The importance of tumor microenvironment modulations in the progression of pancreatic intraductal papillary mucinous neoplasms<sup>†</sup>
Bibliographic record
Abstract
Intraductal papillary mucinous neoplasms (IPMNs) of the pancreas have attracted substantial attention since they represent the most prevalent macroscopic precursor of pancreatic cancer. Most lesions show an epithelium with low-grade dysplasia and will remain indolent and unknown to the patient. Notably, a subgroup of IPMNs will progress to invasive cancer through a stepwise process characterized by the accumulation of specific genomic alterations and concomitant modifications of the tumor microenvironment (TME). The manuscript of Jamouss et al, recently published in The Journal of Pathology, expands the current knowledge on TME dynamics in IPMNs. The neoplastic progression of IPMNs is paralleled by a shift toward an immunosuppressive TME, with depletion of cytotoxic T cells, elevated expression of immune checkpoint molecules, including PD-L1 and VISTA, and increased density of macrophages. Overall, TME modifications are crucial in the progression of pancreatic IPMNs, calling for potential therapeutic strategies focused on TME modulations for cancer interception. © 2025 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".