Stimuli-responsive protein hydrogels: From dynamic tuning of hydrogel mechanics to shape morphing
Bibliographic record
Abstract
Protein hydrogels represent a rapidly evolving class of biomaterials with significant potential in biomedicine, soft robotics, and tissue engineering. These hydrogels are uniquely engineered from natural or recombinant proteins, endowing them with biocompatibility, biodegradability, and precise molecular programmability. By integrating dynamic cross-linking mechanisms and responsive moieties, protein hydrogels can be engineered to respond to external stimuli such as temperature, pH, light, or ligands, and undergo reversible or irreversible changes in shape, volume, or mechanical properties. This review critically summarizes recent advances in the design and fabrication of stimuli-responsive protein hydrogels. Emphasis is placed on the molecular design strategies that are used to dynamically tune the mechanical properties and shape-morphing behaviors of protein hydrogels. Challenges and opportunities related to the rational engineering of next-generation stimuli-responsive protein hydrogels are also discussed.
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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 | 0.001 |
| 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".