Enhanced Transmission of Drug-Resistant Parasites to Mosquitoes following Drug Treatment in Rodent Malaria
Bibliographic record
Abstract
The evolution of drug resistant Plasmodium parasites is a major challenge to effective malaria control. In theory, competitive interactions between sensitive parasites and resistant parasites within infections are a major determinant of the rate at which parasite evolution undermines drug efficacy. Competitive suppression of resistant parasites in untreated hosts slows the spread of resistance; competitive release following treatment enhances it. Here we report that for the murine model Plasmodium chabaudi, co-infection with drug-sensitive parasites can prevent the transmission of initially rare resistant parasites to mosquitoes. Removal of drug-sensitive parasites following chemotherapy enabled resistant parasites to transmit to mosquitoes as successfully as sensitive parasites in the absence of treatment. We also show that the genetic composition of gametocyte populations in host venous blood accurately reflects the genetic composition of gametocytes taken up by mosquitoes. Our data demonstrate that, at least for this mouse model, aggressive chemotherapy leads to very effective transmission of highly resistant parasites that are present in an infection, the very parasites which undermine the long term efficacy of front-line drugs.
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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 | 0.000 |
| 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".