The specific JNK inhibitor SP600125 targets tumour necrosis factor‐α production and epithelial cell apoptosis in acute murine colitis
Bibliographic record
Abstract
Stress-activated protein kinases (SAPKs) are activated in human inflammatory bowel disease (IBD). Recently it has been demonstrated that p38MAPK (mitogen-activated protein kinase) inhibition using SB203580 is effective in reducing disease in both dextran sulphate sodium (DSS)-induced and 2,4,6-trinitrobenzenesulphonic acid (TNBS)-induced murine colitides, underscoring the importance of this pathway in gastrointestinal inflammation. However, the contribution of c-Jun N-terminal kinase (JNK) in intestinal inflammation is unknown. Based on the known involvement of JNK in tumour necrosis factor-alpha (TNF-alpha) expression and in mediating the effects of oxidant stress, we hypothesized that JNK inhibition would also affect colitis. Our studies in mice with DSS-induced colitis treated with the JNK inhibitor SP600125, indicate that there is a significant reduction in wasting as well as a significant reduction in histological damage scores. Both total colonic and mesenteric lymphocyte CD3/CD28-stimulated TNF-alpha levels were dramatically reduced under the same circumstances. This was associated with a reduction in JNK protein expression and activity, as well as a reduction in AP-1 DNA binding with SP600125. Interestingly, there were no apparent changes in either p38MAPK or p42/44ERKs. Immunofluorescence of the colon for the active form of JNK revealed a prominent signal arising from the infiltrating inflammatory cells. SP600125 reduced this as well as, specifically, macrophage infiltration. Strikingly, we also demonstrate reduced epithelial cell apoptosis in response to treatment with SP600125. We conclude that specific inhibition of JNK is beneficial in the DSS model of colitis, and may be of value in human 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".