Time course of 3D fibrocartilage formation by expanded human meniscus fibrochondrocytes in hypoxia
Bibliographic record
Abstract
Abstract Adult human meniscus fibrocartilage is avascular and nonhealing after injury. Meniscus tissue engineering aims to replace injured meniscus with lab‐grown fibrocartilage. Dynamic culture systems may be necessary to generate fibrocartilage of sufficient mechanical properties for implantation; however, the optimal static preculture conditions before initiation of dynamic culture are unknown. This study thus investigated the time course of fibrocartilage formation by human meniscus fibrochondrocytes on a three‐dimensional biomaterial scaffold under various static conditions. Human meniscus fibrochondrocytes from partial meniscectomy were expanded to passage 1 (P1) or P2 (3.0 ± 0.4 and 6.5 ± 0.6 population doublings), seeded onto type I collagen scaffolds, and grown in hypoxia (HYP, 3% O 2 ) or normoxia (NRX, 20% O 2 ) for 3, 6, and 9 weeks. Mechanical properties were not different between P1 and P2 cell‐based constructs. Mechanical properties were lower in HYP, increased continually in NRX only, and were positively correlated with glycosaminoglycan content and accumulation of hyaline cartilage‐like matrix components. The most mechanically competent tissues (NRX/9 weeks) reached 1/5 of the native meniscus instantaneous compression modulus but had an increasingly hypertrophic matrix‐forming phenotype. HYP consistently suppressed the hypertrophic phenotype. The results provide baselines of engineered meniscus fibrocartilage properties under static conditions, which can be used to select a preculture strategy for dynamic culture depending on the desired combination of mechanical properties, hyaline cartilage‐like matrix abundance, and hypertrophic phenotype.
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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".