From Brain to Blood Vessel: Insights From Muscle Sympathetic Nerve Recordings
Bibliographic record
Abstract
Multiunit recordings of postganglionic sympathetic outflow to muscle yield otherwise imperceptible insights into sympathetic neural modulation of human vascular resistance and blood pressure. This Corcoran Lecture will illustrate the utility of microneurography to investigate neurogenic cardiovascular regulation; review data concerning muscle sympathetic nerve activity of women and men with normal and high blood pressure; explore 2 concepts, central upregulation of muscle sympathetic outflow and cortical autonomic neuroplasticity; present sleep apnea as an imperfect model of neurogenic hypertension; and expose the paradox of sympathetic excitation without hypertension. In awake healthy normotensive individuals, resting muscle sympathetic nerve activity increases with age, sleep fragmentation, and obstructive apnea. Its magnitude is not signaled by heart rate. Age-related changes are nonlinear and differ by sex. In men, sympathetic nerve activity increases with age but without relation to their blood pressure, whereas in women, both rise concordantly after age 40. Mean values for muscle sympathetic nerve activity burst incidence are consistently higher in cohorts with hypertension than in matched normotensives, yet women's sympathetic nerve traffic can increase 3-fold between ages 30 and 70 without causing hypertension. Thus, increased sympathetic nerve activity may be necessary but is insufficient for primary hypertension. Moreover, its inhibition does not consistently decrease blood pressure. Despite a half-century of microneurographic research, large gaps remain in our understanding of the content of the sympathetic broadcast from brain to blood vessel and its specific individual consequences for circulatory regulation and cardiovascular, renal, and metabolic risk.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".