Affinity-Based Drug Delivery Systems for Tissue Repair and Regeneration
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
Affinity-based release systems use transient interactions to sustain and control the release of a therapeutic from a polymeric matrix. The most common affinity-based systems use heparin-based scaffolds to sustain the release of heparin-binding proteins, such as fibroblast growth factor-2 (FGF2) and vascular endothelial growth factor (VEGF). However, novel affinity-based systems based on, for example, protein-protein or DNA-protein interactions, are emerging to control the release of an expanding repertoire of therapeutics. Mathematical models of affinity-based systems have provided a thorough understanding of which parameters affect release rate from these systems, and how these release rates can be tuned. In this review, recent affinity-based release systems will be described, including an overview of the various types of affinity interactions used to modulate release, the mechanisms by which release from these systems is tuned, and the time scales of sustained release. This advanced drug delivery paradigm provides tunable and predictable release rates and has expanded the scope of deliverable therapeutics for tissue repair and regeneration.
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) | 0.001 | 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