Forging a path to mesoscopic imaging success with ultra-high field functional magnetic resonance imaging

Functional magnetic resonance imaging (fMRI) studies with ultra-high field (UHF, 7+ Tesla) technology enable the acquisition of high-resolution images. In this work, we discuss recent achievements in UHF fMRI at the mesoscopic scale, on the order of cortical columns and layers, and examine approaches to addressing common challenges. As researchers push to smaller and smaller voxel sizes, acquisition and analysis decisions have greater potential to degrade spatial accuracy, and UHF fMRI data must be carefully interpreted. We consider the impact of acquisition decisions on the spatial specificity of the MR signal with a representative dataset with 0.8 mm isotropic resolution. We illustrate the trade-offs in contrast with noise ratio and spatial specificity of different acquisition techniques and show that acquisition blurring can increase the effective voxel size by as much as 50% in some dimensions. We further describe how different sources of degradations to spatial resolution in functional data may be characterized. Finally, we emphasize that progress in UHF fMRI depends not only on scientific discovery and technical advancement, but also on informal discussions and documentation of challenges researchers face and overcome in pursuit of their goals.This article is part of the theme issue ‘Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity’.     

Adenosine 2A Receptor Antagonist Prevented and Reversed Liver Fibrosis in a Mouse Model of Ethanol-Exacerbated Liver Fibrosis

The effect of moderate alcohol consumption on liver fibrosis is not well understood, but evidence suggests that adenosine may play a role in mediating the effects of moderate ethanol on tissue injury. Ethanol increases the concentration of adenosine in the liver. Adenosine 2A receptor (A2AR) activation is known to enhance hepatic stellate cell (HSC) activation and A2AR deficient mice are protected from fibrosis in mice. Making use of a novel mouse model of moderate ethanol consumption in which female C57BL/6J mice were allowed continued access to 2% (vol/vol) ethanol (11% calories) or pair-fed control diets for 2 days, 2 weeks or 5 weeks and superimposed with exposure to CCl₄, we tested the hypothesis that moderate ethanol consumption increases fibrosis in response to carbon tetrachloride (CCl₄) and that treatment of mice with an A2AR antagonist prevents and/or reverses this ethanol-induced increase in liver fibrosis. Neither the expression or activity of CYP2E1, required for bio-activation of CCl₄, nor AST and ALT activity in the plasma were affected by ethanol, indicating that moderate ethanol did not increase the direct hepatotoxicity of CCl₄. However, ethanol feeding enhanced HSC activation and exacerbated liver fibrosis upon exposure to CCl_4. This was associated with an increased sinusoidal angiogenic response in the liver. Treatment with A2AR antagonist both prevented and reversed the ability of ethanol to exacerbate liver fibrosis.

Conclusion

Moderate ethanol consumption exacerbates hepatic fibrosis upon exposure to CCl₄. A2AR antagonism may be a potential pharmaceutical intervention to decrease hepatic fibrosis in response to ethanol.     

Hierarchical classification of functionally equivalent genes in prokaryotes

Functional classification of genes represents a fundamental problem to many biological studies. Most of the existing classification schemes are based on the concepts of homology and orthology, which were originally introduced to study gene evolution but might not be the most appropriate for gene function prediction, particularly at high resolution level. We have recently developed a scheme for hierarchical classification of genes (HCGs) in prokaryotes. In the HCG scheme, the functional equivalence relationships among genes are first assessed through a careful application of both sequence similarity and genomic neighborhood information; and genes are then classified into a hierarchical structure of clusters, where genes in each cluster are functionally equivalent at some resolution level, and the level of resolution goes higher as the clusters become increasingly smaller traveling down the hierarchy. The HCG scheme is validated through comparisons with the taxonomy of the prokaryotic genomes, Clusters of Orthologous Groups (COGs) of genes and the Pfam system. We have applied the HCG scheme to 224 complete prokaryotic genomes, and constructed a HCG database consisting of a forest of 5339 multi-level and 15 770 single-level trees of gene clusters covering approximately 93% of the genes of these 224 genomes. The validation results indicate that the HCG scheme not only captures the key features of the existing classification schemes but also provides a much richer organization of genes which can be used for functional prediction of genes at higher resolution and to help reveal evolutionary trace of the genes.     

Improving the performance of protein threading using insertion/deletion frequency arrays

As a protein evolves, not every part of the amino acid sequence has an equal probability of being deleted or for allowing insertions, because not every amino acid plays an equally important role in maintaining the protein structure. However, the most prevalent models in fold recognition methods treat every amino acid deletion and insertion as equally probable events. We have analyzed the alignment patterns for homologous and analogous sequences to determine patterns of insertion and deletion, and used that information to determine the statistics of insertions and deletions for different amino acids of a target sequence. We define these patterns as insertion/deletion (indel) frequency arrays (IFAs). By applying IFAs to the protein threading problem, we have been able to improve the alignment accuracy, especially for proteins with low sequence identity. We have also demonstrated that the application of this information can lead to an improvement in fold recognition.     

Barcodes for genomes and applications

Background  

Each genome has a stable distribution of the combined frequency for each k-mer and its reverse complement measured in sequence fragments as short as 1000 bps across the whole genome, for 1<k<6. The collection of these k-mer frequency distributions is unique to each genome and termed the genome's barcode.     

Large-Scale Analyses of Glycosylation in Cellulases

Cellulases are important glycosyl hydrolases (GHs) that hydrolyze cellulose polymers into smaller oligosaccharides by breaking the cellulose β (1→4) bonds,and they are widely used to produce cellulosic ethanol from the plant biomass.N-linked and O-linked glycosylations were proposed to impact the catalytic efficiency,cellulose binding affinity and the stability of cellulases based on observations of individual cellulases.As far as we know,there has not been any systematic analysis of the distributions of N-...     

Abnormal Contextual Modulation of Visual Contour Detection in Patients with Schizophrenia

Schizophrenia patients demonstrate perceptual deficits consistent with broad dysfunction in visual context processing. These include poor integration of segments forming visual contours, and reduced visual contrast effects (e.g. weaker orientation-dependent surround suppression, ODSS). Background image context can influence contour perception, as stimuli near the contour affect detection accuracy. Because of ODSS, this contextual modulation depends on the relative orientation between the contour and flanking elements, with parallel flankers impairing contour perception. However in schizophrenia, the impact of abnormal ODSS during contour perception is not clear. It is also unknown whether deficient contour perception marks genetic liability for schizophrenia, or is strictly associated with clinical expression of this disorder. We examined contour detection in 25 adults with schizophrenia, 13 unaffected first-degree biological relatives of schizophrenia patients, and 28 healthy controls. Subjects performed a psychophysics experiment designed to quantify the effect of flanker orientation during contour detection. Overall, patients with schizophrenia showed poorer contour detection performance than relatives or controls. Parallel flankers suppressed and orthogonal flankers enhanced contour detection performance for all groups, but parallel suppression was relatively weaker for schizophrenia patients than healthy controls. Relatives of patients showed equivalent performance with controls. Computational modeling suggested that abnormal contextual modulation in schizophrenia may be explained by suppression that is more broadly tuned for orientation. Abnormal flanker suppression in schizophrenia is consistent with weaker ODSS and/or broader orientation tuning. This work provides the first evidence that such perceptual abnormalities may not be associated with a genetic liability for schizophrenia.     

Distortion and Signal Loss in Medial Temporal Lobe

Background

The medial temporal lobe (MTL) contains subregions that are subject to severe distortion and signal loss in functional MRI. Air/tissue and bone/tissue interfaces in the vicinity of the MTL distort the local magnetic field due to differences in magnetic susceptibility. Fast image acquisition and thin slices can reduce the amount of distortion and signal loss, but at the cost of image signal-to-noise ratio (SNR).

Methodology/Principal Findings

In this paper, we quantify the severity of distortion and signal loss in MTL subregions for three different echo planar imaging (EPI) acquisitions at 3 Tesla: a conventional moderate-resolution EPI (3×3×3 mm), a conventional high-resolution EPI (1.5×1.5×2 mm), and a zoomed high-resolution EPI. We also demonstrate the advantage of reversing the phase encode direction to control the direction of distortion and to maximize efficacy of distortion compensation during data post-processing. With the high-resolution zoomed acquisition, distortion is not significant and signal loss is present only in the most anterior regions of the parahippocampal gyrus. Furthermore, we find that the severity of signal loss is variable across subjects, with some subjects showing negligible loss and others showing more dramatic loss.

Conclusions/Significance

Although both distortion and signal loss are minimized in a zoomed field of view acquisition with thin slices, this improvement in accuracy comes at the cost of reduced SNR. We quantify this trade-off between distortion and SNR in order to provide a decision tree for design of high-resolution experiments investigating the function of subregions in MTL.     

Parallel Clustering Algorithm for Large Data Sets with Applications in Bioinformatics

Large sets of bioinformatical data provide a challenge in time consumption while solving the cluster identification problem, and that is why a parallel algorithm is so needed for identifying dense clusters in a noisy background. Our algorithm works on a graph representation of the data set to be analyzed. It identifies clusters through the identification of densely intraconnected subgraphs. We have employed a minimum spanning tree (MST) representation of the graph and solve the cluster identification problem using this representation. The computational bottleneck of our algorithm is the construction of an MST of a graph, for which a parallel algorithm is employed. Our high-level strategy for the parallel MST construction algorithm is to first partition the graph, then construct MSTs for the partitioned subgraphs and auxiliary bipartite graphs based on the subgraphs, and finally merge these MSTs to derive an MST of the original graph. The computational results indicate that when running on 150 CPUs, our algorithm can solve a cluster identification problem on a data set with 1,000,000 data points almost 100 times faster than on single CPU, indicating that this program is capable of handling very large data clustering problems in an efficient manner. We have implemented the clustering algorithm as the software CLUMP.