Core–Shell Filament with Excellent Wound Healing Property Made of Cellulose Nanofibrils and Guar Gum via Interfacial Polyelectrolyte Complexation Spinning
Bibliographic record
Abstract
Natural polymer-based sutures have attractive cytocompatibility and degradability in surgical operations. Herein, anionic cellulose nanofibrils (ACNF) and cationic guar gum (CGG) are employed to produce nontoxic CGG/ACNF composite filament with a unique core-shell structure via interfacial polyelectrolyte complexation (IPC) spinning. The comprehensive characterization and application performance of the resultant CGG/ACNF filament as a surgical suture are thoroughly investigated in comparison with silk and PGLA (90% glycolide and 10% l-lactide) sutures in vitro and in vivo, respectively. Results show that the CGG/ACNF filament with the typical core-shell structure and nervation pattern surface exhibits a high orientation index (0.74) and good mechanical properties. The tensile strength and knotting strength of CGG/ACNF suture prepared by twisting CGG/ACNF filaments increase by 69.5%, and CGG/ACNF suture has a similar friction coefficient to silk and PGLA sutures. Moreover, CGG/ACNF suture with antibiosis and cytocompatibility exhibits better growth promotion of cells than silk suture, similar to PGLA suture in vitro. In addition, the stitching experiment of mice with the CGG/ACNF suture further confirms better healing properties and less inflammation in vivo than silk and PGLA sutures do. Hence, the CGG/ACNF suture with a simple preparation method and excellent application properties is promising in surgical operations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".