Analysis of Plasmodium falciparum Resistance to Chloroquine in Côte d'Ivoire after 20 Years: High Prevalence of Wild Strains
Bibliographic record
Abstract
Malaria is a major public health problem worldwide, especially in Africa, where antimalarial drug-resistant strains are spreading. In Côte d'Ivoire, Dihydro-artemisinine Piperaquine (DHA-PPQ) has been included in the policy for simple malaria management, but key mutations of the pfcrt gene are being studied to determine the mutation points that modulate Plasmodium falciparum resistance to Piperaquine. Genomic DNA from 158 patients from the five study sites with P.falciparum malaria was extracted using Chelex 5% tween. Conventional PCR amplification of the pfcrt gene was followed by Sanger sequencing of the amplificates on the Sanger sequencing platform of the CRCHU of Quebec (Canada). Comparison of different proportions was carried out using Rstudio software version 4.1.3. Analysis of individual alleles showed a prevalence of wild strain alleles over mutant alleles at all study sites. The K76T mutation was found at relatively low prevalences at the sites: 4.5% (1/22) in Bouaké; 10% (2/20) in Yamoussoukro; 18.5% (4/20) in Ayame; 20% (5/27) in Man and 34.8% (24/69) in Anonkoua-koute. Analysis of the distribution of the wild strain haplotype (CVMNK) of the pfcrt gene showed a high proportion (55-80% prevalence) compared to mutant strain haplotypes (1-20% prevalence). The high prevalence of the CVMNK haplotype across all sentinel sites supports the potential for regained sensitivity to CQ in the treatment of simple malaria. Therefore, continued molecular surveillance and in vitro analysis of pfcrt gene polymorphism mutations is highly recommended.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".