Study on cartilage nano scaffolds with acellular matrix and collagen II
Bibliographic record
Abstract
Objective: To explore the feasibility of preparing tissue-engineered nano scaffolds using acellular articular cartilage extracellular matrix (CAEM)and Type II collagen (COL II) via electrospinning technology. Methods: Rabbit costal cartilage was decellularized, defatted, and enzymatically digested, followed by drying to obtain CAEM.CAEM and COL II were mixed at a mass ratio of 1:2 and processed into tissue-engineered nano scaffolds using electrospinning technology. The physicochemical properties of the scaffolds were evaluated by measuring their water absorption rate and degradation rate. The cytotoxicity and cell adhesion properties of the scaffolds were assessed using the CCK-8 assay. Results: The fiber diameter of the CAEM-COL II nano scaffolds was (627±165.4) nm, with a water absorption rate of (623.0±27.4) %and a degradation rate of (45.6±5.8) %after 35 days. The CCK-8 assay results indicated that the CAEM-COL II composite scaffolds exhibited good adhesion properties for chondrocytes and favorable biological performance. Conclusion: The CAEM-COL II nano scaffolds provide an excellent microenvironment for the growth and proliferation of chondrocytes and have potential application value in tissue-engineered cartilage reconstruction.
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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".