Biomimetic intrafibrillar mineralization of type I collagen with intermediate precursors-loaded mesoporous carriers

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Simulation of multilevel cell spin transfer switching in a full-Heusler alloy spin-valve nanopillar

Author name used in this publication: Shi, S. Q.2012-2013 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Gene expression and splicing alterations analyzed by high throughput RNA sequencing of chronic lymphocytic leukemia specimens.

BackgroundTo determine differentially expressed and spliced RNA transcripts in chronic lymphocytic leukemia specimens a high throughput RNA-sequencing (HTS RNA-seq) analysis was performed.MethodsTen CLL specimens and five normal peripheral blood CD19+ B cells were analyzed by HTS RNA-seq. The library preparation was performed with Illumina TrueSeq RNA kit and analyzed by Illumina HiSeq 2000 sequencing system.ResultsAn average of 48.5 million reads for B cells, and 50.6 million reads for CLL specimens were obtained with 10396 and 10448 assembled transcripts for normal B cells and primary CLL specimens respectively. With the Cuffdiff analysis, 2091 differentially expressed genes (DEG) between B cells and CLL specimens based on FPKM (fragments per kilobase of transcript per million reads and false discovery rate, FDR q < 0.05, fold change >2) were identified. Expression of selected DEGs (n = 32) with up regulated and down regulated expression in CLL from RNA-seq data were also analyzed by qRT-PCR in a test cohort of CLL specimens. Even though there was a variation in fold expression of DEG genes between RNA-seq and qRT-PCR; more than 90 % of analyzed genes were validated by qRT-PCR analysis. Analysis of RNA-seq data for splicing alterations in CLL and B cells was performed by Multivariate Analysis of Transcript Splicing (MATS analysis). Skipped exon was the most frequent splicing alteration in CLL specimens with 128 significant events (P-value <0.05, minimum inclusion level difference >0.1).ConclusionThe RNA-seq analysis of CLL specimens identifies novel DEG and alternatively spliced genes that are potential prognostic markers and therapeutic targets. High level of validation by qRT-PCR for a number of DEG genes supports the accuracy of this analysis. Global comparison of transcriptomes of B cells, IGVH non-mutated CLL (U-CLL) and mutated CLL specimens (M-CLL) with multidimensional scaling analysis was able to segregate CLL and B cell transcriptomes but the M-CLL and U-CLL transcriptomes were indistinguishable. The analysis of HTS RNA-seq data to identify alternative splicing events and other genetic abnormalities specific to CLL is an added advantage of RNA-seq that is not feasible with other genome wide analysis

Identification of a Novel Marine Fish Virus, Singapore Grouper Iridovirus-Encoded MicroRNAs Expressed in Grouper Cells by Solexa Sequencing

BACKGROUND: MicroRNAs (miRNAs) are ubiquitous non-coding RNAs that regulate gene expression at the post-transcriptional level. An increasing number of studies has revealed that viruses can also encode miRNAs, which are proposed to be involved in viral replication and persistence, cell-mediated antiviral immune response, angiogenesis, and cell cycle regulation. Singapore grouper iridovirus (SGIV) is a pathogenic iridovirus that has severely affected grouper aquaculture in China and Southeast Asia. Comprehensive knowledge about the related miRNAs during SGIV infection is helpful for understanding the infection and the pathogenic mechanisms. METHODOLOGY/PRINCIPAL FINDINGS: To determine whether SGIV encoded miRNAs during infection, a small RNA library derived from SGIV-infected grouper (GP) cells was constructed and sequenced by Illumina/Solexa deep-sequencing technology. We recovered 6,802,977 usable reads, of which 34,400 represented small RNA sequences encoded by SGIV. Sixteen novel SGIV-encoded miRNAs were identified by a computational pipeline, including a miRNA that shared a similar sequence to herpesvirus miRNA HSV2-miR-H4-5p, which suggests miRNAs are conserved in far related viruses. Generally, these 16 miRNAs are dispersed throughout the SGIV genome, whereas three are located within the ORF057L region. Some SGIV-encoded miRNAs showed marked sequence and length heterogeneity at their 3' and/or 5' end that could modulate their functions. Expression levels and potential biological activities of these viral miRNAs were examined by stem-loop quantitative RT-PCR and luciferase reporter assay, respectively, and 11 of these viral miRNAs were present and functional in SGIV-infected GP cells. CONCLUSIONS: Our study provided a genome-wide view of miRNA production for iridoviruses and identified 16 novel viral miRNAs. To the best of our knowledge, this is the first experimental demonstration of miRNAs encoded by aquatic animal viruses. The results provide a useful resource for further in-depth studies on SGIV infection and iridovirus pathogenesis

Online Survival Analysis Software to Assess the Prognostic Value of Biomarkers Using Transcriptomic Data in Non-Small-Cell Lung Cancer

In the last decade, optimized treatment for non-small cell lung cancer had lead to improved prognosis, but the overall survival is still very short. To further understand the molecular basis of the disease we have to identify biomarkers related to survival. Here we present the development of an online tool suitable for the real-time meta-analysis of published lung cancer microarray datasets to identify biomarkers related to survival. We searched the caBIG, GEO and TCGA repositories to identify samples with published gene expression data and survival information. Univariate and multivariate Cox regression analysis, Kaplan-Meier survival plot with hazard ratio and logrank P value are calculated and plotted in R. The complete analysis tool can be accessed online at: www.kmplot.com/lung. All together 1,715 samples of ten independent datasets were integrated into the system. As a demonstration, we used the tool to validate 21 previously published survival associated biomarkers. Of these, survival was best predicted by CDK1 (p<1E-16), CD24 (p<1E-16) and CADM1 (p = 7E-12) in adenocarcinomas and by CCNE1 (p = 2.3E-09) and VEGF (p = 3.3E-10) in all NSCLC patients. Additional genes significantly correlated to survival include RAD51, CDKN2A, OPN, EZH2, ANXA3, ADAM28 and ERCC1. In summary, we established an integrated database and an online tool capable of uni- and multivariate analysis for in silico validation of new biomarker candidates in non-small cell lung cancer

Fatigue-induced changes of impedance and performance in target tracking

Kinematic variability is caused, in part, by force fluctuations. It has been shown empirically and numerically that the effects of force fluctuations on kinematics can be suppressed by increasing joint impedance. Given that force variability increases with muscular fatigue, we hypothesized that joint impedance would increase with fatigue to retain a prescribed accuracy level. To test this hypothesis, subjects tracked a target by elbow flexion and extension both with fatigued and unfatigued elbow flexor and extensor muscles. Joint impedance was estimated from controlled perturbations to the elbow. Contrary to the hypothesis, elbow impedance decreased, whereas performance, expressed as the time-on-target, was unaffected by fatigue. Further analysis of the data revealed that subjects changed their control strategy with increasing fatigue. Although their overall kinematic variability increased, task performance was retained by staying closer to the center of the target when fatigued. In conclusion, the present study reveals a limitation of impedance modulation in the control of movement variability

α-Adducin Gly460Trp Gene Mutation and Essential Hypertension in a Chinese Population: A Meta-Analysis including 10960 Subjects

BACKGROUND: The α-adducin Gly460Trp (G460W) gene polymorphism may be associated with susceptibility to essential hypertension (EH), but this relationship remains controversial. In an attempt to resolve this issue, we conducted a meta-analysis. METHODS: Twenty-three separated studies involving 5939 EH patients and 5021 controls were retrieved and analyzed. Four ethnicities were included: Han, Kazakh, Mongolian, and She. Eighteen studies with 5087 EH patients and 4183 controls were included in the Han subgroup. Three studies with 636 EH patients and 462 controls were included in the Kazakh subgroup. The Mongolian subgroup was represented by only one study with 100 EH patients and 50 controls; similarly, only one study with 116 EH patients and 326 controls was available for the She subgroup. The pooled and ethnic group odds ratios (ORs) along with the corresponding 95% confidence intervals (95% CI) were assessed using a random effects model. RESULTS: There was a significant association between the α-adducin G460W gene polymorphism and EH in the pooled Chinese population under both an allelic genetic model (OR: 1.12, 95% CI: 1.04-1.20, P = 0.002) and a recessive genetic model (OR: 1.40, 95% CI: 1.16-1.70, P = 0.0005). In contrast, no significant association between the α-adducin G460W gene polymorphism and EH was observed in the dominant genetic model (OR: 0.88, 95% CI: 0.72-1.09, P = 0.24). In stratified analysis by ethnicity, significantly increased risk was detected in the Han subgroup under an allelic genetic model (OR: 1.13, 95% CI: 1.04-1.23, P = 0.003) and a recessive genetic model (OR: 1.43, 95% CI: 1.17-1.75, P = 0.0006). CONCLUSIONS: In a Chinese population of mixed ethnicity, the α-adducin G460W gene polymorphism was linked to EH susceptibility, most strongly in Han Chinese