Increased expression of hPygo2 is a cellular response to HPV infection in cervical dysplasia
Bibliographic record
Abstract
We previously demonstrated that the Wnt‐signaling component, hPygo2 was required for cancer growth and that ELF‐1, which is normally regulated by the retinoblastoma (Rb) tumor suppressor, activates hPygo2 expression. Because the E7 protein of Human Papillomavirus (HPV) suppresses Rb function, we hypothesized that hPygo2 expression would be persistent in cervical cells transformed by HPV. Western and immunofluorecence analyses indicated that primary endocervical cell lines (HEN) did not express hPygo2, but that HPV‐transformed endocervical cells and cervical cancer cell lines highly expressed hPygo2. Transfection of a dominant active form of Rb into HPV infected cells reduced hPygo2 expression. Immunohistochemical analysis of hPygo2 and HPV protein expression in a tissue microarray of cervical cancer progression showed weak expression in nuclei of parabasal cells of normal ectocervical epithelium. CIN II and III staged dysplasias showed high levels of expression in cytoplasm and the highest levels of expression were found in squamous cell carcinomas, primarily in the cytoplasm. HPV antibodies stained nuclei and cytoplasm of non‐neoplastic tissues very strongly, and to a lesser extent CINII, III and squamous cell carcinomas. These observations suggested that hPygo2 protein accumulates increasingly with dysplasia leading to frank cancer.
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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) | 0.001 | 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".