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

From LIMSWiki
Jump to navigationJump to search
(Updated article of the week text)
(Updated article of the week text)
(44 intermediate revisions by the same user not shown)
Line 1: Line 1:
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Pluscauskas IntJOfNeoScreen2019 5-1.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Mandrioli Molecules2019 24-11.png|240px]]</div>
'''"[[Journal:Building a newborn screening information management system from theory to practice|Building a newborn screening information management system from theory to practice]]"'''
'''"[[Journal:Fast detection of 10 cannabinoids by RP-HPLC-UV method in Cannabis sativa L.|Fast detection of 10 cannabinoids by RP-HPLC-UV method in Cannabis sativa L.]]"'''


Information management systems are the central process management and communication hub for many newborn screening programs. In late 2014, Newborn Screening Ontario (NSO) undertook an end-to-end assessment of its [[information management]] needs, which resulted in a project to develop a flexible information systems (IS) ecosystem and related process changes. This enabled NSO to better manage its current and future [[workflow]] and communication needs. An idealized vision of a screening information management system (SIMS) was developed that was refined into enterprise and functional architectures. This was followed by the development of technical specifications, user requirements, and procurement. In undertaking a holistic full product lifecycle redesign approach, a number of change management challenges were faced by NSO across the entire program. Strong leadership support and full program engagement were key for overall project success. It is anticipated that improvements in program flexibility and the ability to innovate will outweigh the efforts and costs. ('''[[Journal:Building a newborn screening information management system from theory to practice|Full article...]]''')<br />
[[wikipedia:Cannabis|Cannabis]] has regained much attention as a result of updated legislation authorizing many different uses, and it can be classified on the basis of the content of [[wikipedia:Tetrahydrocannabinol|Δ9-tetrahydrocannabinol]] (Δ9-THC), a psychotropic substance for which there are legal limitations in many countries. For this purpose, accurate qualitative and quantitative determination is essential. The relationship between THC and [[wikipedia:Cannabidiol|cannabidiol]] (CBD) is also significant, as the latter substance is endowed with many specific and non-psychoactive proprieties. For these reasons, it becomes increasingly important and urgent to utilize fast, easy, validated, and harmonized procedures for determination of [[wikipedia:Cannabinoid|cannabinoids]]. The procedure described herein allows rapid determination of 10 cannabinoids from the [[wikipedia:Inflorescence|inflorescences]] of ''Cannabis sativa'' L. by extraction with organic solvents. Separation and subsequent detection are by [[wikipedia:Reversed-phase chromatography|reversed-phase]] [[high-performance liquid chromatography]] with ultraviolet detector (RP-HPLC-UV). ('''[[Journal:Fast detection of 10 cannabinoids by RP-HPLC-UV method in Cannabis sativa L.|Full article...]]''')<br />
<br />
<br />
''Recently featured'':
''Recently featured'':
: ▪ [[Journal:Adapting data management education to support clinical research projects in an academic medical center|Adapting data management education to support clinical research projects in an academic medical center]]
: ▪ [[Journal:What is this sensor and does this app need access to it?|What is this sensor and does this app need access to it?]]
: ▪ [[Journal:Development of an electronic information system for the management of laboratory data of tuberculosis and atypical mycobacteria at the Pasteur Institute in Côte d’Ivoire|Development of an electronic information system for the management of laboratory data of tuberculosis and atypical mycobacteria at the Pasteur Institute in Côte d’Ivoire]]
: ▪ [[Journal:AI meets exascale computing: Advancing cancer research with large-scale high-performance computing|AI meets exascale computing: Advancing cancer research with large-scale high-performance computing]]
: ▪ [[Journal:Codesign of the Population Health Information Management System to measure reach and practice change of childhood obesity programs|Codesign of the Population Health Information Management System to measure reach and practice change of childhood obesity programs]]
: ▪ [[Journal:Building infrastructure for African human genomic data management|Building infrastructure for African human genomic data management]]

Revision as of 16:43, 20 January 2020

Fig1 Mandrioli Molecules2019 24-11.png

"Fast detection of 10 cannabinoids by RP-HPLC-UV method in Cannabis sativa L."

Cannabis has regained much attention as a result of updated legislation authorizing many different uses, and it can be classified on the basis of the content of Δ9-tetrahydrocannabinol (Δ9-THC), a psychotropic substance for which there are legal limitations in many countries. For this purpose, accurate qualitative and quantitative determination is essential. The relationship between THC and cannabidiol (CBD) is also significant, as the latter substance is endowed with many specific and non-psychoactive proprieties. For these reasons, it becomes increasingly important and urgent to utilize fast, easy, validated, and harmonized procedures for determination of cannabinoids. The procedure described herein allows rapid determination of 10 cannabinoids from the inflorescences of Cannabis sativa L. by extraction with organic solvents. Separation and subsequent detection are by reversed-phase high-performance liquid chromatography with ultraviolet detector (RP-HPLC-UV). (Full article...)

Recently featured:

What is this sensor and does this app need access to it?
AI meets exascale computing: Advancing cancer research with large-scale high-performance computing
Building infrastructure for African human genomic data management