A Highly Elastic and Rapidly Crosslinkable Elastin‐Like Polypeptide‐Based Hydrogel for Biomedical Applications
Bibliographic record
Abstract
Elastin-like polypeptides (ELPs) are promising for biomedical applications due to their unique thermoresponsive and elastic properties. ELP-based hydrogels have been produced through chemical and enzymatic crosslinking or photocrosslinking of modified ELPs. Herein, a photocrosslinked ELP gel using only canonical amino acids is presented. The inclusion of thiols from a pair of cysteine residues in the ELP sequence allows disulfide bond formation upon exposure to UV light, leading to the formation of a highly elastic hydrogel. The physical properties of the resulting hydrogel such as mechanical properties and swelling behavior can be easily tuned by controlling ELP concentrations. The biocompatibility of the engineered ELP hydrogels is shown in vitro as well as corroborated in vivo with subcutaneous implantation of hydrogels in rats. ELP constructs demonstrate long-term structural stability in vivo, and early and progressive host integration with no immune response, suggesting their potential for supporting wound repair. Ultimately, functionalized ELPs demonstrate the ability to function as an in vivo hemostatic material over bleeding wounds.
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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".