<i>In Vivo</i> Ultrasound-Assisted Tissue-Engineered Mandibular Condyle: A Pilot Study in Rabbits
Bibliographic record
Abstract
CONTEXT: Tissue engineering of mandibular articular condyles encounters many challenges, especially restoring adequate mechanical strength that is correlated to matrix production by the tissue-engineered mandibular condyles (TEMCs). Low-intensity pulsed ultrasound (LIPUS) has been shown to enhance cell expansion, differentiation, and matrix production by different cells. OBJECTIVE: This study evaluated effect of daily LIPUS treatment (in vitro and in a pilot in vivo study) for 4 weeks on matrix production and functional integration of the TEMCs in rabbits. METHODS: Bone marrow stromal cells were isolated from the femoral bones of skeletally mature New Zealand rabbits, expanded, and differentiated into chondrogenic and osteogenic lineages. Animals employed in the in vivo study were divided into four groups: (1) TEMCs and LIPUS treatment; (2) TEMCs without LIPUS treatment; (3) empty scaffold and LIPUS treatment, and (4) empty scaffolds without LIPUS treatment. RESULTS: In vitro results showed that LIPUS enhanced chondrogenic and osteogenic differentiation of bone marrow stromal cells. The in vivo study showed that LIPUS led to better structural formation (namely, new osteogenic and chondrogenic tissue formation) and integration of the newly formed tissues and original condylar bone than those without LIPUS treatment. LIPUS resulted in a small amount of tissue regeneration in the empty scaffolds, whereas empty scaffolds without LIPUS treatment showed no signs of repair. CONCLUSIONS: The preliminary results of this pilot study suggest that LIPUS can enhance TEMCs both in vitro and in vivo.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".