An Analysis of Genetic Diversity and Inbreeding in Wuchereria bancrofti: Implications for the Spread and Detection of Drug Resistance
Bibliographic record
Abstract
Estimates of genetic diversity in helminth infections of humans often have to rely on genotyping (immature) parasite transmission stages instead of adult worms. Here we analyse the results of one such study investigating a single polymorphic locus (a change at position 200 of the beta-tubulin gene) in microfilariae of the lymphatic filarial parasite Wuchereria bancrofti. The presence of this genetic change has been implicated in benzimidazole resistance in parasitic nematodes of farmed ruminants. Microfilariae were obtained from patients of three West African villages, two of which were sampled prior to the introduction of mass drug administration. An individual-based stochastic model was developed showing that a wide range of allele frequencies in the adult worm populations could have generated the observed microfilarial genetic diversity. This suggests that appropriate theoretical null models are required in order to interpret studies that genotype transmission stages. Wright's hierarchical F-statistic was used to investigate the population structure in W. bancrofti microfilariae and showed significant deficiency of heterozygotes compared to the Hardy-Weinberg equilibrium; this may be partially caused by a high degree of parasite genetic differentiation between hosts. Studies seeking to quantify accurately the genetic diversity of helminth populations by analysing transmission stages should increase their sample size to account for the variability in allele frequency between different parasite life-stages. Helminth genetic differentiation between hosts and non-random mating will also increase the number of hosts (and the number of samples per host) that need to be genotyped, and could enhance the rate of spread of anthelmintic resistance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".