Progesterone receptor reactivity in renal oncocytoma and chromophobe renal cell carcinoma
Bibliographic record
Abstract
AIMS: To investigate the reactivity for oestrogen and progesterone receptors (ER and PR) in renal oncocytoma (RO) and chromophobe renal cell carcinoma (CHRCC). MATERIALS AND METHODS: Thirty-eight RO, 25 CHRCC, 20 papillary RCC with oncocytic cytoplasm and 10 clear cell RCC with dominant eosinophilic cytoplasm were submitted for immunohistochemistry for ER, PR, CD117 and RCC. RESULTS: All cases of RO and CHRCC displayed moderately positive reactivity for PR. The nuclear reactivity ranged from 60% to 90% in RO and from occasional cells to 70% in CHRCC. In CHRCC, reactivity tended to be more prevalent in areas of tumour cells with eosinophilic cytoplasm. Progesterone reactivity was focal in areas. All RO and most CHRCC were reactive for CD117 and neither RO nor CHRCC was reactive for RCC. CD117 reactivity tended to be more intense in CHRCC than in RO. Negative reactivity for CD117 and positive reactivity for RCC were observed in almost all RCC, as reported in the literature. CONCLUSIONS: PR can be used in combination with CD117 and RCC in the differential diagnosis of RO and eosinophilic variant of CHRCC with other RCC with oncocytic or eosinophilic cytoplasm.
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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 | 0.002 |
| 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) | 0.002 | 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".