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¹H NMR: Complex Splitting01:13

¹H NMR: Complex Splitting

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A proton M that is coupled to a proton X results in doublet signals for M. However, NMR-active nuclei can be simultaneously coupled to more than one nonequivalent nucleus. When M is coupled to a second proton A, such as in styrene oxide, each peak in the doublet is split into another doublet.
Splitting diagrams or splitting tree diagrams are routinely used to depict such complex couplings. While drawing splitting diagrams, the splitting with the larger coupling constant is usually applied...
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High-Resolution Mass Spectrometry (HRMS)01:15

High-Resolution Mass Spectrometry (HRMS)

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The resolution of a mass spectrometer depends on the efficiency of separating ions with different ion masses. The mass of an atom is approximated to the sum of the masses of protons and neutrons inside, considering the masses of protons and neutrons as equal. However, the masses of the proton (1.6726 × 10−24 g) and neutron (1.6749 × 10−24 g) are not truly equal. There is a minor error in the expression of atomic masses relative to the simplest atom of hydrogen. For...
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Experimental Determination of Chemical Formula02:37

Experimental Determination of Chemical Formula

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The elemental makeup of a compound defines its chemical identity, and chemical formulas are the most concise way of representing this elemental makeup. When a compound’s formula is unknown, measuring the mass of its constituent elements is often the first step in determining the formula experimentally.
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2D NMR: Heteronuclear Single-Quantum Correlation Spectroscopy (HSQC)01:19

2D NMR: Heteronuclear Single-Quantum Correlation Spectroscopy (HSQC)

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Heteronuclear single-quantum correlation spectroscopy (HSQC) is a 2D NMR technique that reveals one-bond correlations between hydrogen and a heteronucleus. The HSQC experiment is similar to the heteronuclear correlation experiment (HETCOR) but is more sensitive. In the HSQC spectrum, the proton chemical shift is plotted on the horizontal F2 axis, while the 13C chemical shift is plotted on the vertical F1 axis. The corresponding proton and 13C spectra are also shown. The HSQC contour plot does...
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Interpreting ¹H NMR Signal Splitting: The (n + 1) Rule01:10

Interpreting ¹H NMR Signal Splitting: The (n + 1) Rule

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In the AX proton spin system, proton A can sense the two spin states of a coupled proton X, resulting in a doublet NMR signal with two peaks of equal (1:1) intensity. When proton A is coupled to two equivalent protons (AX2 spin system), the spin states of each X can be aligned with or against the external field, creating three possible scenarios. This results in a 1:2:1  triplet signal, where the central peak corresponds to the chemical shift of A and is twice as large or intense as the...
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Mass Spectrum: Interpretation01:24

Mass Spectrum: Interpretation

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An unknown compound can be established by identifying the molecular ion peak in the mass spectrum. The molecular ion peak is often weak or absent due to the predominance of fragmentation in high-energy electron beams. In such cases, a low-energy electron beam can be used to scan the spectrum to enhance the intensity of the molecular ion peak. Additionally, chemical ionization, field ionization, and desorption ionization spectra are used to obtain a relatively intense molecular ion peak.
To...
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A data-driven algorithm to determine 1H-MRS basis set composition.

Christopher W Davies-Jenkins1, Helge J Zöllner1, Dunja Simicic1

  • 1The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Biorxiv : the Preprint Server for Biology
|September 24, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a novel data-driven method using Bayesian Information Criteria (BIC) to determine the optimal basis set for Magnetic Resonance Spectroscopy (MRS). This approach improves the reproducibility and objectivity of metabolite quantification in clinical settings.

Keywords:
2HGCystathioninebasis setinformation criteriamagnetic resonance spectroscopymodel selection

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Area of Science:

  • Neuroimaging
  • Biophysics
  • Computational Biology

Background:

  • Quantitative analysis of Magnetic Resonance Spectroscopy (MRS) data relies on accurate metabolite basis sets for modeling.
  • Current lack of consensus on ideal basis set composition hinders reproducibility in MRS studies.
  • Operator bias and subjective criteria contribute to variability in MRS data analysis.

Purpose of the Study:

  • To develop and validate a novel, data-driven approach for selecting Magnetic Resonance Spectroscopy (MRS) basis sets.
  • To utilize Bayesian Information Criteria (BIC) for objective basis set composition determination.
  • To enhance the reproducibility and objectivity of quantitative MRS analyses.

Main Methods:

  • An iterative algorithm was developed to build basis sets, guided by BIC scores.
  • Two stopping conditions (max-BIC and zero-amplitude) were investigated for algorithm termination.
  • Basis set selection was evaluated at both single-spectrum and group levels using synthetic brain and tumor spectra.

Main Results:

  • Derived basis sets accurately identified high-concentration metabolites and provided good spectral fits.
  • Single-spectrum basis set determination achieved 77-87% accuracy.
  • Group-level optimization improved basis set determination accuracy to 84-92%.

Conclusions:

  • Data-driven basis set determination for MRS is feasible and effective.
  • This approach has the potential to reduce operator bias and increase objectivity in MRS.
  • Refinement of this method could significantly enhance the clinical utility of MRS.