DNMT3B (C46359T) Polymorphisms and Immunoexpression of DNMT3b and DNMT1 Proteins in Oral Lichen Planus
Bibliographic record
Abstract
OBJECTIVE: To investigate the DNMT3B (C46359T) polymorphism and immunoexpression of DNMT3b and DNMT1 in oral lichen planus (OLP) compared to a control group. METHODS: We aimed to investigate the DNMT3B (C46359T) polymorphism and immunoexpression of DNMT3b and DNMT1 in OLP (n = 32), comparing it with oral mucosa (control; n = 24). The DNMT3B (C46359T) polymorphism was analyzed using the RFLP-PCR and DNMT1, and DNMT3a proteins were identified using immunohistochemistry. We also compared the DNMT3B expression in OLP and oral inflammatory fibrous hyperplasia (OIFH), another oral inflammatory disease. Differences between the groups were determined by specific statistical analyses. RESULTS: The CT genotype of DNMT3B was associated with OLP development (p = 0.012). Increased expression of DNMT3B and DNMT1 was observed in OLP compared to the control group (p = 0.014 and p = 0.001, respectively). A significant increase in DNMT3B protein levels was observed in the genotype CT in DNMT3B (C46359T) polymorphisms (p = 0.045). No DNMT3B expression differences between OLP and OIFH were observed. CONCLUSIONS: Our data show that the DNMT3B (C46359T) polymorphism is associated with OLP development. Furthermore, increased expression of the enzyme DNMT3B, an epigenetic-associated protein, is present in OLP.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".