Bio: Dan Liu is an academic researcher from Dalian Institute of Chemical Physics. The author has contributed to research in topics: Ginsenoside & Goji berry. The author has an hindex of 4, co-authored 10 publications receiving 34 citations.
TL;DR: This work applied an ultra-performance liquid chromatography-high resolution mass spectrometry-based peptidomics approach to characterize ginseng peptides and discover novel peptide biomarkers for authentication of mountain-cultivated gINSeng (MCG).
Abstract: The growth conditions and age of Panax ginseng are vital for determining the quality of the ginseng plant. However, the considerable difference in price according to the cultivation method and period of P. ginseng leads to its adulteration in the trade market. We herein focused on ginseng peptides and the possibility of these peptides to be used as biomarker(s) for discrimination of P. ginseng. We applied an ultraperformance liquid chromatography-high resolution mass spectrometry-based peptidomics approach to characterize ginseng peptides and discover novel peptide biomarkers for authentication of mountain-cultivated ginseng (MCG). We identified 52 high-confidence peptides and screened 20 characteristic peptides differentially expressed between MCG and cultivated ginseng (CG). Intriguingly, 6 differential peptides were expressed significantly in MCG and originated from dehydrins that accumulated during cold or drought conditions. In addition, 14 other differential peptides that were significantly expressed in CG derived from ginseng major protein, an essential protein for nitrogen storage. These biological associations confirmed the reliability and credibility of the differential peptides. Additionally, we determined several robust peptide biomarkers for discrimination of MCG through a precise selection process. These findings demonstrate the potential of peptide biomarkers for identification and quality control of P. ginseng in addition to ginsenoside analysis.
TL;DR: An efficient salt-out assisted liquid-liquid extraction (SALLE) to treat plasma, and then analyzed the samples using nano-LC-MS to quantify intact oxytocin (OT) in human and rat plasmas to be an alternative method for quantitative determination of other ultra-trace peptides in plasma.
TL;DR: In this paper, a nontargeted metabolomics approach based on ultra high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS) was used to find the differential composition between Zhongning goji berries (ZNG) and non-ZNG.
TL;DR: It was shown that normal and ovarian tumors have unique metabolic signature in urine and plasma samples, which shed light on the ovarian cancer diagnosis and classification.
Abstract: Diagnosis of ovarian cancer is difficult due to the lack of clinical symptoms and effective screening algorithms. In this study, we aim to develop models for ovarian cancer diagnosis by detecting metabolites in urine and plasma samples. Ultra-high-performance liquid chromatography and quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) in positive ion mode was used for metabolome quantification in 235 urine samples and 331 plasma samples. Then, Urine and plasma metabolomic profiles were analyzed by univariate and multivariate statistics. Four groups of samples: normal control, benign, borderline and malignant ovarian tumors were enrolled in this study. A total of 1330 features and 1302 features were detected from urine and plasma samples respectively. Based on two urine putative metabolites, five plasma putative metabolites and five urine putative metabolites, three models for distinguishing normal-ovarian tumors, benign-malignant (borderline + malignant) and borderline-malignant ovarian tumors were developed respectively. The AUC (Area Under Curve) values were 0.987, 0876 and 0.943 in discovery set and 0.984, 0.896 and 0.836 in validation set for three models. Specially, the diagnostic model based on 5 plasma putative metabolites had better early-stage diagnosis performance than CA125 alone. The AUC values of the model were 0.847 and 0.988 in discovery and validation set respectively. Our results showed that normal and ovarian tumors have unique metabolic signature in urine and plasma samples, which shed light on the ovarian cancer diagnosis and classification.
TL;DR: It is found that N-butyl-4-hydroxy-1,8-naphthalimide (BHN) can provide improved performance as a matrix for small molecule analysis and the ability of BHN to form highly homogenous crystalline particles shows the clear beneficial effects of BhN for the reproducibility of MS detection.
Abstract: Rationale The matrix plays an essential role in defining detection limits and ionization yields of analytes in matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) analysis. Small molecule MALDI-MS analyses commonly suffer from the high background interference generated from matrices. Moreover, the inhomogeneous crystallization of some matrices, such as 2,5-dihydroxybenzoic acid (DHB), is to the detriment of the quality or repeatability of detection. We have found that N-butyl-4-hydroxy-1,8-naphthalimide (BHN) can provide improved performance as a matrix for small molecule analysis. Methods BHN was evaluated in the low-mass region for its ionization efficiency, repeatability and background interference using O-acetyl-L-carnitine hydrochloride, Aβ35-40, Aβ35-42, and oxytocin as the model analytes. In addition, the modification effects of BHN on DHB were investigated for the in situ analysis of endogenous compounds in rat brain slices using Fourier transform ion cyclotron resonance (FTICR)-MS. Results BHN is capable of ionizing small molecules, including O-acetyl-L-carnitine hydrochloride and peptides, with high repeatability and low background interference signals. A low concentration of BHN (3 mM) modifies the crystallization state of DHB but still retains its ionization performance. The determination of small molecules desorbed from tissue slices was significantly improved by using a binary matrix of DHB and BHN, yielding superior signal-to-noise ratio and signal intensities. Conclusions The new matrix BHN has exhibited suitability for the analysis of small molecules. Compared with the conventional matrices, CHCA and DHB, BHN provides a clean background in the low-mass region. In combination with DHB, the ability of BHN to form highly homogenous crystalline particles shows the clear beneficial effects of BHN for the reproducibility of MS detection.
TL;DR: This review is intended to offer a concise critical overview of the most recent achievements about MALDI matrices capable of specifically address the challenging issue of small molecules analysis.
Abstract: Since its introduction in the 1980s, matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) has gained a prominent role in the analysis of high molecular weight biomolecules such as proteins, peptides, oligonucleotides, and polysaccharides. Its application to low molecular weight compounds has remained for long time challenging due to the spectral interferences produced by conventional organic matrices in the low m/z window. To overcome this problem, specific sample preparation such as analyte/matrix derivatization, addition of dopants, or sophisticated deposition technique especially useful for imaging experiments, have been proposed. Alternative approaches based on second generation (rationally designed) organic matrices, ionic liquids, and inorganic matrices, including metallic nanoparticles, have been the object of intense and continuous research efforts. Definite evidences are now provided that MALDI MS represents a powerful and invaluable analytical tool also for small molecules, including their quantification, thus opening new, exciting applications in metabolomics and imaging mass spectrometry. This review is intended to offer a concise critical overview of the most recent achievements about MALDI matrices capable of specifically address the challenging issue of small molecules analysis. Graphical abstract An ideal Book of matrices for MALDI MS of small molecules.
TL;DR: It is proposed that current challenges in the measurement of oxytocin may be analogous to the parable of the blind men and the elephant, with different methods of sample preparation and measurement being sensitive to different states in which the oxytocIn molecule can exist.
TL;DR: In this article , a review of the advances in the phytochemistry, quality control, metabolism, and biosynthesis pathway of ginseng over the past decade (2011-2020), with 410 citations, is presented.
TL;DR: The purpose was to review and summarize the species classification, geographical distribution, and ethnic minorities medicinal records of the genus Panax, and further to review the analytical tools and data analysis methods for the authentication and quality assessment of Panax medicinal materials and Chinese patent medicines.
Abstract: Genus Panax, as worldwide medicinal plants, has a medical history for thousands of years. Most of the entire genus are traditional ethnobotanical medicine in China, Myanmar, Thailand, Vietnam and L...
TL;DR: Ad-hoc efforts are still needed to improve the identification of short peptides and the analysis of the large data set generated, although a more detailed picture of the peptides present or derived from food is provided.
Abstract: In recent years, peptidomics is gaining ever-growing relevance in food science. The emerging field of food peptidomics is defined as the whole pool of peptides existing in food products or generated during food processing, storage or digestion. The recent advancement in high-resolution mass spectrometry techniques provides a more detailed picture, although not yet exhaustive, of the peptides present or derived from food. Food peptidomics techniques have been successfully applied in understanding food protein digestion, in the study of the microbial contribution to food protein hydrolysis, in the identification of food-derived bioactive peptides and peptide biomarkers. Ad-hoc efforts are still needed to improve the identification of short peptides and the analysis of the large data set generated.