Human chondroprogenitors in alginate-collagen hybrid scaffolds produce stable cartilage<i>in vivo</i>
Bibliographic record
Abstract
The goal of this study was to evaluate human epiphyseal chondroprogenitor cells (ECPs) as a potential new cell source for cartilage regeneration. ECPs were compared to human bone marrow stromal cells (MSCs) and human adult articular chondrocytes (ACs) for their chondrogenic potential and phenotypic stability in vitro and in vivo. The cells were seeded in Optimaix-3D scaffolds at 5 × 104 cells/mm3 and gene expression, matrix production and mechanical properties were analysed up to 6 weeks. In vitro, ECPs synthesized consistently high collagen 2 and low collagen 10. AC-seeded constructs exhibited high donor variability in GAG/DNA values as well as in collagen 2 staining, but showed low collagen 10 production. MSCs, on the other hand, expressed high levels of collagen 2 but also of collagens 1 and 10, and were therefore not considered further. In vivo, there was considerable loss of matrix proteins in ECPs compared to in vitro cultured samples. To overcome this, a second implantation study investigated the effect of mixing cells with alginate prior to seeding in the scaffold. ECPs in alginate maintained their cartilage matrix and resisted mineralization and vessel infiltration better 6 weeks after subcutaneous implantation, whereas ACs lost their chondrogenic matrix completely. This study shows the great potential of ECPs as an off-the-shelf, highly chondrogenic cell type that produces stable cartilage in vivo. Copyright © 2016 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".