A Functional Comparison of Homopentameric Nicotinic Acetylcholine Receptors (ACR-16) Receptors From Necator americanus and Ancylostoma ceylanicum
Bibliographic record
Abstract
Effective control of hookworm infections in humans and animals relies on using a small group of anthelmintics. Many of these drugs target cholinergic ligand-gated ion channels, yet the direct activity of anthelmintics has only been studied in a subset of these receptors, primarily in the non-parasitic nematode,Caenorhabditis elegans. Here we report the characterization of a homopentameric ionotropic acetylcholine receptor (AChR), ACR-16, fromNecator americanusandAncylostoma ceylanicum, the first known characterization of human hookworm ion channels. We used two-electrode voltage clamp electrophysiology inXenopus laevisoocytes to determine the pharmacodynamics of cholinergics and anthelmintics on ACR-16 from both species of hookworm. TheA. ceylanicumreceptor (Ace-ACR-16) was more sensitive to acetylcholine (EC50= 20.64 ± 0.32 μM) and nicotine (EC50= 24.37 ± 2.89 μM) than theN. americanusreceptor (Nam-ACR-16) (acetylcholine EC50= 170.1 ± 19.23 μM; nicotine EC50= 597.9 ± 59.12 μM), at which nicotine was a weak partial agonist (% maximal acetylcholine response = 30.4 ± 7.4%). Both receptors were inhibited by 500 μM levamisole (Ace-ACR-16 = 65.1 ± 14.3% inhibition, Nam-ACR-16 = 79.5 ± 7.7% inhibition), and responded to pyrantel, but only Ace-ACR-16 responded to oxantel. We usedin silicohomology modeling to investigate potential structural differences that account for the differences in agonist binding and identified a loop E isoleucine 130 of Nam-ACR-16 as possibly playing a role in oxantel insensitivity. These data indicate that key functional differences exist among ACR-16 receptors from closely related species and suggest mechanisms for differential drug sensitivity.
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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".