Ex vivo susceptibility and molecular signature assessment of antimalarial-based combination therapies (ACT) partner drugs resistance in Senegal
Bibliographic record
Abstract
Abstract Background Over the last decades, Plasmodium falciparum – the main causative agent of malaria – has constantly developed resistance to antimalarial drugs such as chloroquine, sulfadoxine-pyrimethamine or artemisinin derivatives. Therefore, active surveillance in the ex vivo susceptibility to the antimalarial drugs used as partner drugs in artemisinin-based combination therapies (the current frontline antimalarial) such as amodiaquine, lumefantrine or piperaquine, is essential. Methods Here, we evaluated the ex vivo susceptibility, expressed with the ex vivo SYBR™ Green, to six antimalarial drugs (amodiaquine, chloroquine, lumefantrine, mefloquine, piperaquine and quinine) from 34 P. falciparum isolates collected in 2018 in Thiès (Senegal). Whole-genome sequencing (WGS) was used to search for mutations in P. falciparum genes known to be associated with drug resistance. Results P. falciparum isolates showed reduced ex vivo susceptibility only to chloroquine (16% of the isolates). Mutations in pfcrt K76T (21%) and pfmdr1 Y184F (53%) were the most prevalent. A significant correlation was observed between the mutants pfcrt 76T and pfmdr1 184F and IC 50 values for chloroquine. A significant decrease in ex vivo susceptibility to chloroquine and quinine associated with the pfcrt R371I was also detected ( P < 0.001) . Conclusion Our results suggest that the ex vivo susceptibility of P. falciparum isolates to amodiaquine, lumefantrine, mefloquine, piperaquine and quinine remains high in Thiès. Directly measuring ex vivo parasite drug response and sequencing resistance mutations overtime are both useful tools for monitoring parasite drug response in field samples.
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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 | 0.000 | 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".