The increased expression of IL-23 in inflammatory bowel disease promotes intraepithelial and lamina propria lymphocyte inflammatory responses and cytotoxicity
Bibliographic record
Abstract
This study analyzed IL-23p19 expression in inflamed mucosa of IBD and the role in the induction of IEL and NK cell activation as well as Th17 cell differentiation. Expression of IL-23p19 was performed by immunohistochemistry and quantitative real-time PCR. Expression of IL-23R was assessed by flow cytometry. Cytolytic activities of IEL and NK cells by IL-23 were determined by a standard (51)Cr-release assay. Cytokine levels were analyzed by ELISA and quantitative real-time PCR. Expression of IL-23p19 was increased significantly in inflamed mucosa of CD compared with that in UC and healthy controls. Double-staining confirmed that IL-23p19(+) cells were mainly CD68(+) macrophages/DCs. IL-23R(+) cells were increased significantly in PB- and LP-CD4(+) and -CD8(+) T and NK cells. IL-23 markedly promoted IBD IEL and NK cell activation and cytotoxicity and triggered IBD PB- and LP-T cells to secrete significantly higher levels of IFN-γ, TNF, IL-2, and IL-17A compared with controls. Importantly, IL-23 promoted IBD PB- or LP-CD4(+) T cells to differentiate into Th17 cells, characterized by increased expression of IL-17A and RORC. Anti-TNF treatment could markedly reduce IL-23 expression and Th17 cell infiltration in inflamed mucosa of CD patients. These data indicate that IL-23 is highly expressed in inflamed mucosa of IBD and plays an important role in the induction of IEL, NK, and T cell activation, proinflammatory cytokine secretion, and Th17 cell differentiation. Targeted therapy directed against IL-23p19 may have a therapeutic role in treatment of IBD.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".