Immunohistochemical expression of melan-A and tyrosinase in uveal melanoma
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: Melan-A and tyrosinase are new immunohistochemical markers that can be used in the diagnosis of melanocytic lesions. The aim of this study was to investigate the correlation between radiotherapy or clinicohistopathological parameters and the expression of melan-A and tyrosinase in uveal melanoma. METHODS: Thirty-six enucleated cases of uveal melanoma were studied. The formalin-fixed, paraffin-embedded specimens were immunostained with monoclonal antibodies against melan-A and tyrosinase. The samples were classified as either positive or negative. The chi-square or the Student-t tests were used to test for the correlation of the expression rates of melan-A and tyrosinase with clinico-pathological parameters. RESULTS: Melan-A and tyrosinase were positive in 33 (91.7%) and 35 (97.2%) of the specimens, respectively. There was no significant association between the expression of melan-A or tyrosinase and radiotherapy or any clinico-pathological parameter. All specimens were positive for at least one of the immunohistochemical markers. CONCLUSION: To the best of our knowledge this is the first study concluding that the expression of melanocytic markers such as melan-A and tyrosinase is not influenced by radiotherapy or any clinico-pathological parameter. Moreover, when tyrosinase and melan-A are used together, 100% of the formalin-fixed, paraffin-embedded uveal melanoma samples tested positive for one of those markers.
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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 | 0.000 | 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) | 0.000 | 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