Beneficial Effects of Reconstituted High-Density Lipoprotein (rHDL) on Circulating CD34+ Cells in Patients after an Acute Coronary Syndrome
Bibliographic record
Abstract
BACKGROUND: High-density lipoproteins (HDL) favorably affect endothelial progenitor cells (EPC). Circulating progenitor cell level and function are impaired in patients with acute coronary syndrome (ACS). This study investigates the short-term effects of reconstituted HDL (rHDL) on circulating progenitor cells in patients with ACS. METHODS AND FINDINGS: The study population consisted of 33 patients with recent ACS: 20 patients from the ERASE trial (randomized to receive 4 weekly intravenous infusions of CSL-111 40 mg/kg or placebo) and 13 additional patients recruited as controls using the same enrolment criteria. Blood was collected from 16 rHDL (CSL-111)-treated patients and 17 controls at baseline and at 6-7 weeks (i.e. 2-3 weeks after the fourth infusion of CSL-111 in ERASE). CD34+ and CD34+/kinase insert domain receptor (KDR+) progenitor cell counts were analyzed by flow cytometry. We found preserved CD34+ cell counts in CSL-111-treated subjects at follow-up (change of 1.6%), while the number of CD34+ cells was reduced (-32.9%) in controls (p = 0.017 between groups). The level of circulating SDF-1 (stromal cell-derived factor-1), a chemokine involved in progenitor cell recruitment, increased significantly (change of 21.5%) in controls, while it remained unchanged in CSL-111-treated patients (p = 0.031 between groups). In vitro exposure to CSL-111 of early EPC isolated from healthy volunteers significantly increased CD34+ cells, reduced early EPC apoptosis and enhanced their migration capacity towards SDF-1. CONCLUSIONS: The relative increase in circulating CD34+ cells and the low SDF-1 levels observed following rHDL infusions in ACS patients point towards a role of rHDL in cardiovascular repair 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) | 0.001 | 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 | 0.000 | 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".