Mariam Jarouche

Dr. Mariam Jarouche

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Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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13 December 2019 in Plants
Verified
Journal Article
Open access
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MJMariam Jarouche
Mariam Jarouche
HSHarsha Suresh
Harsha Suresh
JHJames Hennell
James Hennell
SSShaun Sullivan
Shaun Sullivan
SLSam Lee
Sam Lee
CKCheang Khoo
Cheang Khoo
Lycium (also known as Goji berry) is used in traditional Chinese medicine (TCM) with claimed benefits, including eye and liver protection, immune system fortification and blood glucose control. The commercially available product comes from either the L. barbarum or L. chinense species, with the former dominating the marketplace due to its better taste profile. The main objective of this study was to develop a validated LC-ESI-MS/MS method to quantify multiple key bio-active analytes in commercially available Lycium berries and to qualitatively assess these samples using a principal component analysis (PCA). A LC-ESI-MS/MS method for the quantitation of seven analytes selected using the Herbal Chemical Marker Ranking System (Herb MaRS) was developed. The Herb MaRS ranking system considered bioavailability, bioactivity and physiological action of each target analyte, its intended use and the commercial availability of an analytical standard. After method optimization combining high resolving power with selective detection, seven analytes were quantified and the Lycium samples were quantitatively profiled. Chromatographic spectra were also obtained using longer run-time LC-UV and GC-MS methods in order to qualitatively assess the samples using a principal component analysis (PCA). The result of the method validation procedure was a 15.5 min LC-ESI-MS/MS method developed for the quantification of seven analytes in commercial Lycium samples. Wide variation in analyte concentration was observed with the following results (analyte range in mg/g): rutin, 16.1–49.2; narcissin, 0.37–1.65; nictoflorin, 0.26–0.78; coumaric acid, 6.84–12.2; scopoletin, 0.33–2.61; caffeic acid, 0.08–0.32; chlorogenic acid, 1.1–9.12. The quantitative results for the L. barbarum and L. chinense species samples indicate that they cannot be differentiated based on the bio-actives tested. A qualitative assessment using PCA generated from un-targeted LC-UV and GC-MS phytochemical spectra led to the same conclusion. The un-targeted quantitative and qualitative phytochemical profiling indicates that commercial L. barbarum and L. chinense cannot be distinguished using chemical analytical methods. Genetic fingerprinting and pharmacological testing may be needed to ensure the efficacy of commercial Lycium in order to validate label claims.

17 April 2019 in Molecules
Verified
Journal Article
Open access
PDF file
MJMariam Jarouche
Mariam Jarouche
HSHarsha Suresh
Harsha Suresh
MLMitchell Low
Mitchell Low
SLSamiuela Lee
Samiuela Lee
CXCindy Xu
Cindy Xu
CKCheang Khoo
Cheang Khoo
Background—The quality control (QC) for commercial herbal formulations is sparse due to a lack of well-developed HPLC-ESI-MS/MS methods. Objective—This study reports the quantification of nine selected analytes for a commercial eight-herb formulation known as Qi Ju Di Huang Wan (QJDHW) used to relieve hypertension. Methods—An HPLC-ESI/MS method for the quantitation of analytes selected using the Herbal Chemical Marker Ranking System (Herb MaRS) was developed. The Herb MaRS ranking system which takes into account bioavailability, bioactivity, and physiological action related to its intended use and the commercial availability of the standard. After a method optimization, seven analytes were found to be ideal for quantitation. Results—The target analytes were identified using an electrospray ionization-tandem MS molecular breakdown comparison between the herbal peak and the commercial standard. The quantitative aspect of analyte variability of eleven samples was studied using fold variation. The fold variation of selected analytes among eleven samples ranged from 1.5 to 28.9. The qualitative aspect of variability was studied using principal component analysis (PCA) and hierarchical cluster analysis (HCA). Conclusions—There is a great degree of chemical variability in herbal formulations which are due to raw material harvesting times, storage techniques, and plant subspecies variability. Highlights—Commercial QJDHW formulations need to be standardised using HPLC-ESI-MS/MS to ensure better product quality control (QC) and product efficacy for the consumer.