Occurrence of the leucine-to-phenylalanine knockdown resistance (kdr) mutation in Anopheles arabiensis populations in Tanzania, detected by a simplified high-throughput SSOP-ELISA method
Bibliographic record
Abstract
Abstract Background Molecular markers of insecticide resistance can provide sensitive indicators of resistance development in malaria vector populations. Monitoring of insecticide resistance in vector populations is an important component of current malaria control programmes. Knockdown resistance (kdr) confers resistance to the pyrethroid class of insecticides with cross-resistance to DDT through single nucleotide polymorphisms (SNPs) in the voltage-gated sodium channel gene. Methods To enable detection of kdr mutations at low frequency a method was developed that uses polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELISA)-based technology, allowing rapid, reliable and cost-effective testing of large numbers of individual mosquitoes. This was used to assay mosquitoes from sites in lower Moshi, Tanzania. Results Sequence-specific oligonucleotide probes (SSOP) were used for simultaneous detection of both East and West African kdr mutations with high specificity and sensitivity. Application of the SSOP-ELISA method to 1,620 field-collected Anopheles arabiensis from Tanzania identified the West African leucine-phenylalanine kdr mutation in two heterozygous individuals, indicating the potential for resistance development that requires close monitoring. Conclusion The presence of the West African kdr mutation at low frequency in this East African population of An. arabiensis has implications for the spread of the kdr gene across the African continent.
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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) | 0.000 | 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".