Biological Evaluation of Chitosan Salts Cross-Linked to Genipin as a Cell Scaffold for Disk Tissue Engineering
Bibliographic record
Abstract
Degenerative disc disease has been implicated as a major component of spine pathology. However, although biological repair of the degenerate disk would be the ideal treatment, there is no universally accepted scaffold for tissue engineering of the intervertebral disk. To help remedy this, we investigated the gelation kinetics of various concentrations (2.5 to 10%) of two water-soluble chitosan chlorides (low molecular weight Protasan UP CL113 and high molecular weight Protasan UP CL213) and two chitosan glutamates (low molecular weight Protasan UP G113 and high molecular weight Protasan UP G213). Various concentrations (5 to 20%) of genipin, a naturally occurring cross-linking reagent used in herbal medicine and in the fabrication of food dyes, were used to prepare cross-linked chitosan hydrogels. The results show that 2.5% Protasan UP G213 cross-linked to 5% genipin was the best candidate. This formulation gelled fastest at 37 degrees C, and maintained 95% viability of encapsulated cultured disk cells. The gel did not produce an inflammatory reaction when injected subcutaneously into C57BL/6 mice and is therefore biocompatible. Most importantly, when injected into the degenerated nucleus pulposus of human cadaveric intervertebral disk, the gel flowed into the clefts without leakage. This study demonstrates that 2.5% Protasan UP G213 cross-linked to 5% genipin might be a promising scaffold for disk tissue engineering.
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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) | 0.000 | 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".