Expression of odontogenic ameloblast‐associated protein, amelotin, ameloblastin, and amelogenin in odontogenic tumors: immunohistochemical analysis and pathogenetic considerations
Bibliographic record
Abstract
Screening for expression of amelogenesis-related proteins represents a powerful molecular approach to characterize odontogenic tumors and investigate their pathogenesis. In this study, we have examined the presence and distribution of odontogenic ameloblast-associated protein (ODAM), amelotin (AMTN), ameloblastin (AMBN), and amelogenin (AMEL) by immunohistochemistry in samples of adenomatoid odontogenic tumor (AOT), calcifying epithelial odontogenic tumor (CEOT), developing odontoma, ameloblastoma, calcifying cystic odontogenic tumor (CCOT), ameloblastic fibroma (AF), myxoma, odontogenic fibroma (OF), and reduced enamel epithelia (REE). Positive results were obtained in those tumors with epithelial component, except for AF, OF, and ameloblastoma. ODAM was found around mineralized structures (dystrophic calcifications) and CEOT's amyloid, whereas AMTN stained the eosinophilic material of AOTs. The CCOT transitory cells to ghost cells were strongly positive with all proteins except AMEL, and the REE as well as odontomas showed immunoexpression for ODAM, AMTN, AMBN, and AMEL similar to those found in normal rat tooth germs. Based on these results, some histopathogenetic theories were formulated.
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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) | 0.000 | 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 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".