Painting blood vessels and atherosclerotic plaques with an adhesive drug depot
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
The treatment of diseased vasculature remains challenging, in part because of the difficulty in implanting drug-eluting devices without subjecting vessels to damaging mechanical forces. Implanting materials using adhesive forces could overcome this challenge, but materials have previously not been shown to durably adhere to intact endothelium under blood flow. Marine mussels secrete strong underwater adhesives that have been mimicked in synthetic systems. Here we develop a drug-eluting bioadhesive gel that can be locally and durably glued onto the inside surface of blood vessels. In a mouse model of atherosclerosis, inflamed plaques treated with steroid-eluting adhesive gels had reduced macrophage content and developed protective fibrous caps covering the plaque core. Treatment also lowered plasma cytokine levels and biomarkers of inflammation in the plaque. The drug-eluting devices developed here provide a general strategy for implanting therapeutics in the vasculature using adhesive forces and could potentially be used to stabilize rupture-prone plaques.
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 | 0.002 | 0.001 |
| 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 | 0.001 |
| 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 it