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)
 
(194 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:Fig1 Mudge AnalBioChem2017 409-12.gif|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Soto-Perdomo SoftwareX2023 24.jpg|240px]]</div>
'''"[[Journal:Leaner and greener analysis of cannabinoids|Leaner and greener analysis of cannabinoids]]"'''
'''"[[Journal:OptiGUI DataCollector: A graphical user interface for automating the data collecting process in optical and photonics labs|OptiGUI DataCollector: A graphical user interface for automating the data collecting process in optical and photonics labs]]"'''
 
OptiGUI DataCollector is a Python 3.8-based graphical user interface (GUI) that facilitates automated data collection in optics and photonics research and development equipment. It provides an intuitive and easy-to-use platform for controlling a wide range of optical instruments, including [[spectrometer]]s and lasers. OptiGUI DataCollector is a flexible and modular framework that enables simple integration with different types of devices. It simplifies experimental workflow and reduces human error by automating parameter control, data acquisition, and [[Data analysis|analysis]]. OptiGUI DataCollector is currently focused on optical mode conversion utilizing fiber optic technologies ... ('''[[Journal:OptiGUI DataCollector: A graphical user interface for automating the data collecting process in optical and photonics labs|Full article...]]''')<br />


There is an explosion in the number of [[Laboratory|labs]] analyzing [[wikipedia:Cannabinoid|cannabinoids]] in marijuana ([[wikipedia:Cannabis|''Cannabis sativa'' L.]], Cannabaceae); however, existing methods are inefficient, require expert analysts, and use large volumes of potentially environmentally damaging [[wikipedia:Solvent|solvents]]. The objective of this work was to develop and validate an accurate method for analyzing cannabinoids in cannabis raw materials and finished products that is more efficient and uses fewer toxic solvents. A method using [[high-performance liquid chromatography]] (HPLC) with [[Chromatography detector|diode-array detection]] (DAD) was developed for eight cannabinoids in ''Cannabis'' flowers and oils using a statistically guided optimization plan based on the principles of green chemistry. A single-laboratory validation determined the linearity, selectivity, accuracy, repeatability, intermediate precision, limit of detection, and limit of quantitation of the method. Amounts of individual cannabinoids above the limit of quantitation in the flowers ranged from 0.02 to 14.9% concentration (w/w), with repeatability ranging from 0.78 to 10.08% relative standard deviation. ('''[[Journal:Leaner and greener analysis of cannabinoids|Full article...]]''')<br />
<br />
''Recently featured'':
''Recently featured'':
: ▪ [[Journal:Laboratory information management software for engineered mini-protein therapeutic workflow|Laboratory information management software for engineered mini-protein therapeutic workflow]]
{{flowlist |
: ▪ [[Journal:Defending our public biological databases as a global critical infrastructure|Defending our public biological databases as a global critical infrastructure]]
* [[Journal:Ten simple rules for managing laboratory information|Ten simple rules for managing laboratory information]]
: ▪ [[Journal:Determining the hospital information system (HIS) success rate: Development of a new instrument and case study|Determining the hospital information system (HIS) success rate: Development of a new instrument and case study]]
* [[Journal:Hierarchical AI enables global interpretation of culture plates in the era of digital microbiology|Hierarchical AI enables global interpretation of culture plates in the era of digital microbiology]]
* [[Journal:Critical analysis of the impact of AI on the patient–physician relationship: A multi-stakeholder qualitative study|Critical analysis of the impact of AI on the patient–physician relationship: A multi-stakeholder qualitative study]]
}}

Latest revision as of 15:05, 17 June 2024

Fig1 Soto-Perdomo SoftwareX2023 24.jpg

"OptiGUI DataCollector: A graphical user interface for automating the data collecting process in optical and photonics labs"

OptiGUI DataCollector is a Python 3.8-based graphical user interface (GUI) that facilitates automated data collection in optics and photonics research and development equipment. It provides an intuitive and easy-to-use platform for controlling a wide range of optical instruments, including spectrometers and lasers. OptiGUI DataCollector is a flexible and modular framework that enables simple integration with different types of devices. It simplifies experimental workflow and reduces human error by automating parameter control, data acquisition, and analysis. OptiGUI DataCollector is currently focused on optical mode conversion utilizing fiber optic technologies ... (Full article...)

Recently featured:

Retrieved from "https://www.limswiki.org/index.php?title=Template:Article_of_the_week&oldid=64487"