Distinct immune characteristics distinguish hereditary and idiopathic chronic pancreatitis
Bibliographic record
Abstract
Chronic pancreatitis (CP) is considered an irreversible fibroinflammatory pancreatic disease. Despite numerous animal model studies, questions remain about local immune characteristics in human CP. We profiled pancreatic immune cell characteristics in control organ donors and CP patients including those with hereditary and idiopathic CP undergoing total pancreatectomy with islet autotransplantation. Flow cytometric analysis revealed a significant increase in the frequency of CD68+ macrophages in idiopathic CP. In contrast, hereditary CP samples showed a significant increase in CD3+ T cell frequency, which prompted us to investigate the T cell receptor β (TCRβ) repertoire in the CP and control groups. TCRβ sequencing revealed a significant increase in TCRβ repertoire diversity and reduced clonality in both CP groups versus controls. Interestingly, we observed differences in Vβ-Jβ gene family usage between hereditary and idiopathic CP and a positive correlation of TCRβ rearrangements with disease severity scores. Immunophenotyping analyses in hereditary and idiopathic CP pancreases indicate differences in innate and adaptive immune responses, which highlights differences in immunopathogenic mechanisms of disease among subtypes of CP. TCR repertoire analysis further suggests a role for specific T cell responses in hereditary versus idiopathic CP pathogenesis, providing insights into immune responses associated with human CP.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".