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Record W4415750136 · doi:10.1101/2025.10.30.685166

The <i>Dirofilaria immitis unc-49</i> gene encodes a pharmacologically unique cys-loop GABA receptor

2025· preprint· W4415750136 on OpenAlexaff
Sierra Varley, Tobias Clark, Nathan Chubb, Nicolas Lamassiaude, Claude Charvet, Cédric Neveu, Sean Forrester

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Language
FieldMedicine
TopicParasitic Diseases Research and Treatment
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsReceptorHomomericNematodeGeneProtein subunitGenome

Abstract

fetched live from OpenAlex

Abstract Nematode cys-loop GABA receptors play important roles in movement and locomotion. GABA receptors encoded by unc-49 appear to be widespread in nematode genomes including parasitic nematodes but are poorly characterized in filarial parasites. Dirofilaria immitis is a filarial parasite responsible for heartworm disease in dogs. Macrocyclic lactones are widely used to prevent heartworm infection. However, like many anthelmintics, resistance has emerged and new solutions are needed including the discovery of new anthelmintic drug targets. In this study, we report the isolation of two unc-49 subunit mRNAs ( unc-49b and unc-49c ) from the canine parasitic nematode D. immitis . When expressed in Xenopus oocytes, Dim-UNC-49B formed a functional homomeric GABA-gated channel, whereas Dim-UNC-49C did not. We further demonstrated that Dim-UNC-49B and Dim-UNC-49C gave rise to a functional heteromeric channel. Pharmacological characterization of these receptors and cross-species co-expression with UNC-49 subunits from the parasitic nematode Haemonchus contortus showed some unique properties compared to the same receptors characterized from other nematodes. These results revealed new properties of UNC-49 receptors in filarial worms.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.001

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 head0.016
GPT teacher head0.283
Teacher spread0.266 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)Same topicParasitic Diseases Research and TreatmentFrench-language works237,207