Dexrazoxane as a viable microsporidia control agent in <i>Anopheles gambiae</i>
Bibliographic record
Abstract
Abstract Microsporidia have long been proposed as biological agents for controlling disease vectors and the parasites they transmit. However, their study in vector biology has been constrained due to challenges in manipulating microsporidia within hosts. In this study, we investigated the effect of Dexrazoxane, a candidate drug against microsporidiosis, on the establishment and development of Vavraia culicis infection in its natural host, the mosquito Anopheles gambiae , the main malaria vector. Our findings show that Dexrazoxane significantly reduces spore load, particularly in mosquitoes reared individually, without affecting the overall infection success of the parasite. This result aligns with studies in Caenorhabditis elegans , where Dexrazoxane inhibited new spore production without hindering initial spore integration into the host gut cells. Dexrazoxane’s DNA topoisomerase II inhibitor mechanism likely explains its impact on mosquito development, as larvae exposed to the drug failed to emerge as adults. These findings highlight Dexrazoxane’s potential as a viable tool for controlling microsporidia in adult mosquitoes and hope to enhance the study of mosquito-microsporidia interactions. Further research is required to explore its broader application in vector-borne disease control, including malaria.
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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".