Bibliographic record
Abstract
The birth and discovery of electrophysiological science took place in the 18--th century laying the path for our understanding of nerve membrane ionic currents. The pore-forming proteins, ion channels, are involved and play critical roles in very important physiological and pathological processes, such as neuronal signaling and cardiac excitability, therefore, they serve as therapeutic drug targets. The study of physiological, pharmacological and biophysical properties of ion channels can be done by patch clamp, a gold standard and powerful electrophysiological technique. The current review, in addition to highlight and cover the history of electrophysiology, patch clamp (conventional and automated) technique, and different types of ion channels, will also discuss the importance of ion channels in different neurological diseases and disorders. As the field of neuroscience is growing, this manuscript is intended as a guide to help in understanding the importance of ion channels, particularly in neuroscience, and also in using the patch clamp technique for the study of molecular physiology, pathophysiology, and pharmacology of neuronal ion channels. Importantly, this review will spotlight on the therapeutic aspect of neuronal ion channels. This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.030 | 0.049 |
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".