Fibrin Sealants from Fresh or Fresh/Frozen Plasma as Scaffolds for <i>In Vitro</i> Articular Cartilage Regeneration
Bibliographic record
Abstract
Our objective was to evaluate human CryoSeal fibrin glue derived from single units of plasma as scaffolds for articular cartilage tissue engineering. Human articular chondrocytes were encapsulated into genipin cross-linked fibrin glue derived from individual units of fresh or frozen plasma using the CryoSeal fibrin sealant (FS) system. The constructs were cultured for up to 7 weeks in vitro under low (5%) or normal (21%) oxygen. Chondrocyte viability was >90% within the fibrin gels. Hypoxia induced significant increases in collagen II and Sox9 gene expression and a significant decrease in collagen I. A significant increase in collagen II was detected in fresh plasma-derived cultures, while only collagen I was significantly increased in frozen plasma cultures. Significant increases in total glycosaminoglycan and collagen were detected in the extracellular matrix secreted by the encapsulated chondrocytes. A significant increase in compression modulus was only observed for fresh plasma-derived gels, which is likely explained by a greater amount of collagen type I detected after 7 weeks in frozen compared to fresh plasma gels. Our results indicate that CryoSeal fibrin glue derived from fresh plasma is suitable as a tissue engineering scaffold for human articular chondrocytes, and therefore should be evaluated for autologous articular cartilage regeneration.
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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 | 0.001 | 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".