Search

Your search keyword '"Wang-Sattler, Rui"' showing total 325 results
Start Over Author "Wang-Sattler, Rui"
325 results on '"Wang-Sattler, Rui"'

1. Bidirectional modulation of TCA cycle metabolites and anaplerosis by metformin and its combination with SGLT2i

Author

Harada, Makoto, Adam, Jonathan, Covic, Marcela, Ge, Jianhong, Brandmaier, Stefan, Muschet, Caroline, Huang, Jialing, Han, Siyu, Rommel, Martina, Rotter, Markus, Heier, Margit, Mohney, Robert P., Krumsiek, Jan, Kastenmüller, Gabi, Rathmann, Wolfgang, Zou, Zhongmei, Zukunft, Sven, Scheerer, Markus F., Neschen, Susanne, Adamski, Jerzy, Gieger, Christian, Peters, Annette, Ankerst, Donna P., Meitinger, Thomas, Alderete, Tanya L., de Angelis, Martin Hrabe, Suhre, Karsten, and Wang-Sattler, Rui

Published
2024
Full Text
View/download PDF

9. Integrated personalized diabetes management goes Europe: A multi-disciplinary approach to innovating type 2 diabetes care in Europe

Author

Jones, Allan, Bardram, Jakob Eyvind, Bækgaard, Per, Cramer-Petersen, Claus Lundgaard, Skinner, Timothy, Vrangbæk, Karsten, Starr, Laila, Nørgaard, Kirsten, Lind, Nanna, Bechmann Christensen, Merete, Glümer, Charlotte, Wang-Sattler, Rui, Laxy, Michael, Brander, Erik, Heinemann, Lutz, Heise, Tim, Schliess, Freimut, Ladewig, Katharina, and Kownatka, Dagmar

Published
2021
Full Text
View/download PDF

10. Prediction of Myocardial Infarction Using a Combined Generative Adversarial Network Model and Feature-Enhanced Loss Function.

Author

Yu, Shixiang, Han, Siyu, Shi, Mengya, Harada, Makoto, Ge, Jianhong, Li, Xuening, Cai, Xiang, Heier, Margit, Karstenmüller, Gabi, Suhre, Karsten, Gieger, Christian, Koenig, Wolfgang, Rathmann, Wolfgang, Peters, Annette, and Wang-Sattler, Rui

Subjects
GENERATIVE adversarial networks, MYOCARDIAL infarction, METABOLOMICS, PREDICTION models, FORECASTING
Abstract

Accurate risk prediction for myocardial infarction (MI) is crucial for preventive strategies, given its significant impact on global mortality and morbidity. Here, we propose a novel deep-learning approach to enhance the prediction of incident MI cases by incorporating metabolomics alongside clinical risk factors. We utilized data from the KORA cohort, including the baseline S4 and follow-up F4 studies, consisting of 1454 participants without prior history of MI. The dataset comprised 19 clinical variables and 363 metabolites. Due to the imbalanced nature of the dataset (78 observed MI cases and 1376 non-MI individuals), we employed a generative adversarial network (GAN) model to generate new incident cases, augmenting the dataset and improving feature representation. To predict MI, we further utilized multi-layer perceptron (MLP) models in conjunction with the synthetic minority oversampling technique (SMOTE) and edited nearest neighbor (ENN) methods to address overfitting and underfitting issues, particularly when dealing with imbalanced datasets. To enhance prediction accuracy, we propose a novel GAN for feature-enhanced (GFE) loss function. The GFE loss function resulted in an approximate 2% improvement in prediction accuracy, yielding a final accuracy of 70%. Furthermore, we evaluated the contribution of each clinical variable and metabolite to the predictive model and identified the 10 most significant variables, including glucose tolerance, sex, and physical activity. This is the first study to construct a deep-learning approach for producing 7-year MI predictions using the newly proposed loss function. Our findings demonstrate the promising potential of our technique in identifying novel biomarkers for MI prediction. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

11. Corrigendum to “Longitudinal associations between metabolites and immediate, short- and medium-term exposure to ambient air pollution: Results from the KORA cohort study” [Sci. Total Environ. 900 (2023) 165780]

Author

Yao, Yueli, primary, Schneider, Alexandra, additional, Wolf, Kathrin, additional, Zhang, Siqi, additional, Wang-Sattler, Rui, additional, Prehn, Cornelia, additional, Adamski, Jerzy, additional, Peters, Annette, additional, and Breitner, Susanne, additional

Published
2023
Full Text
View/download PDF

12. Metabolomics reveals reasons for the efficacy of acupuncture in migraine patients: The role of anaerobic glycolysis and mitochondrial citrate in migraine relief

Author

Gao, Zishan, primary, Yan, Xian-Zhong, additional, Wang-Sattler, Rui, additional, Covic, Marcela, additional, Yu, Guang, additional, Ge, Feifei, additional, Lin, Jia, additional, Chen, Qin, additional, Liu, Juan, additional, Sharma, Sapna, additional, Molnos, Sophie, additional, Kuehnel, Brigitte, additional, Wilson, Rory, additional, Adam, Jonathan, additional, Brandmaier, Stefan, additional, Yu, Shuguang, additional, Mansmann, Ulrich, additional, Liang, Fanrong, additional, and Gieger, Christian, additional

Published
2023
Full Text
View/download PDF

14. Missing view completion for multi-timepoints omics data via representation disentanglement and temporal knowledge transfer

Author

Han, Siyu, primary, Yu, Shixiang, additional, Shi, Mengya, additional, Harada, Makoto, additional, Ge, Jianhong, additional, Lin, Jiesheng, additional, Prehn, Cornelia, additional, Petrera, Agnese, additional, Li, Ying, additional, Sam, Flora, additional, Matullo, Giuseppe, additional, Adamski, Jerzy, additional, Suhre, Karsten, additional, Gieger, Christian, additional, Hauck, Stefanie M., additional, Herder, Christian, additional, Roden, Michael, additional, Casale, Francesco Paolo, additional, Cai, Na, additional, Peters, Annette, additional, and Wang-Sattler, Rui, additional

Published
2023
Full Text
View/download PDF

15. Predictive metabolites for incident myocardial infarction: a two-step meta-analysis of individual patient data from six cohorts comprising 7,897 individuals from the the COnsortium of METabolomic Studies

Author

Nogal, Ana, primary, Alkis, Taryn, additional, Lee, Yura, additional, Kifer, Domagoj, additional, Hu, Jie, additional, Murphy, Rachel A, additional, Huang, Zhe, additional, Wang-Sattler, Rui, additional, Kastenmüler, Gabi, additional, Linkohr, Birgit, additional, Barrios, Clara, additional, Crespo, Marta, additional, Gieger, Christian, additional, Peters, Annette, additional, Price, Jackie, additional, Rexrode, Kathryn M, additional, Yu, Bing, additional, and Menni, Cristina, additional

Published
2023
Full Text
View/download PDF

16. Ldlr−/− and ApoE−/− mice better mimic the human metabolite signature of increased carotid intima media thickness compared to other animal models of cardiovascular disease

Author

Saulnier-Blache, Jean Sébastien, Wilson, Rory, Klavins, Kristaps, Graham, Delyth, Alesutan, Ioana, Kastenmüller, Gabi, Wang-Sattler, Rui, Adamski, Jerzy, Roden, Michael, Rathmann, Wolfgang, Seissler, Jochen, Meisinger, Christine, Koenig, Wolfgang, Thiery, Joachim, Suhre, Karsten, Peters, Annette, Kuro-O, Makuto, Lang, Florian, Dallmann, Guido, Delles, Christian, Voelkl, Jakob, Waldenberger, Melanie, Bascands, Jean-Loup, Klein, Julie, and Schanstra, Joost P.

Published
2018
Full Text
View/download PDF

17. Identification of candidate metabolite biomarkers for metabolic syndrome and its five components in population-based human cohorts

Author

Shi, Mengya, primary, Han, Siyu, additional, Klier, Kristin, additional, Fobo, Gisela, additional, Montrone, Corinna, additional, Yu, Shixiang, additional, Harada, Makoto, additional, Henning, Ann-Kristin, additional, Friedrich, Nele, additional, Bahls, Martin, additional, Dörr, Marcus, additional, Nauck, Matthias, additional, Völzke, Henry, additional, Homuth, Georg, additional, Grabe, Hans J., additional, Prehn, Cornelia, additional, Adamski, Jerzy, additional, Suhre, Karsten, additional, Rathmann, Wolfgang, additional, Ruepp, Andreas, additional, Hertel, Johannes, additional, Peters, Annette, additional, and Wang-Sattler, Rui, additional

Published
2023
Full Text
View/download PDF

19. Association of Atopic Dermatitis with Cardiovascular Risk Factors and Diseases

Author

Standl, Marie, Tesch, Falko, Baurecht, Hansjörg, Rodríguez, Elke, Müller-Nurasyid, Martina, Gieger, Christian, Peters, Annette, Wang-Sattler, Rui, Prehn, Cornelia, Adamski, Jerzy, Kronenberg, Florian, Schulz, Holger, Koletzko, Sibylle, Schikowski, Tamara, von Berg, Andrea, Lehmann, Irina, Berdel, Dietrich, Heinrich, Joachim, Schmitt, Jochen, and Weidinger, Stephan

Published
2017
Full Text
View/download PDF

20. Predictive metabolites for incident myocardial infarction: a two-step meta-analysis of individual patient data from six cohorts comprising 7897 individuals from the COnsortium of METabolomics Studies.

Author

Nogal, Ana, Alkis, Taryn, Lee, Yura, Kifer, Domagoj, Hu, Jie, Murphy, Rachel A, Huang, Zhe, Wang-Sattler, Rui, Kastenmüler, Gabi, Linkohr, Birgit, Barrios, Clara, Crespo, Marta, Gieger, Christian, Peters, Annette, Price, Jackie, Rexrode, Kathryn M, Yu, Bing, and Menni, Cristina

Subjects
MYOCARDIAL infarction, CONSORTIA, METABOLOMICS, METABOLITES, FALSE discovery rate, AMINOACYL-tRNA
Abstract

Aims Myocardial infarction (MI) is a major cause of death and disability worldwide. Most metabolomics studies investigating metabolites predicting MI are limited by the participant number and/or the demographic diversity. We sought to identify biomarkers of incident MI in the COnsortium of METabolomics Studies. Methods and results We included 7897 individuals aged on average 66 years from six intercontinental cohorts with blood metabolomic profiling (n = 1428 metabolites, of which 168 were present in at least three cohorts with over 80% prevalence) and MI information (1373 cases). We performed a two-stage individual patient data meta-analysis. We first assessed the associations between circulating metabolites and incident MI for each cohort adjusting for traditional risk factors and then performed a fixed effect inverse variance meta-analysis to pull the results together. Finally, we conducted a pathway enrichment analysis to identify potential pathways linked to MI. On meta-analysis, 56 metabolites including 21 lipids and 17 amino acids were associated with incident MI after adjusting for multiple testing (false discovery rate < 0.05), and 10 were novel. The largest increased risk was observed for the carbohydrate mannitol/sorbitol {hazard ratio [HR] [95% confidence interval (CI)] = 1.40 [1.26–1.56], P < 0.001}, whereas the largest decrease in risk was found for glutamine [HR (95% CI) = 0.74 (0.67–0.82), P < 0.001]. Moreover, the identified metabolites were significantly enriched (corrected P < 0.05) in pathways previously linked with cardiovascular diseases, including aminoacyl-tRNA biosynthesis. Conclusions In the most comprehensive metabolomic study of incident MI to date, 10 novel metabolites were associated with MI. Metabolite profiles might help to identify high-risk individuals before disease onset. Further research is needed to fully understand the mechanisms of action and elaborate pathway findings. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

22. Metabolomics reveals a link between homocysteine and lipid metabolism and leukocyte telomere length: the ENGAGE consortium

Author

van der Spek, Ashley, Broer, Linda, Draisma, Harmen H. M., Pool, René, Albrecht, Eva, Beekman, Marian, Mangino, Massimo, Raag, Mait, Nyholt, Dale R., Dharuri, Harish K., Codd, Veryan, Amin, Najaf, de Geus, Eco J. C., Deelen, Joris, Demirkan, Ayse, Yet, Idil, Fischer, Krista, Haller, Toomas, Henders, Anjali K., Isaacs, Aaron, Medland, Sarah E., Montgomery, Grant W., Mooijaart, Simon P., Strauch, Konstantin, Suchiman, H. Eka D., Vaarhorst, Anika A. M., van Heemst, Diana, Wang-Sattler, Rui, Whitfield, John B., Willemsen, Gonneke, Wright, Margaret J., Martin, Nicholas G., Samani, Nilesh J., Metspalu, Andres, Eline Slagboom, P., Spector, Tim D., Boomsma, Dorret I., van Duijn, Cornelia M., and Gieger, Christian

Published
2019
Full Text
View/download PDF

24. Metabolite ratios as potential biomarkers for type 2 diabetes: a DIRECT study

Author

Molnos, Sophie, Wahl, Simone, Haid, Mark, Eekhoff, E. Marelise W., Pool, René, Floegel, Anna, Deelen, Joris, Much, Daniela, Prehn, Cornelia, Breier, Michaela, Draisma, Harmen H., van Leeuwen, Nienke, Simonis-Bik, Annemarie M. C., Jonsson, Anna, Willemsen, Gonneke, Bernigau, Wolfgang, Wang-Sattler, Rui, Suhre, Karsten, Peters, Annette, Thorand, Barbara, Herder, Christian, Rathmann, Wolfgang, Roden, Michael, Gieger, Christian, Kramer, Mark H. H., van Heemst, Diana, Pedersen, Helle K., Gudmundsdottir, Valborg, Schulze, Matthias B., Pischon, Tobias, de Geus, Eco J. C., Boeing, Heiner, Boomsma, Dorret I., Ziegler, Anette G., Slagboom, P. Eline, Hummel, Sandra, Beekman, Marian, Grallert, Harald, Brunak, Søren, McCarthy, Mark I., Gupta, Ramneek, Pearson, Ewan R., Adamski, Jerzy, and ’t Hart, Leen M.

Published
2017
Full Text
View/download PDF

27. Non-targeted metabolomics combined with genetic analyses identifies bile acid synthesis and phospholipid metabolism as being associated with incident type 2 diabetes

Author

Fall, Tove, Salihovic, Samira, Brandmaier, Stefan, Nowak, Christoph, Ganna, Andrea, Gustafsson, Stefan, Broeckling, Corey D., Prenni, Jessica E., Kastenmüller, Gabi, Peters, Annette, Magnusson, Patrik K., Wang-Sattler, Rui, Giedraitis, Vilmantas, Berne, Christian, Gieger, Christian, Pedersen, Nancy L., Ingelsson, Erik, and Lind, Lars

Published
2016
Full Text
View/download PDF

28. Identification of proliferative and mature β-cells in the islets of Langerhans

Author

Bader, Erik, Migliorini, Adriana, Gegg, Moritz, Moruzzi, Noah, Gerdes, Jantje, Roscioni, Sara S., Bakhti, Mostafa, Brandl, Elisabeth, Irmler, Martin, Beckers, Johannes, Aichler, Michaela, Feuchtinger, Annette, Leitzinger, Christin, Zischka, Hans, Wang-Sattler, Rui, Jastroch, Martin, Tschop, Matthias, Machicao, Fausto, Staiger, Harald, Haring, Hans-Ulrich, Chmelova, Helena, Chouinard, Julie A., Oskolkov, Nikolay, Korsgren, Olle, Speier, Stephan, and Lickert, Heiko

Subjects
Islands of Langerhans -- Physiological aspects, Cells -- Identification and classification, Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

Insulin-dependent diabetes is a complex multifactorial disorder characterized by loss or dysfunction of β-cells. Pancreatic β-cells differ in size, glucose responsiveness, insulin secretion and precursor cell potential (1-5); understanding the [...]

Published
2016

32. First mitochondrial genome-wide association study with metabolomics

Author

Aboulmaouahib, Brahim, primary, Kastenmüller, Gabi, additional, Suhre, Karsten, additional, Zöllner, Sebastian, additional, Weissensteiner, Hansi, additional, Prehn, Cornelia, additional, Adamski, Jerzy, additional, Gieger, Christian, additional, Wang-Sattler, Rui, additional, Lichtner, Peter, additional, Strauch, Konstantin, additional, and Flaquer, Antònia, additional

Published
2021
Full Text
View/download PDF

37. Effects of Metformin on Metabolite Profiles and LDL Cholesterol in Patients With Type 2 Diabetes

Author

Xu, Tao, Brandmaier, Stefan, Messias, Ana C., Herder, Christian, Draisma, Harmen H.M., Demirkan, Ayse, Yu, Zhonghao, Ried, Janina S., Haller, Toomas, Heier, Margit, Campillos, Monica, Fobo, Gisela, Stark, Renee, Holzapfel, Christina, Adam, Jonathan, Chi, Shen, Rotter, Markus, Panni, Tommaso, Quante, Anne S., He, Ying, Prehn, Cornelia, Roemisch-Margl, Werner, Kastenmüller, Gabi, Willemsen, Gonneke, Pool, René, Kasa, Katarina, van Dijk, Ko Willems, Hankemeier, Thomas, Meisinger, Christa, Thorand, Barbara, Ruepp, Andreas, Hrabé de Angelis, Martin, Li, Yixue, Wichmann, H.-Erich, Stratmann, Bernd, Strauch, Konstantin, Metspalu, Andres, Gieger, Christian, Suhre, Karsten, Adamski, Jerzy, Illig, Thomas, Rathmann, Wolfgang, Roden, Michael, Peters, Annette, van Duijn, Cornelia M., Boomsma, Dorret I., Meitinger, Thomas, and Wang-Sattler, Rui

Published
2015
Full Text
View/download PDF

38. Metabolomics to identify biomarkers and influencing factors of Type 2 Diabetes

Author

Wang-Sattler, Rui

Subjects
FOS: Medical and Health Sciences
Abstract

Type 2 diabetes (T2D) is a lifelong, incapacitating disease affecting multiple organs, and is associated with devastating chronic complications, which impose an immense burden on the quality of life of the patients and account for more than 10% of health care cost in Europe. Presently, T2D cannot be cured and only pre-diabetes can be prevented. Research presented in this thesis focuses on the identification of candidate metabolite biomarkers of pre-diabetes and T2D with stringent quality control of metabolite profiles in human cohort studies. This enabled the systematic characterization of numerous factors that influence T2D onset and progression such as age, smoking, alcohol consumption and metformin usage. A set of novel metabolite biomarkers (glycine, LPC (18:2) and C2), which are distinct from known diabetes risk factors, such as fasting glucose and HbA1C, have been identified. These improved biomarkers might replace currently considered metabolites (branched-chain and aromatic amino acids) for the detection of pre-diabetes and monitoring T2D progression.

Published
2021
Full Text
View/download PDF

40. Validation of Candidate Phospholipid Biomarkers of Chronic Kidney Disease in Hyperglycemic Individuals and Their Organ-Specific Exploration in Leptin Receptor-Deficient db/db Mouse

Author

Huang, Jialing, primary, Covic, Marcela, additional, Huth, Cornelia, additional, Rommel, Martina, additional, Adam, Jonathan, additional, Zukunft, Sven, additional, Prehn, Cornelia, additional, Wang, Li, additional, Nano, Jana, additional, Scheerer, Markus F., additional, Neschen, Susanne, additional, Kastenmüller, Gabi, additional, Gieger, Christian, additional, Laxy, Michael, additional, Schliess, Freimut, additional, Adamski, Jerzy, additional, Suhre, Karsten, additional, de Angelis, Martin Hrabe, additional, Peters, Annette, additional, and Wang-Sattler, Rui, additional

Published
2021
Full Text
View/download PDF

41. Machine learning approaches revealed metabolic signatures of incident chronic kidney disease in persons with pre-and type 2 diabetes

Author

Admin, Ada, primary, Huang, Jialing, primary, Huth, Cornelia, primary, Covic, Marcela, primary, Troll, Martina, primary, Adam, Jonathan, primary, Zukunft, Sven, primary, Prehn, Cornelia, primary, Wang, Li, primary, Nano, Jana, primary, Scheerer, Markus F., primary, Neschen, Susanne, primary, Kastenmüller, Gabi, primary, Suhre, Karsten, primary, Laxy, Michael, primary, Schliess, Freimut, primary, Gieger, Christian, primary, Adamski, Jerzy, primary, Angelis, Martin Hrabe de, primary, Peters, Annette, primary, and Wang-Sattler, Rui, primary

Published
2020
Full Text
View/download PDF

42. Machine Learning Approaches Reveal Metabolic Signatures of Incident Chronic Kidney Disease in Individuals With Prediabetes and Type 2 Diabetes

Author

Huang, Jialing, primary, Huth, Cornelia, additional, Covic, Marcela, additional, Troll, Martina, additional, Adam, Jonathan, additional, Zukunft, Sven, additional, Prehn, Cornelia, additional, Wang, Li, additional, Nano, Jana, additional, Scheerer, Markus F., additional, Neschen, Susanne, additional, Kastenmüller, Gabi, additional, Suhre, Karsten, additional, Laxy, Michael, additional, Schliess, Freimut, additional, Gieger, Christian, additional, Adamski, Jerzy, additional, Hrabe de Angelis, Martin, additional, Peters, Annette, additional, and Wang-Sattler, Rui, additional

Published
2020
Full Text
View/download PDF

44. Human gene expression sensitivity according to large scale meta-analysis

Author

Tu Kang, Ping Jie, Zheng Siyuan, Hao Pei, Gieger Christian, Wang-Sattler Rui, Zhong Yang, and Li Yixue

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
Abstract

Abstract Background Genes show different sensitivities in expression corresponding to various biological conditions. Systematical study of this concept is required because of its important implications in microarray analysis etc. J.H. Ohn et al. first studied this gene property with yeast transcriptional profiling data. Results Here we propose a calculation framework for gene expression sensitivity analysis. We also compared the functions, centralities and transcriptional regulations of the sensitive and robust genes. We found that the robust genes tended to be involved in essential cellular processes. Oppositely, the sensitive genes perform their functions diversely. Moreover while genes from both groups show similar geometric centrality by coupling them onto integrated protein networks, the robust genes have higher vertex degree and betweenness than that of the sensitive genes. An interesting fact was also found that, not alike the sensitive genes, the robust genes shared less transcription factors as their regulators. Conclusion Our study reveals different propensities of gene expression to external perturbations, demonstrates different roles of sensitive genes and robust genes in the cell and proposes the necessity of combining the gene expression sensitivity in the microarray analysis.

Published
2009
Full Text
View/download PDF

47. Circulating Metabolites Differentiate Acute Ischemic Stroke from Stroke Mimics.

Author

Tiedt, Steffen, Brandmaier, Stefan, Kollmeier, Hanna, Duering, Marco, Artati, Anna, Adamski, Jerzy, Klein, Matthias, Liebig, Thomas, Holdt, Lesca M., Teupser, Daniel, Wang‐Sattler, Rui, Schwedhelm, Edzard, Gieger, Christian, Dichgans, Martin, and Wang-Sattler, Rui

Subjects
METABOLITES, PROPENSITY score matching, MAGNETIC resonance imaging, SYMPTOMS, COMPUTED tomography
Abstract

Objective: Early discrimination of patients with ischemic stroke (IS) from stroke mimics (SMs) poses a diagnostic challenge. The circulating metabolome might reflect pathophysiological events related to acute IS. Here, we investigated the utility of early metabolic changes for differentiating IS from SM.Methods: We performed untargeted metabolomics on serum samples obtained from patients with IS (N = 508) and SM (N = 349; defined by absence of a diffusion weighted imaging [DWI] positive lesion on magnetic resonance imaging [MRI]) who presented to the hospital within 24 hours after symptom onset (median time from symptom onset to blood sampling = 3.3 hours; interquartile range [IQR] = 1.6-6.7 hours) and from neurologically normal controls (NCs; N = 112). We compared diagnostic groups in a discovery-validation approach by applying multivariable linear regression models, machine learning techniques, and propensity score matching. We further performed a targeted look-up of published metabolite sets.Results: Levels of 41 metabolites were significantly associated with IS compared to NCs. The top metabolites showing the highest value in separating IS from SMs were asymmetrical and symmetrical dimethylarginine, pregnenolone sulfate, and adenosine. Together, these 4 metabolites differentiated patients with IS from SMs with an area under the curve (AUC) of 0.90 in the replication sample, which was superior to multimodal cranial computed tomography (CT; AUC = 0.80) obtained for routine diagnostics. They were further superior to previously published metabolite sets detected in our samples. All 4 metabolites returned to control levels by day 90.Interpretation: A set of 4 metabolites with known biological effects relevant to stroke pathophysiology shows unprecedented utility to identify patients with IS upon hospital arrival, thus encouraging further investigation, including multicenter studies. ANN NEUROL 2020;88:736-746. [ABSTRACT FROM AUTHOR]

Published
2020
Full Text
View/download PDF

48. Human serum metabolic profiles are age dependent

Author

Yu, Zhonghao, Zhai, Guangju, Singmann, Paula, He, Ying, Xu, Tao, Prehn, Cornelia, Römisch-Margl, Werner, Lattka, Eva, Gieger, Christian, Soranzo, Nicole, Heinrich, Joachim, Standl, Marie, Thiering, Elisabeth, Mittelstra, Kirstin, Wichmann, Heinz-Erich, Peters, Annette, Suhre, Karsten, Li, Yixue, Adamski, Jerzy, Spector, Tim D., Illig, Thomas, and Wang-Sattler, Rui

Published
2012
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results