Molecular and neurological characterizations of three Saudi families with lipoid proteinosis

<p>Abstract</p> <p>Background</p> <p>Lipoid proteinosis is a rare autosomal recessive disease characterized by cutaneous and mucosal lesions and hoarseness appearing in early childhood. It is caused by homozygous or compound heterozygous mutations in the <it>ECM1 </it>gene. The disease is largely uncharacterized in Arab population and the mutation(s) spectrum in the Arab population is largely unknown. We report the neurologic and neuroradiologic characteristics and <it>ECM1 </it>gene mutations of seven individuals with lipoid proteinosis (LP) from three unrelated consanguineous families.</p> <p>Methods</p> <p>Clinical, neurologic, and neuro-ophthalmologic examinations; skin histopathology; brain CT and MRI; and sequencing of the full<it>ECM1 </it>gene.</p> <p>Results</p> <p>All seven affected individuals had skin scarring and hoarseness from early childhood. The two children in Family 1 had worse skin involvement and worse hoarseness than affected children of Families 2 and 3. Both children in Family 1 were modestly mentally retarded, and one had typical calcifications of the amygdalae on CT scan. Affected individuals in Families 2 and 3 had no grossneurologic, neurodevelopmental, or neuroimaging abnormalities. Skin histopathology was compatible with LP in all three families. Sequencing the full coding region of <it>ECM1 </it>gene revealed two novel mutationsin Family 1 (c.1300-1301delAA) and Family 2 (p.Cys269Tyr) and in Family 3 a previously described 1163 bp deletion starting 34 bp into intron 8.</p> <p>Conclusions</p> <p>These individuals illustrate the neurologic spectrum of LP, including variable mental retardation, personality changes, and mesial temporal calcificationand imply that significant neurologic involvement may be somewhat less common than previously thought. The cause of neurologic abnormalities was not clear from either neuroimaging or from what is known about <it>ECM1 </it>function. The severity of dermatologic abnormalities and hoarseness generally correlated with neurologic abnormalities, with Family 1 being somewhat more affected in all spheres than the other two families. Nevertheless, phenotype-genotype correlation was not obvious, possibly because of difficulty quantifying the neurologic phenotype and because of genetic complexity.</p

Exchange rate volatility and UK imports from developing countries: The effect of the global financial crisis

This paper studies the role of exchange rate volatility in determining the UK's real imports from three major developing countries – Brazil, China, and South Africa. The paper contributes to the literature by investigating the third country effect and also by analyzing the impact of the current financial crisis on the relationship between exchange rate volatility and UK imports. This paper further expands the empirical literature on the subject by offering evidence based on the asymmetric autoregressive distributed lag (ARDL) method from the application of monthly data from January 1991 to December 2011. Results suggest that exchange rate volatility plays an important role in determination of trade and also reveal a significant effect of the recent financial crisis on UK imports. This finding remains consistent when we test for the third country volatility effect. We also find that there is a significant causal relationship between exchange rate volatility and UK imports. The third country effect is significant for all the countries investigated. These results have significant implications for the trade policy and international trade in minimizing the underlying risk factors and ensuring stable trade flows in different economic scenarios

The Spot-Forward Exchange Rate Relation in Indian Foreign Exchange Market An Analysis

Forward exchange rate bias explanation generally falls into two categories – assumption of rational expectation resulting in a risk premium and expectation errors which is systematic. The paper tests the bias in the Indian forward exchange markets using one-month and three month forward contracts. The study finds that the three month contracts have larger prediction errors than the one-month contracts. The also paper finds that the prediction errors have information content which leads to assume the presence of risk premium. The study also finds that risk one-month contracts have lesser variability vis-à-vis the three month contracts

Eurozone Membership and Foreign Direct Investment

Our aim in this chapter is to estimate the effects of European Monetary Union (EMU) membership on foreign direct investment (FDI). Previous literature on the cross-border impact of a common currency have concentrated on international trade effects. Our analysis is based on the gravity model, which has been successfully applied to explain most forms of bilateral cross-border flows. We estimate a structural gravity model using data for 34 OECD countries between 1985 and 2013 for bilateral FDI. We use a variety of econometric techniques to ensure the robustness of our findings including stock as well as flow measures of FDI and addressing selection issues. Our estimates of the impact of EMU underlines the role of FDI as a channel for benefits from deep economic integration between countries. The effect of EMU membership on FDI is estimated to be significant and positive, at around 130%

Exploring spatial-frequency-sequential relationships for motor imagery classification with recurrent neural network

Abstract Background Conventional methods of motor imagery brain computer interfaces (MI-BCIs) suffer from the limited number of samples and simplified features, so as to produce poor performances with spatial-frequency features and shallow classifiers. Methods Alternatively, this paper applies a deep recurrent neural network (RNN) with a sliding window cropping strategy (SWCS) to signal classification of MI-BCIs. The spatial-frequency features are first extracted by the filter bank common spatial pattern (FB-CSP) algorithm, and such features are cropped by the SWCS into time slices. By extracting spatial-frequency-sequential relationships, the cropped time slices are then fed into RNN for classification. In order to overcome the memory distractions, the commonly used gated recurrent unit (GRU) and long-short term memory (LSTM) unit are applied to the RNN architecture, and experimental results are used to determine which unit is more suitable for processing EEG signals. Results Experimental results on common BCI benchmark datasets show that the spatial-frequency-sequential relationships outperform all other competing spatial-frequency methods. In particular, the proposed GRU-RNN architecture achieves the lowest misclassification rates on all BCI benchmark datasets. Conclusion By introducing spatial-frequency-sequential relationships with cropping time slice samples, the proposed method gives a novel way to construct and model high accuracy and robustness MI-BCIs based on limited trials of EEG signals

Characterization of Coastal Urban Watershed Bacterial Communities Leads to Alternative Community-Based Indicators

BACKGROUND: Microbial communities in aquatic environments are spatially and temporally dynamic due to environmental fluctuations and varied external input sources. A large percentage of the urban watersheds in the United States are affected by fecal pollution, including human pathogens, thus warranting comprehensive monitoring. METHODOLOGY/PRINCIPAL FINDINGS: Using a high-density microarray (PhyloChip), we examined water column bacterial community DNA extracted from two connecting urban watersheds, elucidating variable and stable bacterial subpopulations over a 3-day period and community composition profiles that were distinct to fecal and non-fecal sources. Two approaches were used for indication of fecal influence. The first approach utilized similarity of 503 operational taxonomic units (OTUs) common to all fecal samples analyzed in this study with the watershed samples as an index of fecal pollution. A majority of the 503 OTUs were found in the phyla Firmicutes, Proteobacteria, Bacteroidetes, and Actinobacteria. The second approach incorporated relative richness of 4 bacterial classes (Bacilli, Bacteroidetes, Clostridia and alpha-proteobacteria) found to have the highest variance in fecal and non-fecal samples. The ratio of these 4 classes (BBC:A) from the watershed samples demonstrated a trend where bacterial communities from gut and sewage sources had higher ratios than from sources not impacted by fecal material. This trend was also observed in the 124 bacterial communities from previously published and unpublished sequencing or PhyloChip- analyzed studies. CONCLUSIONS/SIGNIFICANCE: This study provided a detailed characterization of bacterial community variability during dry weather across a 3-day period in two urban watersheds. The comparative analysis of watershed community composition resulted in alternative community-based indicators that could be useful for assessing ecosystem health