The Potential Impact of Discrete Action Potentials on Resting Sympathetic Vascular Transduction in Humans
Bibliographic record
Abstract
The sympathetic nervous system dynamically regulates blood pressure (BP), primarily through the modification of peripheral vascular tone. Our lab has developed a methodology for quantifying resting sympathetic vascular transduction wherein bursts of muscle sympathetic nerve activity (MSNA) act as a trigger and ensuing changes in BP and vascular conductance are signal‐averaged over the subsequent 15 cardiac cycles to produce characteristic (mean) responses. These previous investigations have focused on the effect of net sympathetic outflow (e.g, burst sequences and burst amplitudes) on the pressor and vascular conductance responses to spontaneous bursts of MSNA. The recent development of methods to identify sympathetic action potentials (APs) to obtain further information regarding sympathetic control of the circulation has led us to begin to examine the potential role that discrete sympathetic APs may play in determining the BP and vascular responses following spontaneous bursts of MSNA. Herein, we compared BP and leg vascular conductance responses between MSNA bursts containing small (i.e., common) or large (i.e., uncommon) APs within quartiles of MSNA normalized to burst amplitude. We hypothesized the presence of large APs in a burst of MSNA would elicit a greater pressor response and a larger decrease in leg vascular conductance. Resting MSNA (microneurography), beat‐to‐beat BP (finger photoplethysmography), and femoral artery blood velocity (Doppler ultrasound) were collected for 10–20 minutes in 5 young healthy adults. Leg vascular conductance index was calculated (LVCi=femoral artery blood velocity/mean arterial pressure). MSNA bursts were sorted into normalized amplitude quartiles (Q1=smallest 25% of bursts; Q4=largest 25% of bursts), and APs were extracted using a matched wavelet methodology. Within Q4, there was no difference in the peak BP or LVCi responses to bursts containing small APs when compared to bursts containing large APs (Δ6±3 small vs. Δ6±2 large mmHg, p=0.74; Δ0.95±2.0 small vs. Δ0.87±1.7 large ml·min −1 ·mmHg −1 , p=0.59). To account for the potential contribution of MSNA bursts occurring in consecutive sequence, we next isolated singlet bursts (separated by ≥1 cardiac cycle lacking MSNA bursts). Within Q4, there was again no difference in the peak BP or LVCi response to singlet bursts containing small APs compared to singlet bursts containing large APs (Q4: Δ7±3 small vs. Δ6±2 large mmHg, p=0.42; Δ0.05±0.07 small vs. Δ0.17±0.11 large ml·min −1 ·mmHg −1 , p=0.08). These preliminary data suggest that the presence of large APs does not appear to translate to greater pressor or decreased leg vascular conductance responses following a spontaneous burst of resting MSNA. Support or Funding Information Funded by the UTA College of Nursing and Health Innovation and Natural Sciences and Engineering Research Council of Canada
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 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".