Acoustic Vibration Enhances Osteogenic Differentiation in Dental Mesenchymal Stem Cells
Bibliographic record
Abstract
Vibration-assisted orthodontic treatment accelerates tooth movement and reduces complications associated with prolonged interventions. While vibration has been shown to enhance osteogenic potential in bone marrow-derived mesenchymal stem cells (MSCs), its effects on dental tissue-derived MSCs remain unclear. This study investigated the impact of acoustic-frequency vibratory stimulation (AFVS) on gingival-tissue-derived MSCs (GT-MSCs) at 20 Hz and 60 Hz under both basal and osteogenic conditions. A custom vibratory platform was developed, and GT-MSCs were assessed for viability, proliferation, and osteogenic differentiation. Resazurin assay, Calcein-AM staining, and vimentin immunohistochemistry were used to evaluate cell viability, proliferation, and morphology, while Alizarin Red staining and calcium accumulation assays measured extracellular matrix mineralization at 7, 14, and 21 days. A Reverse-Transcription Quantitative Polymerase Chain Reaction (RT-qPCR) reaction was performed to quantify osteogenic markers (colagen type I [COL-I], osteopontin [OPN], and alkaline phosphatase [ALP]), and protein expression for COL-I and OPN was confirmed by immunohistochemistry. The results showed that AFVS at 20 Hz and 60 Hz enhanced osteogenic differentiation in GT-MSCs compare with other groups. Extracellular matrix mineralisation increased significantly, with 60 Hz resulting in the highest calcium deposition. Transcript levels of COL-I and OPN were markedly upregulated at 60 Hz, indicating a frequency-dependent response. Cell proliferation was also promoted, with optimal results observed at 60 Hz compare with other groups. These findings highlight the role of mechanical stimulation in enhancing the osteogenic potential of GT-MSCs, suggesting that AFVS is a promising tool for regenerative and orthodontic treatments. This study provides new insights into the frequency-specific effects of vibration, supporting the use of vibration therapy strategies in dental applications.
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 | 0.000 | 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".