The molecular structures, electron affinities, and dissociation energies of the Si(5)H(n)/Si(5)H(n)(-) (n = 3-12) species have been calculated by means of three density functional theory (DFT) methods. The basis set used in this work is of double-zeta plus polarization quality with additional diffuse s- and p-type functions, denoted DZP++. The geometries are fully optimized with each DFT method independently. Three different types of the neutral-anion energy separations presented in this work are the adiabatic electron affinity (EA(ad)), the vertical electron affinity (EA(vert)), and the vertical detachment energy (VDE). The first Si-H dissociation energies for neutral Si(5)H(n) and its anion have also been reported.
Purpose: To determine whether dynamic contrastenhanced magnetic resonance imaging (DCE-MRI) could monitor progression of liver fibrosis in a piglet model, and which DCE-MRI parameter is most accurate for staging this disease.
Materials and Methods:Sixteen piglets were prospectively used to model liver fibrosis and underwent liver DCE-MRI followed by biopsy on the 0, 5th, 9th, 16th, and 21st weekends after modeling of fibrosis. Time of peak (TOP), time to peak (TTP), positive enhancement integral (PEI), maximum slope of increase (MSI), and maximum slope of decrease (MSD) were measured and statistically analyzed for the monitoring and staging.Results: As fibrosis progresses, TOP and TTP tended to increase, whereas MSI, MSD, and PEI tended to decrease (all P < 0.05). TOP, TTP, and MSI could discriminate fibrosis stage 0 from 1-4, 0-1 from 2-4, 0-2 from 3-4, and 0-3 from 4; PEI could distinguish the above-mentioned stages except 0-3 from 4; and MSD could distinguish stage 0-3 from 4, and 0 from 1-4 (all P < 0.05). For predicting stage !1, !2, and !3, the area under receiver operating characteristic curve (AUC) of MSI was largest among all parameters; for stage 4 AUC of TTP was largest.Conclusion: DCE-MRI has the potential to dynamically stage progression of liver fibrosis.
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.