Bibliographic record
Abstract
E-cadherin is a well-recognized molecule that is important in cell adhesion. Its abrogation has been linked to increased invasiveness in several malignancies. The normal immunohistochemical localization of E-cadherin is the cell membrane, however, both cytoplasmic and nuclear immunostaining has been reported. Loss of membrane staining and/or nuclear staining for E-cadherin is seen in 100% of cases of solid pseudopapillary tumors (SPTs) of the pancreas. In the context of SPT, E-cadherin staining is of diagnostic use. Nuclear staining has been seen in cases of pancreatic neuroendocrine tumors, Merkel cell carcinomas, clear cell renal cell carcinoma, esophageal squamous carcinoma, colorectal and gastric cancer, and synovial sarcoma. The difference in the staining patterns seen (complete loss vs. nuclear staining) is due to the type of E-cadherin antibody used. Antibodies recognizing the extracellular domain show loss of E-cadherin staining in SPT, whereas the antibody to the cytoplasmic domain results in nuclear staining in all cases of SPT. Therefore, E-cadherin staining is of diagnostic use in the immunohistochemical work-up of SPT. Nuclear E-cadherin staining of pancreatic neuroendocrine tumors identified a subset of cases with more aggressive potential, whereas nuclear staining of clear cell renal cancers identified a subset of tumors with a better prognosis. The exact mechanism by which E-cadherin enters the nucleus is not known but it is likely that it is closely related to several partner molecules such as beta-catenin, p120, and presenilin-1.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.008 | 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".