HIF-1α hampers dendritic cell function and Th1 generation during chronic visceral leishmaniasis
Bibliographic record
Abstract
Abstract Inflammation, although responsible for controlling infection, is often associated with the pathogenesis of chronic diseases. Leishmania donovani , the causative agent of visceral leishmaniasis, induces a strong inflammatory response that leads to splenomegaly and ultimately immune suppression. Inflamed tissues are typically characterized by low levels of oxygen, a microenvironment that triggers the hypoxia-inducible transcription factor 1α (HIF-1α). Although HIF-1α plays an integral role in dendritic cell function, its involvement in the generation of protective Th1 responses against Leishmania has not yet been studied. Here we demonstrate that HIF-1α inhibits IL-12 production in dendritic cells, limiting therefore Th1 cell development. Indeed, depletion of HIF-1α in CD11c + cells resulted in higher and sustained expression of IL-12 and complete abrogation of IL-10. Moreover, CD11c-specific HIF-1α-deficient mice showed higher frequencies of IFN-γ-producing CD4 T cells in the spleen and bone marrow and, consequently, a significantly reduced parasite burden in both organs. Taken together, our results suggest that HIF-1α expression in dendritic cells largely contributes to the establishment of persistent Leishmania infection and may therefore represent a possible therapeutic target.
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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".