Gene expression modulation and the molecular mechanisms involved in <scp>N</scp>elfinavir resistance in <i><scp>L</scp>eishmania donovani</i> axenic amastigotes
Bibliographic record
Abstract
Drug resistance is a major public health challenge in leishmaniasis chemotherapy, particularly in the case of emerging Leishmania/HIV-1 co-infections. We have delineated the mechanism of cell death induced by the HIV-1 protease inhibitor, Nelfinavir, in the Leishmania parasite. In order to further study Nelfinavir-Leishmania interactions, we selected Nelfinavir-resistant axenic amastigotes in vitro and characterized them. RNA expression profiling analyses and comparative genomic hybridizations of closely related Leishmania species were used as a screening tool to compare Nelfinavir-resistant and -sensitive parasites in order to identify candidate genes involved in drug resistance. Microarray analyses of Nelfinavir-resistant and -sensitive Leishmania amastigotes suggest that parasites regulate mRNA levels either by modulating gene copy numbers through chromosome aneuploidy, or gene deletion/duplication by homologous recombination. Interestingly, supernumerary chromosomes 6 and 11 in the resistant parasites lead to upregulation of the ABC class of transporters. Transporter assays using radiolabelled Nelfinavir suggest a greater drug accumulation in the resistant parasites and in a time-dependent manner. Furthermore, high-resolution electron microscopy and measurements of intracellular polyphosphate levels showed an increased number of cytoplasmic vesicular compartments known as acidocalcisomes in Nelfinavir-resistant parasites. Together these results suggest that Nelfinavir is rapidly and dramatically sequestered in drug-induced intracellular vesicles.
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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".