Injectable gelatin-oligo-catechol conjugates for tough thermosensitive bioadhesion
Bibliographic record
Abstract
Extracellular matrix-derived biomaterials, such as gelatin-based hydrogels, are attractive candidates for sealing internal leakages. However, gelatin derivatives are brittle and suffer from poor adhesion. Modifications of gelatin with adhesive catechol moieties have been limited to low degrees of substitution. Here, we propose oxidative oligomerization of catecholic compounds (namely, caffeic acid [CA]) prior to the coupling reaction to augment the number and availability of grafted catechol groups per carbodiimide conjugation reaction, thereby achieving robust bioadhesion. Ex vivo adhesion tests on pig lungs suggests ∼3× improvement in adhesion strength compared with gelatin methacryloyl controls due to their enhanced cohesion (i.e., ∼5.3× and ∼11.5× improvements in stretchability and toughness, respectively). Functionalization of gelatin with CA oligomers enables rapid formation of physical gels upon exposure to room temperature, tunes the viscosity of the gelatin-caffeic acid pre-gel solution for controllable injectability onto multiply curved tissues, and boosts the antioxidant effects of CA.
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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) | 0.001 | 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".