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Cannabinoid 1 and mu-Opioid Receptor Agonists Synergistically Inhibit Abdominal Pain and Lack Side Effects in Mice

2022· article· en· W4283834689 on OpenAlexafffund
Yang Yu, Quentin Tsang, Josue Jaramillo-Polanco, Alan Lomax, Stephen Vanner, David E. Reed

Bibliographic record

VenueJournal of Neuroscience · 2022
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsQueen's University
FundersCanadian Institutes of Health ResearchCrohn's and Colitis Canada
KeywordsCannabinoidPharmacologyAgonistOpioidNociceptionCannabinoid receptorMedicineCannabinoid Receptor AgonistsOpioid receptorAnalgesicAnesthesiaReceptorChemistryInternal medicine

Abstract

fetched live from OpenAlex

While effective in treating abdominal pain, opioids have significant side effects. Recent legalization of cannabis will likely promote use of cannabinoids as an adjunct or alternative to opioids, despite a lack of evidence. We aimed to investigate whether cannabinoids inhibit mouse colonic nociception, alone or in combination with opioids at low doses. Experiments were performed on C57BL/6 male and female mice. Visceral nociception was evaluated by measuring visceromotor responses (VMR), afferent nerve mechanosensitivity in flat-sheet colon preparations, and excitability of isolated DRG neurons. Blood oxygen saturation, locomotion, and defecation were measured to evaluate side effects. An agonist of cannabinoid 1 receptor (CB1R), arachidonyl-2′-chloroethylamide (ACEA), dose-dependently decreased VMR. ACEA and HU-210 (another CB1R agonist) also attenuated colonic afferent nerve mechanosensitivity. Additionally, HU-210 concentration-dependently decreased DRG neuron excitability, which was reversed by the CB1R antagonist AM-251. Conversely, cannabinoid 2 receptor (CB2R) agonists did not attenuate VMR, afferent nerve mechanosensitivity, or DRG neuron excitability. Combination of subanalgesic doses of CB1R and µ-opioid receptor agonists decreased VMR; importantly, this analgesic effect was preserved after 6 d of twice daily treatment. This combination also attenuated afferent nerve mechanosensitivity and DRG neuron excitability, which was inhibited by neuronal nitric oxide synthase and guanylate cyclase inhibitors. This combination avoided side effects (decreased oxygen saturation and colonic transit) caused by analgesic dose of morphine. Activation of CB1R, but not CB2R, decreased colonic nociception both alone and in synergy with µ-opioid receptor. Thus, CB1R agonists may enable opioid dose reduction and avoid opioid-related side effects. SIGNIFICANCE STATEMENT One of the most cited needs for patients with abdominal pain are safe and effective treatment options. The effectiveness of opioids in the management of abdominal pain is undermined by severe adverse side effects. Therefore, strategies to replace opioids or reduce the doses of opioids to suppress abdominal pain is needed. This study in mice demonstrates that cannabinoid 1 receptor (CB1R) agonists inhibit visceral sensation. Furthermore, a combination of subanalgesic doses of µ-opioid receptor agonist and CB1R agonist markedly reduce abdominal pain without causing the side effects of high-dose opioids. Thus, CB1R agonists, alone or in combination with low-dose opioids, may be a novel and safe treatment strategy for abdominal pain.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.015
GPT teacher head0.288
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations21
Published2022
Admission routes2
Has abstractyes

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