Glutamine supplementation improves the efficacy of miltefosine treatment for visceral leishmaniasis
Bibliographic record
Abstract
BACKGROUND: The disturbance of host metabolic pathways by Leishmania parasites has crucial consequences for the activation status of immune cells and the outcome of infection. Glutamine has been described as an immunomodulatory amino acid, yet its role during Leishmania infection is still unknown. METHODS: We performed transcriptomics in uninfected and L. donovani-infected macrophages 6 hours post-infection. Glutamine quantification by HPLC was assessed in the supernatant of macrophages throughout the infection course. For experimental L. donovani infections, mice were infected with 1.0 x 108 stationary L. donovani promastigotes. Glutaminase (GLS) chemical inhibition was performed using BPTES and glutamine was administered throughout infection. For combined therapy experiment, a daily administration of miltefosine and glutamine was performed by oral gavage. Parasite burden was determined using a Taqman-based assay. Immune cell phenotyping and cytotoxicity were performed in splenic cells using flow cytometry. FINDINGS: We show that glutamine is essential for the control of L. donovani infection. Transcriptomic analysis of L. donovani-infected macrophages demonstrated an upregulation of genes involved in glutamine metabolism. Pharmacological inhibition of glutaminolysis significantly increased the susceptibility to infection, accompanied by an increased recruitment of anti-inflammatory myeloid cells and impaired T cell responses. Remarkably, the supplementation of glutamine to mice infected with L. donovani during miltefosine treatment potentiates parasite clearance through the development of a more effective anti-Leishmania adaptive immune response. CONCLUSIONS: Our data indicates that dietary glutamine supplementation may act as a promising adjuvant for the treatment of visceral leishmaniasis.
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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".