A reconstruction framework for the separation of signal from pyruvate and its downstream metabolites is shown. This reconstruction eliminates the need to acquire additional calibration FID acquisition and allows acceleration through compressed sensing.
A kinetic model is provided to obtain reaction rate constants in successive enzymatic reactions that are monitored using NMR spectroscopy and hyperpolarized substrates. The model was applied for simulation and analysis of the successive oxidation of choline to betaine aldehyde, and further to betaine, by the enzyme choline oxidase. This enzymatic reaction was investigated under two different sets of conditions: two different choline molecular probes were used, [1,1,2,2-D4 , 1-(13) C]choline chloride and [1,1,2,2-D4 , 2-(13) C]choline chloride, in different MR systems (clinical scanner and high-resolution spectrometer), as well as in different reactors and reaction volumes (4.8 and 0.7 mL). The kinetic analysis according to the model yielded similar results in both set-ups, supporting the robustness of the model. This was achieved despite the complex and negating influences of reaction kinetics and polarization decay, and in the presence of uncontrolled mixing characteristics, which may introduce uncertainties in both effective timing and effective pulses. The ability to quantify rate constants using hyperpolarized MR in the first seconds of consecutive enzyme activity is important for further development of the utilization of dynamic nuclear polarization-MR for biological determinations.
T1 bias correction of large flip angle acquisitions using estimated T1 values with flip angle mapping yields fat fraction measurements of similar accuracy and superior precision compared to low flip angle acquisitions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.