MétaCan
Menu
← Back to cohort
Record W4391873782 · doi:10.1093/jcag/gwad061.007

A7 CANNABINOID 1 AND 2 RECEPTOR AGONISTS AND MU-OPIOID RECEPTOR AGONISTS SYNERGISTICALLY INHIBIT COLONIC NOCICEPTION DURING ACUTE COLITIS

2024· article· en· W4391873782 on OpenAlexaff
Quentin Tsang, Alan Lomax, Stephen Vanner, David E. Reed

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2024
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal motility and disorders
Canadian institutionsQueen's University
Fundersnot available
KeywordsCannabinoidNociceptionPharmacologyReceptorCannabinoid receptorOpioidChemistryCannabinoid receptor type 2Cannabinoid Receptor AgonistsColitisAgonistMedicineInternal medicineBiochemistry

Abstract

fetched live from OpenAlex

Abstract Background Abdominal pain is a debilitating symptom in patients with inflammatory bowel disease. Previously we have shown that combining sub-analgesic doses of cannabinoid 1 receptor (CB1R), but not cannabinoid 2 receptor (CB2R), and mu-opioid receptor (MOR) agonists synergistically inhibits colonic nociception in healthy mice. However, it is unknown whether this combination has analgesic efficacy in a pre-clinical model of colitis. Aims To determine the effects of combining sub-analgesic doses of CBR and MOR agonists on colonic nociception during acute colitis. Methods Colitis was induced in male and female C57BL/6 mice with 2.5% dextran sulfate sodium in drinking water. Extracellular afferent nerve recordings were obtained from ex vivo flat sheet preparations of mouse distal colon. Mechanosensitivity of single afferent axons was assessed via probing of the colon with a 1g von Frey hair before and after superfusion of agonists of CB1R or CB2R plus MOR. To examine effects in vivo, visceromotor response (VMR) to colorectal distention (volume range 20-80 µL) was measured via electromyography. Mice were injected intraperitoneally with vehicle, or a combination of CB1R or CB2R agonist plus morphine 30-minutes prior to VMR experiment. Data were analyzed using a one or two-way ANOVA with Bonferroni test. N denotes number of mice; n denotes number of single afferent axons. Results In afferent nerve recordings, in contrast to healthy mice, the CB2R agonist HU-308 (1 µM and 3 µM) inhibited colonic mechanosensitivity in mice with colitis (1 µM: p<0.01, N=5, n=12; 3 µM: p<0.01, N=7, n=10); a lower concentration (300 nM) had no effect (p=0.52, N=6, n=10). The CB1R agonist ACEA (10 µM) reduced mechanosensitivity during acute colitis (p<0.05, n=11, N=6), whereas 100 nM (p>0.99, n=7, N=5) and 1 µM (p=0.25, n=10, N=6) had no effect. A combination of sub-analgesic concentrations of ACEA (100 nM) and DAMGO (MOR agonist, 1 nM) inhibited colonic mechanosensitivity in healthy mice (p<0.01, N=4, n=8) and during acute colitis (p<0.05, N=6, n=8). While a combination of sub-analgesic concentrations of HU-308 (300 nM) and DAMGO (1 nM) had no effect in healthy mice (p=0.70, N=4, n=8), it inhibited colonic mechanosensitivity during acute colitis (p<0.01, N=8, n=15). In VMR experiments, a combination of a sub-analgesic dose of ACEA (0.3 mg/kg) with morphine (0.3 mg/kg) reduced VMR (p<0.01, N=7) during acute colitis. Similarly, a combination of a sub-analgesic dose of HU-308 (1 mg/kg) and morphine (0.3 mg/kg) reduced VMR (p<0.01, N=6) during acute colitis. Conclusions A CB2R agonist inhibits colonic nociception during acute colitis, but not in healthy mice. A sub-analgesic combination of CB1R and MOR agonists can inhibit pain in healthy and inflamed mice, while combining sub-analgesic CB2R and MOR agonists is only inhibitory during acute colitis. Funding Agencies NRC

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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)0.0020.000

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 head0.005
GPT teacher head0.221
Teacher spread0.216 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the Canadian Association of Gastroenterology→Same topicGastrointestinal motility and disorders→French-language works237,207→