Viscoelasticity of Fibrous Hydrogels Driven by Dynamic Intrafibrillar Imine Cross-Linking
Bibliographic record
Abstract
Viscoelasticity of biological fibrous networks impacts cell fates and may reflect pathological conditions in vivo. Imine-cross-linked fibrous hydrogels can serve as effective in vitro models for studying viscoelastic properties of biological tissues; however, the specific role of intrafibrillar dynamic covalent bonds in governing hydrogel elasticity and stress relaxation remains unexplored. Here, for fibrous hydrogels derived from cellulose nanocrystals and polyethylene glycol, we systematically varied the content of intrafibrillar imine cross-links to explore their impact on hydrogels' elastic response, stress relaxation, and fibrous structure. We showed that higher imine group contents resulted in greater elastic moduli and higher degrees of stress relaxation in fibrous hydrogels. The fibrous structure did not significantly change with varying imine group contents, which enabled the decoupling of changes in hydrogel morphology and viscoelastic properties. This work provides the capability of designing fibrous hydrogels with controlled viscoelasticity and exploring their roles in bioengineering.
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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".