Jagged–Notch-mediated divergence of immune cell crosstalk maintains the anti-inflammatory response in visceral leishmaniasis
Bibliographic record
Abstract
ABSTRACT Notch signaling governs crucial aspects of intercellular communication spanning antigen-presenting cells and T-cells. In this study, we investigate how Leishmaniadonovani takes advantage of this pathway to quell host immune responses. We report induction of the Notch ligand Jagged1 in L. donovani-infected bone marrow macrophages (BMMϕs) and subsequent activation of RBPJκ (also known as RBPJ) in T cells, which in turn upregulates the transcription factor GATA3. Activated RBPJκ also associates with the histone acetyltransferase p300 (also known as EP300), which binds with the Bcl2l12 promoter and enhances its expression. Interaction of Bcl2L12 with GATA3 in CD4+ T cells facilitates its binding to the interleukin (IL)-10 and IL-4 promoters, thereby increasing the secretion of these cytokines. Silencing Jagged1 hindered these events in a BMMϕ–T cell co-culture system. Upon further scrutiny, we found that parasite lipophosphoglycan (LPG) induces the host phosphoinositide 3-kinase (PI3K)/Akt pathway, which activates β-catenin and Egr1, the two transcription factors responsible for driving Jagged1 expression. In vivo morpholino-silencing of Jagged1 suppresses anti-inflammatory cytokine responses and reduces organ parasite burden in L. donovani-infected Balb/c mice, suggesting that L. donovani-induced host Jagged1–Notch signaling skews macrophage–T cell crosstalk into disease-promoting Th2 mode in experimental visceral leishmaniasis. This article has an associated First Person interview with the first author of the paper.
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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".