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Record W4391751133 · doi:10.1002/rcm.9711

Identification and quantification of both isomers of hexahydrocannabinol, (9 <i>R</i> )‐hexahydrocannabinol and (9 <i>S</i> )‐hexahydrocannabinol, in three different matrices by mass spectrometry

2024· article· en· W4391751133 on OpenAlexfundno aff
Charline Bottinelli, Pauline Baradian, Amélie Poly, Guillaume Hoizey, Camille Chatenay

Bibliographic record

VenueRapid Communications in Mass Spectrometry · 2024
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicForensic Toxicology and Drug Analysis
Canadian institutionsnot available
FundersMcGill University
KeywordsForensic toxicologySynthetic cannabinoidsChromatographyRepeatabilityWhole bloodStreet drugsCannabidiolMedicineChemistryCannabisPharmacologySurgeryInternal medicineCannabinoid

Abstract

fetched live from OpenAlex

CONTEXT: -THC), has gained recent attention due to its presence in seized materials across Europe. Sold legally in various forms, HHC poses potential health risks, particularly as a legal alternative to THC in some countries. Despite its historical description in the 1940s, limited toxicology data, pharmacological understanding, and analytical methods for HHC exist. METHOD: This study proposes analytical techniques using mass spectrometry to detect, identify, and quantify (9R)-HHC and (9S)-HHC, concurrently with THC and CBD in various matrices, including oral fluid, whole blood, and seized material. Three distinct methods were employed for different matrices: GC/MS for seized material, GC/MS/MS for whole blood, and UHPLC/MS/MS for oral fluid. Methods were validated qualitatively for oral fluid with a FLOQSwab® device and quantitatively in whole blood and seized material according to Peters et al's recommendations and ICH guidelines. RESULTS: systematically >0.992. These methods were applied to authentic cases, including seized materials and biological samples from traffic control (whole blood and oral fluid). In seized materials, (9R)-HHC levels ranged from 2.09% to 8.85% and (9R)-HHC/(9S)-HHC ratios varied from 1.36 to 2.68. In whole blood sample, (9R)-HHC and (9S)-HHC concentrations were, respectively, 2.38 and 1.39 ng/mL. For all analyzed samples, cannabinoids such as THC and CBD were also detected. CONCLUSION: This research contributes analytical insights into differentiating and simultaneously analyzing (9R)-HHC and (9S)-HHC, using widely applicable mass spectrometric methods. The study emphasizes the need for vigilance among toxicologists, as new semisynthetic cannabinoids continue to emerge in Europe, with potential health implications. The findings underscore the importance of reliable analytical methods for monitoring these compounds in forensic and clinical settings.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.037
GPT teacher head0.355
Teacher spread0.317 · 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

Citations11
Published2024
Admission routes1
Has abstractyes

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