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Record W3007537677 · doi:10.1093/jcag/gwz047.123

A124 SYNERGISTIC INTERACTION OF CANNABINOIDS AND OPIOIDS REDUCES PAIN SIGNALING IN COLONIC NOCICEPTIVE NERVES

2020· article· en· W3007537677 on OpenAlexaffabout
Quentin Tsang, Yang Yu, Alan Lomax, Stephen Vanner, David E. Reed

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2020
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsQueen's University
Fundersnot available
KeywordsAgonistDAMGOMedicineCannabinoidNociceptionPharmacologyμ-opioid receptorCannabinoid Receptor AgonistsOpioidVisceral painCannabinoid receptorInternal medicineAnesthesiaReceptorEndocrinologyNeuroscienceOpioid receptorPsychology

Abstract

fetched live from OpenAlex

Abstract Background With the recent legalization of recreational marijuana in Canada, increasing numbers of patients with gastrointestinal (GI) disorders are using cannabis to treat their pain, either alone or together with opioids. However, little is known about potential benefits of cannabinoids for treating visceral pain originating within the GI tract and whether the combined use of cannabinoids and opioids could enable the reduction or even discontinuation of opioids. Aims To investigate the effects of cannabinoids alone or in combination with opioids on colonic nociceptive nerves. Methods Extracellular afferent nerve recordings were obtained from ex vivo flat sheet preparations of male C57BL/6 mouse distal colons. Single unit analysis discriminated individual afferent neuron responses to mechanical probing of the colon with a 1g von Frey hair before and after superfusion of HU-210, a selective CB1 receptor agonist, HU-308, a selective CB2 receptor agonist, DAMGO, a selective mu-opioid receptor (MOR) agonist, or a combination. In parallel studies, perforated patch clamp techniques were employed to assess the rheobase as a measure of neuronal excitability in acutely dissociated dorsal root ganglia (DRG) neurons in the presence of one or more of these agonists. Data were analyzed using a one-way ANOVA with Bonferroni multiple comparisons test. Results Superfusion of HU-210 (1 μM), caused significant inhibition in afferent nerve mechanosensitivity compared to control (6.2±1.1 vs. 13.7±2.5 Hz, p=0.005, n=10); lower concentrations (10 nM and 100 nM) had no effect (p>0.99, n=11; p=0.600, n=10 respectively). Conversely, the CB2 agonist HU-308 (1 μM and 10 μM), did not alter mechanosensitivity (p>0.9, n=8 for both concentrations). Superfusion of HU-210 alone (100 nM) or DAMGO (1 nM) alone in the same recording had no effect, but when both agonists were superfused together, there was a significant reduction in mechanosensitivity (8.1±1.7 vs. 14.8±2.3 Hz, p<0.01, n=10). In patch clamp recordings of DRG neurons, HU-210 (1 μM) decreased excitability (i.e. increased rheobase, 94.4±9.4 vs. 62.7±6.4 pA; p=0.031, n=9), whereas a lower concentration (100 nM) had no effect. Similar to afferent nerve recordings, when applied alone, DAMGO (1 nM) and HU-210 (100 nM) did not affect rheobase (DAMGO: p>0.99, n=9; HU-210: p>0.99, n=10), whereas the combination of both agonists significantly decreased excitability (123.0±13.4 vs. 62.7±6.4 pA, p<0.01, n=10). Conclusions Activation of CB1 receptors inhibits mechanosensitivity of colonic afferent nerves while a CB2 agonist had no effect. Interestingly, combination of sub-threshold concentrations of CB1 and MOR agonists inhibited colonic afferent nerves and thus, may suggest that cannabinoids could enable opioid dose reduction or discontinuation. Funding Agencies None

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)0.000
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.013
GPT teacher head0.261
Teacher spread0.248 · 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

Citations2
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the Canadian Association of Gastroenterology→Same topicCannabis and Cannabinoid Research→French-language works237,207→