scholarly journals Saururus chinensis Prevents Estrogen Deficiency-Induced Osteoporosis in Rats: A Metabolomic Study Using UPLC/Q-TOF MS

2021 ◽  
Vol 11 (4) ◽  
pp. 1392
Author(s):  
Sanghee Lee ◽  
Gwang Ju Jang ◽  
Miyoung Yoo ◽  
Haeng Jeon Hur ◽  
Mi Jeong Sung
Keyword(s):  
Discriminant Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
Estrogen Deficiency ◽  
Ovariectomized Rats ◽  
Sprague Dawley ◽  
Natural Medicine ◽  
Ovx Rats ◽  
Saururus Chinensis ◽  
Tof Ms

Saururus chinensis (SC), a traditional medicine, has been used for the treatment of edema, jaundice, gonorrhea, and several inflammatory diseases in China and Korea. Our previous studies reported the anti-osteoporotic activity of SC extract (SCE) in ovariectomized (OVX) rats but the mechanism of this effect was unclear. The aim of this study was to explore the anti-osteoporotic effect of SCE and elucidate the underlying mechanisms in ovariectomized rats using a metabolomics approach based on ultra-performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight mass spectrometry (UPLC/ESI-Q-TOF MS) to analyze metabolic changes. Female Sprague-Dawley (SD) rats were divided into sham, OVX, and SCE treatment groups. Partial least squares-discriminant analysis (PLS-DA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) score plots separated OVX and sham groups fairly well. Further, 22 potential biomarkers were identified in the rat models of estrogen deficiency-induced osteoporosis, and SCE showed regulatory effects on three vital metabolic pathways associated with these biomarkers, namely, glycerophospholipid metabolism, glycosylphosphatidylinositol-anchor biosynthesis, and linoleic acid metabolism. The metabolomics approach reliably confirmed that SCE exerted its anti-osteoporotic effect by intervening with lipid metabolism, thus preventing osteoporosis. This study also showed the promising potential of this approach in an evaluation of natural medicine efficacy.

scholarly journals Serum Metabolomics Study Based on LC-MS and Antihypertensive Effect of Uncaria on Spontaneously Hypertensive Rats

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Ana Liu ◽  
Yan-Jun Chu ◽  
Xiaoming Wang ◽  
Ruixue Yu ◽  
Haiqiang Jiang ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Discriminant Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
Antihypertensive Effect ◽  
Combination Method ◽  
Serum Samples ◽  
Multivariate Statistical ◽  
Spontaneously Hypertensive ◽  
Tof Ms

Our previous studies have shown that Uncaria has an important role in lowering blood pressure, but its intervention mechanism has not been clarified completely in the metabolic level. Therefore, in this study, a combination method of HPLC-TOF/MS-based metabolomics and multivariate statistical analyses was employed to explore the mechanism and evaluate the antihypertensive effect of Uncaria. Serum samples were analyzed and identified by HPLC-TOF/MS, while the acquired data was further processed by partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA) to discover the perturbed metabolites. A clear cluster among the different groups was obtained, and 7 significantly changed potential biomarkers were screened out. These biomarkers were mainly associated with lipid metabolism (dihydroceramide, ceramide, PC, LysoPC, and TXA2) and vitamin and amino acids metabolism (nicotinamide riboside, 5-HTP). The result indicated that Uncaria could decrease the blood pressure effectively, partially by regulating the above biomarkers and metabolic pathways. Analyzing and verifying the specific biomarkers, further understanding of the therapeutic mechanism and antihypertensive effect of Uncaria was acquired. Metabolomics provided a new insight into estimate of the therapeutic effect and dissection of the potential mechanisms of traditional Chinese medicine (TCM) in treating hypertension.

Sparse Partial-least-squares Discriminant Analysis for Different Geographical Origins of Salvia miltiorrhiza by 1 H-NMR-based Metabolomics

2013 ◽  
Vol 25 (1) ◽  
pp. 50-58 ◽  
Author(s):  
Miaomiao Jiang ◽  
Chunhua Wang ◽  
Yu Zhang ◽  
Yifan Feng ◽  
Yuefei Wang ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
Salvia Miltiorrhiza ◽  
H Nmr

scholarly journals 1H-NMR spectroscopy identifies potential biomarkers in serum metabolomic signatures for early stage esophageal squamous cell carcinoma

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e8151 ◽  
Author(s):  
Yan-Yan Liu ◽  
Zhong-Xian Yang ◽  
Li-Min Ma ◽  
Xu-Qing Wen ◽  
Huan-Lin Ji ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Discriminant Analysis ◽  
Nmr Spectroscopy ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Least Squares ◽  
Partial Least Squares ◽  
Early Stage ◽  
H Nmr ◽  
Potential Biomarkers

Background Esophageal squamous cell carcinoma (ESCC) is one of the most prevalent types of upper gastrointestinal malignancies. Here, we used 1H nuclear magnetic resonance spectroscopy (1H-NMR) to identify potential serum biomarkers in patients with early stage ESCC. Methods Sixty-five serum samples from early stage ESCC patients (n = 25) and healthy controls (n = 40) were analysed using 1H-NMR spectroscopy. We distinguished between different metabolites through principal component analysis, partial least squares-discriminant analysis, and orthogonal partial least squares-discriminant analysis (OPLS-DA) using SIMCA-P+ version 14.0 software. Receiver operating characteristic (ROC) analysis was conducted to verify potential biomarkers. Results Using OPLS-DA, 31 altered serum metabolites were successfully identified between the groups. Based on the area under the ROC curve (AUROC), and the biomarker panel with AUROC of 0.969, six serum metabolites (α-glucose, choline, glutamine, glutamate, valine, and dihydrothymine) were selected as potential biomarkers for early stage ESCC. Dihydrothymine particularly was selected as a new feasible biomarker associated with tumor occurrence. Conclusions 1H-NMR spectroscopy may be a useful tumour detection approach in identifying useful metabolic ESCC biomarkers for early diagnosis and in the exploration of the molecular pathogenesis of ESCC.

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