Heart rate variability and muscle sympathetic nerve activity response to acute stress: the effect of breathing
Bibliographic record
Abstract
Previous research has suggested a relationship between low-frequency power of heart rate variability (HRV; LF in normalized units, LFnu) and muscle sympathetic nerve activity (MSNA). However, investigations have not systematically controlled for breathing, which can modulate both HRV and MSNA. Accordingly, the aims of this experiment were to investigate the possibility of parallel responses in MSNA and HRV (LFnu) to selected acute stressors and the effect of controlled breathing. After data were obtained at rest, 12 healthy males (28 +/- 5 yr) performed isometric handgrip exercise (30% maximal voluntary contraction) and the cold pressor test in random order, and were then exposed to hypoxia (inspired fraction of O(2) = 0.105) for 7 min, during randomly assigned spontaneous and controlled breathing conditions (20 breaths/min, constant tidal volume, isocapnic). MSNA was recorded from the peroneal nerve, whereas HRV was calculated from ECG. At rest, controlled breathing did not alter MSNA but decreased LFnu (P < 0.05 for all) relative to spontaneous breathing. MSNA increased in response to all stressors regardless of breathing. LFnu increased with exercise during both breathing conditions. During cold pressor, LFnu decreased when breathing was spontaneous, whereas in the controlled breathing condition, LFnu was unchanged from baseline. Hypoxia elicited increases in LFnu when breathing was controlled, but not during spontaneous breathing. The parallel changes observed during exercise and controlled breathing during hypoxia suggest that LFnu may be an indication of sympathetic outflow in select conditions. However, since MSNA and LFnu did not change in parallel with all stressors, a cautious approach to the use of LFnu as a marker of sympathetic activity is warranted.
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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 | 0.001 |
| 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".