Rapid Profiling and Identification of Vitexin Metabolites in Rat Urine, Plasma and Faeces after Oral Administration Using a UHPLC-Q-Exactive Orbitrap Mass Spectrometer Coupled With Multiple Data-mining Methods

2021 ◽  
Vol 21 ◽  
Author(s):  
Pingping Dong ◽  
Lei Shi ◽  
Shaoping Wang ◽  
Shan Jiang ◽  
Haoran Li ◽  
...  
Keyword(s):  
Data Mining ◽  
Oral Administration ◽  
Mass Spectrometer ◽  
Flavonoid Compound ◽  
Ring Cleavage ◽  
Rat Urine ◽  
Multiple Data ◽  
Orbitrap Mass Spectrometer ◽  
Q Exactive ◽  
Mining Methods

Background: Vitexin is a natural flavonoid compound with multiple pharmacological activities and is extracted from the leaves and seeds of Vitex negundo L. var. cannabifolia (Sieb. et Zucc.) Hand.-Mazz. However, the metabolite characterization of this component remains insufficient. Objective: To establish a rapid profiling and identification method for vitexin metabolites in rat urine, plasma and faeces after oral administration using a UHPLC-Q-Exactive orbitrap mass spectrometer coupled with multiple data-mining methods. Methods: In this study, a simple and rapid systematic strategy for the detection and identification of constituents was proposed based on UHPLC-Q-Exactive Orbitrap mass spectrometry in parallel reaction monitoring mode combining diagnostic fragment ion filtering techniques. Results: A total of 49 metabolites were fully or partially characterized based on their accurate mass, characteristic fragment ions, retention times, corresponding ClogP values, and so on. It is obvious that C-glycosyl flavonoids often display an [M+H-120]+ ion that represents the loss of C4H8O4. As a result, these metabolites were presumed to be generated through glucuronidation, sulfation, deglucosylation, dehydrogenation, methylation, hydrogenation, hydroxylation, ring cleavage and their composite reactions. Moreover, the characteristic fragmentation pathways of flavonoids, chalcones, and dihydrochalcones were summarized for the subsequent metabolite identification. Conclusion: The current study provided an overall metabolic profile of vitexin, which will be of great help in predicting the in vivo pharmacokinetic profiles and understanding the action mechanism of this active ingredient.

Comprehensive and Rapid Identification of Astilbin Metabolites in Rats Based on Multiple Metabolite Templates Combined with UHPLC-Q-ExactiveMass Spectrometry

2021 ◽  
Vol 22 ◽  
Author(s):  
Shan Jiang ◽  
Haoran Li ◽  
Ailin Yang ◽  
Hongbing Zhang ◽  
Pingping Dong ◽  
...  
Keyword(s):  
Mass Spectrometer ◽  
Biological Effects ◽  
Rat Plasma ◽  
Rapid Identification ◽  
Negative Ion ◽  
Ring Cleavage ◽  
Rat Urine ◽  
Q Exactive ◽  
Negative Ion Mode

Background : Astilbin, a dihydroflavonoid compound widely found in plants, exhibits a variety of pharmacological activities and biological effects. However, little is known about the metabolism of this active compound in vivo, which is very helpful for elucidating the pharmacodynamic material basis and application of astilbin. Objective: To establish a rapid profiling and identification method for metabolites in rat urine, faeces and plasma using a UHPLC-Q-Exactive mass spectrometer in negative ion mode. Methods: In this study, a simple and rapid systematic strategy and 7 metabolite templates, which were established based on previous reports, were utilized to screen and identify astilbin metabolites. Results: As a result, a total of 72 metabolites were detected and characterized, among which 33 metabolites were found in rat urine, while 28 and 38 metabolites were characterized from rat plasma and faeces, respectively. These metabolites were presumed to be generated through ring cleavage, sulfation, dehydrogenation, methylation, hydroxylation, glucuronidation, dehydroxylation and their composite reactions. Conclusion: This study illustrated the capacity of the sensitive UHPLC-Q-Exactive mass spectrometer analytical system combined with the data-mining methods to rapidly elucidate the unknown metabolism. Moreover, the comprehensive metabolism study of astilbin provided an overall metabolic profile, which will be of great help in predicting the in vivo pharmacokinetic profiles and understanding the action mechanism of this active ingredient.

Rapid profiling and identification of puerarin metabolites in rat urine and plasma after oral administration by UHPLC-LTQ-Orbitrap mass spectrometer

2017 ◽  
Vol 1068-1069 ◽  
pp. 180-192 ◽  
Author(s):  
Zhanpeng Shang ◽  
Qiqi Xin ◽  
Wenjing Zhao ◽  
Zhibin Wang ◽  
Qinqing Li ◽  
...  
Keyword(s):  
Oral Administration ◽  
Mass Spectrometer ◽  
Rat Urine ◽  
Orbitrap Mass Spectrometer

scholarly journals Exploring ECD on a Benchtop Q Exactive Orbitrap Mass Spectrometer

2017 ◽  
Vol 17 (2) ◽  
pp. 926-933 ◽  
Author(s):  
Kyle L. Fort ◽  
Christian N. Cramer ◽  
Valery G. Voinov ◽  
Yury V. Vasil’ev ◽  
Nathan I. Lopez ◽  
...  
Keyword(s):  
Mass Spectrometer ◽  
Orbitrap Mass Spectrometer ◽  
Q Exactive

scholarly journals Mass Spectrometry-based Proteomics Using Q Exactive, a High-performance Benchtop Quadrupole Orbitrap Mass Spectrometer

2011 ◽  
Vol 10 (9) ◽  
pp. M111.011015 ◽  
Author(s):  
Annette Michalski ◽  
Eugen Damoc ◽  
Jan-Peter Hauschild ◽  
Oliver Lange ◽  
Andreas Wieghaus ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Mass Spectrometer ◽  
High Performance ◽  
Orbitrap Mass Spectrometer ◽  
Q Exactive

scholarly journals Computational Design Map for Heterogeneous Experimental Studies

2021 ◽  
Author(s):  
Chhaya Kulkarni ◽  
Nuzhat Maisha ◽  
Leasha J Schaub ◽  
Jacob Glaser ◽  
Erin Lavik ◽  
...  
Keyword(s):  
Data Mining ◽  
Blood Loss ◽  
Decision Trees ◽  
Data Science ◽  
Computational Design ◽  
Science Methods ◽  
Frequent Patterns ◽  
Multiple Data ◽  
Mining Methods ◽  
Using Data

This paper focuses on the discovery of a computational design map of disparate heterogeneous outcomes from bioinformatics experiments in pig (porcine) studies to help identify key variables impacting the experiment outcomes. Specifically we aim to connect discoveries from disparate laboratory experimentation in the area of trauma, blood loss and blood clotting using data science methods in a collaborative ensemble setting. Trauma related grave injuries cause exsanguination and death, constituting up to 50% of deaths especially in the armed forces. Restricting blood loss in such scenarios usually requires the presence of first responders, which is not feasible in certain cases. Moreover, a traumatic event may lead to a cytokine storm, reflected in the cytokine variables. Hemostatic nanoparticles have been developed to tackle these kinds of situations of trauma and blood loss. This paper highlights a collaborative effort of using data science methods in evaluating the outcomes from a lab study to further understand the efficacy of the nanoparticles. An intravenous administration of hemostatic nanoparticles was executed in pigs that had to undergo hemorrhagic shock and blood loss and other immune response variables, cytokine response variables are measured. Thus, through various hemostatic nanoparticles used in the intervention, multiple data outcomes are produced and it becomes critical to understand which nanoparticles are critical and what variables are key to study further variations in the lab. We propose a collaborative data mining framework which combines the results from multiple data mining methods to discover impactful features. We used frequent patterns observed in the data from these experiments. We further validate the connections between these frequent rules by comparing the results with decision trees and feature ranking. Both the frequent patterns and the decision trees help us identify the critical variables that stand out in the lab studies and need further validation and follow up in future studies. The outcomes from the data mining methods help produce a computational design map of the experimental results. Our preliminary results from such a computational design map provided insights in determining which features can help in designing the most effective hemostatic nanoparticles.

Sign in / Sign up

Export Citation Format

Share Document