Abnormal DNA content in oral epithelial dysplasia is associated with increased risk of progression to carcinoma
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Oral epithelial dysplasia (OED) is a histologically detectable lesion that may progress to carcinoma but there are no accurate markers that predict progression. This study examined the development of carcinoma from oral dysplastic lesions, and the association between abnormal DNA content and progression to carcinoma. METHODS: Epithelial dysplasias from the Oral Pathology Diagnostic Service were matched against the Ontario Cancer Registry database to identify cases that progressed to carcinoma. A case-control study was conducted to compare DNA image cytometry of dysplasias that progressed with those that have not progressed. For a subset of the progressed dysplasias, DNA content of the carcinoma was also analysed. RESULTS: A total of 8% of epithelial dysplasias progressed to carcinoma after 6-131 months. In all, 28 of 99 dysplasias showed abnormal DNA content by image cytometry. In multivariate analysis of time to progression, abnormal DNA content was a significant predictor with hazard ratio of 3.3 (95% confidence interval: 1.5-7.4) corrected for site and grade of dysplasia. Analysis of sequential samples of dysplasia and carcinoma suggested that epithelial cell populations with grossly abnormal DNA content were transient intermediates during oral cancer development. CONCLUSIONS: Abnormal DNA content is a significant biomarker of a subset of OED that progress to carcinoma.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.001 |
| 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 it