Marijuana and hemp represent two broad classes of
- Award ID(s):
- 1827209
- NSF-PAR ID:
- 10173871
- Date Published:
- Journal Name:
- 2020 American Academy of Forensic Sciences Annual Scientific Meeting
- Page Range / eLocation ID:
- pp. 234
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Cannabis sativa plants that are distinguished based on the concentration of the psychoactive cannabinoid delta‐9‐tetrahydrocannabinol (Δ9‐THC). In this work, solvent extracts derived from marijuana and hemp were characterized using optical and spectroscopic techniques. The crystalline components of the solvent extracts were first analyzed using polarized light microscopy to determine optical properties, namely, crystal system, optical sign, and principle refractive indices. Crystals from the marijuana‐derived extracts exhibited an orthorhombic crystal system and were optically negative, with nβbetween 1.6320 and 1.6330 ± 0.0002. In contrast, crystals from hemp‐derived extracts exhibited a monoclinic crystal system and were optically positive, with nβbetween 1.600 and 1.6040 ± 0.0002. Crystals were further distinguished through infrared spectroscopy, which highlighted structural differences between the two sample types, primarily based on differences in O‐H stretching. Finally, single‐crystal X‐ray diffraction was used to definitively identify the crystalline components, confirming the presence of tetrahydrocannabinolic acid in marijuana‐derived extracts and cannabidiol in hemp‐derived extracts. Given the differences in crystal structure identified between marijuana‐derived and hemp‐derived solvent extracts, optical characterization provides a screening method to differentiate visually similar samples prior to confirmatory analysis. -
Abstract Nalbuphine was a semisynthetic opioid analgesic widely used in the treatment of both acute and chronic pain. We developed and validated a rapid, simple and sensitive method by ultra-performance liquid chromatography–tandem mass spectrometry (MS/MS) for the simultaneous quantitation of nalbuphine in human plasma, and we reported the pharmacokinetic features of patients during general anesthesia for abdominal surgery. Sample separation was achieved on a Kinetex Phenyl-Hexyl column (50 × 2.1 mm, 1.7 μm) after simple protein precipitation with acetonitrile. The mobile phase was composed of acetonitrile and 3 mM of ammonium acetate aqueous solution with 0.1% formic acid. Gradient elution was used in 4.5 min with a flow rate of 0.5 mL/min at 40°C. MS detection using AB Sciex QTRAP 5500 mass spectrometer was characterized by electrospray ionization for positive ions in multiple reaction monitoring mode. Quantitative ion pairs were m/z 358.4 → 340.1 for nalbuphine and m/z 340.0 → 268.3 for nalmefene, which were used as the internal standard (IS). The calibration curves showed good linearity (r2>0.99) over concentration range of 0.1–500 ng/mL. The intra-and inter-batch precisions were within 10.67%, and accuracy ranged from 94.07 to 105.34%. The IS–normalized matrix factors were 1.02–1.03 with RSD% (≤5.82%). The recoveries ranged from 101.09 to 106.30%. In conclusion, a rapid, simple, sensitive and economical analytical method was developed and validated to detect the concentration in plasma samples obtained from patients receiving nalbuphine intravenous injection and was successfully applicated to human pharmacokinetic studies of nalbuphine.
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Abstract Background Hemp and marijuana are the two major varieties of
Cannabis sativa . While both contain Δ9-tetrahydrocannabinol (THC), the primary psychoactive component ofC. sativa , they differ in the amount of THC that they contain. Presently, U.S. federal laws stipulate thatC. sativa containing greater than 0.3% THC is classified as marijuana, while plant material that contains less than or equal to 0.3% THC is hemp. Current methods to determine THC content are chromatography-based, which requires extensive sample preparation to render the materials into extracts suitable for sample injection, for complete separation and differentiation of THC from all other analytes present. This can create problems for forensic laboratories due to the increased workload associated with the need to analyze and quantify THC in allC. sativa materials.Method The work presented herein combines direct analysis in real time—high-resolution mass spectrometry (DART-HRMS) and advanced chemometrics to differentiate hemp and marijuana plant materials. Samples were obtained from several sources (e.g., commercial vendors, DEA-registered suppliers, and the recreational
Cannabis market). DART-HRMS enabled the interrogation of plant materials with no sample pretreatment. Advanced multivariate data analysis approaches, including random forest and principal component analysis (PCA), were used to optimally differentiate these two varieties with a high level of accuracy.Results When PCA was applied to the hemp and marijuana data, distinct clustering that enabled their differentiation was observed. Furthermore, within the marijuana class, subclusters between recreational and DEA-supplied marijuana samples were observed. A separate investigation using the silhouette width index to determine the optimal number of clusters for the marijuana and hemp data revealed this number to be two. Internal validation of the model using random forest demonstrated an accuracy of 98%, while external validation samples were classified with 100% accuracy.
Discussion The results show that the developed approach would significantly aid in the analysis and differentiation of
C. sativa plant materials prior to launching painstaking confirmatory testing using chromatography. However, to maintain and/or enhance the accuracy of the prediction model and keep it from becoming outdated, it will be necessary to continue to expand it to include mass spectral data representative of emerging hemp and marijuana strains/cultivars. -
Abstract Microbial production of cannabinoids promises to provide a consistent, cheaper, and more sustainable supply of these important therapeutic molecules. However, scaling production to compete with traditional plant-based sources is challenging. Our ability to make strain variants greatly exceeds our capacity to screen and identify high producers, creating a bottleneck in metabolic engineering efforts. Here, we present a yeast-based biosensor for detecting microbially produced Δ9-tetrahydrocannabinol (THC) to increase throughput and lower the cost of screening. We port five human cannabinoid G protein-coupled receptors (GPCRs) into yeast, showing the cannabinoid type 2 receptor, CB2R, can couple to the yeast pheromone response pathway and report on the concentration of a variety of cannabinoids over a wide dynamic and operational range. We demonstrate that our cannabinoid biosensor can detect THC from microbial cell culture and use this as a tool for measuring relative production yields from a library of Δ9-tetrahydrocannabinol acid synthase (THCAS) mutants.
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