Hourly staircase sprinting exercise “snacks” improve femoral artery shear patterns but not flow-mediated dilation or cerebrovascular regulation: a pilot study
Bibliographic record
Abstract
Healthy males (n = 10; age: 24 ± 4 years; body mass index: 24 ± 2 kg·m −2 ) completed 2 randomized conditions separated by ≥48 h involving 6–8.5 h of sitting with (“stair snacks”) and without (sedentary) hourly staircase sprint interval exercise (∼14–20 s each). Resting blood flow and shear rates were measured in the femoral artery, internal carotid artery, and vertebral artery (Duplex ultrasound). Flow-mediated dilation (FMD) was quantified as an index of peripheral endothelial function in the femoral artery. Neurovascular coupling (NVC; regional blood flow response to local increases in cerebral metabolism) was assessed in the posterior cerebral artery (transcranial Doppler ultrasound). Femoral artery hemodynamics were higher following the active trial with no change in the sedentary trial, including blood flow (+32 ± 23% vs. −10 ± 28%; P = 0.015 and P = 0.253, respectively), vascular conductance (+32 ± 27% vs. −15 ± 26%; P = 0.012 and P = 0.098, respectively), and mean shear rate (+17 ± 8% vs. −8 ± 28%; P = 0.004 and P = 0.310, respectively). The change in FMD was not different within or between conditions (P = 0.184). Global cerebral blood flow (CBF), conductance, shear patterns, and NVC were not different within or between conditions (all P > 0.05). Overall, exercise “stair snacks” improve femoral artery blood flow and shear patterns but not peripheral (e.g., FMD) or cerebral (e.g., CBF and NVC) vascular function following prolonged sitting. The study was registered at ClinicalTrials.gov (NCT03374436). Novelty: Breaking up 8.5 h of sitting with hourly staircase sprinting exercise “snacks” improves resting femoral artery shear patterns but not FMD. Cerebral blood flow and neurovascular coupling were unaltered following 6 h of sitting with and without hourly exercise breaks.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".