Low-Level Laser Irradiation Promotes Proliferation and Differentiation on Apical Papilla Stem Cells
Bibliographic record
Abstract
Introduction: Low-level laser therapy (LLLT) has been reported to improve cell proliferation and differentiation. The stem cells derived from dental apical papilla (SCAPs) are a promising therapy because they are easily obtained from immature human teeth. The effect of LLLT over SCAPs is still unknown. This study aimed to evaluate the proliferation and osteogenic potential of the SCAPs stimulated with LLLT. Methods: SCAPs were isolated from the third molars of a healthy donor and characterized according to the minimum established criteria. SCAPs were cultured for 24 hours before being exposed to LLLT. Cells were exposed to different doses, energy, and wavelengths for selecting the irradiation parameters. SCAPs proliferation was evaluated with the MTT assay at 24 hours and 7-day post-laser exposure. VEGF and TGFβ2 expression were assessed with a specific enzyme-linked immunosorbent assay (ELISA). The osteogenic differentiation potential was analyzed with alizarin red staining, and the nodule quantification was performed by the relative optical density (ROD) analysis using ImageJ software. Results: The cells isolated from the apical papilla showed phenotype and stem cell properties. SCAPs irradiated with one dose at 6 J/m2 and 650 nm exhibited significantly higher proliferation (P>0.05) than the controls nonirradiated. LLLT stimulated SCAPs’ expression of factors VEGF and TGFβ2. Also, SCAPs irradiated showed higher osteogenic activity (P<0.05). Conclusion: LLLT promotes proliferation, osteogenic differentiation, and VEGF and TGFβ2 expression on SCAPs. LLLT is a practical approach for the preconditioning of SCAPs in vitro for future regenerative therapies. More studies are needed to determine the underlying molecular processes that determine the mechanism of the LLLT.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".