Cytocompatible gel formation of chitosan‐glycerol phosphate solutions supplemented with hydroxyl ethyl cellulose is due to the presence of glyoxal
Bibliographic record
Abstract
To deliver and retain viable repair cells in a surgically prepared cartilage lesion, we previously developed an adhesive in situ-gelling cell carrier by suspending cells in a solution of hydroxyethyl cellulose (HEC), which was then mixed with chitosan-glycerol phosphate to form a chitosan-GP/HEC gel. The purpose of this study was to elucidate the mechanism of gelation to maximally control gel time and viability of encapsulated cells. We analyzed the role of osmolality, pH, gelation temperature, gel shrinkage, and HEC. A chitosan-GP solution at pH 6.8 with cytocompatible osmotic pressure (419 mOsm/kg) was achieved by lowering disodium GP concentration from 370 to 135 mM. This solution was still thermogelling but only at 73 degrees C. We next discovered that glyoxal, a common additive in ether cellulose manufacturing, was responsible for chitosan gelation. Monolayer cells survived and proliferated in up to 1 mM of glyoxal, however only a very narrow range of glyoxal concentration in chitosan-GP/HEC, 0.1-0.15 mM, permitted gel formation, cell survival, and cell proliferation. Chitosan gels containing HEC required slightly less glyoxal to solidify. Chitosan-GP/HEC loaded with viable chondrocytes formed an adhesive seal with ex vivo mosaic arthroplasty defects from sheep knee joints. In mosaic arthroplasty defects of live sheep, bleeding occurred beneath part of the hydrogel carrier, and the gel was cleared after 1 month in vivo. These data indicate that chitosan-GP/HEC is suitable as an adhesive and injectable delivery vehicle for clinical orthopedic applications involving single use treatments that guide acute cartilage repair processes.
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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) | 0.001 | 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".