Ivermectin resistance and overview of the Consortium for Anthelmintic Resistance SNPs
Bibliographic record
Abstract
Ivermectin (IVM) has transformed nematode parasite control in veterinary medicine and the control of some nematode infections in humans, such as onchocerciasais, lymphatic filariasis in Africa and strongyloidiasis. Unfortunately, IVM resistance is now a serious problem for parasite control in livestock and there is a concern about resistance development and spread in nematode parasites of humans. IVM is believed to act by opening glutamate-gated chloride channels and GABA-gated channels in invertebrate neurons or muscle cells, leading to hyperpolarisation of the cells and to an inhibitory paralysis. However, in the filarial nematodes, it is not altogether clear that the effect of IVM is confined to these actions or even whether these are the most important. Alterations in some ligand-gated ion channel (LGIC) receptor subunits may play a role in the mechanisms of IVM resistance in some nematodes, but the evidence that changes in LGICs are the most important cause of IVM resistance in nematodes is far from clear. What is evident is that IVM is an excellent substrate for some ATP-binding cassette transporters, IVM selects for changes in expression levels of ABC transporters, such as P-glycoproteins, and that altered levels of some ABC transporters contribute to IVM resistance. In addition, there is growing evidence that IVM selects on β-tubulin, at least in some nematodes. Based on these various mechanisms, which contribute to IVM resistance, it may become possible to develop panels of molecular markers for IVM resistance in different nematode parasites. In order to stimulate the development of such markers, an international Consortium for Anthelmintic Resistance SNPs (CARS) has been developed to help coordinate marker development, advance our knowledge of helminth biology and possibly assist with the development of new anthelmintic molecules.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 0.013 |
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".