Evidence for sympatholysis at the onset of forearm exercise
Bibliographic record
Abstract
The effect of augmented sympathetic outflow on forearm vascular conductance after single handgrip contractions of graded intensity was examined to determine whether sympatholysis occurs early in exercise (n = 7). While supine, subjects performed contractions that were 1 s in duration and 15, 30, and 60% of maximal voluntary contraction (MVC) in intensity. The contractions were repeated during control and lower body negative pressure (LBNP) (-40 mmHg) sessions. Forearm blood flow (FBF; Doppler ultrasound) and mean arterial pressure were measured continuously for 30 s before and 60 s after the single contractions. Vascular conductance (VC) was calculated. Total postcontraction blood flow increased in an exercise intensity-dependent manner. Compared with control, LBNP caused a reduction in baseline and postexercise FBF (P < 0.05), VC (P < 0.01), as well as total excess flow (P < 0.01). Specifically, during LBNP, baseline FBF and VC were reduced by 29 and 34% of control, respectively (P < 0.05). After the 15% MVC contraction, peak VC during LBNP was reduced by a magnitude similar to that during baseline (i.e., ~30%), but it was only reduced by 15% during both the 30 and 60% MVC trials (P < 0.01). It was concluded that the stimuli for exercise hyperemia during moderate and heavy, but not mild, handgrip exercise intensities, diminish the vasoconstrictor effects of LBNP. Furthermore, these data demonstrate that this sympatholysis occurs early in exercise.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".