Multiple inhibitory effects of Au(CN)<sub>2</sub><sup>−</sup> ions on cystic fibrosis transmembrane conductance regulator Cl<sup>−</sup> channel currents
Bibliographic record
Abstract
Lyotropic pseudohalide anions are potentially useful as high affinity probes of Cl(-) channel pores. However, the interaction between these pseudohalides and the cystic fibrosis transmembrane conductance regulator (CFTR) Cl(-) channel have not been described in detail. Here we show that Au(CN)(2-) ions applied to the intracellular face of membrane patches from stably transfected baby hamster kidney cells inhibit CFTR channel currents by at least two mechanisms, which can be distinguished at the single channel level or by inhibiting channel closure using 2 mM pyrophosphate. Low concentrations (< 10 microM) of Au(CN)(2-) significantly reduced CFTR channel open probability. This effect was apparently voltage insensitive, independent of extracellular Cl(-) concentration, and lost following exposure to pyrophosphate. Higher concentrations of intracellular Au(CN)(2-) caused an apparent reduction in unitary current amplitude, presumably due to a kinetically fast blocking reaction. This effect, isolated following exposure to pyrophosphate, was strongly voltage dependent (apparent K(d) 61.6 microM at -100 mV and 913 microM at +60 mV). Both the affinity and voltage dependence of block were highly sensitive to extracellular Cl(-) concentration. We propose that Au(CN)(2-) has at least two inhibitory effects on CFTR currents: a high affinity effect on channel gating due to action on a cytoplasmically accessible aspect of the channel and a lower affinity block within the open channel pore. These results offer important caveats for the use of lyotropic pseudohalide anions such as Au(CN)(2-) as specific high affinity probes of Cl(-) channel pores.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".