Interleukin 8-CXCR2–mediated neutrophil extracellular trap formation in biliary atresia associated with neutrophil extracellular trap–induced stellate cell activation
Bibliographic record
Abstract
BACKGROUND AND AIMS: Biliary atresia (BA) entails an inflammatory sclerosing lesion of the biliary tree, with prominent fibrosis in infancy. Previous studies revealed that neutrophil-activating IL-8 and neutrophil extracellular traps (NETs) positively correlated with bilirubin and the risk of liver transplant. The aims of this study were to determine the mechanism of NET formation (NETosis) in BA and whether NETs induce stellate cell activation. APPROACH AND RESULTS: BA and other liver disease control plasma and tissue were obtained at diagnosis and transplant. Elastase, NETs, and IL-8 were quantified by ELISA for plasma and by immunohistochemistry for liver tissue. FACS analysis of neutrophils co-cultured with BA or control plasma measured BA-specific NETosis. Stellate cell activation from co-culture studies of stellate cells with NETs was measured by real-time quantitative PCR, ELISA, and FACS. Liver neutrophils and NETs, and plasma elastase, NETs, and IL-8, were significantly increased in BA at diagnosis and transplant. Normal neutrophils co-cultured with BA plasma had increased NETosis and activation of CXCR2, an IL-8 receptor; CXCR2 inhibition decreased NET production. Immunohistochemistry identified increased NET expression of profibrogenic tissue factor and IL-17. NETs co-cultured with stellate cells resulted in stellate cell activation based on increased ACTA2 and COL1A1 mRNA, collagen protein, and cell surface expression of actin, collagen1A, and platelet-derived growth factor receptor-beta. CONCLUSIONS: Patients with BA have persistent IL-8-CXCR2-mediated NETosis that correlates with biomarkers of injury and fibrosis, and NETs induce stellate cell activation, suggesting a role for NETs in the immunopathogenesis of disease. Future investigations should focus on therapeutic agents that inhibit NETs in BA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".