Genipin Cross-Linked Fibrin Hydrogels for in vitro Human Articular Cartilage Tissue-Engineered Regeneration
Bibliographic record
Abstract
Our objective was to examine the potential of a genipin cross-linked human fibrin hydrogel system as a scaffold for articular cartilage tissue engineering. Human articular chondrocytes were incorporated into modified human fibrin gels and evaluated for mechanical properties, cell viability, gene expression, extracellular matrix production and subcutaneous biodegradation. Genipin, a naturally occurring compound used in the treatment of inflammation, was used as a cross-linker. Genipin cross-linking did not significantly affect cell viability, but significantly increased the dynamic compression and shear moduli of the hydrogel. The ratio of the change in collagen II versus collagen I expression increased more than 8-fold over 5 weeks as detected with real-time RT-PCR. Accumulation of collagen II and aggrecan in hydrogel extracellular matrix was observed after 5 weeks in cell culture. Overall, our results indicate that genipin appeared to inhibit the inflammatory reaction observed 3 weeks after subcutaneous implantation of the fibrin into rats. Therefore, genipin cross-linked fibrin hydrogels can be used as cell-compatible tissue engineering scaffolds for articular cartilage regeneration, for utility in autologous treatments that eliminate the risk of tissue rejection and viral infection.
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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".