2010
DOI: 10.1016/j.jmr.2009.09.021
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Quantitative two-dimensional HSQC experiment for high magnetic field NMR spectrometers

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Cited by 50 publications
(44 citation statements)
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“…For example the finite RF power available on the carbon channel in proton-carbon correlation experiments leads to non-uniform excitation of carbon resonances across the spectrum, although this is somewhat ameliorated by using adiabatic-pulse experiments [26]. If the experiment permits longer acquisition times, a range of quantitative 2D HSQC experiments [27,28] have been developed to mitigate this artifact.…”
Section: Discussionmentioning
confidence: 99%
“…For example the finite RF power available on the carbon channel in proton-carbon correlation experiments leads to non-uniform excitation of carbon resonances across the spectrum, although this is somewhat ameliorated by using adiabatic-pulse experiments [26]. If the experiment permits longer acquisition times, a range of quantitative 2D HSQC experiments [27,28] have been developed to mitigate this artifact.…”
Section: Discussionmentioning
confidence: 99%
“…A high analytical performance was demonstrated for the homo-nuclear INADEQUATE pulse sequence (Fig. Adapted from Koskela et al (2010). was essentially attributed to a much cleaner diagonal in the case of INADEQUATE. The high degree of precision reached by this technique Figure 3.10 NMR spectra from a human blood plasma sample: (A) 1 H NMR spectrum, (B) expansions of Q-OCCAHSQC spectrum.…”
Section: Applications For Metabolic Studiesmentioning
confidence: 99%
“…The fundamental problem with the use of such two-dimensional approaches is that the biggest advantage of qNMR, its uniformity of response across analytes, is lost, and care must be taken to minimize these deviations and account for them in the uncertainty budget. Such bias can arise from factors including T 1 and T 2 relaxation during the pulse sequence, nonuniform magnetization transfer due to variation in 1 J CH (Koskela et al, 2005(Koskela et al, , 2010, and nonuniform excitation in the second dimension (Webb, 2008). Approaches such as time zero HSQC (HSQC 0 ) have been applied to reduce such biases (Hu et al, 2011).…”
Section: Quantification With a Two-dimensional Approachmentioning
confidence: 99%