Distinct Roles for CD4+ Foxp3+ Regulatory T Cells and IL-10–Mediated Immunoregulatory Mechanisms during Experimental Visceral Leishmaniasis Caused by <i>Leishmania donovani</i>
Bibliographic record
Abstract
Abstract The outcome of intracellular parasitic infection can be determined by the immunoregulatory activities of natural regulatory CD4+ Foxp3+ T (Treg) cells and the anti-inflammatory cytokine IL-10. These mechanisms protect tissue but can also suppress antiparasitic CD4+ T cell responses. The specific contribution of these regulatory pathways during human parasitic diseases remains unclear. In this study, we investigated the roles of Treg cells and IL-10 during experimental visceral leishmaniasis caused by Leishmania donovani infection of C57BL/6 mice. We report only a limited contribution of Treg cells in suppressing antiparasitic immunity, but important roles in delaying the development of splenic pathology and restricting leukocyte expansion. We next employed a range of cell-specific, IL-10– and IL-10R–deficient mice and found these Treg cell functions were independent of IL-10. Instead, conventional CD4+ T cells and dendritic cells were the most important cellular sources of IL-10, and the absence of IL-10 in either cell population resulted in greater control of parasite growth but also caused accelerated breakdown in splenic microarchitecture. We also found that T cells, dendritic cells, and other myeloid cells were the main IL-10–responding cells because in the absence of IL-10R expression by these cell populations, there was greater expansion of parasite-specific CD4+ T cell responses associated with improved control of parasite growth. Again, however, there was also an accelerated breakdown in splenic microarchitecture in these animals. Together, these findings identify distinct, cell-specific, immunoregulatory networks established during experimental visceral leishmaniasis that could be manipulated for clinical advantage.
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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 | 0.001 | 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".