A5001405633- Metabolomics and Mass Spectrometry Studies
- Analytical Chemistry and Chromatography
- Advanced Chemical Sensor Technologies
- Mass Spectrometry Techniques and Applications
- Pesticide Residue Analysis and Safety
- Computational Drug Discovery Methods
- GABA and Rice Research
- Diet and metabolism studies
- Laser-Plasma Interactions and Diagnostics
- Plant biochemistry and biosynthesis
- Spectroscopy and Chemometric Analyses
- Gut microbiota and health
- Laser-induced spectroscopy and plasma
- Bioinformatics and Genomic Networks
- Aquatic Ecosystems and Phytoplankton Dynamics
- Microbial Metabolic Engineering and Bioproduction
- Petroleum Processing and Analysis
- Hydrocarbon exploration and reservoir analysis
- Water Treatment and Disinfection
- Rice Cultivation and Yield Improvement
- Laser-Matter Interactions and Applications
- Liver Disease Diagnosis and Treatment
- Mercury impact and mitigation studies
- Advanced Proteomics Techniques and Applications
- Astro and Planetary Science
Dalian Institute of Chemical Physics
2016-2025
Chinese Academy of Sciences
2016-2025
University of Chinese Academy of Sciences
2013-2025
Northeastern University
2024
Aerospace Information Research Institute
2024
Leeds Trinity University
2024
University of Notre Dame
2024
ZheJiang Academy of Agricultural Sciences
2024
Liaoning Ocean and Fisheries Research Institute
2023
East China University of Science and Technology
2023
HighlightsDeveloped a data preprocessing strategy to cope with missing values and mask effects in analysis from high variation of abundant metabolites.A new method- 'x-VAST' was developed amend the measurement deviation enlargement.Applying above strategy, several low masked differential metabolites were rescued. Metabolomics is booming research field. Its success highly relies on discovery by comparing different sets (for example, patients vs. controls). One challenges that differences...
Identification of the metabolites is an essential step in metabolomics study to interpret regulatory mechanism pathological and physiological processes. However, it still difficult LC–MSn-based studies because complexity mass spectrometry, chemical diversity metabolites, deficiency standards database. In this work, a comprehensive strategy developed for accurate batch metabolite identification nontargeted studies. First, well-defined procedure was applied generate reliable standard LC–MS2...
Abstract Senescence is the final stage of leaf growth and development. Many different physiological activities occur during this process. A comprehensive metabolomics analysis tobacco middle leaves at 5 developmental stages was implemented through multi-platform methods based on liquid chromatography, capillary electrophoresis gas chromatography coupled with mass spectrometry. In total, 412 metabolites were identified, including pigments, sterols, lipids, amino acids, polyamines, sugars...
Hydroxycinnamic acid amides (HCAAs), diversely distributed secondary metabolites in plants, play essential roles plant growth and developmental processes. Most current approaches can be used to analyze a few known HCAAs given plant. A novel method for comprehensive detection of is urgently needed. In this study, deep annotation was proposed on the basis ultra-high-performance liquid chromatography–high-resolution mass spectrometry (UHPLC–HRMS) its silico database HCAAs. To construct an...
Abstract Lung cancer is one of the most common and lethal cancers in world. In this study, a home‐devised hydrophilic interaction chromatography/RPLC‐MS (HILIC/RPLC‐MS) system was developed to study urinary metabonomics lung patients. This combined orthogonal selectivity HILIC RPLC could chromatographically reveal more comprehensive information metabolites. Within total analysis time 50 min, we detected 577 polar metabolite ions on first column 261 apolar ones second column. addition, an...
Fuzzy c-means (FCM) clustering is an unsupervised method derived from fuzzy logic that suitable for solving multiclass and ambiguous problems. In this study, FCM applied to cluster metabolomics data. performed directly on the data matrix generate a membership which represents degree of association samples have with each cluster. The parametrized number clusters (C) fuzziness coefficient (m), denotes in algorithm. Both been optimized by combining partial least-squares (PLS) using as Y PLS...
Diabetic retinopathy (DR) is a serious microvascular syndrome of diabetes, and one the most frequent causes blindness in world. It has three progressive stages with complex metabolic deregulations holistic system Western medicine. Chinese medicine classifies DR into two different types; integrating to treat validated therapeutic approach China. In this research, systemic metabolite change was investigated from viewpoint both medicine, using metabolomics based on gas chromatography–mass...
Modifications of genes and proteins have been extensively studied in systems biology using comprehensive analytical strategies. Although metabolites are frequently modified, these modifications not -omics approaches. Here a general strategy for the nontargeted profiling modified metabolites, which we call "nontargeted modification-specific metabolomics", is reported. A key aspect this was combination in-source collision-induced dissociation liquid chromatography-mass spectrometry (LC-MS)...
Liquid chromatography-high-resolution mass spectrometry (LC-HRMS) is widely used in untargeted metabolomics, but large-scale and high-accuracy metabolite annotation remains a challenge due to the complex nature of biological samples. Recently introduced electron impact excitation ions from organics (EIEIO) fragmentation can generate information-rich fragment ions. However, effective utilization EIEIO tandem (MS/MS) hindered by lack reference spectral databases. Molecular networking (MN)...
The pseudotargeted metabolomics method integrates advantages of nontargeted and targeted analysis because it can acquire data metabolites in the multireaction monitoring (MRM) mode mass spectrometry (MS) without needing standards. key is ion-pair information collection from samples to be analyzed. It well-known that sequential windowed acquisition all theoretical Fragment ion (SWATH) MS MS2 a maximum extent. To expediently as many ion-pairs possible with optimal collision energy (CE), an...
The incidence of nonsmoking female patients with non-small cell lung cancer (NSCLC) has increased in recent decades; however, the pathogenesis is unclear, and early diagnosis biomarkers are urgent need. In this study, 136 subjects (65 NSCLC, 6 benign tumors, 65 healthy controls) were enrolled, their metabolic profiling was investigated by using pseudotargeted gas chromatography–mass spectrometry. A total 56 annotated metabolites found verified to be significantly different females NSCLC...
Retention time (RT) prediction contributes to identification of small molecules measured by high-performance liquid chromatography coupled with high-resolution mass spectrometry. Deep learning algorithms based on big data can enhance the accuracy RT prediction. But at different chromatographic conditions, RTs compounds are different, and number known is in most cases. Therefore, transfer necessary. In this work, a strategy using deep neural network (DNN) pretrained weighed autoencoders...