In Vivo Degradation and Tissue Response to Poly(5-ethylene ketal ε-caprolactone-<i>co</i>-<scp>d</scp>,<scp>l</scp>-lactide)
Bibliographic record
Abstract
Low molecular weight poly(5-ethylene ketal ε-caprolactone-co-D,L-lactide) (PEKCDLLA) is being considered as a viscous liquid, injectable depot for localized drug delivery. This polymer degrades in vitro via surface erosion, which is potentially advantageous for the proposed application. However, the in vivo degradation rate and mechanism, and tissue response, to polymers based on 5-ethylene ketal ε-caprolactone have not yet been reported. The purpose of this study was to measure the in vivo weight loss and change in polymer properties and assess the tissue response to PEKCDLLA after subcutaneous injection in rats. The tissue response was assessed histologically using Masson's trichrome staining and immunohistochemically by staining for CD68 positive cells. The polymer lost weight with time in a nearly linear fashion but did not exhibit significant changes in number average molecular weight, polydispersity index, and glass transition temperature or monomer ratio, consistent with a surface erosion process. The tissue response to the polymer was moderate and comparable to that reported in the literature for other degradable polymers used in clinical applications. These findings indicate that PEKCDLLA is a promising candidate for injectable drug delivery.
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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) | 0.001 | 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) | 0.001 | 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".