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Record W2897772612 · doi:10.1097/pcr.0000000000000278

Pancreatic-Type Mixed Acinar Neuroendocrine Carcinoma Arising in the Common Bile Duct: A Case Report

2018· article· en· W2897772612 on OpenAlexaff
Khurram Shafique, Lik Hang Lee, Arbaz Samad, Lu Wang, David S. Klimstra

Bibliographic record

VenueAJSP Review and Reports · 2018
Typearticle
Languageen
FieldMedicine
TopicNeuroendocrine Tumor Research Advances
Canadian institutionsSt. Paul's HospitalUniversity of British Columbia
Fundersnot available
KeywordsSynaptophysinChromogranin APancreasPathologyBile ductCommon bile ductPancreatic ductImmunohistochemistryCholestasisMedicineInternal medicine

Abstract

fetched live from OpenAlex

Abstract Mixed acinar neuroendocrine carcinoma (MAcNEC) of pancreatic type arising in an extrapancreatic location is extremely rare. We present a case of a 70-year-old woman with constipation, abdominal discomfort, and jaundice. Imaging studies revealed a 1.8-cm solid mass in the common bile duct causing dilatation of intrahepatic and extrahepatic bile ducts, which was resected. Microscopically, the tumor was limited to the wall of the bile duct, without involvement of the pancreas, and was composed of solid sheets and nests of relatively monomorphic cells with minimal to moderate amounts of cytoplasm, granular chromatin, focally prominent nucleoli, and up to 160 mitoses per 10 high-power fields. Immunohistochemistry showed equal to or greater than 30% positivity for synaptophysin, chromogranin, chymotrypsin, and trypsin. A diagnosis of MAcNEC was rendered. Immunohistochemistry plays a pivotal role in the identification of these tumors and discrimination from other related entities, neuroendocrine neoplasms in particular. Because pancreatic heterotopia has been described in the common bile duct, we postulate that this case of MAcNEC in the common bile duct, the first to be reported in the literature, may have arisen via malignant transformation of pancreatic heterotopia.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.153
Threshold uncertainty score0.580

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.033
GPT teacher head0.355
Teacher spread0.322 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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