Localization of integrin αvß3 and vascular endothelial growth factor receptor-2 \n(KDR/Flk-1) in cutaneous and oral melanomas of dog
Bibliographic record
Abstract
Melanomas are common neoplasms of dogs \nand arise from pigment-producing cells called \nmelanocytes or melanoblasts. Melanomas of skin are \noften easily cured by surgical excision, but those of oral \nmucosa are aggressive, metastasize to the regional \nlymph nodes and lungs, and respond poorly to \nconventional therapy. Tumor growth is sustained by \nproliferation of microvessels via a process called \nangiogenesis. Integrin \nα \nvß3 is expressed in proliferating \nbut not in quiescent microvessels suggesting a role in \nangiogenesis. Vascular endothelial growth factor \n(VEGF) manifests its mitogenic and angiogenic effects \nmainly via VEGF receptor-2 (VEGFR-2/Flk-1). We \nconducted this immunocytochemical study to investigate \nthe expression of integrin \nα \nvß3 and VEGFR-2 in \narchival and fresh samples from cases of canine \nmelanomas. Results show that integrin \nα \nvß3 was \nexpressed in 72% and 88% of cutaneous and oral \nmelanomas, respectively, and the expression was \nrestricted to and immediately around the melanocytes \nand endothelial cells. VEGFR-2 staining of selected \ncases of melanoma revealed that its expression \noverlapped with the \nα \nv \nβ \n3 integrin. Dual immuno-gold \nelectron microscopy confirmed co-localization of \nintegrin \nα \nvß3 and VEGFR-2 in melanocytes and \nendothelial cells. These data demonstrate expression and \nco-localization of integrin \nα \nvß3 and VEGFR-2 in \ncutaneous and oral melanomas of dogs.
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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) | 0.002 | 0.001 |
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".