Pancreatic intraductal papillary mucinous neoplasm in a patient with Lynch syndrome
Bibliographic record
Abstract
Intraductal papillary mucinous neoplasm (IPMN) is a mucin-producing epithelial neoplasm that carries a risk of progression to invasive pancreatic ductal adenocarcinoma. Lynch syndrome is an autosomal dominant condition caused by germline mutations in mismatch repair genes such as MSH2 that lead to microsatellite instability and increased risk of tumor formation. Although families with Lynch syndrome have an increased risk of pancreatic cancer, a clear connection between Lynch syndrome and IPMN has not been drawn. We present a report of a 58 year-old Caucasian woman with multiple cancers and a germline mutation of MSH2 consistent with Lynch syndrome. A screening abdominal computed tomography scan revealed a dilated main pancreatic duct and cystic ductular structure in the uncinate process that were consistent with IPMN of the main pancreatic duct on excision. Immunohistochemistry and polymerase chain reaction of the patient's pancreas specimen did not reveal microsatellite instability or mismatch repair gene loss of expression or function. Our findings may be explained by the fact that loss of mismatch repair function and microsatellite instability is a late event in neoplastic transformation. Given the relative rarity of main duct IPMN, its appearance in the setting of somatic MSH2 mutation suggests that IPMN may fit into the constellation of Lynch syndrome related malignancies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".