Combined transmyocardial revascularization and cell-based angiogenic gene therapy increases transplanted cell survival
Bibliographic record
Abstract
We hypothesized that pretreatment of an infarcted heart by mechanical transmyocardial revascularization (TMR) before transplantation of bone marrow cells (BMCs) or BMC-expressing angiogenic growth factors would increase transplanted BMC survival and enhance myocardial repair. Female Lewis rats underwent coronary ligation 3 wk before creation of 10 needle TMR channels (3 groups) or no TMR (3 groups), followed by transplantation of 3 x 10(6) male donor BMCs, BMC transfected with vascular endothelial growth factor (VEGF), basic fibroblast growth factor (bFGF), and insulin-like growth factor-1 (IGF-1) (BMC + VBI), or medium alone. At 1, 3, and 7 days, we evaluated transplanted cell survival, vascular densities, and left ventricular (LV) function (N = 4 per group x 6 groups x 3 time points). At 3 days, vascular densities in the scar were increased by TMR + BMC + VBI and by BMC + VBI (P < 0.05), and at 7 days, vascular densities were greatest in rats receiving TMR + BMC + VBI (P < 0.05). Transplanted cell survival at 3 and 7 days was increased by TMR and by BMC + VBI. Combined therapy with TMR + BMC + VBI resulted in the greatest cell survival at 3 days (P < 0.05) versus BMC. After 7 days, LV ejection fraction (LVEF) was lowest in rats receiving neither BMC nor TMR and greatest in rats receiving TMR + BMC + VBI (P = 0.004). We concluded that mechanical pretreatment of infarcted myocardium by TMR enhances the effect of subsequent cell-based gene therapy on transplanted cell survival, angiogenesis, and LV function. Scar pretreatment with TMR combined with cell-based multigene therapy may maximize myocardial repair.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".