Impaired brachial artery flow-mediated vasodilation in response to handgrip exercise-induced increases in shear stress in young smokers
Bibliographic record
Abstract
Smoking is an established risk factor for cardiovascular disease. It has also been shown to result in endothelial dysfunction as assessed by flow-mediated dilation (FMD) in response to reactive hyperemia (RH)-induced increases in shear stress. Handgrip exercise (HGEX) is an emerging alternative method to increase shear stress for FMD assessment (HGEX-FMD) and the purpose of this study was to identify the impact of smoking on HGEX-FMD in young healthy subjects. Brachial artery RH-FMD and HGEX-FMD (10-minute bout of HGEX) was assessed in eight smokers (S) and 14 non-smokers (NS) (age 21 ± 2 years). Brachial artery diameter and mean blood velocity were assessed with echo and Doppler ultrasound, respectively. Shear stress was estimated by shear rate (SR = brachial artery blood velocity/diameter). The SR stimulus did not differ between groups for either test (RH-FMD (SR area under the curve until peak diameter measurement), p = 0.897; HGEX-FMD (average SR over 10-minute exercise bout), p = 0.599). The RH-FMD magnitude was not significantly different between groups (S: 7.7 ± 2.2% vs NS: 7.9 ± 2.4%, p = 0.838); however, the HGEX-FMD magnitude was significantly impaired in smokers (S: 6.1 ± 3.4% vs NS: 9.6 ± 3.6%, p = 0.037). In conclusion, HGEX-FMD assessment detected vascular dysfunction in young healthy smokers while RH-FMD did not. This suggests that HGEX-FMD may be useful in the early detection of smoking-induced impairments in endothelial function. Further research is required to explore this phenomenon in other populations and to isolate underlying mechanisms.
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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 | 0.001 | 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".