Overexpression of BMI1, a polycomb group repressor protein, in bladder tumors: a preliminary report.
Bibliographic record
Abstract
INTRODUCTION: A Polycomb group repressor protein named BMI1 represses the genes that induce cellular senescence and cell death, and it can contribute to cancer when improperly expressed. We aimed to evaluate expression of BMI1 gene in bladder tumors. MATERIALS AND METHODS: Tissue specimens containing bladder tumor were evaluated and compared with intact tissues from tumor margins and normal bladders. There were 40 tumor specimens of patients with transitional cell carcinoma of the bladder, 20 tumor-free tissues taken from the margin of the tumors, and 8 specimens from patients without tumor. Specific primers for BMI1 and B2M (as an internal control) were used for reverse transcript polymerase chain reaction technique. The production and distribution of BMI1 protein was also examined by western blotting and immunohistochemistry techniques. RESULTS: Polymerase chain reaction generated a 683-bp product, corresponding to the expected size of BMI1 amplified region. The identity of the amplified fragment was then confirmed by direct DNA sequencing. The mean of expression of BMI1 detected in tumor tissues was significantly higher than that in intact tissues, and there was also a significant association between the mean of gene expression and the stage of malignancy (P < .001). The expression of BMI1 at protein level was further confirmed by western blotting and immunohistochemistry. CONCLUSION: BMI1 is a potent repressor of retinoblastoma and p53 pathways, and hence, elucidating its role in tumorigenesis is very important. We reported for the first time the expression of BMI1 and its correlation with incidence and progress of bladder tumors.
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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 | 0.000 | 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 | 0.000 |
| 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".