Genetic Polymorphisms and Drug Susceptibility in Four Isolates of Leishmania tropica Obtained from Canadian Soldiers Returning from Afghanistan
Bibliographic record
Abstract
BACKGROUND: Cutaneous leishmaniasis (CL) is a vector-borne parasitic disease characterized by the presence of one or more lesions on the skin that usually heal spontaneously after a few months. Most cases of CL worldwide occur in Southwest Asia, Africa and South America, and a number of cases have been reported among troops deployed to Afghanistan. No vaccines are available against this disease, and its treatment relies on chemotherapy. The aim of this study was to characterize parasites isolated from Canadian soldiers at the molecular level and to determine their susceptibility profile against a panel of antileishmanials to identify appropriate therapies. METHODOLOGY/PRINCIPAL FINDINGS: Parasites were isolated from skin lesions and characterized as Leishmania tropica based on their pulsed field gel electrophoresis profiles and pteridine reductase 1 (PTR1) sequences. Unusually high allelic polymorphisms were observed at several genetic loci for the L. tropica isolates that were characterized. The drug susceptibility profile of intracellular amastigote parasites was determined using an established macrophage assay. All isolates were sensitive to miltefosine, amphotericin B, sodium stibogluconate (Pentostam) and paromomycin, but were not susceptible to fluconazole. Variable levels of susceptibility were observed for the antimalarial agent atovaquone/proguanil (Malarone). Three Canadian soldiers from this study were successfully treated with miltefosine. CONCLUSIONS/SIGNIFICANCE: This study shows high heterogeneity between the two L. tropica allelic versions of a gene but despite this, L. tropica isolated from Afghanistan are susceptible to several of the antileishmanial drugs available.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| 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".