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Study of the nematode putative GABA type‐A receptor subunits: evidence for modulation by ivermectin

2002· article· en· W1504724494 on OpenAlexaff
Xiao‐Peng Feng, Jon H. Hayashi, Robin N. Beech, Roger K. Prichard

Bibliographic record

VenueJournal of Neurochemistry · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsMcGill University
Fundersnot available
KeywordsBiologyReceptorAlleleGABAA receptorIvermectinXenopusgamma-Aminobutyric acidGABA receptorGeneticsAvermectinGeneMolecular biologyAnatomy

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.404

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.051
GPT teacher head0.293
Teacher spread0.242 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations131
Published2002
Admission routes1
Has abstractyes

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