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Record W4411724351 · doi:10.1093/jat/bkaf055

Cross-reactivity in urine of 53 cannabinoid analogs and metabolites using a carboxylic acid enzyme-linked immunosorbent assay (ELISA) and homogenous enzyme immunoassay (HEIA) kit and immunalysis synthetic cannabinoid HEIA kits

2025· article· en· W4411724351 on OpenAlexaff
Justin L. Poklis, Alaina K Holt, Ciena Bayard, Stephen A. Raso, Michelle R. Peace

Bibliographic record

VenueJournal of Analytical Toxicology · 2025
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsOffice of the Chief Medical Examiner
FundersNational Institute of Justice
KeywordsCannabinoidSynthetic cannabinoidsImmunoassayChemistryMetaboliteUrineCannabinoid receptorCross-reactivityCannabinoid Receptor AgonistsPharmacologyChromatographyBiochemistryCross reactionsReceptorMedicineAntibodyImmunology

Abstract

fetched live from OpenAlex

Advancing knowledge of endocannabinoid receptor agonists and the federal legalization of hemp has created a cannabinoid market of naturally abundant phytocannabinoids to a wide array of semi-synthetic and synthetic cannabinoid analogs. Public safety and toxicological concerns exist from lack of regulation, limited pharmacological and metabolomic data, and minimal knowledge of detection ability. Structural similarities of the cannabinoid analogs may allow detection on immunoassays including enzyme-linked immunosorbent assays (ELISA) and homogenous enzyme immunoassays (HEIA), screening platforms in forensic toxicology laboratories for rapid presumptive testing. The cross-reactivity of 27 cannabinoid analogs and 26 commercially available metabolites was evaluated using the Medica EasyRA Enzymatic Immunoassay Analyzer with the Immunalysis Cannabinoids (THC) and Synthetic Cannabinoids 1-3 kits. These analogs were also evaluated using the Dynex DSX Automated ELISA System with the OraSure Technologies Cannabinoids Intercept Microplate EIA. The cannabinoid kits target 11-nor-9-carboxy-Δ9-tetrahydrocannabinol (Δ9-THCCOOH) at a 50 ng/mL cutoff, and the synthetic cannabinoid kits target the N-pentanoic acid metabolite of JWH-018, UR-144, and AB-PINACA at a 10 ng/mL cutoff. Cross-reactivity was evaluated at concentrations of 20, 50, 100, 500, and 1000 ng/mL in urine in triplicate. Absence of cross-reactivity at 1000 ng/mL was considered undetectable. No cross-reactivity was detected on the synthetic cannabinoid kits. Cross-reactivity to Δ9-THCCOOH kits was variable with Δ8-THCCOOH and R-HHCCOOH cross-reacting at the cutoff on the ELISA, with several additional phase I metabolites cross-reacting at 100 ng/mL on both platforms. Analogs lacking the Δ9-THC tricyclic structure and pyran ring cyclization including cannabidiol were undetectable. Alicyclic bond location and alkyl chain length variably affected cross-reactivity, with alkyl lengths 2-4 having increased cross-reactivity comparatively. Compound chirality was also observed to effect instrumental response, with the ELISA having increased cross-reactivity and instrumental response to R-isomers. As knowledge and prevalence of analogs increases, it is crucial to understand the impact on utilized testing platforms.

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)0.004
metaresearch head score (Gemma)0.005
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 score0.004
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.018
GPT teacher head0.325
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 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
Published2025
Admission routes1
Has abstractyes

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