Genotypes and phenotypes of resistance in Ecuadorian Plasmodium falciparum
Bibliographic record
Abstract
BACKGROUND: Malaria continues to be endemic in the coast and Amazon regions of Ecuador. Clarifying current Plasmodium falciparum resistance in the country will support malaria elimination efforts. In this study, Ecuadorian P. falciparum parasites were analysed to determine their drug resistance genotypes and phenotypes. METHODS: Molecular analyses were performed to search for mutations in known resistance markers (Pfcrt, Pfdhfr, Pfdhps, Pfmdr1, k13). Pfmdr1 copy number was determined by qPCR. PFMDR1 transporter activity was characterized in live parasites using live cell imaging in combination with the Fluo-4 transport assay. Chloroquine, quinine, lumefantrine, mefloquine, dihydroartemisinin, and artemether sensitivities were measured by in vitro assays. RESULTS: The majority of samples from this study presented the CVMNT genotype for Pfcrt (72-26), NEDF SDFD mutations in Pfmdr1 and wild type genotypes for Pfdhfr, Pfdhps and k13. The Ecuadorian P. falciparum strain ESM-2013 showed in vitro resistance to chloroquine, but sensitivity to quinine, lumefantrine, mefloquine, dihydroartemisinin and artemether. In addition, transport of the fluorochrome Fluo-4 from the cytosol into the digestive vacuole (DV) of the ESM-2013 strain was minimally detected in the DV. All analysed samples revealed one copy of Pfmdr1. CONCLUSION: This study indicates that Ecuadorian parasites presented the genotype and phenotype for chloroquine resistance and were found to be sensitive to SP, artemether-lumefantrine, quinine, mefloquine, and dihydroartemisinin. The results suggest that the current malaria treatment employed in the country remains effective. This study clarifies the status of anti-malarial resistance in Ecuador and informs the P. falciparum elimination campaigns in the country.
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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 | 0.001 |
| 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) | 0.002 | 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".