Ivermectin imposes selection pressure on P-glycoprotein from <i>Onchocerca volvulus</i>: linkage disequilibrium and genotype diversity
Bibliographic record
Abstract
Widespread use of ivermectin (IVM) as part of the Onchocerciasis Control Program (OCP) in West Africa could influence the evolution of the human filarial parasite Onchocerca volvulus. Use of IVM, in some areas for 15 years, may have restricted genetic diversity of O. volvulus, resembling effects attributed to a population bottleneck. Large population-based chemotherapy programmes, such as the OCP, may impose strong selection pressure on parasites and an examination of possible genetic selection by IVM in O. volvulus is warranted. IVM is a substrate for P-glycoprotein; a homologue from O. volvulus (OvPGP) has been linked with IVM sensitivity. Linkage disequilibrium (LD) patterns of 28 genetic markers spanning the OvPGP locus were examined in 4 O. volvulus populations from the Volta Region of Ghana, West Africa. Reduced gene diversity, increased heterozygosity and an increase in the number of markers not in Hardy-Weinberg equilibrium were associated with increasing IVM treatment. The number of regions in LD decreased with treatment and with time. However, between 1999 and 2002, seven regions of OvPGP were always in complete LD, while surrounding areas showed a reduction in genetic variation. The use of IVM for onchocerciasis control has imposed strong selection on O. volvulus populations, reducing genetic variation and disrupting LD.
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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".