Corelease of Bioactive VEGF and HGF from Viscous Liquid Poly(5-ethylene ketal ε-caprolactone-<i>co</i>-<scp>d</scp>,<scp>l</scp>-lactide)
Bibliographic record
Abstract
The potential of a viscous liquid injectable delivery system composed of poly(5-ethylene ketal ε-caprolactone-co-D,L-lactide) (PEKCDLLA) to release bioactive vascular endothelial growth factor (VEGF) and hepatocyte growth factor (HGF) using an osmotic pressure release mechanism for the purpose of treating critical limb ischemia was investigated. VEGF and HGF were lyophilized separately with trehalose and bovine serum albumin (BSA) and incorporated into the polymer by simple mixing. VEGF and HGF were released by convective flow through superhydrated regions formed within the polymer as a result of the osmotic activity generated upon dissolution of the particles, along with the contributions of polymer degradation at later time points. A sustained release of highly bioactive VEGF and HGF for over 40 days with minimal burst was achieved under conditions of multidirectional delivery. The solubility of the growth factors in the concentrated trehalose solution formed upon dissolution of the particle within the polymer was determined to be a key parameter governing the rate and extent of growth factor release. This formulation approach, of using a low viscosity polymer delivery vehicle, is potentially useful for localized delivery of acid and temperature sensitive proteins, such as VEGF and HGF. This system may also serve as a platform for controlled and predictable delivery patterns for other therapeutic proteins in other clinical settings.
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.
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) | 0.001 | 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".