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Record W4323351133 · doi:10.1093/jcag/gwac036.002

A2 ACUTE COLITIS CAUSES CHANGES TO THE EFFICACY OF CANNABINOID-1 AND MU-OPIOID RECEPTOR AGONISTS ON INHIBITING ABDOMINAL PAIN

2023· article· en· W4323351133 on OpenAlexaff
Quentin Tsang, Claudius E. Degro, H M Schincariol, Alan Lomax, S Vanner, David E. Reed

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2023
Typearticle
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsAgonistMedicineCannabinoidμ-opioid receptorNociceptionMorphinePharmacologyOpioidVisceral painColitisCannabinoid receptorDAMGOReceptorAnesthesiaCannabinoid Receptor AgonistsOpioid receptorEndocrinologyInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background Abdominal pain is a debilitating symptom in patients with inflammatory bowel disease. Previously we have shown that both cannabinoid-1 receptor (CB1R) and mu opioid receptor (MOR) agonists inhibit mechanosensitivity of colonic nociceptive nerves in healthy mice. However, it is unknown whether CBR and MOR agonists continue to have effects during colitis. Purpose To determine the effects of CBR and MOR agonists on colonic nociceptive nerves during acute colitis. Method Colitis was induced in male and female C57BL/6 mice using 2.5% dextran sodium sulfate in drinking water. Visceromotor response (VMR) to colorectal distention (CRD) (volume range 20-80 µL) was measured using telemetric transmitters. Mice were injected intraperitoneally with vehicle, ACEA, a selective CB1R agonist and/or morphine, a MOR agonist, 30-minutes prior to distention. Extracellular afferent nerve recordings were obtained from ex vivo flat sheet preparations of mouse distal colon. Mechanosensitivity of single afferent axons was assessed via mechanical probing of the colon with a 1g von Frey hair before and after superfusion of ACEA and/or DAMGO (MOR agonist). 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. Result(s) ACEA (3 mg/kg), a dose that significantly inhibited VMR in healthy mice, did not inhibit VMR in mice with colitis (p=0.55, N=6). At a dose that previously had no effect in healthy controls, morphine (0.3 mg/kg) significantly inhibited VMR to CRD, when compared to vehicle (34% reduction, p<0.01, N = 8). A combination of a sub-analgesic dose of ACEA (0.3 mg/kg) with morphine (0.3 mg/kg) significantly reduced VMR (p<0.01, N=5); at 60 µL and 80 µL distention there was a 44% and 49% reduction, respectively (p<0.05 for both). Interestingly, the effect of the combination of ACEA and morphine was larger than that of morphine alone (0.3 mg/kg), but this did not reach statistical significance (-62% vs. -34%; p=0.06, N=5-8). In extracellular afferent nerve recordings, compared to the previous findings in healthy mice, a higher concentration of ACEA (10 µM) was required to inhibit mechanosensitivity (15.2 vs. 11.6 Hz; p<0.05, n=11, N=6) whereas 100nM (p>0.99, n=7, N=5) and 1µM (p=0.25, n=10, N=6) had no effect. DAMGO (1 nM), which previously had no effect in healthy controls, had a tendency to reduce colonic mechanosensitivity, but this did not reach statistical significance (p=0.12, n=7 units, N=5). Interestingly, a combination of sub-analgesic concentrations of ACEA (100 nM) and DAMGO (1 nM) significantly reduced colonic mechanosensitivity (18.4 vs. 12.0 Hz; p<0.05, n=7, N=5). Conclusion(s) At doses that previously inhibited nociception in healthy mice, CB1R agonists may have lost their analgesic effect during acute colitis. Conversely, less of MOR agonists may be needed to achieve analgesia. Interestingly, sub-analgesic doses of CB1R agonists potentiate the analgesic effect of the MOR agonist during colitis. Please acknowledge all funding agencies by checking the applicable boxes below NRC Disclosure of Interest None Declared

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)0.0030.001

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 head0.012
GPT teacher head0.254
Teacher spread0.242 · 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
Published2023
Admission routes1
Has abstractyes

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