Gene therapy for in-stent restenosis: Targets and delivery system
Bibliographic record
Abstract
the advent of the drug-eluting stent, the incidence of in-stent restenosis remains unacceptably high. Gene therapeutic strategies, including catheter-based gene delivery and gene-eluting stents, offer novel treatment methods to promote re-endothelialization, and inhibit inflammation, neointimal hyperplasia and late stent thrombosis. The translation of gene therapy into clinical application must be safe and requires an effective, site-specific delivery system as well as the ability to provide sustained transgene expression. The progress of magnetic nanotechnology and genetic engineering of human stem cells can provide such elements. In the present review, the authors discuss the evolution of antirestenosis therapy, underlying mechanisms of restenosis and the applications of gene therapy to prevent in-stent restenosis. Current gene delivery methods, including gene vectors and delivery strategies, are critically reviewed.
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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 | 0.001 | 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".