Histopathological classification and immunohistochemical characterization of canine mammary tumours
Bibliographic record
Abstract
The present study was carried out to investigate breed wise and age wise prevalence of canine mammary tumours (CMTs) along with histopathological and immunohistochemical characterization. A total of 97 CMTs samples were collected from different parts of Gujarat, India over period of three years (April 2014-March 2017). The mean age of the dogs, involvement of breeds and mammary glands were recorded. The mean±SD age of all affected dogs was 7.5±2.8 years. Among 12 breeds affected, most cases (n=77) of CMTs were recorded in four breeds viz., Pomeranian, Mongrel, Germen Shepard and Labrador. Caudal abdominal and inguinal mammary glands were frequently showed neoplastic growth. Among histological characterization of 97 CMTs, 16(16.49%) were non neoplastic proliferative/dysplastic lesions, 11 (11.34%) were benign neoplasms and 70 (72.16%) were malignant tumours. Out of 70 malignant neoplasms, epithelial neoplasms, special type epithelial neoplasms, mesenchymal neoplasms and carcinosarcomas were 53(54.64%), 6(6.19%), 8(8.25%), and 3(3.09%), respectively. Further, mixed carcinoma, tubulopapillary carcinoma, solid carcinoma, carcinoma and malignant myoepithelioma, tubular carcinoma and ductal carcinoma were frequently noted. Immunohistochemistry was found to be a powerful tool to classify the CMTs. In the present study, smooth muscle actin (SMA) helped in diagnosing complex adenoma, complex carcinoma, malignant myoepithelioma and fibrosarcoma. In complex adenoma, complex carcinoma and malignant myoepithelioma, myoepithelial cells showed strong SMA immunoreactivity, although stromal myofibroblasts and vascular smooth muscle cells also immunostained.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".