Open Access. Powered by Scholars. Published by Universities.®
- Discipline
Articles 1 - 2 of 2
Full-Text Articles in Internal Medicine
Integrated Multilayer Omics Reveals The Genomic, Proteomic, And Metabolic Influences Of Histidyl Dipeptides On The Heart, Keqiang Yan, Zhanlong Mei, Jingjing Zhao, Md Aminul Islam Prodhan, Detlef Obal, Kartik Katragadda, Benjamin Doelling, David Hoetker, Dheeraj Kumar Posa
Integrated Multilayer Omics Reveals The Genomic, Proteomic, And Metabolic Influences Of Histidyl Dipeptides On The Heart, Keqiang Yan, Zhanlong Mei, Jingjing Zhao, Md Aminul Islam Prodhan, Detlef Obal, Kartik Katragadda, Benjamin Doelling, David Hoetker, Dheeraj Kumar Posa
Internal Medicine, East Africa
Background: Histidyl dipeptides such as carnosine are present in a micromolar to millimolar range in mammalian hearts. These dipeptides facilitate glycolysis by proton buffering. They form conjugates with reactive aldehydes, such as acrolein, and attenuate myocardial ischemia-reperfusion injury. Although these dipeptides exhibit multifunctional properties, a composite understanding of their role in the myocardium is lacking.
Methods and Results: To identify histidyl dipeptide-mediated responses in the heart, we used an integrated triomics approach, which involved genome-wide RNA sequencing, global proteomics, and unbiased metabolomics to identify the effects of cardiospecific transgenic overexpression of the carnosine synthesizing enzyme, carnosine synthase (Carns), in …
Bayesmetab: Treatment Of Missing Values In Metabolomic Studies Using A Bayesian Modeling Approach, Jasmit Shah, Guy N. Brock, Jeremy Gaskins
Bayesmetab: Treatment Of Missing Values In Metabolomic Studies Using A Bayesian Modeling Approach, Jasmit Shah, Guy N. Brock, Jeremy Gaskins
Internal Medicine, East Africa
Background: With the rise of metabolomics, the development of methods to address analytical challenges in the analysis of metabolomics data is of great importance. Missing values (MVs) are pervasive, yet the treatment of MVs can have a substantial impact on downstream statistical analyses. The MVs problem in metabolomics is quite challenging and can arise because the metabolite is not biologically present in the sample, or is present in the sample but at a concentration below the lower limit of detection (LOD), or is present in the sample but undetected due to technical issues related to sample pre-processing steps. The …