Intramacrophage lipid accumulation compromises T cell responses and is associated with impaired drug therapy against visceral leishmaniasis
Bibliographic record
Abstract
Abstract Under perturbing conditions such as infection with Leishmania, a protozoan parasite living within the phagosomes in mammalian macrophages, cellular and organellar structures, and metabolism are dynamically regulated for neutralizing the pressure of parasitism. However, how modulations of the host cell metabolic pathways support Leishmania infection remains unknown. Herein, we report that lipid accumulation heightens the susceptibility of mice to L. donovani infection and promotes resistance to first‐line anti‐leishmanial drugs. Despite being pro‐inflammatory, the in vitro generated uninfected lipid‐laden macrophages (LLMs) or adipose‐tissue macrophages (ATMs) display lower levels of reactive oxygen and nitrogen species. Upon infection, LLMs secrete higher IL‐10 and lower IL‐12p70 cytokines, inhibiting CD4+ T cell activation and Th1 response suggesting a key modulatory role for intramacrophage lipid accumulation in anti‐leishmanial host defence. We, therefore, examined this causal relationship between lipids and immunomodulation using an in vivo high‐fat diet (HFD) mouse model. HFD increased the susceptibility to L. donovani infection accompanied by a defective CD4+ Th1 and CD8+ T cell response. The white adipose tissue of HFD mice displays increased susceptibility to L. donovani infection with the preferential infection of F4/80+CD11b+CD11c+ macrophages with higher levels of neutral lipids reserve. The HFD increased resistance to a first‐line anti‐leishmanial drug associated with a defective adaptive immune response. These data demonstrate that the accumulation of neutral lipids contributes to susceptibility to visceral leishmaniasis hindering host‐protective immune response and reducing the efficacy of antiparasitic drug therapies.
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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".