APPLICATION OF STEM CELLS IN TREATMENT OF ORAL LICHEN PLANUS
Bibliographic record
Abstract
Background: Oral lichen planus (OLP) is a chronic inflammatory mucocutaneous disorder of autoimmune origin, often presenting as painful erosive or atrophic lesions in the oral cavity. Conventional therapies such as corticosteroids and immunosuppressants offer temporary relief but are associated with side effects and recurrence. Recent advancements in regenerative medicine highlight mesenchymal stem cells (MSCs), particularly gingiva-derived MSCs (GMSCs), for their immunomodulatory and regenerative potential. Objective: This study aimed to evaluate the safety and clinical efficacy of autologous gingiva-derived mesenchymal stem cells in the management of erosive OLP through a randomized, double-blind, placebo-controlled clinical trial. Methods: A total of 48 patients aged 30–65 years with clinically and histopathologically confirmed erosive OLP were randomized into two groups (n=24 each). The experimental group received three biweekly submucosal injections of GMSCs (1×10⁶ cells/mL), while the control group received placebo saline injections. Pain was assessed using the Visual Analog Scale (VAS), lesion size measured via digital calipers, and lesion severity evaluated using the Thongprasom score. Quality of life was assessed with the OHIP-14 questionnaire, and salivary levels of IL-6 and TNF-α were analyzed using ELISA at baseline, 2, 4, and 12 weeks post-treatment. Safety and adverse events were also monitored. Results: The MSC group demonstrated significant reductions in pain (VAS: from 6.9 to 1.0), lesion size (from 86.5 mm² to 20.7 mm²), and Thongprasom score (from 4.3 to 0.8) by week 12 (p<0.001). Salivary cytokines IL-6 and TNF-α significantly decreased, indicating reduced inflammation. Adverse events were mild and comparable between groups. Conclusion: GMSC therapy is a safe and effective treatment for erosive OLP, offering substantial clinical improvement and anti-inflammatory benefits. These findings support the potential of stem cell-based therapies as a regenerative alternative for chronic oral autoimmune conditions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".