Bioengineering pediatric scaffold‐free auricular cartilaginous constructs
Bibliographic record
Abstract
OBJECTIVE: The use of exogenous materials as scaffolds in cartilage tissue engineering has limited the clinical application of resultant constructs due to the risk of postoperative complications. In an effort to minimize such complications, we aim to generate human, scaffold-free auricular cartilaginous constructs. STUDY DESIGN: Laboratory study using pediatric auricular cartilage. METHODS: Remnant, normal pediatric auricular cartilage samples that would have otherwise been discarded were collected and digested to free cells. Harvested cells were cultured and expanded in vitro for two passages and plated as micromass cultures. The culture medium was replaced with a chemically defined chondrogenic medium, and cellular monolayers surrounding micromass cultures were continuously scraped off. Constructs were allowed to mature for a period of 8 weeks. RESULTS: Micromass constructs showed mechanical stability and structurally resembled native auricular tissue, with a perichondrium-like layer of cells surrounding the inner cartilaginous zone. Constructs accumulated equivalent sulphated glycosaminoglycan and 50% of collagen content compared to native auricular cartilage by mass, while displaying 156% more cellularity. CONCLUSIONS: High-density micromass cultures of pediatric auricular chondrocytes can generate stable cartilaginous constructs following prolonged chondrogenic inductions in vitro. This technique is an essential step toward the development of three-dimensional constructs to recreate clinically applicable auricular cartilaginous constructs. LEVEL OF EVIDENCE: NA. Laryngoscope, 127:E153-E158, 2017.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".