Interleukin-17-Mediated Control of Parasitemia in Experimental<i>Trypanosoma congolense</i>Infection in Mice
Bibliographic record
Abstract
BALB/c mice are highly susceptible to experimental Trypanosoma congolense infections, whereas C57BL/6 mice are relatively resistant. Infected highly susceptible BALB/c mice die of systemic inflammatory response syndrome. Because interleukin-17 (IL-17) and Th17 cells regulate inflammatory responses, we investigated their role in the pathogenesis of experimental African trypanosomiasis in mice. We show that the production of IL-17 by spleen and liver cells and the serum IL-17 level increased after T. congolense infection in mice. Interestingly, infected highly susceptible BALB/c mice produced more IL-17 and had more Th17 cells than infected relatively resistant C57BL/6 mice. Paradoxically, neutralization of IL-17 with anti-IL-17 monoclonal antibody in vivo induced higher parasitemia in both the susceptible and the relatively resistant mice. Interestingly, anti-IL-17 antibody-treated mice had higher serum levels of alanine aminotransferase and aspartate aminotransferase, and the production of IL-10 and nitric oxide by liver cells was markedly decreased. Moreover, recombinant IL-17-treated mice exhibited significantly faster parasite control and lower peak parasitemia compared to control mice. Collectively, these results suggest that the IL-17/Th17 axis plays a protective role in murine experimental African trypanosomiasis.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".