Evidence map›Paper›PMID 42256394›Full record

ReviewFrontiers in pharmacology2026

Nicotinic acetylcholine receptors in pain modulation.

Junya Cheng, Junliang Chang, Shuai Li

Abstract readReview
In one paragraph

Review in Frontiers in pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Junya ChengChangchun Institute of Biological Products Co., Ltd., Changchun, China.
Junliang ChangChangchun Institute of Biological Products Co., Ltd., Changchun, China.
Shuai LiChangchun Institute of Biological Products Co., Ltd., Changchun, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chronic pain is widely recognized as a major global health problem that affects approximately one-fifth of the adult population and is associated with significant physical, psychological, and socioeconomic burden. Current clinical analgesic strategies are mainly based on non-steroidal anti-inflammatory drugs, opioids, and adjuvant agents including antidepressants and antiepileptic drugs. However, these therapies are limited by insufficient efficacy in neuropathic pain, considerable adverse effects, and the risks of tolerance and addiction. Therefore, the development of safer and more effective non-opioid analgesics remains an important unmet clinical need. Nicotinic acetylcholine receptors (nAChRs) have been identified as promising targets for the development of next-generation analgesics because of their roles in pain signal transmission, neuroinflammation, and immune-neural interactions. nAChRs are pentameric ligand-gated ion channels composed of different subunit combinations, which give rise to multiple receptor subtypes with distinct expression patterns and functional properties. Increasing evidence suggests that specific nAChR subtypes, including α3β4, α4β2, α6β4, α9α10, and α7, participate in the regulation of inflammatory pain, neuropathic pain, and cancer-related pain. This review summarizes recent progress in the understanding of subtype-specific roles of nAChRs in pain regulation. The development of highly selective tool compounds, particularly α-conotoxin-derived peptides, is discussed together with current knowledge regarding the mechanisms associated with nAChR-mediated analgesia. Challenges related to clinical translation and potential therapeutic strategies are also considered.

Indexed as

chronic painnAChR subtypesnAChR-targeted analgesicsnicotinic acetylcholine receptorstranslational pharmacology

Identifiers

PMID42256394
PMCPMC13236936

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.