Local Delivery of Therapeutics for Percutaneous Coronary Intervention
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Percutaneous coronary intervention (PCI) has become a highly effective alternative for the treatment of coronary artery disease. The use of stents has reduced the rates of restenosis by preventing elastic recoil and negative remodeling, however neointima formation still remains an issue. Local drug delivery is an attractive option to maintain effective drug concentrations at the site of arterial injury without risking systemic toxicity. Drug-eluting stents (DESs) are implanted to provide local drug delivery to combat neointima formation by slowing cell proliferation and migration. However, problems still remain with DES use including the non-specificity of therapeutics, incomplete endothelialization leading to late thrombosis, necessity for longer term anti-platelet drug use, and local hypersensitivity to polymer delivery matrices. This review describes recent advances in local drug delivery for the prevention of restenosis. Many different drug therapeutics have been considered, as well as the material properties of the drug delivery systems. Systems for delivery include DESs, balloon catheters, polymeric cuffs and nanoparticles. Our own experience designing a controlled release device for a new therapeutic agent, Serp-1, an anti-inflammatory protein, is briefly presented. The release of Serp-1 can be extended using diffusion controlled release from physically crosslinked poly(vinyl alcohol) hydrogels, where its release properties can be tuned by the processing parameters of the hydrogel.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it