Leishmania infantum lipophosphoglycan induced-Prostaglandin E2 production in association with PPAR-γ expression via activation of Toll like receptors-1 and 2
Bibliographic record
Abstract
Abstract Lipophosphoglycan (LPG) is a key virulence factor expressed on the surfaces ofLeishmaniapromastigotes. Although LPG is known to activate macrophages, the underlying mechanisms resulting in the production of prostaglandin E2(PGE2) via signaling pathways remain unknown. Here, the inflammatory response arising from stimulation byLeishmania infantumLPG and/or its lipid and glycan motifs was evaluated with regard to PGE2induction. Intact LPG, but not its glycan and lipid moieties, induced a range of proinflammatory responses, including PGE2and nitric oxide (NO) release, increased lipid droplet formation, and iNOS and COX2 expression. LPG also induced ERK-1/2 and JNK phosphorylation in macrophages, in addition to the release of PGE2, MCP-1, IL-6, TNF-α and IL-12p70, but not IL-10. Pharmacological inhibition of ERK1/2 and PKC affected PGE2and cytokine production. Moreover, treatment with rosiglitazone, an agonist of peroxisome proliferator-activated receptor gamma (PPAR-γ), also modulated the release of PGE2and other proinflammatory mediators. Finally, we determined that LPG-induced PPAR-γ signaling occurred via TLR1/2. Taken together, these results reinforce the role played byL.infantum-derived LPG in the proinflammatory response seen inLeishmaniainfection.
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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) | 0.002 | 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".