Drug susceptibility of a clinical isolate of <i>Balamuthia mandrillaris</i> , a pathogenic free-living amoeba
Bibliographic record
Abstract
ABSTRACT Balamuthia amoebic encephalitis (BAE) is a highly fatal infection caused by Balamuthia mandrillaris , an amoeba that lives in soil and water. In Thailand, three fatal cases of BAE have been documented, but no survivors have been reported, raising questions about current treatment regimens. Previous drug repurposing studies reveal some potent pharmacological compounds, but the drug susceptibility of the clinical isolate of pathogenic amoeba remains variable. Given the success in isolating B. mandrillaris from the human biopsied brain, this study aims to assess the amoebicidal effect of several previously repurposed drugs and suggested therapies for BAE. The trophozoites of a new clinical isolate, the KM-20 strain, were exposed to 12 compounds, including pentamidine, the most widely used antiprotozoal drug, and nitroxoline, the recent radical cure for BAE. The amoebicidal effect was assessed using the ATP level as a cell survival biomarker. The circularity and surface area of the cells were used as recrudescence indicators. Among all drugs tested, nitroxoline is the most potent amoebicidal drug without recrudescence. Topical antiseptic agents caused amoeba lysis at all doses tested, suggesting potential use for cutaneous balamuthiasis. Compared with two laboratory-adapted V039 and PRA-291 strains, the KM-20 isolate had reduced drug susceptibility to all of the tested compounds, suggesting strain dependency of amoebicidal activity. This study provides drug susceptibility data against a novel and geographically diverse clinical isolate of B. mandrillaris to assist in prioritizing anti- Balamuthia agents for further drug development testing, followed by in vivo efficacy testing animal models before clinical trials and drug repurposing.
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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".