Voltage Gated Calcium Channels as Targets for Analgesics
Bibliographic record
Abstract
Management of pain is an essential aspect of medicine; however, current therapies are frequently insufficient owing to severe side effects or limited effectiveness. Therefore, the discovery of new analgesics is needed, especially to treat the proportion of painful patients poorly improved by available analgesics. The transmission of nociceptive stimuli in primary afferent neurons critically depends on a peculiar repertoire of various types of ion channels such as a number of TRP channels, persistent sodium channels, inwardly rectifying potassium channels and voltage-gated calcium channels that either detect noxious stimuli, or regulate cellular excitability and synaptic transmission. Moreover, some of these channels are redistributed and upregulated in pathological states leading to abnormal detection or transmission of harmful stimuli, and consequently lead to states of chronic pain. Hence, these channels are considered key targets for the development of analgesics. The nervous system expresses multiple types of calcium channels with specialized roles in neurophysiology. Here, we review the role of these channels and their accessory subunits in nociceptive signaling, and their potential as targets for development of innovative analgesics.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".