Circulating Humoral Factors and Endothelial Progenitor Cells in Patients With Differing Coronary Collateral Support
Bibliographic record
Abstract
BACKGROUND: The mechanisms underlying the variation in collateral formation between patients, even with similar patterns of coronary artery disease, remain unclear. This study investigates whether circulating humoral or cellular factors can provide an insight into this variation. METHODS AND RESULTS: Thirty patients with isolated left anterior descending coronary artery disease underwent percutaneous coronary intervention with collateral flow index (CFI) determined using a pressure wire. Patients with inadequate (CFI <0.25) compared with those with adequate (CFI > or =0.25) collateral support had, or tended to have, lower concentrations of coronary sinus growth factors and plasma exerting a weaker effect on endothelial cell migration and angiogenesis in vitro. However, there was an inverse correlation between serum mitogenicity and CFI (r=-0.61, P<0.01). No significant differences were detected between the 2 groups in plasma levels of total vascular endothelial growth factor, vascular endothelial growth factor165, or placental growth factor. There was a strong positive correlation between numbers of CD34/CD133-positive circulating hemopoietic precursor cells and CFI (r=0.75, P<0.001). In patients with inadequate, compared with those with adequate, CFI, the numbers of differentiated endothelial progenitor cells (EPCs) appearing in the circulation and in culture were significantly reduced by 75% (P<0.05) and 70% (P<0.05), respectively. CONCLUSIONS: In this study, inadequate coronary collateral development is associated with reduced numbers of circulating EPCs and impaired chemotactic and proangiogenic but not mitogenic activity. These findings are consistent with current efforts to enhance collateral formation by augmentation of circulating EPCs.
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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 | 0.003 |
| 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 | 0.000 | 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".