<scp>SMARCB1</scp> (<scp>INI1</scp>)‐deficient sinonasal carcinoma manifesting as oral lesions: A report of two cases
Bibliographic record
Abstract
BACKGROUND: Sinonasal carcinomas represent a rare group of malignancies, accounting for less than 5% of all head and neck cancers and a worldwide incidence of less than 1 case per 100 000 inhabitants annually. Despite the restricted anatomical location, sinonasal carcinomas harbor some of the most histologically and molecularly diverse groups of tumors. SMARCB1 (INI1)-deficient sinonasal carcinomas are locally aggressive tumors commonly detected late, leading to devastating morbidity and mortality. CASE REPORT: We present two cases of SMARCB1-deficient sinonasal carcinoma involving the oral cavity and presenting as progressive radiolucent lesions with local swelling associated with maxillary dentition and alveolar bone. Both cases were initially considered odontogenic in origin and involved the destruction of the left anterior maxilla. CONCLUSION: Given the rarity and the variable presentation of these tumors, they pose a challenge for head and neck surgeons, dentists, and pathologists due to the potential overlapping features with odontogenic and non-odontogenic inflammatory and neoplastic lesions. These cases highlight the importance of a multidisciplinary team and include SMARCB1-deficient sinonasal carcinomas in the differential diagnosis of destructive lesions of the maxilla.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".