Characterization of Ocular and Metastatic Uveal Melanoma in an Animal Model
Bibliographic record
Abstract
PURPOSE: To characterize, in detail, tumor development, malignant cell dissemination, and metastasis in a 10-week animal model of uveal melanoma. METHODS: One million 92.1 human primary uveal melanoma cells were injected into the suprachoroidal space of the right eye of 27 immunosuppressed albino rabbits. Intraocular tumor growth was monitored weekly by fundoscopy and by ultrasonography at the end of the experiment. To document the progression of the disease, one animal per week was killed. The enucleated eyes, lungs, and livers were macroscopically examined and histopathologically studied by hematoxylin and eosin, periodic acid-Schiff, and immunohistochemistry. Mononuclear layers isolated from the rabbits' blood samples were cultured. RESULTS: Histopathology showed intraocular tumors in 89% of the animals. Tumor growth was found 1 week after cell inoculation, and by the end of the experiment large tumor masses were observed. Microscopic pulmonary metastatic foci were first observed 4 weeks after cell injection. By the end of the experiment, all the animals had metastasis to the lungs. Interestingly, 18% of the animals also had micrometastasis to the liver. Viable adherent uveal melanoma cells were successfully isolated from peripheral blood and grown in vitro. CONCLUSIONS: In this study, most rabbits developed intraocular tumors followed by lung metastasis, and some of these rabbits later developed liver micrometastases. This novel source of research material warrants a follow-up longer than 10 weeks to further explore the pathophysiologic bases of liver involvement commonly encountered in humans. The success in the isolation and culture of circulating malignant cells in this animal model suggests that it might be worthwhile to explore the application of this technique to the management of patients with primary uveal melanoma.
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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 | 0.000 |
| 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".