Review of data types and model dimensionality for cardiac DTI SMS-related artefact removal

As diffusion tensor imaging (DTI) gains popularity in cardiac imaging due to its unique ability to non-invasively assess the cardiac microstructure, deep learning-based Artificial Intelligence is becoming a crucial tool in mitigating some of its drawbacks, such as the long scan times. As it often happens in fast-paced research environments, a lot of emphasis has been put on showing the capability of deep learning while often not enough time has been spent investigating what input and architectural properties would benefit cardiac DTI acceleration the most. In this work, we compare the effect of several input types (magnitude images vs complex images), multiple dimensionalities (2D vs 3D operations), and multiple input types (single slice vs multi-slice) on the performance of a model trained to remove artefacts caused by a simultaneous multi-slice (SMS) acquisition. Despite our initial intuition, our experiments show that, for a fixed number of parameters, simpler 2D real-valued models outperform their more advanced 3D or complex counterparts. The best performance is although obtained by a real-valued model trained using both the magnitude and phase components of the acquired data. We believe this behaviour to be due to real-valued models making better use of the lower number of parameters, and to 3D models not being able to exploit the spatial information because of the low SMS acceleration factor used in our experiments.Comment: 11 pages, 3 tables, 1 figure. To be published at the STACOM workshop, MICCAI 202

Effect on falls of providing single lens distance vision glasses to multifocal glasses wearers: VISIBLE randomised controlled trial

Objective To determine whether the provision of single lens distance glasses to older wearers of multifocal glasses reduces falls

Dependence and Imperialism in India

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/69044/2/10.1177_048661347300500111.pd

Enhanced Transcriptome Maps from Multiple Mouse Tissues Reveal Evolutionary Constraint in Gene Expression for Thousands of Genes

We characterized by RNA-seq the transcriptional profiles of a large and heterogeneous collection of mouse tissues, augmenting the mouse transcriptome with thousands of novel transcript candidates. Comparison with transcriptome profiles obtained in human cell lines reveals substantial conservation of transcriptional programs, and uncovers a distinct class of genes with levels of expression across cell types and species, that have been constrained early in vertebrate evolution. This core set of genes capture a substantial and constant fraction of the transcriptional output of mammalian cells, and participates in basic functional and structural housekeeping processes common to all cell types. Perturbation of these constrained genes is associated with significant phenotypes including embryonic lethality and cancer. Evolutionary constraint in gene expression levels is not reflected in the conservation of the genomic sequences, but is associated with strong and conserved epigenetic marking, as well as to a characteristic post-transcriptional regulatory program in which sub-cellular localization and alternative splicing play comparatively large roles

Metabolic synergies in the biotransformation of organic and metallic toxic compounds by a saprotrophic soil fungus

The saprotrophic fungus Penicillium griseofulvum was chosen as model organism to study responses to a mixture of hexachlorocyclohexane (HCH) isomers (α-HCH, β-HCH, γ-HCH, δ-HCH) and of potentially toxic metals (vanadium, lead) in solid and liquid media. The P. griseofulvum FBL 500 strain was isolated from polluted soil containing high concentrations of HCH isomers and potentially toxic elements (Pb, V). Experiments were performed in order to analyse the tolerance/resistance of this fungus to xenobiotics, and to shed further light on fungal potential in inorganic and organic biotransformations. The aim was to examine the ecological and bioremedial potential of this fungus verifying the presence of mechanisms that allow it to transform HCH isomers and metals under different, extreme, test conditions. To our knowledge, this work is the first to provide evidence on the biotransformation of HCH mixtures, in combination with toxic metals, by a saprotrophic non-white-rot fungus and on the metabolic synergies involved

Integration of Expressed Sequence Tag Data Flanking Predicted RNA Secondary Structures Facilitates Novel Non-Coding RNA Discovery

Many computational methods have been used to predict novel non-coding RNAs (ncRNAs), but none, to our knowledge, have explicitly investigated the impact of integrating existing cDNA-based Expressed Sequence Tag (EST) data that flank structural RNA predictions. To determine whether flanking EST data can assist in microRNA (miRNA) prediction, we identified genomic sites encoding putative miRNAs by combining functional RNA predictions with flanking ESTs data in a model consistent with miRNAs undergoing cleavage during maturation. In both human and mouse genomes, we observed that the inclusion of flanking ESTs adjacent to and not overlapping predicted miRNAs significantly improved the performance of various methods of miRNA prediction, including direct high-throughput sequencing of small RNA libraries. We analyzed the expression of hundreds of miRNAs predicted to be expressed during myogenic differentiation using a customized microarray and identified several known and predicted myogenic miRNA hairpins. Our results indicate that integrating ESTs flanking structural RNA predictions improves the quality of cleaved miRNA predictions and suggest that this strategy can be used to predict other non-coding RNAs undergoing cleavage during maturation

Landscape of transcription in human cells

Eukaryotic cells make many types of primary and processed RNAs that are found either in specific sub-cellular compartments or throughout the cells. A complete catalogue of these RNAs is not yet available and their characteristic sub-cellular localizations are also poorly understood. Since RNA represents the direct output of the genetic information encoded by genomes and a significant proportion of a cell’s regulatory capabilities are focused on its synthesis, processing, transport, modifications and translation, the generation of such a catalogue is crucial for understanding genome function. Here we report evidence that three quarters of the human genome is capable of being transcribed, as well as observations about the range and levels of expression, localization, processing fates, regulatory regions and modifications of almost all currently annotated and thousands of previously unannotated RNAs. These observations taken together prompt to a redefinition of the concept of a gene