Evaluation of SYK protein expression in treated versus untreated retinoblastoma
Bibliographic record
Abstract
Introduction Retinoblastoma is the most common intraocular malignancy in infants and children younger than 5 years. If untreated, retinoblastoma can metastasize and becomes fatal. Treatment mainly constitutes chemotherapy or enucleation in advanced cases. RB1 inactivation and epigenetic mutations play different roles in retinoblastoma tumorigenesis . Spleen tyrosine kinase ( SYK ) is a proto-oncogene that was found to be highly expressed in retinoblastoma. Aim We studied SYK expression in retinoblastoma in relation to histopathologic high-risk factors (HRF) while exploring the possible effects of chemotherapy on SYK expression. Material and methods Immunohistochemical staining of sections of paraffin-embedded retinoblastoma tissue was carried out. Detailed study of histopathologic HRF in relation to SYK expression and difference in SYK expression between treated and untreated cases were statistically analyzed. Results Cytoplasmic expression of SYK was detected in all studied cases. No statistical relation between SYK expression and any of the histopathologic HRF (degree of differentiation, nerve invasion, choroidal invasion, and necrosis) was detected. Further, there was no statistically significant difference in SYK expression between treated and untreated cases. Conclusion Expression of SYK in all retinoblastoma cases makes it a promising target for therapy. SYK expression was not correlated with any pathologic HRF. Neoadjuvant chemotherapy did not affect SYK expression.
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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 | 0.001 |
| 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) | 0.002 | 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".