Comprehensive classification of USA cannabis samples based on chemical profiles of major cannabinoids and terpenoids

Application of gas chromatography in the analysis of phytocannabinoids: An update (2020-2023)

INTRODUCTION

Cannabinoids are a group of compounds that bind to cannabinoid receptors. They possess pharmacological properties like that of the plant Cannabis sativa. Gas chromatography (GC) is one of the popular chromatographic techniques that has been routinely used in the analysis of cannabinoids in different matrices.

OBJECTIVE

The article aims to review the literature on the application of GC-based analytical methods for the analysis of phytocannabinoids published during the period from January 2020 to August 2023.

METHODOLOGY

A thorough literature search was conducted using different databases, like Web of Knowledge, PubMed, Google Scholar, and other relevant published materials including published books. The keywords used, in various combinations, with cannabinoids being present in all combinations, in the search were cannabinoids, Cannabis sativa, marijuana, analysis, GC, quantitative, qualitative, and quality control. From the search results, only the publications that incorporate the GC analysis of phytocannabinoids were reviewed, and papers on synthetic cannabinoids were excluded.

RESULTS

Since the publication of the review article on GC analysis of phytocannabinoids in early 2020, several GC-based methods for the analysis of phytocannabinoids have appeared in the literature. While simple 1D GC-mass spectrometry (MS) and GC-flame ionisation detector (FID) methods are still quite common in phytocannabinoids analysis, 2D GC-MS and GC-MS/MS are increasingly becoming popular, as these techniques offer more useful data for identification and quantification of phytocannabinoids in various matrices. The use of automation in sample preparation and the utilisation of mathematical and computational models for optimisation of different protocols have become a norm in phytocannabinoids analysis. Pre-analyses have been found to incorporate different derivatisation techniques and environmentally friendly extraction protocols.

CONCLUSIONS

GC-based analysis of phytocannabinoids, especially using GC-MS, remains one of the most preferred methods for the analysis of these compounds. New derivatisation methods, ionisation techniques, mathematical models, and computational approaches for method optimisation have been introduced.

Untargeted cannabinomics reveals the chemical differentiation of industrial hemp based on the cultivar and the geographical field location

Cannabis sativa has long been harvested for industrial applications related to its fibers. Industrial hemp cultivars, a botanical class of Cannabis sativa with a low expression of intoxicating Δ9-tetrahydrocannabinol (Δ9-THC) have been selected for these purposes and scarcely investigated in terms of their content in bioactive compounds. Following the global relaxation in the market of industrial hemp-derived products, research in industrial hemp for pharmaceutical and nutraceutical purposes has surged. In this context, metabolomics-based approaches have proven to fulfill the aim of obtaining comprehensive information on the phytocompound profile of cannabis samples, going beyond the targeted evaluation of the major phytocannabinoids. In the present paper, an HRMS-based metabolomics study was addressed to seven distinct industrial hemp cultivars grown in four experimental fields in Northern, Southern, and Insular Italy. Since the role of minor phytocannabinoids as well as other phytocompounds was found to be critical in discriminating cannabis chemovars and in determining its biological activities, a comprehensive characterization of phytocannabinoids, flavonoids, and phenolic acids was carried out by LC-HRMS and a dedicated data processing workflow following the guidelines of the metabolomics Quality Assurance and Quality Control Consortium. A total of 54 phytocannabinoids, 134 flavonoids, and 77 phenolic acids were annotated, and their role in distinguishing hemp samples based on the geographical field location and cultivar was evaluated by ANOVA-simultaneous component analysis. Finally, a low-level fused model demonstrated the key role of untargeted cannabinomics extended to lesser-studied phytocompound classes for the discrimination of hemp samples.

Evaluating Cannabis sativa L.'s neuroprotection potential: From bench to bedside

BACKGROUND

Neurodegenerative diseases and dementia pose a global health challenge in an aging population, exemplified by the increasing incidence and prevalence of its most common form, Alzheimer's disease. Although several approved treatments exist for Alzheimer's disease, they only afford transient symptomatic improvements and are not considered disease-modifying. The psychoactive properties of Cannabis sativa L. have been recognized for thousands of years and now with burgeoning access to medicinal formulations globally, research has turned to re-evaluate cannabis and its myriad phytochemicals as a potential treatment and adjunctive agent for neurodegenerative diseases.

PURPOSE

This review evaluated the neuroprotective potential of C. sativa's active constituents for potential therapeutic use in dementia and Alzheimer's disease, based on published studies demonstrating efficacy in experimental preclinical settings associated with neurodegeneration.

STUDY DESIGN

Relevant information on the neuroprotective potential of the C. sativa's phytoconstituents in preclinical studies (in vitro, in vivo) were included. The collated information on C. sativa's component bioactivity was organized for therapeutic applications against neurodegenerative diseases.

METHODS

The therapeutic use of C. sativa related to Alzheimer's disease relative to known phytocannabinoids and other phytochemical constituents were derived from online databases, including PubMed, Elsevier, The Plant List (TPL, www.theplantlist.org), Science Direct, as well as relevant information on the known pharmacological actions of the listed phytochemicals.

RESULTS

Numerous C. sativa -prevalent phytochemicals were evidenced in the body of literature as having efficacy in the treatment of neurodegenerative conditions exemplified by Alzheimer's disease. Several phytocannabinoids, terpenes and select flavonoids demonstrated neuroprotection through a myriad of cellular and molecular pathways, including cannabinoid receptor-mediated, antioxidant and direct anti-aggregatory actions against the pathological toxic hallmark protein in Alzheimer's disease, amyloid β.

CONCLUSIONS

These findings provide strong evidence for a role of cannabis constituents, individually or in combination, as potential neuroprotectants timely to the emergent use of medicinal cannabis as a novel treatment for neurodegenerative diseases. Future randomized and controlled clinical studies are required to substantiate the bioactivities of phytocannabinoids and terpenes and their likely synergies.

Emissions from Heated Terpenoids Present in Vaporizable Cannabis Concentrates

Vaporizable cannabis concentrates (VCCs) consumed as a liquid (vaping) or a waxy solid (dabbing) are becoming increasingly popular. However, their associated emissions and impacts have not been fully described. Mixtures containing different proportions of 12 VCC terpenoids and high MW compounds were heated at 100-500 °C inside a room-sized chamber to simulate emissions. Terpenoids, thermal degradation byproducts, and ultrafine particles (UFPs) were quantified in the chamber air. Air samples contained over 50% of emitted monoterpenes and less than 40% of released sesquiterpenes and terpene alcohols. Eleven degradation byproducts were quantified, including acrolein (1.3-3.9 μg m^-3) and methacrolein (2.0 μg m^-3). A large amount of UFPs were released upon heating and remained airborne for at least 3 h. The mode diameter increased from 80 nm at 100 °C to 140 nm at 500 °C, and particles smaller than 250 nm contributed to 90% of PM_1.0. The presence of 0.5% of lignin, flavonoid, and triterpene additives in the heated mixtures resulted in a threefold increase in the particle formation rate and PM_1.0 concentration, suggesting that these high-molecular-weight compounds enhanced aerosol inception and growth. Predicted UFP emission rates in typical consumption scenarios (6 × 10¹¹-2 × 10¹³ # min^-1) were higher than, or comparable with, other common indoor sources such as smoking and cooking.