Cation and voltage dependence of lidocaine inhibition of the hyperpolarization-activated cyclic nucleotide-gated HCN1 channel
Bibliographic record
Abstract
Abstract Lidocaine is known to inhibit the hyperpolarization-activated mixed cation current (Ih) in cardiac myocytes and neurons, as well in cells transfected with cloned Hyperpolarization-activated Cyclic Nucleotide-gated (HCN) channels. However, the molecular mechanism of Ihinhibition by this drug has been limitedly explored. Here, we show that inhibition of Ihby lidocaine, recorded from Chinese hamster ovary (CHO) cells expressing the HCN1 channel, reached a steady state within one minute and was reversible. Lidocaine inhibition of Ihwas greater at less negative voltages and smaller current amplitudes whereas the voltage-dependence of Ihactivation was unchanged. Lidocaine inhibition of Ihmeasured at −130 mV (a voltage at which Ihis fully activated) was reduced, and Ihamplitude was increased, when the concentration of extracellular potassium was raised to 60 mM from 5.4 mM. By contrast, neither Ihinhibition by the drug nor Ihamplitude at +30 mV (following a test voltage-pulse to −130 mV) were affected by this rise in extracellular potassium. Together, these data indicate that lidocaine inhibition of Ihinvolves a mechanism which is antagonized by hyperpolarizing voltages and current flow.
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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) | 0.002 | 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".