Selecting marker substances of main producing area of Codonopsis lanceolata in Korea using UPLC-QTOF-MS analysis

2021 ◽  
Vol 64 (3) ◽  
pp. 245-251
Author(s):  
Young Min An ◽  
Hyun-Jae Jang ◽  
Doo-Young Kim ◽  
Nam-In Baek ◽  
Sei-Ryang Oh ◽  
...  
Keyword(s):  
Codonopsis Lanceolata ◽  
Ms Analysis ◽  
Marker Substances

HPLC-MS analysis of resveratrol in different nutritions

2011 ◽  
Vol 49 (05) ◽  
Author(s):  
S Szabó ◽  
L Márk ◽  
S Kiss ◽  
É Polyák ◽  
A Kisbenedek ◽  
...  
Keyword(s):  
Ms Analysis

LC-ESI-MS/MS analysis of Quassia amara leaves tea. Is antiplasmodial activity of the tea is due to quassinoids?

Planta Medica ◽  
2012 ◽  
Vol 78 (11) ◽  
Author(s):  
N Fabre ◽  
E Deharo ◽  
HL Le ◽  
C Girardi ◽  
A Valentin ◽  
...  
Keyword(s):  
Antiplasmodial Activity ◽  
Esi Ms ◽  
Ms Analysis ◽  
Quassia Amara

MS Analysis of Retinoids by Atmospheric Solids Atomization Probe

Planta Medica ◽  
2013 ◽  
Vol 79 (10) ◽  
Author(s):  
S Dobreniecki ◽  
JR Porter
Keyword(s):  
Ms Analysis

FTIR, GC-MS and HPLC analysis of Baliospermum montanum (Willd.) Muell. Arg.

2020 ◽  
Vol 11 (4) ◽  
pp. 5059-5066
Author(s):  
Sushma B K ◽  
Raveesha H R
Keyword(s):  
Acetic Acid ◽  
Quantitative Estimation ◽  
Chemical Constituents ◽  
Standard Procedure ◽  
Naphthalene Acetic Acid ◽  
Root Extract ◽  
Pentanoic Acid ◽  
Trimethylsilyl Ester ◽  
Isolation And Characterization ◽  
Ms Analysis

The present work is aimed to determine the chemical constituents in Baliospermum montanum methanolic extracts. An in vitro regenerated procedure was developed for the induction of callus from stem explant cultured on Murashige and Skoog (MS) medium fortified with various concentration and permutations of 2, 4-dichloro phenoxy acetic acid, 1-naphthalene acetic acid, 6-benzyl amino purine and gibberellic acid. FTIR & GC-MS analysis was done according to standard procedure. The quantitative estimation of β-sitosterol was done by HPLC method. Maximum fresh and dry weight of callus was estimated in the combination of GA3 (0.5 mg/L) + NAA (2 mg/L) compared to other concentration. The FTIR analysis showed various functional compounds with different characteristic peak values in the extracts. Major bioactive constituents were recognized in the GC-MS analysis. Root extract revealed the existence of 1-hexadecanol, pentanoic acid, 2-(aminooxy)- and 1-hexacosanol. Leaf extract showed the presence of propanoic acid, 2-oxo-, trimethylsilyl ester, 9,12-octadecadienoic acid (z,z)-, trimethylsilyl ester, docosane, 1,22-dibromo- and pentatriacontane. Stem and stem derived callus exhibit the presence of 1,6,3,4-dihydro-2-deoxy-beta-d-lyxo-hexopyranose, n-hexadecanoic acid and pentanoic acid, 2-(aminooxy). The methanolic extract of leaf exhibited 0.2149 % of β-sitosterol content. There were no peaks observed in the root, stem and stem derived callus. Further studies are necessary for the isolation and characterization of bioactive compounds from B. montanum.

Algorithm of combining chromatography mass spectrometry-untargeted profiling and multivariate analysis for identification of marker-substances in samples of complex composition

2020 ◽  
Vol 86 (7) ◽  
pp. 12-19
Author(s):  
I. V. Plyushchenko ◽  
D. G. Shakhmatov ◽  
I. A. Rodin
Keyword(s):  
Mass Spectrometry ◽  
Multivariate Analysis ◽  
Large Scale ◽  
Complex Composition ◽  
Unified Protocol ◽  
Chromatography Mass Spectrometry ◽  
Marker Substances ◽  
Selection Testing ◽  
Untargeted Profiling

A viral development of statistical data processing, computing capabilities, chromatography-mass spectrometry, and omics technologies (technologies based on the achievements of genomics, transcriptomics, proteomics, metabolomics) in recent decades has not led to formation of a unified protocol for untargeted profiling. Systematic errors reduce the reproducibility and reliability of the obtained results, and at the same time hinder consolidation and analysis of data gained in large-scale multi-day experiments. We propose an algorithm for conducting omics profiling to identify potential markers in the samples of complex composition and present the case study of urine samples obtained from different clinical groups of patients. Profiling was carried out by the method of liquid chromatography mass spectrometry. The markers were selected using methods of multivariate analysis including machine learning and feature selection. Testing of the approach was performed using an independent dataset by clustering and projection on principal components.

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