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 that included hereditary and idiopathic CP undergoing total pancreatectomy with islet auto-transplantation. Flow cytometric analysis revealed a significant increase in the frequency of CD68+ macrophages in idiopathic CP. In contrast, hereditary CP showed a significant increase in CD3+ T cell frequency, which prompted us to investigate the T cell receptor beta (TCR beta repertoire in CP and controls. TCR beta-sequencing revealed a significant increase in TCR beta repertoire diversity and reduced clonality in both CP groups versus controls. Interestingly, we observed differences in V-J gene family usage between hereditary and idiopathic CP and a positive correlation of TCR beta rearrangements with CP disease severity scores. Immunophenotyping analyses in hereditary and idiopathic CP pancreata indicate differences in innate and adaptive immune responses, which highlights differences in immunopathogenic mechanism 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 new 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.005 |
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".