Leishmania donovani promastigotes evade the activation of mitogen-activated protein kinases p38, c-Jun N-terminal kinase, and extracellular signal-regulated kinase-1/2 during infection of naive macrophages
Bibliographic record
Abstract
The protozoan parasite Leishmania fails to activate naive macrophages for proinflammatory cytokines production, and selectively impairs signal transduction pathways in infected macrophages. Because mitogen-activated protein kinases (MAPK)- and NF-kappaB-dependent signaling pathways regulate proinflammatory cytokines release, we investigated their activation in mouse bone marrow-derived macrophages (BMM) exposed to Leishmania donovani promastigotes. In naive BMM, the parasite failed to induce the phosphorylation of p38 MAPK, c-Jun N-terminal kinase (JNK), and extracellular signal-regulated kinase (ERK)1/2, as well as the degradation of IkappaB-alpha. The use of L. donovani mutants defective in the biosynthesis of lipophosphoglycan revealed that evasion of ERK1/2 activation requires surface expression of the repeating unit moiety of this virulence determinant. In IFN-gamma-primed BMM, L. donovani promastigotes strongly induced the phosphorylation of p38 MAPK and ERK1/2, and the use of selective inhibitors for ERK (PD98059) and p38 MAPK (SB203580) revealed that both kinases are required for L. donovani-induced TNF-alpha but not NO(2)(-) release. Collectively, these data suggest that both p38 MAPK and ERK1/2 pathways participate in some Leishmania-induced responses in IFN-gamma-primed BMM. The ability of L. donovani promastigotes to avoid MAPK and NF-kappaB activation in naive macrophages may be part of the strategy evolved by this parasite to evade innate immune responses.
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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 | 0.000 |
| 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".