Screening Medical Marijuana for Pesticides by GC-MS/MS
Di Wang, Laura Chambers, William Lipps, Zhuangzhi ‘Max’ Wang, Robert Clifford; Shimadzu Scientific Instruments, Columbia, MD, USA
Since medical marijuana (MM) was legalized in California in 1996, 23 states and Washington, D.C. have passed laws allowing its use for a variety of medical conditions. From a consumer safety point-of-view, quantitation of the pesticide residues in MM products has begun to attract wide interest. There are several problems associated with analysis of pesticide residues in MM. First and foremost, there are very few regulatory guidelines established to define which pesticides to include or what the detection limits should be, and secondly the matrix is very complex with significant interferences. Finally, sample load is growing exponentially, so the chosen method must be quick and easy to perform. Trace level pesticide analysis in complex food matrices have been done for many years with similar challenges, thus many of the analytical protocols emerging for the MM matrix are based on these well-established techniques.
Triple-quadrupole GC-MS/MS operated in MRM mode provides significant sensitivity and selectivity, but method development can be expensive and time consuming. This poster describes streamlined method development process for analysis of pesticide residues in MM using a QuEChERS sample preparation method, followed by GC-MS/MS detection and quantitation.
Analysis of Extract Drying Criteria for Oil & Grease Method 1664A/BPoster
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Role of Elevated Airway Glucose (and Other Biochemicals) in Bacterial InfectionsPoster
Bacteria that live in the airways need something to eat: they mainly use host derived biochemicals, for example glucose. When levels of airway biochemicals are dysregulated, bacterial colonisation increases, enabling infection. We investigated how changes in airway glucose effect bacterial infection.READ MORE
New Biotransformation Prediction Engine Integrated into a Metabolite Identification SolutionPoster
Here we present a new prediction algorithm that determines the likelihood of biotransformation reactions, and subsequent metabolite identification, within an automated processing routine.READ MORE
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10th International Conference on Mass Spectrometry and Chromatography
Oct 08 - Oct 09, 2018