2018
DOI: 10.1016/j.dib.2018.04.001
|View full text |Cite
|
Sign up to set email alerts
|

Metabolomics data of Mitragyna speciosa leaf using LC-ESI-TOF-MS

Abstract: Mitragyna speciosa is a psychoactive plant known as “ketum” in Malaysia and “kratom” in Thailand. This plant is distinctly known to produce two important alkaloids, namely mitragynine (MG) and 7-hydroxymitragynine (7-OH-MG) that can bind to opioid receptors [1]. MG was reported to exhibit antidepressant properties in animal studies [2]. These compounds were also proposed to have the potential to replace opioid analgesics with much lower risks of side effects [3]. To date, there are only over 40 metabolites ide… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
2

Citation Types

0
12
0
1

Year Published

2019
2019
2024
2024

Publication Types

Select...
7
2
1

Relationship

6
4

Authors

Journals

citations
Cited by 15 publications
(19 citation statements)
references
References 9 publications
0
12
0
1
Order By: Relevance
“…The scan range was from 100–1000 m / z . Data processing was performed using the software Data Analysis 4.0 and Profile Analysis (Bruker Daltonics) [ 37 ].…”
Section: Methodsmentioning
confidence: 99%
“…The scan range was from 100–1000 m / z . Data processing was performed using the software Data Analysis 4.0 and Profile Analysis (Bruker Daltonics) [ 37 ].…”
Section: Methodsmentioning
confidence: 99%
“…Other compounds, such as flavonoids, terpenoid saponins, polyphenols, and various glycosides are also present [25]. Veeramohan et al [31] performed a metabolomics study using the mature leaves of the green variety of Mitragyna speciosa in order to obtain a more complete profile of kratom’s secondary metabolites.…”
Section: Introductionmentioning
confidence: 99%
“…Raw material in “d format” was supplied to Bruker Compass Data Analysis Viewer version 4.2 (Bruker Daltonics, Bremen, Germany) and imported into the Profile Analysis 2.0 data bucketing software (Bruker Daltonics, Bremen, Germany) ( Mamat et al, 2018 ; Veeramohan et al, 2018 ). The parameters for compound detecting were: signal/noise threshold: 5; correlation coefficient: 0.7; minimum compound length: 8; smoothing width: 2.…”
Section: Methodsmentioning
confidence: 99%