Membrane loss and aberrant nuclear localization of E‐cadherin are consistent features of solid pseudopapillary tumour of the pancreas. An immunohistochemical study using two antibodies recognizing different domains of the E‐cadherin molecule
Bibliographic record
Abstract
AIM: To examine the expression of E-cadherin in solid pseudopapillary tumours (SPT) of the pancreas using two monoclonal antibodies recognizing two different domains of the E-cadherin molecule. METHODS AND RESULTS: Twenty cases of SPT were collected and a tissue microarray (TMA) constructed. The TMA was stained with commercially available antibodies to E-cadherin and beta-catenin. All 20 cases displayed nuclear beta-catenin as well as aberrant E-cadherin expression. With the antibody that stains the cytoplasmic domain of E-cadherin (clone 36, BD Transduction Laboratories), all 20 cases demonstrated nuclear E-cadherin reactivity, whereas with use of the antibody that recognizes the extracellular domain (clone 36B5, Vector Laboratories), no reactivity was observed in any of the cases. CONCLUSION: This study shows that aberrant beta-catenin and E-cadherin protein expression occurs in 100% of SPT, is probably linked mechanistically to beta-catenin nuclear localization, and two distinct patterns of E-cadherin immunoreactivity are seen in SPT: nuclear (with the antibody against the cytoplasmic domain), or immunonegativity (complete loss) when stained with the antibody for the E-cadherin extracellular fragment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".