A Facile Way to Tune Mechanical Properties of Artificial Elastomeric Proteins-Based Hydrogels
Bibliographic record
Abstract
Protein-based hydrogels have attracted considerable interests due to their potential applications in biomedical engineering and material sciences. Using a tandem modular protein (GB1)(8) as building blocks, we have engineered chemically cross-linked hydrogels via a photochemical cross-linking strategy, which is based on the cross-linking of two adjacent tyrosine residues into dityrosine adducts. However, because of the relatively low reactivity of tyrosine residues in GB1, (GB1)(8)-based hydrogels exhibit poor mechanical properties. Here, we report a Bolton-Hunter reagent-based, facile method to improve and tune the mechanical properties of such protein-based hydrogels. Using Bolton-Hunter reagent, we can derivatize lysine residues with phenolic functional groups to modulate the phenolic (tyrosine-like) content of (GB1)(8). We show that hydrogels made from derivatized (GB1)(8) with increased phenolic content show significantly improved mechanical properties, including improved Young's modulus, breaking modulus as well as reduced swelling. These results demonstrate the great potential of this derivatization method in constructing protein-based biomaterials with desired macroscopic mechanical properties.
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How this classification was reachedexpand
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) | 0.000 | 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 | 0.001 |
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 teacher head, 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".