<scp>BerEP4</scp> is widely expressed in tumors of the sweat apparatus: a source of potential diagnostic error
Bibliographic record
Abstract
BACKGROUND: A 63-year-old man presented with an ulcerated nodule with a rolled pearly edge on his back. A punch biopsy showed diffuse strong BerEP4 expression and retraction artifact. Consequently the tumor was diagnosed as a basal cell carcinoma but on excision the tumor proved to be a porocarcinoma. Although Jimenez et al. reported BerEP4 expression in porocarcinoma, this result is not widely appreciated. This observation prompted us to investigate BerEP4 expression in sweat apparatus tumors. METHODS: Immunocytochemistry was performed using Dako monoclonal mouse BerEP4 with Ventana Benchmark XT immunostainer. Omission of the primary antibody served as a negative control. RESULTS: Fourteen of 26 porocarcinomas had at least focal BerEP4 expression and two were diffusely and at least focally strongly positive. Seven of seven chondroid syringomas stained diffusely positive, with strong ductal expression; the single chondroid syringocarcinoma was negative. Five of 6 poromas and two of two hidradenomas had focal expression, and staining particularly highlighted the ducts, a co-localization also apparent in the four spiradenomas and three cylindromas. The single primary mucinous carcinoma had diffuse strong BerEP4 expression. DISCUSSION: This case and pilot study shows that BerEP4 expression is common in these selected sweat apparatus tumors, and staining may be strongly so. This observation should be borne in mind in clinical practice.
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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 | 0.002 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".