Circulating Endothelial Progenitor Cells in Youth: Fitness, Physical Activity and Adiposity
Bibliographic record
Abstract
Circulating endothelial progenitor cells (EPCs) are early markers of cardiovascular impairment. The role of EPCs in youth remains unclear, and is complicated by differences in how cells are identified. This study (1) described EPCs in pre- and late-pubertal males and females, (2) examined their association with fitness, activity and adiposity, and (3) compared EPCs to published cell definitions. 94 participants completed 2 sessions. During the first session, aerobic fitness (Wpeak) and moderate-to-vigorous physical activity (MVPA) were assessed. During the second session, percent body fat (%BF) was determined by DXA, and a fasted blood sample was collected to measure EPCs by flow cytometry. EPCs were identified as CD31(+)CD34(bright)CD45(dim)CD133(+). Samples were reanalyzed and cell counts were compared to 8 previously published EPC definitions. EPCs were similar in pre- and late-pubertal males and females (p>0.05). Neither EPC concentrations nor proportions were correlated with Wpeak (ρ=- 0.04 to-0.06), MVPA (ρ=- 0.09 to - 0.07) or %BF (ρ=0.20 to 0.14). Agreement between cell data analyzed according the different cell definitions ranged from Κ=-0.06 to 0.82. Our findings suggest that EPCs were not associated with fitness, MVPA or adiposity in youth. The overall poor agreement across definitions may be indicative of distinct EPC subpopulations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".