lmmunohistochemical demonstration of metallothionein in benign and malignant canine mammary tumours
Bibliographic record
Abstract
Immunocytochemical demonstration of metallothionein (MT) has been reported as a useful prognostic tool in human breast cancer. The aim of this study was to determine the immunohistochemical location of MT in canine mammary tumours and its possible correlation with the morphologic characteristics of these tumours. Surgical specimens from spontaneous malignant (n=20) and benign mammary neoplasms (n=20) were processed for routine histological examination and immunohistochemical study. An indirect immunoperoxidase technique, using monoclonal antibody E9 against horse MT was employed. Intensity of the stain, the percentage of immunoreactive tumour cells and immunohistochemical overexpression of MT was estimated for each case. Metallothionein overexpression, defined as those cases with more than 10% immunopositive cells, was detected in both benign and malignant mammary tumours. However, strong immunostaining intensity was seen in benign tumours, whereas in malignant tumours immunopositive cells stained weakly. Positive MT immunostaining occurred in neoplastic epithelial cells, and some chondrocytes present in mixed mammary tumours. I-Iowever, staining intensity was variable in immunopositive cells. Differences in staining intensity between the primary malignant mammary tumour, tumour emboli and metastatic cells within a lymph node were also noted. Myoepithelial cells and connective tissue did not stain for MT. We concluded that metallothionein immunostaining cannot be used as a diagnostic or prognostic tool in canine mammary neoplasms. However, results of this study support the hypothesis that MT has a role in tumour proliferation and tumour progression.
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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".