Combination of polyetherketoneketone scaffold and human mesenchymal stem cells from temporomandibular joint synovial fluid enhances bone regeneration
Bibliographic record
Abstract
Therapies using human mesenchymal stem cells (MSCs) combined with three-dimensional (3D) printed scaffolds are a promising strategy for bone grafting. But the harvest of MSCs still remains invasive for patients. Human synovial fluid MSCs (hSF-MSCs), which can be obtained by a minimally invasive needle-aspiration procedure, have been used for cartilage repair. However, little is known of hSF-MSCs in bone regeneration. Polyetherketoneketone (PEKK) is an attractive bone scaffold due to its mechanical properties comparable to bone. In this study, 3D-printed PEKK scaffolds were fabricated using laser sintering technique. hSF-MSCs were characterized and cultured on PEKK to evaluate their cell attachment, proliferation, and osteogenic potential. Rabbit calvarial critical-sized bone defects were created to test the bone regenerative effect of PEKK with hSF-MSCs. In vitro results showed that hSF-MSCs attached, proliferated, and were osteogenic on PEKK. In vivo results indicated that PEKK seeded with hSF-MSCs regenerated twice the amount of newly formed bone when compared to PEKK seeded with osteogenically-induced hSF-MSCs or PEKK scaffolds alone. These results suggested that there was no need to induce hSF-MSCs into osteoblasts prior to their transplantations in vivo. In conclusion, the combined use of PEKK and hSF-MSCs was effective in regenerating critical-sized bone defects.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".