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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Anwar PLOSMed2019 16-5.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig0 Cardenia JofFoodDrugAnal2018 26-4.jpg|240px]]</div>
'''"[[Journal:Heart failure and healthcare informatics|Heart failure and healthcare informatics]]"'''
'''"[[Journal:Development and validation of a fast gas chromatography–mass spectrometry method for the determination of cannabinoids in Cannabis sativa L|Development and validation of a fast gas chromatography–mass spectrometry method for the determination of cannabinoids in Cannabis sativa L]]"'''


As biomedical research expands our armory of effective, evidence-based therapies, there is a corresponding need for high-quality implementation science—the study of strategies to integrate and embed research advances into [[Health care|clinical practice]]. Large-scale collection and analysis of routinely collected healthcare data may facilitate this in three main ways. Firstly, evaluation of key healthcare metrics can help to identify the areas of practice that differ most from guideline recommendations. Secondly, with sufficiently granular data, it may be possible to detect the underlying drivers of deficiencies in practice. Thirdly, longitudinal data collection should enable us to evaluate large-scale policy initiatives and compare the effectiveness of differing strategies on process and patient outcomes. ('''[[Journal:Heart failure and healthcare informatics|Full article...]]''')<br />
A routine method for determining [[wikipedia:Cannabinoid|cannabinoids]] in ''Cannabis sativa'' L. [[wikipedia:Inflorescence|inflorescence]], based on fast [[gas chromatography]] coupled to [[mass spectrometry]] (fast GC-MS), was developed and validated. To avoid the [[wikipedia:Decarboxylation|decarboxylation]] of the carboxyl group of cannabinoids, different derivatization approaches—i.e., silylation and esterification (diazomethane-mediated) reagents and solvents (pyridine or ethyl acetate)—were tested. The methylation significantly increased the signal-to-noise ratio of all carboxylic cannabinoids, except for cannabigerolic acid (CBGA). Since [[wikipedia:Diazomethane|diazomethane]] is not commercially available, is considered a hazardous reactive, and requires one-day synthesis by specialized chemical staff, the process of silylation was used along the entire validation of a routine method. The method gave a fast (total analysis time < 7.0 min) and satisfactory resolution (R > 1.1), with a good repeatability (intraday < 8.38%; interday < 11.10%) and sensitivity (LOD < 11.20 ng/mL). ('''[[Journal:Development and validation of a fast gas chromatography–mass spectrometry method for the determination of cannabinoids in Cannabis sativa L|Full article...]]''')<br />
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''Recently featured'':
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Revision as of 17:13, 9 December 2019

Fig0 Cardenia JofFoodDrugAnal2018 26-4.jpg

"Development and validation of a fast gas chromatography–mass spectrometry method for the determination of cannabinoids in Cannabis sativa L"

A routine method for determining cannabinoids in Cannabis sativa L. inflorescence, based on fast gas chromatography coupled to mass spectrometry (fast GC-MS), was developed and validated. To avoid the decarboxylation of the carboxyl group of cannabinoids, different derivatization approaches—i.e., silylation and esterification (diazomethane-mediated) reagents and solvents (pyridine or ethyl acetate)—were tested. The methylation significantly increased the signal-to-noise ratio of all carboxylic cannabinoids, except for cannabigerolic acid (CBGA). Since diazomethane is not commercially available, is considered a hazardous reactive, and requires one-day synthesis by specialized chemical staff, the process of silylation was used along the entire validation of a routine method. The method gave a fast (total analysis time < 7.0 min) and satisfactory resolution (R > 1.1), with a good repeatability (intraday < 8.38%; interday < 11.10%) and sensitivity (LOD < 11.20 ng/mL). (Full article...)

Recently featured:

Design and refinement of a data quality assessment workflow for a large pediatric research network
Identification of Cannabis sativa L. (hemp) retailers by means of multivariate analysis of cannabinoids
Data sharing at scale: A heuristic for affirming data cultures