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The Non‐psychoactive Phytocannabinoid, Cannabidiol (CBD), and the Synthetic Derivatives, HU308 and CBD‐DMH, Reduces Hyperalgesia and Inflammation in a Mouse Model of Corneal injury.

2017· article· en· W2895842235 on OpenAlexaffabout
Dinesh Thapa, James Thomas Toguri, Anna Szcześniak

Bibliographic record

VenueThe FASEB Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsCannabidiolPharmacologyHyperalgesiaCannabinoidEndocannabinoid systemMedicineInflammationCannabinoid receptorCannabinoid receptor type 2NociceptionAntagonistReceptorImmunologyInternal medicineCannabis

Abstract

fetched live from OpenAlex

Background and Purpose Damage to corneal tissue results in intense ocular pain, dysfunction in nociceptive signaling and release of inflammatory mediators. Current treatments for corneal pain and inflammation are frequently ineffective. The endocannabinoid system (ECS) is an emerging therapeutic target in the modulation of pain and inflammation. The ECS consists of endogenous cannabinoid ligands that mediate their actions via G‐protein coupled receptors, cannabinoid 1 receptor (CB 1 R) and cannabinoid 2 receptor (CB 2 R). Cannabinoids that bind to CB 1 R, like tetrahydrocannabinol (THC), have shown utility in treating pain, however, their therapeutic applications are limited by CB 1 R‐mediated behavioral side‐effects. The non‐psychoactive phytocannabinoid, cannabidiol (CBD), and CBD derivatives, CBD‐DMH and HU‐308, have reported anti‐inflammatory effects, which may be mediated independent of CB 1 R, and could offer an alternative to CB 1 R ligands in the treatment of ocular pain and inflammation. Therefore, the purpose of this research is to investigate the antinociceptive and anti‐inflammatory properties of CBD, CBD‐DMH and HU308 in a mouse model of corneal injury. Methods Experimental corneal hyperalgesia and inflammation were generated using chemical cauterization of the cornea in wildtype (WT) and CB 2 R knockout (CB 2 R −/− ) mice. Cauterized eyes were treated with topical cannabinoids (0.2–5% w/v) in the presence or absence of the CB 1 R antagonist, AM281 (2.5mg/kg ip). The ocular blink response, indicative of corneal hyperalgesia following chemical stimulation by capsaicin, was recorded 6 hours post‐injury. Mice were euthanized and eyes were enucleated at 12 hours and neutrophil infiltration into the cornea, a marker for inflammation, was analyzed using immunohistochemistry in the corneal sections. Results Corneal cauterization resulted in an increased blink response to capsaicin 6 hours post‐injury compared to sham control eyes (p < 0.0001). Application of 5% CBD, 5% CBD‐DMH and 1.5% HU308 reduced blinks in WT mice compared to vehicle‐treated eyes (p < 0.01). The antinociceptive effects of CBD and HU308 (p < 0.01 & p < 0.05, respectively), but not CBD‐DMH, were reduced in CB 2 R −/− mice. The antinociceptive effects of CBD‐DMH, but not CBD and HU308 (p < 0.0001), were blocked by the CB 1 R antagonist, AM281. Neutrophil infiltration into the cornea was increased 12 hours post injury, compared to non‐cauterized eyes in WT mice (p < 0.0001). Neutrophil infiltration was exacerbated in CB 2 R −/− mice compared to WT mice (p < 0.001). 5% CBD and 1.5% HU308 reduced neutrophil infiltration (p <0.001 & p <0.0001, respectively); these effects were reduced in CB 2 R −/− mice (p < 0.01 & p < 0.05, respectively). Conclusion CBD‐DMH had antinociceptive actions through CB 1 R, whereas, the antinociceptive and anti‐inflammatory actions of CBD and HU308 were independent of CB 1 R and mediated via CB 2 R activation. Therefore, the cannabinoids, CBD and HU308, could offer a novel therapy for ocular pain and inflammation with reduced CB 1 R mediated side‐effects. Support or Funding Information Canadian Institutes of Health Research (CIHR).

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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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
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 head0.018
GPT teacher head0.290
Teacher spread0.272 · 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

Citations4
Published2017
Admission routes2
Has abstractyes

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