Recent evidences suggest that endoplasmic reticulum (ER) stress was involved in multi pathological conditions, including diabetic nephropathy (DN). X-box binding protein 1(XBP1), as a key mediator of ER stress, has been proved having the capability of preventing oxidative stress. In this study, we investigated the effects of spliced XBP1 (XBP1S), the dominant active form of XBP1, on high glucose (HG)-induced reactive oxygen species (ROS) production and extracellular matrix (ECM) synthesis in cultured renal mesangial cells (MCs) and renal cortex of STZ-induced diabetic rats. Real time PCR and Western blot were used to evaluate the mRNA and protein levels respectively. Transfection of recombinant adenovirus vector carrying XBP1S gene (Ad-XBP1S) was used to upregulate XBP1S expression. XBP1S siRNA was used to knockdown XBP1S expression. ROS level was detected by dihydroethidium (DHE) fluorescent probe assay. The results showed that HG treatment significantly reduced XBP1S protein and mRNA level in the cultured MCs while no obvious change was observed in unspliced XBP1 (XBP1U). In the mean time, the ROS production, collagen IV and fibronectin expressions were increased. Diphenylene-chloride iodonium (DPI), a NADPH oxidase inhibtor, prevented HG-induced increases in ROS as well as collagen IV and fibronectin expressions. Transfection of Ad-XBP1S reversed HG-induced ROS production and ECM expressions. Knockdown intrinsic XBP1S expression induced increases in ROS production and ECM expressions. Supplementation of supreoxide reversed the inhibitory effect of Ad-XBP1S transfection on ECM synthesis. P47phox was increased in HG-treated MCs. Ad-XBP1S transfection reversed HG-induced p47phox increase while XBP1S knockdown upregulated p47phox expression. In the renal cortex of diabetic rats, the expression of XBP1S was reduced while p47phox, collagen IV and fibronectin expression were elevated. These results suggested that XBP1S pathway of ER stress was involved in HG-induced oxidative stress and ECM synthesis. A downstream target of XBP1S in regulating ROS formation might be NADPH oxidase.

We describe a conditional in vivo protein trap mutagenesis system that reveals spatio-temporal protein expression dynamics and assesses gene function in the vertebrate Danio rerio. Integration of pGBT-RP2 (RP2), a gene-breaking transposon containing a protein trap, efficiently disrupts gene expression with >97% knockdown of normal transcript levels while simultaneously reporting protein expression of each locus. The mutant alleles are revertible in somatic tissues via Cre recombinase or splice-site blocking morpholinos, thus representing the first systematic conditional mutant alleles outside the mouse model. We report a collection of 350 zebrafish lines including a diverse array of molecular loci. RP2 integrations reveal the complexity of genomic architecture and gene function in a living organism and can provide information on protein subcellular localization. The RP2 mutagenesis system is a step towards a unified codex of protein expression and direct functional annotation of the vertebrate genome.

Using first principles calculations, we investigate the electronic structures of semi-hydrogenated BC3, BC5, BC7, and B-doped graphone sheets. We find that all the semi-hydrogenated boron-carbon sheets exhibit half-metallic behaviors. The magnetism originates from the non-bonding pz orbitals of carbon atoms, which cause the flat bands to satisfy the Stoner criterion. On the other hand, boron atoms weaken the magnetic moments of nearby carbon atoms and act as holes doped in the sheets. It induces the down shift of the Fermi level and the half-metallicity in semi-hydrogenated sheets. Our studies demonstrate that the semi-hydrogenation is an effective route to achieve half-metallicity in the boron-carbon systems.

An iterative algorithm is suited to reconstruct CT images from noisy or truncated projection data. However, as a disadvantage, the algorithm requires significant computational time. Although a parallel technique can be used to reduce the computational time, a large amount of communication overhead becomes an obstacle to its performance (Li et al. in J. X-Ray Sci. Technol. 13:1–10, 2005). To overcome this problem, we proposed an innovative parallel method based on the local iterative CT reconstruction algorithm (Wang et al. in Scanning 18:582–588, 1996 and IEEE Trans. Med. Imaging 15(5):657–664, 1996). The object to be reconstructed is partitioned into a number of subregions and assigned to different processing elements (PEs). Within each PE, local iterative reconstruction is performed to recover the subregion. Several numerical experiments were conducted on a high performance computing cluster. And the FORBILD head phantom (Lauritsch and Bruder http://www.imp.uni-erlangen.de/phantoms/head/head.html) was used as benchmark to measure the parallel performance. The experimental results showed that the proposed parallel algorithm significantly reduces the reconstruction time, hence achieving a high speedup and efficiency.

In the past decade, tools derived from DNA transposons have made major contributions to vertebrate genetic studies from gene delivery to gene discovery. Multiple, highly complementary systems have been developed, and many more are in the pipeline. Judging which DNA transposon element will work the best in diverse uses from zebrafish genetic manipulation to human gene therapy is currently a complex task. We have summarized the major transposon vector systems active in vertebrates, comparing and contrasting known critical biochemical and in vivo properties, for future tool design and new genetic applications.

AIM: To investigate the therapeutic effect of traditional Chinese traditional medicines Da Cheng Qi Decoction (Timely-Purging and Yin-Preserving Decoction) and Glauber’s salt combined with conservative measures on abdominal compartment syndrome (ACS) in severe acute pancreatitis (SAP) patients.

METHODS: Eighty consecutive SAP patients, admitted for routine non-operative conservative treatment, were randomly divided into study group and control group (40 patients in each group). Patients in the study group received Da Cheng Qi Decoction enema for 2 h and external use of Glauber’s salt, once a day for 7 d. Patients in the control group received normal saline (NS) enema. Routine non-operative conservative treatments included non-per os nutrition (NPON), gastrointestinal decompression, life support, total parenteral nutrition (TPN), continuous peripancreatic vascular pharmaceutical infusion and drug therapy. Intra-cystic pressure (ICP) of the two groups was measured during treatment. The effectiveness and outcomes of treatment were observed and APACHE II scores were applied in analysis.

RESULTS: On days 4 and 5 of treatment, the ICP was lower in the study group than in the control group (P < 0.05). On days 3-5 of treatment, acute physiology and chronic health evaluation II (APACHE II) scores for the study and control groups were significantly different (P < 0.05). Both the effectiveness and outcome of the treatment with Da Cheng Qi Decoction on abdominalgia, burbulence relief time, ascites quantity, cyst formation rate and hospitalization time were quite different between the two groups (P < 0.05). The mortality rate for the two groups had no significant difference.

CONCLUSION: Da Cheng Qi Decoction enema and external use of Glauber’s salt combined with routine non-operative conservative treatment can decrease the intra-abdominal pressure (IAP) of SAP patients and have preventive and therapeutic effects on abdominal compartment syndrome of SAP.

Background

A protein structural class (PSC) belongs to the most basic but important classification in protein structures. The prediction technique of protein structural class has been developing for decades. Two popular indices are the amino-acid-frequency (AAF) based, and amino-acid-arrangement (AAA) with long-term correlation (LTC) – based indices. They were proposed in many works. Both indices have its pros and cons. For example, the AAF index focuses on a statistical analysis, while the AAA-LTC emphasizes the long-term, biological significance. Unfortunately, the datasets used in previous work were not very reliable for a small number of sequences with a high-sequence similarity.

Results

By modifying a statistical strategy, we proposed a new index method that combines probability and information theory together with a long-term correlation. We also proposed a numerically and biologically reliable dataset included more than 5700 sequences with a low sequence similarity. The results showed that the proposed approach has its high accuracy. Comparing with amino acid composition (AAC) index using a distance method, the accuracy of our approach has a 16–20% improvement for re-substitution test and about 6–11% improvement for cross-validation test. The values were about 23% and 15% for the component coupled method (CCM).

Conclusion

A new index method, combining probability and information theory together with a long-term correlation was proposed in this paper. The statistical method was improved significantly based on our new index. The cross validation test was conducted, and the result show the proposed method has a great improvement.

The Second Symposium on Computations in Bioinformatics and Bioscience (SCBB07) was held in Iowa City, Iowa, USA, on August 13–15, 2007. This annual event attracted dozens of bioinformatics professionals and students, who are interested in solving emerging computational problems in bioscience, from China, Japan, Taiwan and the United States. The Scientific Committee of the symposium selected 18 peer-reviewed papers for publication in this supplemental issue of BMC Bioinformatics. These papers cover a broad spectrum of topics in computational biology and bioinformatics, including DNA, protein and genome sequence analysis, gene expression and microarray analysis, computational proteomics and protein structure classification, systems biology and machine learning.

Background

Genetic association studies have been used to map disease-causing genes. A newly introduced statistical method, called exhaustive haplotype association study, analyzes genetic information consisting of different numbers and combinations of DNA sequence variations along a chromosome. Such studies involve a large number of statistical calculations and subsequently high computing power. It is possible to develop parallel algorithms and codes to perform the calculations on a high performance computing (HPC) system. However, most existing commonly-used statistic packages for genetic studies are non-parallel versions. Alternatively, one may use the cutting-edge technology of grid computing and its packages to conduct non-parallel genetic statistical packages on a centralized HPC system or distributed computing systems. In this paper, we report the utilization of a queuing scheduler built on the Grid Engine and run on a Rocks Linux cluster for our genetic statistical studies.

Results

Analysis of both consecutive and combinational window haplotypes was conducted by the FBAT (Laird et al., 2000) and Unphased (Dudbridge, 2003) programs. The dataset consisted of 26 loci from 277 extended families (1484 persons). Using the Rocks Linux cluster with 22 compute-nodes, FBAT jobs performed about 14.4–15.9 times faster, while Unphased jobs performed 1.1–18.6 times faster compared to the accumulated computation duration.

Conclusion

Execution of exhaustive haplotype analysis using non-parallel software packages on a Linux-based system is an effective and efficient approach in terms of cost and performance.

The first symposium of computations in bioinformatics and bioscience (SCBB06) was held in Hangzhou, China on June 21–22, 2006. Twenty-six peer-reviewed papers were selected for publication in this special issue of BMC Bioinformatics. These papers cover a broad range of topics including bioinformatics theories, algorithms, applications and tool development. The main technical topics contain gene expression analysis, sequence analysis, genome analysis, phylogenetic analysis, gene function prediction, molecular interaction and system biology, genetics and population study, immune strategy, protein structure prediction and proteomics.

Background

DNA Microarray technology is an innovative methodology in experimental molecular biology, which has produced huge amounts of valuable data in the profile of gene expression. Many clustering algorithms have been proposed to analyze gene expression data, but little guidance is available to help choose among them. The evaluation of feasible and applicable clustering algorithms is becoming an important issue in today's bioinformatics research.

Results

In this paper we first experimentally study three major clustering algorithms: Hierarchical Clustering (HC), Self-Organizing Map (SOM), and Self Organizing Tree Algorithm (SOTA) using Yeast Saccharomyces cerevisiae gene expression data, and compare their performance. We then introduce Cluster Diff, a new data mining tool, to conduct the similarity analysis of clusters generated by different algorithms. The performance study shows that SOTA is more efficient than SOM while HC is the least efficient. The results of similarity analysis show that when given a target cluster, the Cluster Diff can efficiently determine the closest match from a set of clusters. Therefore, it is an effective approach for evaluating different clustering algorithms.

Conclusion

HC methods allow a visual, convenient representation of genes. However, they are neither robust nor efficient. The SOM is more robust against noise. A disadvantage of SOM is that the number of clusters has to be fixed beforehand. The SOTA combines the advantages of both hierarchical and SOM clustering. It allows a visual representation of the clusters and their structure and is not sensitive to noises. The SOTA is also more flexible than the other two clustering methods. By using our data mining tool, Cluster Diff, it is possible to analyze the similarity of clusters generated by different algorithms and thereby enable comparisons of different clustering methods.