Cellular dynamics of immune evasion during <i>Leishmania major</i> infection
Bibliographic record
Abstract
Abstract Despite the generation of a strong T cell response, clearance of Leishmania major is incomplete. Understanding of the persistence mechanisms is lacking, but Leishmania major driven induction of the immunosuppressive microenvironment through recruitment of regulatory T cells has been proposed to prevent parasite clearance in vivo. In the presented study, we used a novel TCR transgenic mouse model, where CD4+ T cells recognize an immunodominant peptide derived from Leishmania-glycosomal phosphoenolpyruvate carboxykinase (PEPCK), to visualize the dynamics of anti-L. major CD4+ T cell responses and to characterize mechanisms which restrain their effector function. We show that macrophage:T cell interaction dynamics were prolonged upon antigen recognition. This leads to a production of high levels of IFNγ and can be significantly suppressed by PEPCK-specific Tregs in vitro, as compared to polyclonal Treg controls. Treg antigen activation leads to a substantial increase in IL-10 levels, while decreasing IL-12, TNF, and IL-2 production. Intravital microscopy studies characterizing PEPCK-specific CD4+ T cell migration within skin lesions in mice show a significant recruitment of adoptively transferred effector T cells to the lesion site in vivo, displaying behaviours consistent with antigen recognition at early stages, but not at chronic stages. Imaging of infected FoxP3-GFP reporter mice show recruitment of Tregs to the lesion site, where they localize in the lesion, unlike the effectors cells which surround it. Collectively, our findings show for the first time that Leishmania-specific Tregs influence effector CD4+ T cell responses and this could be a mechanism that derives antigen persistence in L. major infection. Research funded by a grant from the GSK-CIHR Partnered Chair Program
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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 | 0.000 |
| 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".