Underwater instant adhesion mechanism of self-assembled amphiphilic hemostatic granular hydrogel from Andrias davidianus skin secretion
Bibliographic record
Abstract
The widespread use of biological tissue adhesives for tissue repair is limited by their weak adhesion in a wet environment. Herein, we report the wet adhesion mechanism of a dry granular natural bioadhesive from Andrias davidianus skin secretion (ADS). Once contacting water, ADS granules self-assemble to form a hydrophobic hydrogel strongly bonding to wet substrates in seconds. ADS showed higher shear adhesion than current commercial tissue adhesives and an impressive 72-h underwater adhesion strength of ∼47kPa on porcine skin tissue. The assembled hydrogel in water maintained a dissipation energy of ∼8 kJ/m 3 , comparable to the work density of muscle, exhibiting its robustness. Unlike catechol adhesion mechanism, ADS wet adhesion mechanism is attributed to water absorption by granules, and the unique equilibrium of protein hydrophobicity, hydrogen bonding, and ionic complexation. The in vivo adhesion study demonstrated its excellent wet adhesion and hemostasis performance in a rat hepatic and cardiac hemorrhage model.
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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".