Targeting IL-17A Improves the Dysmotility of the Small Intestine and Alleviates the Injury of the Interstitial Cells of Cajal during Sepsis
Bibliographic record
Abstract
Intestinal dysmotility is a frequent complication during sepsis and plays an important role in the development of secondary infections and multiple organ failure. However, the central mechanisms underlying this process have not been well elucidated. Currently, effective therapies are still lacking for the treatment of sepsis-induced intestinal dysmotility. In this study, we found that the activation of IL-17 signaling within the muscularis propria might be associated with dysmotility of the small intestine during polymicrobial sepsis. Furthermore, we demonstrated that targeting IL-17A partially rescued the motility of the small intestine and alleviated interstitial cells of Cajal (ICC) injury during sepsis. The blockade of IL-17A suppressed the dominant sepsis-induced infiltration of M1-polarized macrophages into the muscularis. Additionally, impaired ICC survival may be associated with the oxidative stress injury induced by dominant infiltration of M1-polarized macrophages. Our findings reveal the important role of the IL-17 signaling pathway in the small intestine during sepsis and provide clues for developing a novel therapeutic strategy for treating gastrointestinal dysmotility during sepsis.
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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) | 0.001 | 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".