Bibliographic record
Abstract
Introdução: o Melanoma Uveal (MU) e o tumor intraocular primario mais comum em adultos, levando a metastases e obito em 40% dos casos dentro de 10 anos do diagnostico do tumor primario, apesar de qualquer tipo de tratamento local e/ou sistemico. O receptor c-Kit (CD117) e um receptor de membrana do tipo tirosinaquinase e sua superexpressao tem sido observada em varias neoplasias. Mesilato de Imatinib (MI)e um composto aprovado pelo FDA (Food and Drugs Administration) que inibe receptores tirosinaquinase, como o c-kit. MI controla o crescimento tumoral em ate 85% dos casos de tumor estromal gastrointestinal avancado, uma neoplasia resistente a terapia convencional. Objetivo: caracterizar a expressao imuno-histoquimica do receptor c-kit no MU e a resposta in vitro de linhagens celulares de MU ao composto MI. Material e Metodos: cinquenta e cinco especimes de MU primario selecionados dos arquivos do Ocular Pathology Laboratory, McGill University, Montreal, Canada, foram submetidos a imunohistoquimica para c-kit. Todas as celulas que apresentaram distinta imunorreatividade foram consideradas positivas. Quatro linhagens humanas de celulas de MU e uma linhagem de melanocito uveal humano transformado foram testadas com Mesilato de Imatinib (concentracao de 10µM) in vitro atraves de ensaios de proliferacao (TOX-6) e invasao. Resultados: a expressao de c-Kit foi positiva em 78.2% dos MU. Houve uma diminuicao estatisticamente significante nas taxas de proliferacao e invasao de todas as 5 linhagens celulares. Conclusao: a maioria dos MU expressam c-Kit e as taxas de proliferacao e invasao das linhagens celulares de MU diminuiram com o uso de MI. Estes resultados podem justificar a necessidade de um ensaio clinico para investigar a resposta do MU in vivo ao MI
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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) | 0.002 | 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".