Jinchun Sun
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Researcher
Also affiliated: Jiangnan University (2004–2005); United States Department of Health and Human Services (2012); United States Food and Drug Administration (2008–2024); University of Kentucky (2007–2009); Chinese Academy of Sciences (2020); Lanzhou University of Technology (2000); Thomas Jefferson National Accelerator Facility (2012); Institute of Oceanology (2020); Qingdao National Laboratory for Marine Science and Technology (2020); Institute on Aging (2007); Lanzhou City University (2000); Food and Drug Administration (2012); University of Chinese Academy of Sciences (2020); Lanzhou University (1998–2000)
Faculty Researcher
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Jinchun Sun's research focuses on the application of metabolomics and lipidomics techniques to identify biomarkers for various health conditions and treatment outcomes. Sun has investigated how serum metabolite profiles can predict outcomes in critically ill patients receiving renal replacement therapy and has explored novel proteomic biomarkers for kidney recovery in dialysis-dependent acute kidney injury patients. Additionally, Sun's work includes evaluating the impact of violet-blue light on ex vivo platelet concentrates using metabolomics and lipidomics. Further research has examined the metabolic functional changes induced by cefoperazone in mice and the developmental effects of fentanyl on neural stem cell models, including lipidomic profiling.
Sun's publications also address untargeted metabolomics and lipidomics in the context of COVID-19 patient plasma to reveal disease severity biomarkers. This work contributes to the understanding of disease mechanisms and the development of diagnostic or prognostic tools. Sun has a history of collaboration with researchers at the National Center for Toxicological Research, including Richard D. Beger, Laura K. Schnackenberg, Lisa Pence, and Vikrant Vijay, with multiple shared publications.
Metrics
- h-index: 26
- Publications: 60
- Citations: 1,831
Selected Publications
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Assessing the developmental effects of fentanyl and impacts on lipidomic profiling using neural stem cell models (2025)
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Untargeted metabolomics and lipidomics in COVID-19 patient plasma reveals disease severity biomarkers (2024)
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Metabolomics evaluation of the photochemical impact of violet-blue light (405 nm) on ex vivo platelet concentrates (2023)
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Evaluating Cefoperazone-Induced Gut Metabolic Functional Changes in MR1-Deficient Mice (2022)
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Reference materials for MS-based untargeted metabolomics and lipidomics: a review by the metabolomics quality assurance and quality control consortium (mQACC) (2022)
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Serum metabolite profiles predict outcomes in critically ill patients receiving renal replacement therapy (2021)
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Discovery of Novel Proteomic Biomarkers for the Prediction of Kidney Recovery from Dialysis-Dependent AKI Patients (2021)
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Bile Acid Profile and its Changes in Response to Cefoperazone Treatment in MR1 Deficient Mice (2020)
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Metabolomics Test Materials for Quality Control: A Study of a Urine Materials Suite (2019)
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Microbiota of MR1 deficient mice confer resistance against Clostridium difficile infection (2019)
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Stability of the Human Plasma Proteome to Pre-analytical Variability as Assessed by an Aptamer-Based Approach (2019)
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Metabolomics‐based pathway changes in testis fragments treated with ethinylestradiol in vitro (2019)
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Evaluation of the Performance of Lipidyzer Platform and Its Application in the Lipidomics Analysis in Mouse Heart and Liver (2019)
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An Integrated Analysis of Metabolites, Peptides, and Inflammation Biomarkers for Assessment of Preanalytical Variability of Human Plasma (2019)
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An Aptamer‐Based Approach to Assess the Human Plasma Proteome for Pre‐Analytical Variability (2018)
Collaboration Network
Top Collaborators
- Reference materials for MS-based untargeted metabolomics and lipidomics: a review by the metabolomics quality assurance and quality control consortium (mQACC)
- Discovery of Novel Proteomic Biomarkers for the Prediction of Kidney Recovery from Dialysis-Dependent AKI Patients
- Serum metabolite profiles predict outcomes in critically ill patients receiving renal replacement therapy
- Metabolomics evaluation of the photochemical impact of violet-blue light (405 nm) on ex vivo platelet concentrates
- Evaluating Cefoperazone-Induced Gut Metabolic Functional Changes in MR1-Deficient Mice
Showing 5 of 7 shared publications
- Discovery of Novel Proteomic Biomarkers for the Prediction of Kidney Recovery from Dialysis-Dependent AKI Patients
- Serum metabolite profiles predict outcomes in critically ill patients receiving renal replacement therapy
- Evaluating Cefoperazone-Induced Gut Metabolic Functional Changes in MR1-Deficient Mice
- Discovery of Novel Proteomic Biomarkers for the Prediction of Kidney Recovery from Dialysis-Dependent AKI Patients
- Serum metabolite profiles predict outcomes in critically ill patients receiving renal replacement therapy
- Untargeted metabolomics and lipidomics in COVID-19 patient plasma reveals disease severity biomarkers
- Discovery of Novel Proteomic Biomarkers for the Prediction of Kidney Recovery from Dialysis-Dependent AKI Patients
- Serum metabolite profiles predict outcomes in critically ill patients receiving renal replacement therapy
- Discovery of Novel Proteomic Biomarkers for the Prediction of Kidney Recovery from Dialysis-Dependent AKI Patients
- Serum metabolite profiles predict outcomes in critically ill patients receiving renal replacement therapy
- Discovery of Novel Proteomic Biomarkers for the Prediction of Kidney Recovery from Dialysis-Dependent AKI Patients
- Serum metabolite profiles predict outcomes in critically ill patients receiving renal replacement therapy
- Discovery of Novel Proteomic Biomarkers for the Prediction of Kidney Recovery from Dialysis-Dependent AKI Patients
- Serum metabolite profiles predict outcomes in critically ill patients receiving renal replacement therapy
- Discovery of Novel Proteomic Biomarkers for the Prediction of Kidney Recovery from Dialysis-Dependent AKI Patients
- Serum metabolite profiles predict outcomes in critically ill patients receiving renal replacement therapy
- Discovery of Novel Proteomic Biomarkers for the Prediction of Kidney Recovery from Dialysis-Dependent AKI Patients
- Discovery of Novel Proteomic Biomarkers for the Prediction of Kidney Recovery from Dialysis-Dependent AKI Patients
- Reference materials for MS-based untargeted metabolomics and lipidomics: a review by the metabolomics quality assurance and quality control consortium (mQACC)
- Reference materials for MS-based untargeted metabolomics and lipidomics: a review by the metabolomics quality assurance and quality control consortium (mQACC)
- Reference materials for MS-based untargeted metabolomics and lipidomics: a review by the metabolomics quality assurance and quality control consortium (mQACC)
- Reference materials for MS-based untargeted metabolomics and lipidomics: a review by the metabolomics quality assurance and quality control consortium (mQACC)
- Reference materials for MS-based untargeted metabolomics and lipidomics: a review by the metabolomics quality assurance and quality control consortium (mQACC)
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