ArticleHeredity2025
A proof-of-concept experimental-theoretical model to predict pesticide resistance evolution.
Article in Heredity, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Ivermectin in veterinary medicine: a narrative review of antiparasitic efficacy, resistance evolution, antiviral evidence, and One Health implications.Frontiers in veterinary science · 2026Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Insecticide resistance poses a major challenge to sustainable agriculture, yet studying its evolution in laboratory settings is notoriously difficult due to challenges related to maintaining large populations of pest species. While theoretical models offer valuable predictions, an experimental system for validating insecticide resistance management strategies remains lacking. Here, we explore C. elegans as a model organism for studying insecticide resistance evolution. We developed an in silico population genetics model and tested its predictive power in laboratory experiments, comparing the computational predictions to experimental resistance selection dynamics. Two compounds with distinct modes of action were tested to assess the generalizability of this system across different resistance mechanisms. Our results showed that in silico predictions generally resembled multigenerational in vivo resistance selection outcomes, demonstrating the feasibility of integrating in vivo and in silico modelling approaches in resistance research. By bridging the gap between theoretical and empirical research, this framework paves the way for addressing a wide range of open questions in resistance management, permitting the development of better informed and more effective resistance management strategies for the agricultural industry.
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.