Inhibition of microRNA-155 attenuates concanavalin-A-induced autoimmune hepatitis by regulating Treg/Th17 cell differentiation
Bibliographic record
Abstract
Autoimmune hepatitis (AIH) is a chronic progressive autoimmune disease characterized by hepatic inflammation. This study aimed to investigate the effect of antagomir-155 on concanavalin A (ConA)-induced AIH, and its possible mechanisms. According to the results, the expression of miR-155 was raised in liver tissues after 48 h exposure to ConA. Treatment with antagomir-155 attenuated ConA-induced liver injury in mice by reducing serum alanine aminotransferase, aspartate aminotransferase, and alkaline phosphatase levels. In addition, antagomir-155 significantly alleviated the differentiation of Treg/Th17 cells in the livers of AIH mice, and suppressed Th17-cells-mediated production of pro-inflammatory cytokines IL-17A, IL-23, but not Treg-cells-mediated production of anti-inflammatory cytokine IL-10. Finally, the beneficial effect of antagomir-155 on ConA-induced AIH was abolished by administration of recombinant IL-17A. Our data demonstrated that antagomir-155 treatment could prevent AIH via regulating the differentiation of Treg and Th17 cells, suggesting that microRNA-155 may be an intriguing therapeutic target of AIH.
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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".