Engineering Protein-Clay Nanosheets Composite Hydrogels with Designed Arginine-Rich Proteins
Bibliographic record
Abstract
Clay nanosheets (CNSs) have been widely used in the design of nanocomposite biomaterials. CNSs display a disk-like morphology with strong negatively charged surfaces. It has been shown that guanidinium-containing molecules can bind CNSs through noncovalent salt-bridge interactions and thus serve as "molecular glues" for CNSs. Making use of the guanidinium side chain in arginine, here, we designed novel arginine-rich elastomeric proteins to engineer protein-CNS nanocomposite hydrogels. Our results showed that these arginine-rich proteins can interact with CNSs effectively and can cross-link CNSs into hydrogels. Rheological measurements showed that mechanical properties of the resultant hydrogels depended on the arginine content in the arginine-rich proteins as well as CNS/protein concentration. Compared with hydrogels constructed from CNSs or proteins alone, the novel protein-CNS nanocomposite hydrogels show much improved mechanical properties. Our work opens up a new avenue to engineer functional protein hydrogels for various applications.
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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) | 0.000 | 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".