Tests of scaling assumptions and construct validity of the Chinese (HK) version of the SF-36 Health Survey

Few health-related quality of life (HRQOL) survey instruments are available to the Chinese, although many have been developed for Western populations. This article describes the testing of the acceptability, conceptual equivalence, scaling assumptions and construct validity of a Chinese (HK [Hong Kong]) version of the MOS SF-36 Health Survey. A Chinese (HK) SF-36 survey form was developed by an iterative translation process. It was administered to 236 Chinese subjects who also rated the understanding, difficulty, relevance, and acceptability of each question. The scores were tested against the original scaling assumptions. The SF-36 profile of our subjects was compared to U.S. results for conceptual equivalence. Most subjects did not have any problem in understanding and answering the SF-36. Item means were generally clustered as hypothesized. All but a few items satisfied all scaling assumptions. The shape of the eight-scale SF-36 profile was similar to that of American patients, suggesting conceptual equivalence. We conclude that the Chinese (HK) version of the SF-36 Health Survey has achieved conceptual equivalence and satisfied the psychometric scaling assumptions well enough to warrant further use and testing, using the standard scoring algorithms.postprin

One-to-many laser fanout generated by single large-size two-dimensional holographic photonic crystal

The phenomenon of one-to-many laser fanout in large-size two-dimensional (2D) holographic photonic crystals (H-PhCs) is presented. Theoretical analysis demonstrates that the phenomenon is induced by multiple substrate waveguiding effect of 2D H-PhCs, and the orientations of the waveguided beams depend on the lattice structures of 2D H-PhCs. The fanout angle and separations between output spots are determined by lambda/d, light incident angle and thickness of glass substrate, therefore can be controlled via fabricating special lattice structures. The phenomenon has the potential to enable the application of 2D PhCs as interconnection devices in optical networks. (c) 2005 American Institute of Physics

Probing the Interplay between Quantum Charge Fluctuations and Magnetic Ordering in LuFe2O4

Ferroelectric and ferromagnetic materials possess spontaneous electric and magnetic order, respectively, which can be switched by the corresponding applied electric and magnetic fields. Multiferroics combine these properties in a single material, providing an avenue for controlling electric polarization with a magnetic field and magnetism with an electric field. These materials have been intensively studied in recent years, both for their fundamental scientific interest as well as their potential applications in a broad range of magnetoelectric devices [1, 2, 3, 4]. However, the microscopic origins of magnetism and ferroelectricity are quite different, and the mechanisms producing strong coupling between them are not always well understood. Hence, gaining a deeper understanding of magnetoelectric coupling in these materials is the key to their rational design. Here, we use ultrafast optical spectroscopy to show that quantum charge fluctuations can govern the interplay between electric polarization and magnetic ordering in the charge-ordered multiferroic LuFe2O4

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

Residual hepatocellular carcinoma after oxaliplatin treatment has increased metastatic potential in a nude mouse model and is attenuated by Songyou Yin

<p>Abstract</p> <p>Background</p> <p>The opposite effects of chemotherapy, which enhance the malignancy of treated cancers such as hepatocellular carcinoma (HCC), are not well understood. We investigated this phenomenon and corresponding mechanisms to develop a novel approach for improving chemotherapy efficacy in HCC.</p> <p>Methods</p> <p>Human hepatocellular carcinoma cell lines HepG2 (with low metastatic potential) and MHCC97L (with moderate metastatic potential) were used for the in vitro study. An orthotopic nude mouse model of human HCC was developed using MHCC97L cells. We then assessed the metastatic potential of surviving tumor cells after in vitro and in vivo oxaliplatin treatment. The molecular changes in surviving tumor cells were evaluated by western blot, immunofluorescence, and immunohistochemistry. The Chinese herbal extract Songyou Yin (composed of five herbs) was investigated in vivo to explore its effect on the metastatic potential of oxaliplatin-treated cancer cells.</p> <p>Results</p> <p>MHCC97L and HepG2 cells surviving oxaliplatin treatment showed enhanced migration and invasion in vitro. Residual HCC after in vivo oxaliplatin treatment demonstrated significantly increased metastasis to the lung (10/12 vs. 3/12) when re-inoculated into the livers of new recipient nude mice. Molecular changes consistent with epithelial-mesenchymal transition (EMT) were observed in oxaliplatin-treated tumor tissues and verified by in vitro experiments. The Chinese herbal extract Songyou Yin (4.2 and 8.4 g/kg) attenuated EMT and inhibited the enhanced metastatic potential of residual HCC in nude mice (6/15 vs. 13/15 and 3/15 vs. 13/15, respectively).</p> <p>Conclusions</p> <p>The surviving HCC after oxaliplatin treatment underwent EMT and demonstrated increased metastatic potential. Attenuation of EMT by Songyou Yin may improve the efficacy of chemotherapy in HCC.</p

Feature Selection via Chaotic Antlion Optimization

Selecting a subset of relevant properties from a large set of features that describe a dataset is a challenging machine learning task. In biology, for instance, the advances in the available technologies enable the generation of a very large number of biomarkers that describe the data. Choosing the more informative markers along with performing a high-accuracy classification over the data can be a daunting task, particularly if the data are high dimensional. An often adopted approach is to formulate the feature selection problem as a biobjective optimization problem, with the aim of maximizing the performance of the data analysis model (the quality of the data training fitting) while minimizing the number of features used.This work was partially supported by the IPROCOM Marie Curie initial training network, funded through the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme FP7/2007-2013/ under REA grants agreement No. 316555, and by the Romanian National Authority for Scientific Research, CNDIUEFISCDI, project number PN-II-PT-PCCA-2011-3.2- 0917. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Health related quality of life measured by SF-36: a population-based study in Shanghai, China

<p>Abstract</p> <p>Background</p> <p>Health related quality of life (HRQL) is a research topic that has attracted increasing interests around the world over the past two decades. The 36-item Short Form (SF-36) is a commonly used instrument for measuring HRQL. However, the information on Chinese adults' quality of life is limited. This paper reports on the feasibility of using the Mandarin version of SF-36 to evaluate HRQL in the population of Shanghai, China.</p> <p>Methods</p> <p>A total of 1034 subjects were randomly sampled using a stratified multiple-stage sampling method in Shanghai. Demographic information was collected, and SF-36 was used to measure HRQL.</p> <p>Results</p> <p>Internal reliability coefficients were greater than 0.7 in six of the eight SF-36 dimensions, except social function and mental health. Intraclass correlation coefficients ranged from 0.689 to 0.972. Split-half reliability coefficients were higher than 0.9 in five SF-36 dimensions. Validity was assessed by factor analysis and correlation analysis. Our results were basically in accordance with the theoretical construction of SF-36. The average scores of most SF-36 dimensions were higher than 80. The primary influencing risk factors of HRQL included chronic diseases, age, frequency of activities, and geographical region, which were identified using multivariate stepwise regression.</p> <p>Conclusion</p> <p>Overall, HRQL in the population of Shanghai is quite good. The Mandarin version of SF-36 is a valid and reliable tool for assessing HRQL.</p

Identification of Direct Target Genes Using Joint Sequence and Expression Likelihood with Application to DAF-16

A major challenge in the post-genome era is to reconstruct regulatory networks from the biological knowledge accumulated up to date. The development of tools for identifying direct target genes of transcription factors (TFs) is critical to this endeavor. Given a set of microarray experiments, a probabilistic model called TRANSMODIS has been developed which can infer the direct targets of a TF by integrating sequence motif, gene expression and ChIP-chip data. The performance of TRANSMODIS was first validated on a set of transcription factor perturbation experiments (TFPEs) involving Pho4p, a well studied TF in Saccharomyces cerevisiae. TRANSMODIS removed elements of arbitrariness in manual target gene selection process and produced results that concur with one's intuition. TRANSMODIS was further validated on a genome-wide scale by comparing it with two other methods in Saccharomyces cerevisiae. The usefulness of TRANSMODIS was then demonstrated by applying it to the identification of direct targets of DAF-16, a critical TF regulating ageing in Caenorhabditis elegans. We found that 189 genes were tightly regulated by DAF-16. In addition, DAF-16 has differential preference for motifs when acting as an activator or repressor, which awaits experimental verification. TRANSMODIS is computationally efficient and robust, making it a useful probabilistic framework for finding immediate targets