IFN-gamma mediated inflammatory monocyte recruitment neutralizes iNOS-dependent parasite killing by expanding the permissive host cell reservoir during early <i>Leishmania amazonensis</i> infection
Bibliographic record
Abstract
Abstract IFN-γ is a key factor in the elimination of intracellular parasites. However, during early L. amazonensis infection IFN-γ production does not correlate with a reduction in parasite growth and IFN-γ−/− mice do not have enhanced parasite loads. The reason why IFN-γ production does not reduce parasite loads during early L.a. infection is controversial. In order to investigate the role of IFN-γ during early L.a. infection we infected C57BL/6 Wt and IFN-γ−/− mice with 104 RFP+ parasites in the ear and followed disease for 6 wks. IFN-γ−/− mice showed equivalent lesion sizes and parasite numbers compared to Wt mice for the first 4 wks p.i., despite higher expression of the putative disease promoting factors IL-4 and arginase I. IFN-γ−/− mice had no CD11b+iNOS+ phagocytes while iNOS production was detected as early as 2 wks p.i. in Wt mice. Interestingly, Wt mice had higher numbers of inflammatory monocytes per ear during early infection. Inflammatory monocytes represented the majority of total infected cells and parasites within inflammatory monocytes cells were viable. Inflammatory monocytes were a small proportion of CD11b+iNOS+ cells in Wt mice and had significantly reduced levels of IFN-γR versus dendritic cells and macrophages. The enhanced host cell infiltrate observed in Wt mice may counteract the protective role of IFN-γ mediated iNOS expression. This could explain, in part, why IFN-γ production does not lead to a reduction in parasite load during early L. amazonesis infection. We propose IFN-γ plays a dual role, inducing both the expression of iNOS and parasite killing and the recruitment of inflammatory monocytes that support parasite replication during early infection.
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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".