Species-Specific Antimonial Sensitivity in Leishmania Is Driven by Post-Transcriptional Regulation of AQP1
Bibliographic record
Abstract
Leishmania is a digenetic protozoan parasite causing leishmaniasis in humans. The different clinical forms of leishmaniasis are caused by more than twenty species of Leishmania that are transmitted by nearly thirty species of phlebotomine sand flies. Pentavalent antimonials (such as Pentostam or Glucantime) are the first line drugs for treating leishmaniasis. Recent studies suggest that pentavalent antimony (Sb(V)) acts as a pro-drug, which is converted to the more active trivalent form (Sb(III)). However, sensitivity to trivalent antimony varies among different Leishmania species. In general, Leishmania species causing cutaneous leishmaniasis (CL) are more sensitive to Sb(III) than the species responsible for visceral leishmaniasis (VL). Leishmania aquaglyceroporin (AQP1) facilitates the adventitious passage of antimonite down a concentration gradient. In this study, we show that Leishmania species causing CL accumulate more antimonite, and therefore exhibit higher sensitivity to antimonials, than the species responsible for VL. This species-specific differential sensitivity to antimonite is directly proportional to the expression levels of AQP1 mRNA. We show that the stability of AQP1 mRNA in different Leishmania species is regulated by their respective 3'-untranslated regions. The differential regulation of AQP1 mRNA explains the distinct antimonial sensitivity of each species.
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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".