Human papillomavirus‐related cellular changes measured by cytometric analysis of DNA ploidy and chromatin texture
Bibliographic record
Abstract
BACKGROUND: Image cytometry has provided two highly sensitive markers for the identification of the malignant potential of squamous lesions. Aneuploidy and chromatin texture have been investigated as quantitative measures of nuclear damage in premalignant lesions and carcinoma. Real-time PCR methods have evolved to yield highly specific measurements of mRNA expression in very sparse cellular samples. METHODS: Human papillomavirus (HPV) 16 and 18 E7 mRNA expression was measured using quantitative RT-PCR. DNA index and chromatin measures were taken from image cytology samples. The chromatin features, through discriminant analysis, were aggregated into a score, and both measurements were related to mRNA expression. RESULTS: mRNA level and DNA index show an increasing trend over increasing histological grades. However, DNA index and chromatin score were not correlated to mRNA levels in these samples. Chromatin score differed by mRNA type found with HPV 18 infected samples having a higher score than those with HPV 16. Samples infected with HPV 16 and HPV 18 had even higher chromatin scores. CONCLUSIONS: DNA index and chromatin score were not directly correlated with mRNA levels. However both mRNA and DNA index were related to histological grade, and chromatin score was associated with HPV type. Therefore, DNA index and mRNA levels could be independent predictors of cervical dysplasia, and chromatin score could be related to the viral integration process in cells infected with HPV 18 or dual infections.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".