A uniquely adaptable pore is consistent with NALCN being an ion sensor
Bibliographic record
Abstract
NALCN is an intriguing, orphan ion channel among the 4x6TM family of related voltage-gated cation channels, sharing a common architecture of four homologous domains consisting of six transmembrane helices, separated by three cytoplasmic linkers and delimited by N and C-terminal ends. NALCN is one of the shortest 4x6TM family members, lacking much of the variation that provides the diverse palate of gating features, and tissue specific adaptations of sodium and calcium channels. NALCN's most distinctive feature is that that it possesses a highly adaptable pore with a calcium-like EEEE selectivity filter in radially symmetrical animals and a more sodium-like EEKE or EKEE selectivity filter in bilaterally symmetrical animals including vertebrates. Two lineages of animals evolved alternative calcium-like EEEE and sodium-like EEKE / EKEE pores, spliced to regulate NALCN functions in differing cellular environments, such as muscle (heart and skeletal) and secretory tissue (brain and glands), respectively. A highly adaptable pore in an otherwise conserved ion channel in the 4x6TM channel family is not consistent with a role for NALCN in directly gating a significant ion conductance that can be either sodium ions or calcium ions. NALCN was proposed to be an expressible Gd ( 3+) -sensitive, NMDG (+) -impermeant, non-selective and ohmic leak conductance in HEK-293T cells, but we were unable to distinguish these reported currents from leaky patch currents (ILP) in control HEK-293T cells. We suggest that NALCN functions as a sensor for the much larger UNC80/UNC79 complex, in a manner consistent with the coupling mechanism known for other weakly or non-conducting 4x6TM channel sensor proteins such as Nax or Cav 1.1. We propose that NALCN serves as a variable sensor that responds to calcium or sodium ion flux, depending on whether the total cellular current density is generated more from calcium-selective or sodium-selective channels.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".