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Record W2922201026 · doi:10.1111/jvp.12629

Session 10: Anaesthesia and Pain Control

2018· article· en· W2922201026 on OpenAlexaboutno aff

Bibliographic record

VenueJournal of Veterinary Pharmacology and Therapeutics · 2018
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsnot available
Fundersnot available
KeywordsSession (web analytics)Pain controlAnesthesiaPain managementMedicinePsychologyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

INTRODUCTION/OBJECTIVE: In several EU and some US states, medical marijuana is an option for people suffering from various ailments and seeking relief. As cannabis is now sold as an oil extract, it has become a conceivable option for dogs too. There is anecdotal evidence of cannabis benefiting dogs with a range of clinical signs and diseases including seizures, nausea and other gastrointestinal signs, stress and anxiety, arthritis and cancer pain, but no information on its pharmacokinetics is available in dogs. \n \nMATERIALS AND METHODS: Six healthy intact female adult (5–7 years) Labrador dogs were used. Animals were randomly divided into 2 groups (n = 3). Group I was administered with Bedrocan (olive oil containing 20% tetrahydrocannabinol (THC) and 0.5% cannabidiol (CBD)) at 1.5 mg kg−1 THC after 12 h of fasting, while group II was administered with the same dose 15 minutes after being fed. Blood collections were performed at pre‐assigned time. Samples were analysed for THC and CBD content by LC/MS using an intra‐laboratory validated method. Briefly, to 100 μl of blood THC‐d3 and CBD‐d3 were added as internal standards (5 ng ml−1), followed by precipitation with 200 μl of acetonitrile. After shaking and centrifugation (3000 × g, 5 min), the supernatant was diluted 1:1 with the HPLC mobile phase and transferred into a LC vial. 25 μl of the sample were directly injected onto the LC‐HRMS system (a Q Exactive Orbitrap mass spectrometer coupled to a Dionex UltiMate 3000 with TurboFlow technology). Pharmacokinetic analyses were performed according to a non‐compartmental model. \n \nRESULTS AND CONCLUSIONS: No sign of excitation/sedation or visible adverse effects were detected in the dogs following the treatment. THC was quantified over the time period 45 min to 10 h and 15 min to 10 h after Bedrocan administration in the fasting and fed group, respectively. No detectable concentrations of CDB were found at any time. Fed dogs showed faster absorption Tmax (0.62 ± 0.17 h fed versus 2.33 ± 1.52 h fasted) and a higher maximal blood concentration (49.2 ± 25.5 ng ml−1 fed versus 19.1 ±8.7 ng ml−1 fasted). In contrast, feeding did not significantly affected the half‐life (2.3 ± 1.0 fasted versus 1.5 ± 0.5 h fed) or the AUC (73.8 ± 15.8 fasted versus 63.3 ± 9.2 fed ng×h ml−1) values. Although this is the first phase of a 2 × 2 cross‐over study and the power of the study is not yet adequate, after oral administration of Bedrocan, THC appears to be absorbed to the same extent reported in humans.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.276
Threshold uncertainty score0.924

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.2760.101

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 head0.038
GPT teacher head0.345
Teacher spread0.307 · 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 designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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