An integrated multi-system to screen quality markers of blossom of Citrus aurantium L. var. amara Engl. via combining lipid-lowering and expectorant assays.
Wenhui ZengDong WuMengchu LiWen-Ping HuangJie ZhangYing JiangJing LiPublished in: Biomedical chromatography : BMC (2024)
The present research demonstrated that an integrated multi-system based on the assays of lipid-lowering and expectorant effects was used to screen quality markers of an edible and medical material-the blossom of Citrus aurantium L. var. amara Engl. (BCAVA)-and a portion of active constituents were quantified in multiple batches to provide scientific data to establish a quality standard for BCAVA. Mouse models were developed to evaluate the lipid-lowering and expectorant effects, facilitating the investigation of medicinal parts through different polar extractions of BCAVA. Subsequently, ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry was utilized for the in vivo and in vitro identification of chemical profiles within the medicinal parts of BCAVA. This methodological approach led to the selection and quantification of several active compounds from 21 batches of BCAVA sourced from different geographical regions samples. Notably, the ethanol extract of BCAVA exhibited significant lipid-lowering and expectorant effects while 183 compounds were identified in vitro and 109 in vivo, respectively. Then, five key ingredients were quantified, and the quantitative data were subjected to statistical analysis to discriminate between samples from various geographical regions. Overall, the findings underscore the significance of an integrated, assay-based approach for the characterization and quality assessment of BCAVA.
Keyphrases
- high throughput
- tandem mass spectrometry
- fatty acid
- ultra high performance liquid chromatography
- healthcare
- mass spectrometry
- electronic health record
- simultaneous determination
- quality improvement
- oxidative stress
- big data
- machine learning
- liquid chromatography
- artificial intelligence
- single cell
- high performance liquid chromatography
- deep learning
- solid phase extraction