Browsing by Author "You, Jinsam"

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    An integrated clinico-metabolomic model improves prediction of death in sepsis
    (American Association for the Advancement of Science, 2013) Langley, Raymond J.; Tsalik, Ephraim L.; van Velkinburgh, Jennifer C.; Glickman, Seth W.; Rice, Brandon J.; Wang, Chunping; Chen, Bo; Carin, Lawrence; Suarez, Arturo; Mohney, Robert P.; Freeman, Debra H.; Wang, Mu; You, Jinsam; Wulff, Jacob; Thompson, J. Will; Moseley, M. Arthur; Reisinger, Stephanie; Edmonds, Brian T.; Grinnell, Brian; Nelson, David R.; Dinwiddie, Darrell L.; Miller, Neil A.; Saunders, Carol J.; Soden, Sarah S.; Rogers, Angela J.; Gazourian, Lee; Fredenburgh, Laura E.; Massaro, Anthony F.; Baron, Rebecca M.; Choi, Augustine M. K.; Corey, G. Ralph; Ginsburg, Geoffrey S.; Cairns, Charles B.; Otero, Ronny M.; Fowler, Vance G., Jr.; Rivers, Emanuel P.; Woods, Christopher W.; Kingsmore, Stephen F.; Medicine, School of Medicine
    Sepsis is a common cause of death, but outcomes in individual patients are difficult to predict. Elucidating the molecular processes that differ between sepsis patients who survive and those who die may permit more appropriate treatments to be deployed. We examined the clinical features and the plasma metabolome and proteome of patients with and without community-acquired sepsis, upon their arrival at hospital emergency departments and 24 hours later. The metabolomes and proteomes of patients at hospital admittance who would ultimately die differed markedly from those of patients who would survive. The different profiles of proteins and metabolites clustered into the following groups: fatty acid transport and β-oxidation, gluconeogenesis, and the citric acid cycle. They differed consistently among several sets of patients, and diverged more as death approached. In contrast, the metabolomes and proteomes of surviving patients with mild sepsis did not differ from survivors with severe sepsis or septic shock. An algorithm derived from clinical features together with measurements of five metabolites predicted patient survival. This algorithm may help to guide the treatment of individual patients with sepsis.
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    Protein Target Quantification Decision Tree
    (Hindawi, 2013) Kim, Jong Won; You, Jinsam; Biochemistry and Molecular Biology, School of Medicine
    The utility of mass spectrometry-(MS-) based proteomic platforms and their clinical applications have become an emerging field in proteomics in recent years. Owing to its selectivity and sensitivity, MS has become a key technological platform in proteomic research. Using this platform, a large number of potential biomarker candidates for specific diseases have been reported. However, due to lack of validation, none has been approved for use in clinical settings by the Food and Drug Administration (FDA). Successful candidate verification and validation will facilitate the development of potential biomarkers, leading to better strategies for disease diagnostics, prognostics, and treatment. With the recent new developments in mass spectrometers, high sensitivity, high resolution, and high mass accuracy can be achieved. This greatly enhances the capabilities of protein biomarker validation. In this paper, we describe and discuss recent developments and applications of targeted proteomics methods for biomarker validation.
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    Quantification of cellular NEMO content and its impact on NF-κB activation by genotoxic stress
    (PLoS, 2015-03-05) Hwang, Byounghoon; Phan, Funita P.; McCool, Kevin; Choi, Eun Young; You, Jinsam; Johnson, Adam; Audhya, Anjon; Miyamoto, Shigeki; Department of Biochemistry and Molecular Biology, IU School of Medicine
    NF-κB essential modulator, NEMO, plays a key role in canonical NF-κB signaling induced by a variety of stimuli, including cytokines and genotoxic agents. To dissect the different biochemical and functional roles of NEMO in NF-κB signaling, various mutant forms of NEMO have been previously analyzed. However, transient or stable overexpression of wild-type NEMO can significantly inhibit NF-κB activation, thereby confounding the analysis of NEMO mutant phenotypes. What levels of NEMO overexpression lead to such an artifact and what levels are tolerated with no significant impact on NEMO function in NF-κB activation are currently unknown. Here we purified full-length recombinant human NEMO protein and used it as a standard to quantify the average number of NEMO molecules per cell in a 1.3E2 NEMO-deficient murine pre-B cell clone stably reconstituted with full-length human NEMO (C5). We determined that the C5 cell clone has an average of 4 x 10(5) molecules of NEMO per cell. Stable reconstitution of 1.3E2 cells with different numbers of NEMO molecules per cell has demonstrated that a 10-fold range of NEMO expression (0.6-6x10(5) molecules per cell) yields statistically equivalent NF-κB activation in response to the DNA damaging agent etoposide. Using the C5 cell line, we also quantified the number of NEMO molecules per cell in several commonly employed human cell lines. These results establish baseline numbers of endogenous NEMO per cell and highlight surprisingly normal functionality of NEMO in the DNA damage pathway over a wide range of expression levels that can provide a guideline for future NEMO reconstitution studies.