Sustained release of antibiotics from injectable and thermally responsive polypeptide depots
Bibliographic record
Abstract
Biodegradable polymeric scaffolds are of interest for delivering antibiotics to local sites of infection in orthopaedic applications, such as bone and diarthrodial joints. The objective of this study was to develop a biodegradable scaffold with ease of drug loading in aqueous solution, while providing for drug depot delivery via syringe injection. Elastin-like polypeptides (ELPs) were used for this application, biopolymers of repeating pentapeptide sequences that were thermally triggered to undergo in situ depot formation at body temperature. ELPs were modified to enable loading with the antibiotics, cefazolin, and vancomycin, followed by induction of the phase transition in vitro. Cefazolin and vancomycin concentrations were monitored, as well as bioactivity of the released antibiotics, to test an ability of the ELP depot to provide for prolonged release of bioactive drugs. Further tests of formulation viscosity were conducted to test suitability as an injectable drug carrier. Results demonstrate sustained release of therapeutic concentrations of bioactive antibiotics by the ELP, with first-order time constants for drug release of approximately 25 h for cefazolin and approximately 500 h for vancomycin. These findings illustrate that an injectable, in situ forming ELP depot can provide for sustained release of antibiotics with an effect that varies across antibiotic formulation. ELPs have important advantages for drug delivery, as they are known to be biocompatible, biodegradable, and elicit no known immune response. These benefits suggest distinct advantages over currently used carriers for antibiotic drug delivery in orthopedic applications.
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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 | 0.000 | 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 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".