Effect of temperature on gelation and cross-linking of gelatin methacryloyl for biomedical applications
Bibliographic record
Abstract
Hydrogels with or without chemical cross-linking have been studied and used for biomedical applications, such as tissue repair, surgical sealants, and three dimensional biofabrication. These materials often undergo a physical sol–gel or gel–sol transition between room and body temperatures and can also be chemically cross-linked at these temperatures to give dimensional stability. However, few studies have clearly shown the effect of heating/cooling rates on such transitions. Moreover, only a little is known about the effect of cross-linking temperature or the state on the modulus after cross-linking. We have established rheological methods to study these effects, an approach to determine transition temperatures, and a method to prevent sample drying during measurements. All the rheological measurements were performed minimizing the normal stress build-up to compensate for the shrinking and expansion due to temperature and phase changes. We chemically modified gelatin to give gelatin methacryloyl and determined the degree of methacryloylation by proton nuclear magnetic resonance. Using the gelatin methacryloyl as an example, we have found that the gel state or lower temperature can give more rigid gelatin-based polymers by cross-linking under visible light than the sol state or higher temperature. These methods and results can guide researchers to perform appropriate studies on material design and map applications, such as the optimal operating temperature of hydrogels for biomedical applications. We have also found that gelation temperatures strongly depend on the cooling rate, while solation temperatures are independent of the heating rate.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".