What is the Origin of Pancreatic Endocrine Tumors?
Bibliographic record
Abstract
The cell of origin of pancreatic neuroendocrine neoplasia (PanNEN) is still the subject of debate. Data obtained using different -omics approaches as well as genetically engineered mice indicate diffuse neuroendocrine cells as the origin of PanNET and in general of neuroendocrine tumors. Lately, epigenetic signatures have indicated at least two major groups of PanNETs, one originating from β- and another from α-cells of the endocrine pancreas, with increased susceptibility for MEN1 and DAXX/ATRX mutations in α-cell tumors. Insulinomas originate from β-cells upon characteristic genetic alterations, even though transdifferentiation toward α-cells has been postulated in rare cases both in humans and in mouse models. Specific endocrine lineage transcription factors are expressed in agreement with the epigenetic group. While these data suggest an origin from adult endocrine cells, the expression of scattered progenitor markers in a subset of PanNET may indicate also a possible origin from endocrine precursor cells. In addition, cell plasticity and cell transdifferentiation complicate the delineation of a clear cell of origin in certain PanNENs. Interestingly, pancreatic neuroendocrine carcinomas seem to originate from acinar and ductal cells rather than from neuroendocrine ones.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".