Functional heterogeneity of meniscal fibrochondrocytes and microtissue models is dependent on modality of fibrochondrocyte isolation
Bibliographic record
Abstract
Collagenase digestion (d) and cellular outgrowth (og) are the current modalities of meniscus fibrochondrocytes (MFC) isolation for bioengineering and mechanobiology-related studies. However, the impact of these modalities on study outcomes is unknown. Here, we show that og- and d-isolated MFC have distinct proliferative capacities, transcriptomic profiles via RNA sequencing (RNAseq), extracellular matrix (ECM)-forming, and migratory capacities. Our data indicate that microtissue pellet models developed from og-isolated MFC display a contractile phenotype with higher expressions of alpha-smooth muscle actin (ACTA2) and transgelin (TAGLN) and are mechanically stiffer than their counterparts from d-MFC. Moreover, we introduce a novel method of MFC isolation designated digestion-after-outgrowth (dog). The transcriptomic profile of dog-MFC is distinct from d- and og-MFC, including a higher expression of mechanosensing caveolae-associated caveolin-1 (CAV1). Additionally, dog-MFC were superior chondrogenically and generated larger-size microtissue pellet models containing a higher frequency of smaller collagen fibre diameters. Thus, we demonstrate that the modalities of MFC isolation influence the downstream outcomes of bioengineering and mechanobiology-related studies.
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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".