Difference between revisions of "Template:Article of the week"

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'''"[[Journal:National and transnational security implications of asymmetric access to and use of biological data|National and transnational security implications of asymmetric access to and use of biological data]]"'''
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig3 Mudge ScientificReports2018 8.png|240px]]</div>
'''"[[Journal:Chemometric analysis of cannabinoids: Chemotaxonomy and domestication syndrome|Chemometric analysis of cannabinoids: Chemotaxonomy and domestication syndrome]]"'''


Biology and [[biotechnology]] have changed dramatically during the past 20 years, in part because of increases in computational capabilities and use of engineering principles to study biology. The advances in supercomputing, data storage capacity, and [[Cloud computing|cloud platforms]] enable scientists throughout the world to generate, analyze, share, and store vast amounts of data, some of which are biological and much of which may be used to understand the human condition, agricultural systems, evolution, and environmental ecosystems. These advances and applications have enabled: (1) the emergence of data science, which involves the development of new algorithms to analyze and [[Data visualization|visualize data]]; and (2) the use of engineering approaches to manipulate or create new biological organisms that have specific functions, such as production of industrial chemical precursors and development of environmental bio-based sensors. Several biological sciences fields harness the capabilities of computer, data, and engineering sciences, including synthetic biology, precision medicine, precision agriculture, and systems biology. These advances and applications are not limited to one country. This capability has economic and physical consequences but is vulnerable to unauthorized intervention. ('''[[Journal:National and transnational security implications of asymmetric access to and use of biological data|Full article...]]''')<br />
''[[wikipedia:Cannabis|Cannabis]]'' is an interesting domesticated crop with a long history of cultivation and use. [[wikipedia:Cannabis strains|Strains]] have been selected through informal breeding programs with undisclosed parentage and criteria. The term “strain” refers to minor morphological differences and grower branding rather than distinct cultivated varieties. We hypothesized that strains sold by different licensed producers are chemotaxonomically indistinguishable and that the commercial practice of identifying strains by the ratio of total Δ9-[[wikipedia:Tetrahydrocannabinol|tetrahydrocannabinol]] (THC) and [[wikipedia:Cannabidiol|cannabidiol]] (CBD) is insufficient to account for the reported human health outcomes. We used targeted [[wikipedia:Metabolomics|metabolomics]] to analyze 11 known [[wikipedia:Cannabinoid|cannabinoid]]s and an untargeted metabolomics approach to identify 21 unknown cannabinoids. Five clusters of chemotaxonomically indistinguishable strains were identified from the 33 commercial products. Only three of the clusters produce cannabidiolic acid (CBDA) in significant quantities, while the other two clusters redirect metabolic resources toward the [[wikipedia:Tetrahydrocannabinolic acid|tetrahydrocannabinolic acid]] (THCA) production pathways. ('''[[Journal:Chemometric analysis of cannabinoids: Chemotaxonomy and domestication syndrome|Full article...]]''')<br />
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Revision as of 18:14, 1 July 2019

Fig3 Mudge ScientificReports2018 8.png

"Chemometric analysis of cannabinoids: Chemotaxonomy and domestication syndrome"

Cannabis is an interesting domesticated crop with a long history of cultivation and use. Strains have been selected through informal breeding programs with undisclosed parentage and criteria. The term “strain” refers to minor morphological differences and grower branding rather than distinct cultivated varieties. We hypothesized that strains sold by different licensed producers are chemotaxonomically indistinguishable and that the commercial practice of identifying strains by the ratio of total Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD) is insufficient to account for the reported human health outcomes. We used targeted metabolomics to analyze 11 known cannabinoids and an untargeted metabolomics approach to identify 21 unknown cannabinoids. Five clusters of chemotaxonomically indistinguishable strains were identified from the 33 commercial products. Only three of the clusters produce cannabidiolic acid (CBDA) in significant quantities, while the other two clusters redirect metabolic resources toward the tetrahydrocannabinolic acid (THCA) production pathways. (Full article...)

Recently featured:

National and transnational security implications of asymmetric access to and use of biological data
Developing workforce capacity in public health informatics: Core competencies and curriculum design
Assessing cyberbiosecurity vulnerabilities and infrastructure resilience