Delivery approaches for angiogenic growth factors in the treatment of ischemic conditions
Bibliographic record
Abstract
INTRODUCTION: Despite current medical treatments, cardiovascular disease resulting in local ischemia remains a significant clinical problem. Therapeutic angiogenesis, that is, the growth and remodeling of new blood vessels from pre-existing blood vessels to the ischemic area, is a promising solution to this problem. AREAS COVERED: Therapeutic angiogenesis can be generated in vivo through the local release of various proangiogenic factors. This review describes the various formulation approaches that have been devised for this purpose, highlighting the advantages and disadvantages of each. EXPERT OPINION: Formulations that release single proangiogenic growth factors have not yet been demonstrated to achieve functional therapeutic angiogenesis. Formulations capable of multiple growth factor delivery are needed; however, the complexity of the physiologic process requires the examination of appropriate growth factor doses, as well as release sequence, to guide effectively new formulation design. Furthermore, new formulation approaches need to be tested in vivo in appropriate animal models over extended time periods to assess clearly the potential of the delivery approach.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".