An acellular matrix‐bound ligand enhances the mobilization, recruitment and therapeutic effects of circulating progenitor cells in a hindlimb ischemia model
Bibliographic record
Abstract
Circulating progenitor cells home to and engraft to sites of ischemia, mediated in part by the adhesion molecule L-selectin; however, accumulation in tissues such as the heart is low. In this study, an acellular collagen-based matrix containing sialyl Lewis(X) (sLe(X)), which binds L-selectin, was developed in order to enhance the endogenous progenitor cell therapeutic response. Its effect on progenitor cells and angiogenesis were assessed in vitro and using a hindlimb ischemia model with rats. In culture, the sLe(X)-collagen matrix recruited more CD133(+)CD34(+)L-selectin(+) cells than collagen-only matrix, with adhesion mediated by L-selectin binding. Increased angiogenic/chemotactic cytokine production and improved resistance to apoptosis appeared in cells cultured on sLe(X)-collagen matrix. In vivo, mobilization of endogenous circulating progenitor cells was increased, and greater recruitment of these and systemically injected human peripheral blood CXCR4(+)L-selectin(+) cells to sLe(X)-collagen treated limbs was observed compared to collagen-only. This condition was associated with differences in angiogenic/chemotactic cytokine levels, with greater arteriole density and increased perfusion in sLe(X)-collagen treated hindlimbs. With these factors taken together, we demonstrated that an acellular matrix-bound ligand approach can enhance the mobilization, recruitment, and therapeutic effects of endogenous and/or transplanted progenitor cells, possibly through paracrine and antiapoptotic mechanisms, and could be used to improve cell-based regenerative therapies.
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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) | 0.000 | 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) | 0.000 | 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".