Paper Spray Mass Spectrometry for the Quantitation of Drugs of Abuse in Biofluids and Street Drug Samples
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Notice bibliographique
Résumé
Paper spray mass spectrometry (PS-MS) has been developed as a tool for the analysis of drugs of abuse (DoA) in street drug samples, urine, and oral fluid. PS-MS is presented as a viable alternative to the traditional gas chromatography and liquid chromatography-mass spectrometry methods. PS-MS achieves sensitive and quantitative results in as little as 1-2 minutes with little to no sample preparation. Initial research presented in this thesis illustrates how PS-MS was developed for the analysis of fentanyl and related analogs of powdered drug slurries acting as a proxy for street drug samples, as a proof of concept for real world drug checking. Analysis of DoA in these pseudo-drug samples demonstrated the potential for both quantitative and qualitative analysis of fentanyl analogs. PS-MS was then demonstrated and evaluated for its effectiveness for real world drug checking applications during a world first demonstration of PS-MS for on-site drug checking in the Downtown Eastside of Vancouver, British Columbia, a recognized epicenter of the opioid overdose crisis. During the pilot test, 113 samples were submitted for analysis and successfully quantified using PS-MS, which targeted and quantified 49 different drug targets. Of these 113 drug samples, 44% of all samples were found to contain fentanyl, with a median concentration of 3.6% (w/w). The benzodiazepine etizolam was detected in 10 samples, none of the people who submitted these 10 samples expected a benzodiazepine to be present in their sample. It was later found that other drug checking technologies in use were underreporting the presence of etizolam or other benzodiazepines present in drug samples. These results, coupled with the quantitative capabilities and low levels of detection observed during the pilot test of PS-MS for drug checking demonstrated the efficacy of PS-MS and inspired further development of the application. PS-MS was then implemented by the Vancouver Island Drug Checking Project for the routine quantitative measurement of thousands of drug samples. During the span of this routine measurement, two unidentified compounds began appearing in carfentanil-containing drug samples. High resolution accurate mass (HRAM) mass spectrometry was used to determine the chemical composition of these two unknowns as C23H29N3O2 (m/z 380.2333) and C23H29N2O3 (m/z 381.2137). Further tandem mass spectrometry experiments were used for structural elucidation and the unknowns were putatively identified as desmethylcarfentanil amide and desmethylcarfentanil acid. LC-MS data on different drug samples containing the same compounds further supported the identification of these carfentanil structural analogs. µ-Opioid receptor binding modeling determined that the binding poses, and binding energies of these structural analogs were nearly identical to that of carfentanil, suggesting potentially similar activities/toxicities. PS-MS was further applied to the analysis of cannabinoids in urine and oral fluid samples. Due to the inherently low ionization efficiencies and sensitivity to cannabinoids observed with PS-MS, a reactive paper spray ionization method utilizing a diazonium salt as a on-paper derivatization reagent was developed. The derivatization scheme dramatically lowered the limits of detection for tetrahydrocannabinol (THC) in oral fluid and THC metabolite in urine, to levels able to meet forensic and clinical cutoff values (low parts per billion). The quantitative results were compared to a LC-MS results from a commercial clinical laboratory, demonstrating good agreement between the two methods. The results presented herein demonstrate the applicability and dramatic benefits of PS-MS for drug checking applications, as well as for cannabinoids in oral fluid and urine. High resolution mass spectrometry is demonstrated for the structural elucidation and identification of unknown drug compounds in an ever-changing street drug supply.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle