Regulatory T cells (Tregs) contribute to suppression of anti-malarial immunity by concurrent nematode infection (51.1)
Bibliographic record
Abstract
Abstract Here, we investigated the mechanisms involved in modulation of anti-malarial immunity by concurrent nematode infection. Both WT C57BL/6 (B6) and STAT-6 deficient (KO) mice co-infected with the gastrointestinal nematode Heligmosomoides polygyrus (Hp) 2 wk prior to blood-stage Plasmodium chabaudi AS (Pc) infection had significantly higher parasitemias and significantly lower serum IFN-γ levels compared to their respective controls infected with Pc alone. Hp-infected STAT-6 KO compared to WT mice produced significantly lower levels of Th2 cytokines (IL-4, IL-13) but Tregs (CD4+CD25+Foxp3− and CD4+CD25−Foxp3+) were significantly and similarly increased within 2 wk after Hp infection in both strains. Transfer of CD4+CD25+ Tregs from uninfected and Hp-infected B6 mice significantly increased malaria parasitemia in recipient mice while depletion of CD25+ cells suppressed parasitemia in Pc-infected mice but not in co-infected mice. FACS analysis revealed that anti-CD25 mAb (PC61) treatment reduced both CD4+CD25+ Tregs and CD4+Foxp3+ Tregs in Pc-infected but not in co-infected mice. Co-infection with Hp significantly enhanced Pc-induced TGF-β1 and IL-10 production. In vivo neutralization of TGF-β1 and blocking IL-10R with mAbs significantly reduced parasitemia in both Pc-infected and co-infected B6 mice; anti-IL-10R mAb treatment resulted in severe mortality. These results suggest that Tregs, and possibly immunoregulatory but not Th2 cytokines, contribute to suppression of anti-malarial immunity in nematode and malaria co-infected mice.
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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 | 0.000 | 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".