Study of the nematode putative GABA type‐A receptor subunits: evidence for modulation by ivermectin
Bibliographic record
Abstract
Two alleles of the HG1 gene, which encodes a putative GABA receptor alpha/gamma subunit, were isolated from Haemonchus contortus. These two alleles were shown previously to be associated with ivermectin susceptibility (HG1A) and resistance (HG1E), respectively. Sequence analysis indicates that they differ in four amino acids. To explore the functional properties of the two alleles, a full-length cDNA encoding the beta subunit, a key functional component of the GABA receptor, was isolated from Caenorhabditis elegans (gab-1, corresponding to the GenBank locus ZC482.1) and coexpressed in Xenopus oocytes with the HG1 alleles. When gab-1 was coexpressed with either the HG1A allele or the HG1E allele in Xenopus oocytes, gamma-aminobutyric acid (GABA)-responsive channels with different sensitivity to the agonist were formed. The effects of ivermectin on the hetero-oligomeric receptors were determined. Application of ivermectin alone had no effect on the receptors. However, when coapplied with 10 micro m GABA, ivermectin potentiated the GABA-evoked current of the GAB-1/HG1A receptor, but attenuated the GABA response of the GAB-1/HG1E receptor. We demonstrated that the coexpressed HG1 and GAB-1 receptors are GABA-responsive, and provide evidence for the possible involvement of GABA receptors in the mechanism of ivermectin resistance.
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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".