Nonfunctional pancreatic endocrine tumor in the peripancreatic region in a Chinese patient with multiple endocrine neoplasia type 1
Bibliographic record
Abstract
Nonfunctional pancreatic neuroendocrine tumors (NF-pNETs) in patients with multiple endocrine neoplasia type 1 (MEN1), which results from a mutation in the MEN1 gene, are commonly small, multiple tumors located in the pancreatic head and inside the pancreatic parenchyma. We herein describe a 35-year-old woman with bone pain and a 7-year history of a prolactinoma. She was clinically diagnosed with MEN1 based on the presence of the prolactinoma and parathyroid hyperplasia. Abdominal computed tomography revealed a 5-cm mass close to the splenic hilum. This soft tissue tumor, which was located outside the pancreatic parenchyma and the tissue origin of which could not be identified preoperatively, was found to be connected to the pancreatic tail. After resection, histological examination revealed a well-differentiated neuroendocrine tumor of pancreatic origin. Genetic testing revealed a heterozygous transition mutation of guanine to adenine at the coding nucleotide 133 in exon 2 (c.133G>A), resulting in an amino acid substitution of glutamic acid with lysine (E45K) in the MEN1 gene. This patient with MEN1 presented with a clinical condition involving a single non-metastatic NF-pNET located outside the pancreatic parenchyma with a missense mutation in the MEN1 gene, which could easily have been misdiagnosed as an accessory spleen.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".