Negative Giant Longitudinal Magnetoresistance in NiMnSb/InSb: An interface effect

We report on the electrical and magneto-transport properties of the contact formed between polycrystalline NiMnSb thin films grown using pulsed laser deposition (PLD) and n-type degenerate InSb (100) substrates. A negative giant magnetoresistance (GMR) effect is observed when the external magnetic field is parallel to the surface of the film and to the current direction. We attribute the observed phenomenon to magnetic precipitates formed during the magnetic film deposition and confined to a narrow layer at the interface. The effect of these precipitates on the magnetoresistance depends on the thermal processing of the system.Comment: 14 pages, 4 figure

Successful Treatment of Postoperative External Biliary Fistula by Selective Nasobiliary Drainage

A 25-year old man presented with a high output external biliary fistula after an operation for a giant hydatid cyst of the liver. Endoscopic sphincterotomy was inadequate to close the fistula. A nasobiliary tube was selectively inserted into the leaking hepatic duct and bile was continuously aspirated. The fistula and the residual cavity healed completely. Details of the patients' management using this alternative technique, are discussed

Importance of replication in analyzing time-series gene expression data: Corticosteroid dynamics and circadian patterns in rat liver

<p>Abstract</p> <p>Background</p> <p>Microarray technology is a powerful and widely accepted experimental technique in molecular biology that allows studying genome wide transcriptional responses. However, experimental data usually contain potential sources of uncertainty and thus many experiments are now designed with repeated measurements to better assess such inherent variability. Many computational methods have been proposed to account for the variability in replicates. As yet, there is no model to output expression profiles accounting for replicate information so that a variety of computational models that take the expression profiles as the input data can explore this information without any modification.</p> <p>Results</p> <p>We propose a methodology which integrates replicate variability into expression profiles, to generate so-called 'true' expression profiles. The study addresses two issues: (i) develop a statistical model that can estimate 'true' expression profiles which are more robust than the average profile, and (ii) extend our previous micro-clustering which was designed specifically for clustering time-series expression data. The model utilizes a previously proposed error model and the concept of 'relative difference'. The clustering effectiveness is demonstrated through synthetic data where several methods are compared. We subsequently analyze <it>in vivo </it>rat data to elucidate circadian transcriptional dynamics as well as liver-specific corticosteroid induced changes in gene expression.</p> <p>Conclusions</p> <p>We have proposed a model which integrates the error information from repeated measurements into the expression profiles. Through numerous synthetic and real time-series data, we demonstrated the ability of the approach to improve the clustering performance and assist in the identification and selection of informative expression motifs.</p

Comparative analysis of acute and chronic corticosteroid pharmacogenomic effects in rat liver: Transcriptional dynamics and regulatory structures

<p>Abstract</p> <p>Background</p> <p>Comprehensively understanding corticosteroid pharmacogenomic effects is an essential step towards an insight into the underlying molecular mechanisms for both beneficial and detrimental clinical effects. Nevertheless, even in a single tissue different methods of corticosteroid administration can induce different patterns of expression and regulatory control structures. Therefore, rich <it>in vivo </it>datasets of pharmacological time-series with two dosing regimens sampled from rat liver are examined for temporal patterns of changes in gene expression and their regulatory commonalities.</p> <p>Results</p> <p>The study addresses two issues, including (1) identifying significant transcriptional modules coupled with dynamic expression patterns and (2) predicting relevant common transcriptional controls to better understand the underlying mechanisms of corticosteroid adverse effects. Following the orientation of meta-analysis, an extended computational approach that explores the concept of agreement matrix from consensus clustering has been proposed with the aims of identifying gene clusters that share common expression patterns across multiple dosing regimens as well as handling challenges in the analysis of microarray data from heterogeneous sources, e.g. different platforms and time-grids in this study. Six significant transcriptional modules coupled with typical patterns of expression have been identified. Functional analysis reveals that virtually all enriched functions (gene ontologies, pathways) in these modules are shown to be related to metabolic processes, implying the importance of these modules in adverse effects under the administration of corticosteroids. Relevant putative transcriptional regulators (e.g. RXRF, FKHD, SP1F) are also predicted to provide another source of information towards better understanding the complexities of expression patterns and the underlying regulatory mechanisms of those modules.</p> <p>Conclusions</p> <p>We have proposed a framework to identify significant coexpressed clusters of genes across multiple conditions experimented from different microarray platforms, time-grids, and also tissues if applicable. Analysis on rich <it>in vivo </it>datasets of corticosteroid time-series yielded significant insights into the pharmacogenomic effects of corticosteroids, especially the relevance to metabolic side-effects. This has been illustrated through enriched metabolic functions in those transcriptional modules and the presence of GRE binding motifs in those enriched pathways, providing significant modules for further analysis on pharmacogenomic corticosteroid effects.</p