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We foresee the primary applications of ITOCSY to be metabolic flux analysis, isotope dilution, and metabolite quantification using standards produced in vivo.
Methylene diphosphonic acid (2 mmol l−1) in a sealed capillary was used as chemical shift reference (18.6 p.p.m ., and as an external standard for metabolite quantification using P-NMR.
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We compared the number of VOCs identified, the classes of compounds identified and the variability in metabolite quantification when using each treatment.
Multivariate partial least squares discriminant analysis (PLS-DA) modeling and relative metabolite quantification were used to analyze the MR data.
As the first step towards technical qualification, different measures for accuracy of metabolite quantification were calculated using a set of 100 synthetic samples spiked with four selected metabolites: citrate, lactate, glucose, and creatinine in concentrations ranging from 10 to 10,000 μg/mL.
To apply the method to data sets more representative of conditions encountered in biological fluids, but still with definitive quantitative predictions to test, we applied the FMLR method to the analysis of data from our earlier study using fast metabolite quantification (FMQ).
The software package LCModel (Provencher, 1993, 2001) was used for metabolite quantification (Supporting Information Fig. S1).
This clearly indicates that H NMR quantification is suitable for routine measurements in (rat) urine, which is in agreement with investigations of Slupsky et al. showing that H NMR spectroscopy can be used for metabolite quantification in human urine, when algorithms are selected properly [ 17].
An external reference, trimethylsilyl propionic-2,2,3,3,-d4 acid (TMSP, 0.5 mmol/l for hydrophilic and 1.2 mmol/l for lipid extracts), was used for metabolite quantification of fully relaxed H-MRS spectra and as a H chemical shift reference (0 ppm).
Relative metabolite quantification was performed by peak integration using mean normalized spectra after removal of water, lipids and contaminations.
Using high-throughput metabolite quantification, we have demonstrated metabolic signatures of insulin resistance in young adults beyond the traditional characteristics of the metabolic syndrome (6).
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