Effect of Fitness on Reflex Sympathetic Neurovascular Transduction in Middle-Age Men
Bibliographic record
Abstract
PURPOSE: Muscle sympathetic nerve activity (MSNA) is increased in older endurance-trained men, yet the reflex sympathetic forearm vasoconstrictor response to graded lower body negative pressure (LBNP) diminishes with age. The aim of this study was to assess the influence of aerobic exercise capacity on this altered neurovascular coupling. We hypothesized that during graded LBNP, the forearm vascular resistance (FVR)-MSNA relationship would be steeper in sedentary versus fit men. METHODS: We therefore studied 20 healthy middle-age men (age = 52 ± 2 yr, mean ± SE), 10 physically active (FIT) and 10 sedentary (SED) (129% ± 4% vs 85% ± 3% of predicted peak oxygen uptake) during 4 min each of LBNP at -5, -10, -20, and -40 mm Hg, applied in a random order. We determined HR, plasma norepinephrine, and MSNA (microneurography) and derived FVR from blood pressure and forearm blood flow (plethysmography). The FVR-MSNA relationship was determined by linear regression in each group separately, and groups were compared using multiple linear regression. RESULTS: MSNA burst frequency and FVR at rest and during LBNP (P < 0.003) were similar in the two groups, whereas HR was significantly lower (P < 0.002) both at rest and during LBNP in FIT men (P < 0.05). FVR during LBNP correlated positively with MSNA in the SED group (r = 0.44, P < 0.001) but not in the FIT group (r = 0.19, P = 0.10). Multiple linear regression confirmed that both MSNA (P < 0.001) and fitness level (P = 0.04) contribute to the forearm vascular response. CONCLUSIONS: Thus, during simulated orthostasis, middle-age SED men exhibit a significant FVR-MSNA relationship, which is not evident in age-matched FIT men. This alteration in neurovascular coupling may potentially affect cardiovascular risk in middle-age men.
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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".