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Record W4378219811 · doi:10.1186/s13041-023-01036-8

Analgesia by intrathecal delta-9-tetrahydrocannabinol is dependent on Cav3.2 calcium channels

2023· article· en· W4378219811 on OpenAlexafffund
Vinícius de Maria Gadotti, Flavia Tasmin Techera Antunes, Gerald W. Zamponi

Bibliographic record

VenueMolecular Brain · 2023
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsHotchkiss Brain InstituteAlberta Children's HospitalUniversity of Calgary
FundersCanadian Institutes of Health ResearchAlberta InnovatesCanada Research ChairsUniversity of Calgary
KeywordsCannabinoidPharmacologyCannabinoid receptorDorsal root ganglionAnalgesicHyperalgesiaNeuropathic painSpinal cordVoltage-dependent calcium channelCannabinoid Receptor AgonistsMedicineAnesthesiaNociceptionNeuroscienceChemistryCalciumReceptorInternal medicineBiologyAgonist

Abstract

fetched live from OpenAlex

Abstract Delta-9-tetrahydrocannabinol (Δ 9 -THC) is known to produce systemic analgesia that involves CB 1 and CB 2 cannabinoid receptors. However, there is compelling evidence that Δ 9 -THC can potently inhibit Cav3.2T-type calcium channels which are highly expressed in dorsal root ganglion neurons and in the dorsal horn of the spinal cord. Here, we investigated whether spinal analgesia produced by Δ 9 -THC involves Cav3.2 channels vis a vis cannabinoid receptors. We show that spinally delivered Δ 9 -THC produced dose-dependent and long-lasting mechanical anti-hyperalgesia in neuropathic mice, and showed potent analgesic effects in models of inflammatory pain induced by formalin or Complete Freund’s Adjuvant (CFA) injection into the hind paw, with the latter showing no overt sex differences. The Δ 9 -THC mediated reversal of thermal hyperalgesia in the CFA model was abolished in Cav3.2 null mice, but was unaltered in CB 1 and CB 2 null animals. Hence, the analgesic effects of spinally delivered Δ 9 -THC are due to an action on T-type calcium channels, rather than activation of spinal cannabinoid receptors.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.533
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.018
GPT teacher head0.311
Teacher spread0.292 · 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 teacher head, not a consensus.

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

Citations10
Published2023
Admission routes2
Has abstractyes

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