Parasite-Derived Arginase Influences Secondary Anti-<i>Leishmania</i> Immunity by Regulating Programmed Cell Death-1–Mediated CD4+ T Cell Exhaustion
Bibliographic record
Abstract
The breakdown of L-arginine to ornithine and urea by host arginase supports Leishmania proliferation in macrophages. Studies using arginase-null mutants show that Leishmania-derived arginase plays an important role in disease pathogenesis. We investigated the role of parasite-derived arginase in secondary (memory) anti-Leishmania immunity in the resistant C57BL/6 mice. We found that C57BL/6 mice infected with arginase-deficient (arg(-)) L. major failed to completely resolve their lesion and maintained chronic pathology after 16 wk, a time when the lesion induced by wild-type L. major is completely resolved. This chronic disease was associated with impaired Ag-specific proliferation and IFN-γ production, a concomitant increase in programmed cell death-1 (PD-1) expression on CD4(+) T cells, and failure to induce protection against secondary L. major challenge. Treatment with anti-PD-1 mAb restored T cell proliferation and IFN-γ production in vitro and led to complete resolution of chronic lesion in arg(-) L. major-infected mice. These results show that infection with arg(-) L. major results in chronic disease due in part to PD-1-mediated clonal exhaustion of T cells, suggesting that parasite-derived arginase contributes to the overall quality of the host immune response and subsequent disease outcome in L. major-infected mice. They also indicate that persistent parasites alone do not regulate the quality of secondary anti-Leishmania immunity in mice and that the quality of the primary immune response may be playing a hitherto unrecognized dominant role in this process.
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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".