A Bayesian model for highly accelerated phase-contrast MRI.

PURPOSE: Phase-contrast magnetic resonance imaging is a noninvasive tool to assess cardiovascular disease by quantifying blood flow; however, low data acquisition efficiency limits the spatial and temporal resolutions, real-time application, and extensions to four-dimensional flow imaging in clinical settings. We propose a new data processing approach called Reconstructing Velocity Encoded MRI with Approximate message passing aLgorithms (ReVEAL) that accelerates the acquisition by exploiting data structure unique to phase-contrast magnetic resonance imaging. THEORY AND METHODS: The proposed approach models physical correlations across space, time, and velocity encodings. The proposed Bayesian approach exploits the relationships in both magnitude and phase among velocity encodings. A fast iterative recovery algorithm is introduced based on message passing. For validation, prospectively undersampled data are processed from a pulsatile flow phantom and five healthy volunteers. RESULTS: The proposed approach is in good agreement, quantified by peak velocity and stroke volume (SV), with reference data for acceleration rates R≤10. For SV, Pearson r≥0.99 for phantom imaging (n = 24) and r≥0.96 for prospectively accelerated in vivo imaging (n = 10) for R≤10. CONCLUSION: The proposed approach enables accurate quantification of blood flow from highly undersampled data. The technique is extensible to four-dimensional flow imaging, where higher acceleration may be possible due to additional redundancy. Magn Reson Med 76:689-701, 2016. © 2015 Wiley Periodicals, Inc.

Modeling and estimation of signal-dependent noise in hyperspectral imagery.

The majority of hyperspectral data exploitation algorithms are developed using statistical models for the data that include sensor noise. Hyperspectral data collected using charge-coupled devices or other photon detectors have sensor noise that is directly dependent on the amplitude of the signal collected. However, this signal dependence is often ignored. Additionally, the statistics of the noise can vary spatially and spectrally as a result of camera characteristics and the calibration process applied to the data. Here, we examine the expected noise characteristics of both raw and calibrated visible/near-infrared hyperspectral data and provide a method for estimating the noise statistics using calibration data or directly from the imagery if calibration data is unavailable.

Model-based deconvolution of cell cycle time-series data reveals gene expression details at high resolution.

In both prokaryotic and eukaryotic cells, gene expression is regulated across the cell cycle to ensure "just-in-time" assembly of select cellular structures and molecular machines. However, present in all time-series gene expression measurements is variability that arises from both systematic error in the cell synchrony process and variance in the timing of cell division at the level of the single cell. Thus, gene or protein expression data collected from a population of synchronized cells is an inaccurate measure of what occurs in the average single-cell across a cell cycle. Here, we present a general computational method to extract "single-cell"-like information from population-level time-series expression data. This method removes the effects of 1) variance in growth rate and 2) variance in the physiological and developmental state of the cell. Moreover, this method represents an advance in the deconvolution of molecular expression data in its flexibility, minimal assumptions, and the use of a cross-validation analysis to determine the appropriate level of regularization. Applying our deconvolution algorithm to cell cycle gene expression data from the dimorphic bacterium Caulobacter crescentus, we recovered critical features of cell cycle regulation in essential genes, including ctrA and ftsZ, that were obscured in population-based measurements. In doing so, we highlight the problem with using population data alone to decipher cellular regulatory mechanisms and demonstrate how our deconvolution algorithm can be applied to produce a more realistic picture of temporal regulation in a cell.

Expression profiling of the Arabidopsis ferric chelate reductase (FRO) gene family reveals differential regulation by iron and copper.

The Arabidopsis FRO2 gene encodes the iron deficiency-inducible ferric chelate reductase responsible for reduction of iron at the root surface; subsequent transport of iron across the plasma membrane is carried out by a ferrous iron transporter (IRT1). Genome annotation has identified seven additional FRO family members in the Arabidopsis genome. We used real-time RT-PCR to examine the expression of each FRO gene in different tissues and in response to iron and copper limitation. FRO2 and FRO5 are primarily expressed in roots while FRO8 is primarily expressed in shoots. FRO6 and FRO7 show high expression in all the green parts of the plant. FRO3 is expressed at high levels in roots and shoots, and expression of FRO3 is elevated in roots and shoots of iron-deficient plants. Interestingly, when plants are Cu-limited, the expression of FRO6 in shoot tissues is reduced. Expression of FRO3 is induced in roots and shoots by Cu-limitation. While it is known that FRO2 is expressed at high levels in the outer layers of iron-deficient roots, histochemical staining of FRO3-GUS plants revealed that FRO3 is predominantly expressed in the vascular cylinder of roots. Together our results suggest that FRO family members function in metal ion homeostasis in a variety of locations in the plant.

Light regulation of asexual development in the rice blast fungus, Magnaporthe oryzae.

Light is a major environmental factor that influences many biological processes. We characterized the roles of light in asexual development (including the formation of aerial hyphae and conidiophore) in Magnaporthe oryzae, which is the causal agent of rice blast disease. Our data revealed a complex nature of light regulation in the asexual developments of M. oryzae. Asexual development of M. oryzae is suppressed by blue light in a light/dark cycling environment and asexual spore release is controlled by both blue and red light. We demonstrated that even very dim light, about 10 micromol m(-2), is sufficient to suppress spore-release behavior in M. oryzae. We also generated knockout strains of a blue light receptor, mgwc-1, the M. oryzae homolog of white collar-1 in Neurospora crassa, and demonstrated blue-light-specific regulation in the asexual development and spore release in M. oryzae. Our findings in this agriculturally important pathogen, M. oryzae, broaden our understanding of the roles of light in fungal development.

Identification and characterization of Armillaria tabescens from the southeastern United States.

In the southeastern USA, Armillaria root rot disease on peach (Prunus persica) is caused by Armillaria tabescens, and to a lesser degree by A. mellea. Recent attempts to genetically characterize A. tabescens isolates using rDNA indicated the existence of heterozygosity in diploid isolates. In order to clarify this heterozygosity, DNA from stipe and single spore cultures of A. tabescens isolate SC.MF-1.01 was characterized using RFLP and sequence analysis. Direct sequencing of rDNA amplicons from diploid stipe tissue indicated heterozygosity in the IGS1 and ITS2 regions. IGS1 copies A and B, and ITS copies A and B segregated in a 1:1 ratio in single spore progeny, whereby IGS1 copy A always segregated with ITS copy A and IGS1 copy B always segregated with ITS copy B. The results indicate the existence of divergent haplotypes in the two nuclei of SC.MF-1.01 diploid mycelium and a single locus for rDNA tandem repeats. Additional IGS1 copies, designated IGS1 copy C, D, and E, with variable AluI restriction sites were cloned from SC.MF-1.01 diploid mycelium indicating polymorphism within ribosomal tandem repeats in A. tabescens. IGS1 copies C, D, and E were found once each in 100 clones analyzed, and therefore seemed to be rare compared to copies A (44 clones) and B (53 clones). RFLP and sequence analysis of the ribosomal IGS1 and ITS1 regions in North American A. tabescens isolates indicated that heterozygosity is common in A. tabescens diploid mycelium. A PCR-based molecular technique was developed to distinguish A. tabescens from many other North American Armillaria species, including A. mellea.