Towards a Fitting Model of Macromolecular Spectra: Amino Acids

Borbath, T; Murali Manohar, S; Henning, A

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Meeting Abstract

Towards a Fitting Model of Macromolecular Spectra: Amino Acids

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Borbath, T
Research Group MR Spectroscopy and Ultra-High Field Methodology, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Murali Manohar, S
Research Group MR Spectroscopy and Ultra-High Field Methodology, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Henning, A
Research Group MR Spectroscopy and Ultra-High Field Methodology, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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http://indexsmart.mirasmart.com/ISMRM2019/PDFfiles/1068.html
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Citation

Borbath, T., Murali Manohar, S., & Henning, A. (2019). Towards a Fitting Model of Macromolecular Spectra: Amino Acids. In ISMRM 27th Annual Meeting & Exhibition.

Cite as: https://hdl.handle.net/21.11116/0000-0003-96C4-6

Abstract

Broad signals underlying in vivo 1H MRS spectra are referred to in literature as macromolecules, and have been assigned to amino acids by Behar et al. These amino acids are creating proteins through chemical bonds. Depending on the protein structure and sequence of amino acids, they have different chemical shifts as published in protein NMR databases. This work uses these published chemical shifts to create a fitting model for the macromolecular baselines of human brain using amino acids.