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