K+ Channels in Primary Afferents and Their Role in Nerve Injury-Induced Pain
Bibliographic record
Abstract
Sensory abnormalities generated by nerve injury, peripheral neuropathy or disease are often expressed as neuropathic pain. This type of pain is frequently resistant to therapeutic intervention and may be intractable. Numerous studies have revealed the importance of enduring increases in primary afferent excitability and persistent spontaneous activity in the onset and maintenance of peripherally-induced neuropathic pain. Much of this activity results from increased activity, modulation and /or expression of voltage-gated Na+ channels and hyperpolarization-activated cyclic nucleotide–gated (HCN) channels (particularly Nav1.3, 1.7, 1.8 and 1.9 and HCN2). Expression and/or function of K+ channels is reduced. This also increases excitability, alters axonal conduction and increases neurotransmitter release from primary afferent terminals in the spinal dorsal horn. The properties of nociceptive free nerve endings may also be affected. Although A-channels (Kv1.4, 3.3, 3.4, 4.1, 4.2 and 4.3), KCNQ or M-channels (Kv7.2, 7.3, 7.4 and 7.5) and ATP-sensitive channels (Kir6.2) have been extensively studied in this regard, less information is available for other K+ channel types particularly Ca2+-activated K+ channels (KCa1.1, 2.1, 2.2, 2.3 and 3.1), Na+-activated K+ channels (KCa4.1 and 4.2) and two pore domain leak channels (K2p; TWIK related channels). This review presents the distribution, physiological role and effect of injury on K+ channels in nociceptive and non-nociceptive primary afferents and how injury-induced changes might contribute to the onset and persistence of neuropathic pain. Whilst it is established that various mediators, including cytokines and growth factors bring about injury-induced changes in DRG function and excitability, evidence presently available points to a seminal role for interleukin 1 (IL-1) in control of K+ channel function. Despite the current state of knowledge, attempts to target K+ channels for therapeutic pain management have met with very limited success. Moreover, K+ channel activators such as pinacidil, retigabine, flupirtine and diazoxide which are approved for other therapeutic applications, have not gained widespread acceptance in the area of pain management. This situation may change with the advent of personalized medicine. Identification of specific sensory abnormalities and genetic profiling of individual patients may predict therapeutic benefit of K+ channel activators.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".