Generation of double-layered equine mesenchymal stromal cell-derived osteochondral constructs
Bibliographic record
Abstract
Background: In vitro tissue engineering of osteochondral implants is an attractive solution to circumvent the limitations of these therapies by providing readily available grafts for patients. Objective: Generate and evaluate the mechanical properties of osteochondral constructs through double indentation and stress-relaxation tests. Methods: A stepwise approach was used to generate and improve osteochondral constructs. Unconfined compression and double indentation tests were used to obtain mechanical properties. Appearance of neocartilage was examined through histochemistry, immunohistochemistry, terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL), and live/dead staining. Results: We developed a method of cartilage generation from mesenchymal stromal cells (MSCs) on a porous calcium polyphosphate substrate, improving upon previous iterations to avoid the digestion of chondrocytes and circumvent cell contraction through the transient supplementation of a Rho-associated kinase (ROCK) inhibitor. We further improved neocartilage by producing them with an even surface and increasing their thickness through a double layering approach. Mechanical properties of osteochondral constructs were lower than native equine joint cartilage, however, stress-strain values at equilibrium was comparable to the medial trochlea and patellar groove regions from the native joint. Conclusions: MSC-derived osteochondral constructs generated through double-layering permit the formation of flat and thicker cartilage, with load-bearing capacity comparable to non-weight bearing regions from the native joint.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".