Hypovolemia and MSNA discharge patterns: assessing and interpreting sympathetic responses
Bibliographic record
Abstract
We previously demonstrated that diuretic-induced hypovolemia resulted in an enhanced baroreflex-mediated increase in integrated muscle sympathetic nerve activity (MSNA) and vasomotor tone during lower body negative pressure (LBNP) (Am J Physiol Heart Circ Physiol 282: H645-H655, 2002). The purpose of this study was to perform a retrospective analysis of these data and examine the ability of relative MSNA burst amplitude distributions to highlight differences in baseline sympathetic nerve discharge patterns. An additional purpose was to determine whether differential responses in MSNA burst frequency and burst amplitude affect conclusions regarding sympathetic reflex control. MSNA, stroke volume (SV, Doppler), and estimated central venous pressure (CVP, dependent arm technique) were measured during LBNP within the placebo (Normo) and diuretic (Hypo; 100 mg/day spironolactone for 3 days) conditions (n = 8). Compared with Normo, MSNA burst frequency at rest was elevated, and there was a rightward shift in the median of the relative burst amplitude distribution (P < 0.05) in Hypo. During LBNP, the larger rise in total MSNA during Hypo versus Normo was due to greater increases in relative burst amplitude with no difference in the burst frequency response. The MSNA burst frequency response to LBNP was shifted to a higher position on the same MSNA-CVP curve during Hypo compared with Normo. In contrast, the Hypo burst amplitude response was shifted to a new curve with a slope that was similar to the Normo relationship. These data support the use of probability distribution analysis to examine intraindividual differences in baseline and reflex-mediated increases in MSNA burst amplitude. Furthermore, the differential effect of hypovolemia on the responses of burst frequency and amplitude during graded LBNP suggests that burst frequency data alone may not adequately represent reflex control of sympathetic outflow.
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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 | 0.000 |
| 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) | 0.000 | 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".