Complete motor recovery after acute paraparesis caused by spontaneous spinal epidural hematoma: case report

<p>Abstract</p> <p>Background</p> <p>Spontaneous spinal epidural hematoma is a relatively rare but potentially disabling disease. Prompt timely surgical management may promote recovery even in severe cases.</p> <p>Case presentation</p> <p>We report a 34-year-old man with a 2-hour history of sudden severe back pain, followed by weakness and numbness over the bilateral lower limbs, progressing to intense paraparesis and anesthesia. A spinal magnetic resonance imaging scan was performed and revealed an anterior epidural hematoma of the thoracic spine. He underwent an emergency decompression laminectomy of the thoracic spine and hematoma evacuation. Just after surgery, his lower extremity movements improved. After 1 week, there was no residual weakness and ambulation without assistance was resumed, with residual paresthesia on the plantar face of both feet. After 5 months, no residual symptoms persisted.</p> <p>Conclusions</p> <p>The diagnosis of spontaneous spinal epidural hematoma must be kept in mind in cases of sudden back pain with symptoms of spinal cord compression. Early recognition, accurate diagnosis and prompt surgical treatment may result in significant improvement even in severe cases.</p

Isoform Diversity and Regulation in Peripheral and Central Neurons Revealed through RNA-Seq

To fully understand cell type identity and function in the nervous system there is a need to understand neuronal gene expression at the level of isoform diversity. Here we applied Next Generation Sequencing of the transcriptome (RNA-Seq) to purified sensory neurons and cerebellar granular neurons (CGNs) grown on an axonal growth permissive substrate. The goal of the analysis was to uncover neuronal type specific isoforms as a prelude to understanding patterns of gene expression underlying their intrinsic growth abilities. Global gene expression patterns were comparable to those found for other cell types, in that a vast majority of genes were expressed at low abundance. Nearly 18% of gene loci produced more than one transcript. More than 8000 isoforms were differentially expressed, either to different degrees in different neuronal types or uniquely expressed in one or the other. Sensory neurons expressed a larger number of genes and gene isoforms than did CGNs. To begin to understand the mechanisms responsible for the differential gene/isoform expression we identified transcription factor binding sites present specifically in the upstream genomic sequences of differentially expressed isoforms, and analyzed the 3′ untranslated regions (3′ UTRs) for microRNA (miRNA) target sites. Our analysis defines isoform diversity for two neuronal types with diverse axon growth capabilities and begins to elucidate the complex transcriptional landscape in two neuronal populations

An efficient algorithm for the stochastic simulation of the hybridization of DNA to microarrays

<p>Abstract</p> <p>Background</p> <p>Although oligonucleotide microarray technology is ubiquitous in genomic research, reproducibility and standardization of expression measurements still concern many researchers. Cross-hybridization between microarray probes and non-target ssDNA has been implicated as a primary factor in sensitivity and selectivity loss. Since hybridization is a chemical process, it may be modeled at a population-level using a combination of material balance equations and thermodynamics. However, the hybridization reaction network may be exceptionally large for commercial arrays, which often possess at least one reporter per transcript. Quantification of the kinetics and equilibrium of exceptionally large chemical systems of this type is numerically infeasible with customary approaches.</p> <p>Results</p> <p>In this paper, we present a robust and computationally efficient algorithm for the simulation of hybridization processes underlying microarray assays. Our method may be utilized to identify the extent to which nucleic acid targets (e.g. cDNA) will cross-hybridize with probes, and by extension, characterize probe robustnessusing the information specified by MAGE-TAB. Using this algorithm, we characterize cross-hybridization in a modified commercial microarray assay.</p> <p>Conclusions</p> <p>By integrating stochastic simulation with thermodynamic prediction tools for DNA hybridization, one may robustly and rapidly characterize of the selectivity of a proposed microarray design at the probe and "system" levels. Our code is available at <url>http://www.laurenzi.net</url>.</p