The publication data currently available has been vetted by Vanderbilt faculty, staff, administrators and trainees. The data itself is retrieved directly from NCBI's PubMed and is automatically updated on a weekly basis to ensure accuracy and completeness.
If you have any questions or comments, please contact us.
Selective inversion recovery (SIR) is a quantitative magnetization transfer (qMT) method that provides estimates of parameters related to myelin content in white matter, namely the macromolecular pool-size-ratio (PSR) and the spin-lattice relaxation rate of the free pool (R), without the need for independent estimates of ∆B, B, and T. Although the feasibility of performing SIR in the human brain has been demonstrated, the scan times reported previously were too long for whole-brain applications. In this work, we combined optimized, short-TR acquisitions, SENSE/partial-Fourier accelerations, and efficient 3D readouts (turbo spin-echo, SIR-TSE; echo-planar imaging, SIR-EPI; and turbo field echo, SIR-TFE) to obtain whole-brain data in 18, 10, and 7 min for SIR-TSE, SIR-EPI, SIR-TFE, respectively. Based on numerical simulations, all schemes provided accurate parameter estimates in large, homogenous regions; however, the shorter SIR-TFE scans underestimated focal changes in smaller lesions due to blurring. Experimental studies in healthy subjects (n = 8) yielded parameters that were consistent with literature values and repeatable across scans (coefficient of variation: PSR = 2.2-6.4%, R = 0.6-1.4%) for all readouts. Overall, SIR-TFE parameters exhibited the lowest variability, while SIR-EPI parameters were adversely affected by susceptibility-related image distortions. In patients with relapsing remitting multiple sclerosis (n = 2), focal changes in SIR parameters were observed in lesions using all three readouts; however, contrast was reduced in smaller lesions for SIR-TFE, which was consistent with the numerical simulations. Together, these findings demonstrate that efficient, accurate, and repeatable whole-brain SIR can be performed using 3D TFE, EPI, or TSE readouts; however, the appropriate readout should be tailored to the application.
Copyright © 2020 Elsevier Inc. All rights reserved.
In the course of investigations of the kinetics of individual reactions of cytochrome P450 (P450) enzymes, a number of points about the complexity of P450 enzyme kinetics have become apparent. Several of these are of particular relevance to work with P450 enzymes in the course of drug development and lead optimization, particularly with regard to estimating in vitro kinetic parameters and dealing with enzyme inhibitors. Modern simulation modeling has been applied to situations involving issues of preincubation time with moderate strength and strong inhibitors, inhibition by tightly bound ligands that have been identified in P450 enzymes, extensive substrate depletion, P450 reactions with a rate-limiting step after product formation, and the consumption of an inhibitor during a reaction by either a P450 enzyme being monitored or another one in a mixture. The results all follow from first principles, and simulations reveal the extent of their significance in various settings. The order of addition of substrate and inhibitors can change the apparent outcome (inhibition constant, ), and the effect of the order is more pronounced with a stronger inhibitor. Substrate depletion alters parameters (Michaelis constant, ) and can generate apparently sigmoidal plots. A rate-limiting step after product formation lowers the apparent and distorts Consumption of an inhibitor during a reaction affects and differs depending on which enzyme is involved. The results are relevant with P450 enzymes and other enzymes as well. SIGNIFICANCE STATEMENT: Kinetic simulations have been used to address several potential problems in enzyme kinetic analysis. Although the simulations done here are general for enzyme reactions, several problems addressed here are particularly relevant to cytochrome P450 reactions encountered in drug development work.
Copyright © 2019 by The American Society for Pharmacology and Experimental Therapeutics.
Background α Carboxyl terminus 1 (αCT1) is a 25-amino acid therapeutic peptide incorporating the zonula occludens-1 (ZO-1)-binding domain of connexin 43 (Cx43) that is currently in phase 3 clinical testing on chronic wounds. In mice, we reported that αCT1 reduced arrhythmias after cardiac injury, accompanied by increases in protein kinase Cε phosphorylation of Cx43 at serine 368. Herein, we characterize detailed molecular mode of action of αCT1 in mitigating cardiac ischemia-reperfusion injury. Methods and Results To study αCT1-mediated increases in phosphorylation of Cx43 at serine 368, we undertook mass spectrometry of protein kinase Cε phosphorylation assay reactants. This indicated potential interaction between negatively charged residues in the αCT1 Asp-Asp-Leu-Glu-Iso sequence and lysines (Lys345, Lys346) in an α-helical sequence (helix 2) within the Cx43-CT. In silico modeling provided further support for this interaction, indicating that αCT1 may interact with both Cx43 and ZO-1. Using surface plasmon resonance, thermal shift, and phosphorylation assays, we characterized a series of αCT1 variants, identifying peptides that interacted with either ZO-1-postsynaptic density-95/disks large/zonula occludens-1 2 or Cx43-CT, but with limited or no ability to bind both molecules. Only peptides competent to interact with Cx43-CT, but not ZO-1-postsynaptic density-95/disks large/zonula occludens-1 2 alone, prompted increased pS368 phosphorylation. Moreover, in an ex vivo mouse model of ischemia-reperfusion injury, preischemic infusion only with those peptides competent to bind Cx43 preserved ventricular function after ischemia-reperfusion. Interestingly, a short 9-amino acid variant of αCT1 (αCT11) demonstrated potent cardioprotective effects when infused either before or after ischemic injury. Conclusions Interaction of αCT1 with the Cx43, but not ZO-1, is correlated with cardioprotection. Pharmacophores targeting Cx43-CT could provide a translational approach to preserving heart function after ischemic injury.
Neuroimaging often involves acquiring high-resolution anatomical images along with other low-resolution image modalities, like diffusion and functional magnetic resonance imaging. Performing gray matter statistics with low-resolution image modalities is a challenge due to registration artifacts and partial volume effects. Gray matter surface based spatial statistics (GS-BSS) has been shown to provide higher sensitivity using gray matter surfaces compared to that of skeletonization approach of gray matter based spatial statistics which is adapted from tract based spatial statistics in diffusion studies. In this study, we improve upon GS-BSS incorporating neurite orientation dispersion and density imaging (NODDI) based search (denoted N-GSBSS) by 1) enhancing metrics mapping from native space, 2) incorporating maximum orientation dispersion index (ODI) search along surface normal, and 3) proposing applicability to other modalities, such as functional MRI (fMRI). We evaluated the performance of N-GSBSS against three baseline pipelines: volume-based registration, FreeSurfer's surface registration and ciftify pipeline for fMRI and simulation studies. First, qualitative mean ODI results are shown for N-GSBSS with and without NODDI based search in comparison with ciftify pipeline. Second, we conducted one-sample t-tests on working memory activations in fMRI to show that the proposed method can aid in the analysis of low resolution fMRI data. Finally we performed a sensitivity test in a simulation study by varying percentage change of intensity values within a region of interest in gray matter probability maps. N-GSBSS showed higher sensitivity in the simulation test compared to the other methods capturing difference between the groups starting at 10% change in the intensity values. The computational time of N-GSBSS is 68 times faster than that of traditional surface-based or 86 times faster than that of ciftify pipeline analysis.
Copyright © 2019 Elsevier Inc. All rights reserved.
PURPOSE - MR fingerprinting (MRF) sequences permit efficient T and T estimation in cranial and extracranial regions, but these areas may include substantial fat signals that bias T and T estimates. MRI fat signal fraction estimation is also a topic of active research in itself, but may be complicated by B heterogeneity and blurring during spiral k-space acquisitions, which are commonly used for MRF. An MRF method is proposed that separates fat and water signals, estimates water T and T, and accounts for B effects with spiral blurring correction, in a single sequence.
THEORY AND METHODS - A k-space-based fat-water separation method is further extended to unbalanced steady-state free precession MRF with swept echo time. Repeated application of this k-space fat-water separation to demodulated forms of the measured data allows a B map and correction to be approximated. The method is compared with MRF without fat separation across a broad range of fat signal fractions (FSFs), water Ts and Ts, and under heterogeneous static fields in simulations, phantoms, and in vivo.
RESULTS - The proposed method's FSF estimates had a concordance correlation coefficient of 0.990 with conventional measurements, and reduced biases in the T and T estimates due to fat signal relative to other MRF sequences by several hundred ms. The B correction improved the FSF, T, and T estimation compared to those estimates without correction.
CONCLUSION - The proposed method improves MRF water T and T estimation in the presence of fat and provides accurate FSF estimation with inline B correction.
Copyright © 2019 Elsevier Inc. All rights reserved.
OBJECTIVES - Bilateral vocal fold immobility (BVFI) is a rare and life-threatening condition in which both vocal folds are fixed, resulting in airway obstruction associated with life-threatening respiratory compromise. Treatment of BVFI is largely surgical and remains an unsatisfactory compromise between voice, breathing, and swallowing. No comparisons between currently employed techniques currently exist. We sought to employ computational fluid dynamics (CFD) modeling to delineate the optimal surgical approach for BVFI.
METHODS - Utilizing clinical computed tomography of BVFI subjects, coupled with image analytics employing CFD models and subject pulmonary function data, we compared the airflow features in the baseline pathologic states and changes seen between endoscopic cordotomy, endoscopic suture lateralization, and posterior cricoid expansion.
RESULTS - CFD modeling demonstrated that the greatest airflow velocity occurs through the posterior glottis on inspiration and anterior glottis on expiration in both the normal condition and in BVFI. Glottic airflow velocity and resistance were significantly higher in the BVFI condition compared to normal. Geometric indices (cross-sectional area of airway) were lower in posterior cricoid expansion surgery when compared to alternate surgical approaches. CFD measures (airflow velocity and resistance) improved with all surgical approaches but were superior with posterior cricoid expansion.
CONCLUSION - CFD modeling can provide discrete, quantitative assessment of the airflow through the laryngeal inlet, and offers insights into the pathophysiology and changes that occur after surgery for BVFI.
LEVEL OF EVIDENCE - NA. Laryngoscope, 130:E57-E64, 2020.
© 2019 The American Laryngological, Rhinological and Otological Society, Inc.
PURPOSE - Multi-exponential relaxometry is a powerful tool for characterizing tissue, but generally requires high image signal-to-noise ratio (SNR). This work evaluates the use of principal-component-analysis (PCA) denoising to mitigate these SNR demands and improve the precision of relaxometry measures.
METHODS - PCA denoising was evaluated using both simulated and experimental MRI data. Bi-exponential transverse relaxation signals were simulated for a wide range of acquisition and sample parameters, and experimental data were acquired from three excised and fixed mouse brains. In both cases, standard relaxometry analysis was performed on both original and denoised image data, and resulting estimated signal parameters were compared.
RESULTS - Denoising reduced the root-mean-square-error of parameters estimated from multi-exponential relaxometry by factors of ≈3×, for typical acquisition and sample parameters. Denoised images and subsequent parameter maps showed little or no signs of spatial artifact or loss of resolution.
CONCLUSION - Experimental studies and simulations demonstrate that PCA denoising of MRI relaxometry data is an effective method of improving parameter precision without sacrificing image resolution. This simple yet important processing step thus paves the way for broader applicability of multi-exponential MRI relaxometry.
© 2019 International Society for Magnetic Resonance in Medicine.
Conventional radiation therapy of brain tumors often produces cognitive deficits, particularly in children. We investigated the potential efficacy of merging Orthovoltage X-ray Minibeams (OXM). It segments the beam into an array of parallel, thin (~0.3 mm), planar beams, called minibeams, which are known from synchrotron x-ray experiments to spare tissues. Furthermore, the slight divergence of the OXM array make the individual minibeams gradually broaden, thus merging with their neighbors at a given tissue depth to produce a solid beam. In this way the proximal tissues, including the cerebral cortex, can be spared. Here we present experimental results with radiochromic films to characterize the method's dosimetry. Furthermore, we present our Monte Carlo simulation results for physical absorbed dose, and a first-order biologic model to predict tissue tolerance. In particular, a 220-kVp orthovoltage beam provides a 5-fold sharper lateral penumbra than a 6-MV x-ray beam. The method can be implemented in arc-scan, which may include volumetric-modulated arc therapy (VMAT). Finally, OXM's low beam energy makes it ideal for tumor-dose enhancement with contrast agents such as iodine or gold nanoparticles, and its low cost, portability, and small room-shielding requirements make it ideal for use in the low-and-middle-income countries.
Single-cell RNA sequencing (scRNA-seq) has become a powerful tool for the systematic investigation of cellular diversity. As a number of computational tools have been developed to identify and visualize cell populations within a single scRNA-seq dataset, there is a need for methods to quantitatively and statistically define proportional shifts in cell population structures across datasets, such as expansion or shrinkage or emergence or disappearance of cell populations. Here we present sc-UniFrac, a framework to statistically quantify compositional diversity in cell populations between single-cell transcriptome landscapes. sc-UniFrac enables sensitive and robust quantification in simulated and experimental datasets in terms of both population identity and quantity. We have demonstrated the utility of sc-UniFrac in multiple applications, including assessment of biological and technical replicates, classification of tissue phenotypes and regional specification, identification and definition of altered cell infiltrates in tumorigenesis, and benchmarking batch-correction tools. sc-UniFrac provides a framework for quantifying diversity or alterations in cell populations across conditions and has broad utility for gaining insight into tissue-level perturbations at the single-cell resolution.
Arrays of radiofrequency coils are widely used in magnetic resonance imaging to achieve high signal-to-noise ratios and flexible volume coverage, to accelerate scans using parallel reception, and to mitigate field non-uniformity using parallel transmission. However, conventional coil arrays require complex decoupling technologies to reduce electromagnetic coupling between coil elements, which would otherwise amplify noise and limit transmitted power. Here we report a novel self-decoupled RF coil design with a simple structure that requires only an intentional redistribution of electrical impedances around the length of the coil loop. We show that self-decoupled coils achieve high inter-coil isolation between adjacent and non-adjacent elements of loop arrays and mixed arrays of loops and dipoles. Self-decoupled coils are also robust to coil separation, making them attractive for size-adjustable and flexible coil arrays.