Proinflammatory role of basophils in oxazolone‐induced chronic intestinal inflammation
Bibliographic record
Abstract
Abstract Background and Aim The functions of basophils have not been elucidated until recently because of their rarity. However, with recent developments in basophil‐specific antibodies and basophil‐deficient animals, the roles of basophils in various diseases related to chronic inflammation have been clarified. In this study, we aimed to investigate the roles of basophils in human ulcerative colitis (UC) and oxazolone (OXA) colitis using genetically engineered Mcpt8DTRmice. Methods Immunohistochemical staining of human colon specimens was performed to examine the involvement of basophils in the pathogenesis of UC. We examined the correlation between the number of infiltrating basophils and the UC endoscopic index of severity (UCEIS), Mayo score, and Matts score. We also examined the correlation between eosinophil count and basophil infiltration. In murine experiments, we examined whether basophil infiltration was involved in OXA‐induced colitis and whether basophil depletion improved inflammation in Mcpt8DTRmice. Results Colonic basophil infiltration was significantly increased in patients with UC. There were significant correlations between UCEIS, Mayo score, Matts score, and the number of infiltrating basophils. In murine OXA‐induced colitis, a significant increase in basophil infiltration was observed. When basophils were depleted by diphtheria toxin in Mcpt8DTRmice, inflammation improved significantly and mRNA expression of some proinflammatory cytokines, including Tnf‐α and Ifn‐γ decreased significantly. Conclusion Basophil infiltration correlated with endoscopic, clinical, and pathological scores in human UC independently of eosinophil infiltration, and depletion of basophils ameliorated mucosal inflammation in murine OXA‐induced colitis, collectively suggesting that basophils exert a proinflammatory role in chronic intestinal inflammation such as UC.
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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 | 0.000 |
| 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".