Circulating Endothelial Cells in Children
Bibliographic record
Abstract
PURPOSE: Circulating endothelial cells (CEC) are thought to be useful biomarkers of endothelial dysfunction and overall cardiovascular health. The extent to which CEC are influenced by fitness, physical activity, and adiposity in youth remains unknown, as they have seldom been examined in the pediatric population. This study assessed resting levels of CEC in boys and girls of different chronological and biological age and explored the relationship between these cells and aerobic fitness, physical activity, and adiposity. METHODS: Seventy-five children (39 males; median [interquartile range], age = 14.4 [5.8]) completed two study visits. During the first visit, basic anthropometric data were collected and biological age was calculated. Peak mechanical power (Wpeak) was determined using the McMaster All-Out Continuous cycling test. Participants then wore an accelerometer over a 7-d period to assess habitual levels of moderate-to-vigorous physical activity. During visit 2, percent body fat (%BF) was assessed by dual-energy x-ray absorptiometry. A fasted blood sample was also collected from which concentrations of CEC, identified as CD31CD34CD45CD133, were quantified by flow cytometry. RESULTS: No differences were seen in CEC by sex, chronological age, or biological age. The median (interquartile range) CEC concentration was 32.3 × 10 (63.0 × 10), representing 1.3% (2.7%) of collected peripheral blood mononuclear cells. CEC concentration was associated with Wpeak normalized to lean body mass (r = 0.36, P < 0.01) and time spent in moderate-to-vigorous physical activity (r = -0.27, P = 0.02). No relationship was observed between CEC and %BF. CONCLUSION: Healthy children demonstrate relatively low concentrations of CECs. Because CEC represent a population of mature endothelial cells shed from the intima after irreversible damage, they may be more reflective of recent physical activity levels rather than fitness or level of adiposity.
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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 | 0.001 | 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 | 0.001 |
| 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".