Applied Compressive Strain Governs Hyaline-like Cartilage versus Fibrocartilage-like ECM Produced within Hydrogel Constructs
Bibliographic record
Abstract
The goal of cartilage tissue engineering (CTE) is to regenerate new hyaline cartilage in joints and treat osteoarthritis (OA) using cell-impregnated hydrogel constructs. However, the production of an extracellular matrix (ECM) made of fibrocartilage is a potential outcome within hydrogel constructs when in vivo. Unfortunately, this fibrocartilage ECM has inferior biological and mechanical properties when compared to native hyaline cartilage. It was hypothesized that compressive forces stimulate fibrocartilage development by increasing production of collagen type 1 (Col1), an ECM protein found in fibrocartilage. To test the hypothesis, 3-dimensional (3D)-bioprinted hydrogel constructs were fabricated from alginate hydrogel impregnated with ATDC5 cells (a chondrogenic cell line). A bioreactor was used to simulate different in vivo joint movements by varying the magnitude of compressive strains and compare them with a control group that was not loaded. Chondrogenic differentiation of the cells in loaded and unloaded conditions was confirmed by deposition of cartilage specific molecules including glycosaminoglycans (GAGs) and collagen type 2 (Col2). By performing biochemical assays, the production of GAGs and total collagen was also confirmed, and their contents were quantitated in unloaded and loaded conditions. Furthermore, Col1 vs. Col2 depositions were assessed at different compressive strains, and hyaline-like cartilage vs. fibrocartilage-like ECM production was analyzed to investigate how applied compressive strain affects the type of cartilage formed. These assessments showed that fibrocartilage-like ECM production tended to reduce with increasing compressive strain, though its production peaked at a higher compressive strain. According to these results, the magnitude of applied compressive strain governs the production of hyaline-like cartilage vs. fibrocartilage-like ECM and a high compressive strain stimulates fibrocartilage-like ECM formation rather than hyaline cartilage, which needs to be addressed by CTE approaches.
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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".