Pathomorphological features and mast cell count in canine visceral hemangiosarcomas
Bibliographic record
Abstract
Visceral hemangiosarcoma were analyzed at the Department of Veterinary Pathology of the Faculty of Veterinary Medicine, University of Zagreb, over a 5-year period. From a total of 52 tumor masses in a total of 31 dogs, histological growth patterns (cavernous, capillary or solid) and the amount of tumor supporting stroma were evaluated. Additionally, sections were stained with toluidine blue for the purpose of mast cell detection and their number was determined in the tumor parenchyma, tumor stroma and edges. The average age of the affected animals was 10 years, males predominated, and the tumors occurred most frequently in cross breeds, German Shepherd dogs and Labrador Retrievers. The highest number of visceral hemangiosarcoma was found in the spleen (27/52). The most common growth pattern of visceral hemangiosarcoma was solely cavernous with a mixture of cavernous and solid patterns in different proportions. Mast cells were found in 44/52 (84.6%) of the visceral hemangiosarcomas. A smaller number of mast cells were found in the tumor parenchyma, and higher number were found in the stroma and tumor edges. The number of mast cells in tumors was not significantly associated with the tumor growth pattern, but there was a positive correlation between MCC - tumor parenchyma and stroma (rs = 0.28, P<0.05), MCC - tumor stroma + edges (rs = 0.74, P<0.05) and MCC - tumor parenchyma and MCC- tumor stroma+edges (rs = 0.30, P<0.05) in all the examined tumors. In splenic tumors, there was only a significant positive correlation between MCC - stroma+edges (rs P = 0.68 P<0.05). These results suggest a higher mast cell count in tumors with more developed stromal components in canine visceral hemangiosarcomas, and certainly indicate the need for further research on their role and the factors they release in the development and progression of hemangiosarcomas.
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How this classification was reachedexpand
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 | 0.001 |
| 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 teacher head, 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".