Bone Marrow–derived Endothelial Progenitor Cells Are Associated with Bone Mass and Strength
Bibliographic record
Abstract
Objective. Blood vessels of bone are thought to influence osteogenesis of bone. No clinical studies have determined whether angiogenesis is related to bone mass and gene expression of growth factors. We compared bone marrow endothelial progenitor cells (EPC), which control angiogenesis of bone in postmenopausal women incurring fragility fracture, with osteoporosis or traumatic fracture with normal bone mass (COM). Methods. Bone specimens were obtained from age-matched women with osteoporosis or COM. Mononuclear cells were isolated and EPC were detected by flow cytometry. The expression levels of specific genes were measured. Bone mineral density (BMD) was determined, and serum markers of bone turnover also were measured. Differences between OP and COM were assessed with Student t test or Mann-Whitney U test, and correlations were determined using Spearman’s correlation. Results. Compared with COM, patients with OP had significantly lower levels of serum osteocalcin, procollagen type-1 N-terminal propeptide, and 25-hydroxy vitamin D, as well as decreased BMD of total hip and femoral neck and fewer bone marrow EPC. Expression levels of vascular endothelial growth factor, angiopoietin-1 (Ang-1), angiopoietin 2 (Ang-2), and the osteoblast-specific genes runt-related transcription factor 2 (RUNX2)andosterixin bone were significantly lower in OP than in COM. We determined that mature EPC were correlated positively with BMD of the femoral neck and total hip, gene expression of Ang-1,RUNX2, andCD31, and negatively with gene expression of receptor activator of nuclear factor-κB ligand and Ang-2. Conclusion. Our results demonstrate correlations of bone marrow EPC with bone mass and gene expression of growth factors, which support a hypothesis of crosstalk between angiogenesis and osteogenesis in bone health.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".