SYSTOLIC IMPLEMENTATION OF THE WINOGRAD FOURIER TRANSFORM ALGORITHM.

A bit-level systolic array system is proposed for the Winograd Fourier transform algorithm. The design uses bit-serial arithmetic and, in common with other systolic arrays, features nearest neighbor interconnections, regularity, and high throughput. The short interconnections in this method contrast favorably with the long interconnections between butterflies required in the FFT. The structure is well suited to VLSI implementations. It is demonstrated how long transforms can be implemented with components designed to perform short-length transforms. These components build into longer transforms, preserving the regularity and structure of the short-length transform design.

Reconfigurable full-search video motion estimation architecture

In this paper, a new reconfigurable multi-standard architecture is introduced for integer-pixel motion estimation and a standard-cell based chip design study is presented. This has been designed to cover most of the common block-based video compression standards, including MPEG-2, MPEG-4, H.263, H.264, AVS and WMV-9. The architecture exhibits simpler control, high throughput and relative low hardware cost and highly competitive when compared with excising designs for specific video standards. It can also, through the use of control signals, be dynamically reconfigured at run-time to accommodate different system constraint such as the trade-off in power dissipation and video-quality. The computational rates achieved make the circuit suitable for high end video processing applications. Silicon design studies indicate that circuits based on this approach incur only a relatively small penalty in terms of power dissipation and silicon area when compared with implementations for specific standards.

TMAX – a Database System Integrating Tissue Biomarker & Genomic Data

Background: Popular approaches in human tissue-based biomarker discovery include tissue microarrays (TMAs) and DNA Microarrays (DMAs) for protein and gene expression profiling respectively. The data generated by these analytic platforms, together with associated image, clinical and pathological data currently reside on widely different information platforms, making searching and cross-platform analysis difficult. Consequently, there is a strong need to develop a single coherent database capable of correlating all available data types.

Method: This study presents TMAX, a database system to facilitate biomarker discovery tasks. TMAX organises a variety of biomarker discovery-related data into the database. Both TMA and DMA experimental data are integrated in TMAX and connected through common DNA/protein biomarkers. Patient clinical data (including tissue pathological data), computer assisted tissue image and associated analytic data are also included in TMAX to enable the truly high throughput processing of ultra-large digital slides for both TMAs and whole slide tissue digital slides. A comprehensive web front-end was built with embedded XML parser software and predefined SQL queries to enable rapid data exchange in the form of standard XML files.

Results & Conclusion: TMAX represents one of the first attempts to integrate TMA data with public gene expression experiment data. Experiments suggest that TMAX is robust in managing large quantities of data from different sources (clinical, TMA, DMA and image analysis). Its web front-end is user friendly, easy to use, and most importantly allows the rapid and easy data exchange of biomarker discovery related data. In conclusion, TMAX is a robust biomarker discovery data repository and research tool, which opens up the opportunities for biomarker discovery and further integromics research.

Entinostat prevents leukemia maintenance in a collaborating oncogene-dependent model of CN-AML.

The incidence of refractory acute myeloid leukemia (AML) is on the increase due in part to an aging population that fails to respond to traditional therapies. High throughput genomic analysis promises better diagnosis, prognosis and therapeutic intervention based on improved patient stratification. Relevant pre-clinical models are urgently required to advance drug development in this area. The collaborating oncogenes, HOXA9 and MEIS1, are frequently co-overexpressed in cytogenetically normal AML (CN-AML) and a conditional transplantation mouse model was developed that demonstrated oncogene-dependency and expression levels comparable to CN-AML patients. Integration of gene signatures obtained from the mouse model and a cohort of CN-AML patients using statistically significant connectivity Map (sscMap) analysis identified Entinostat as a drug with the potential to alter the leukemic condition towards the normal state. Ex vivo treatment of leukemic cells, but not age-matched normal bone marrow controls, with Entinostat validated the gene signature and resulted in reduced viability in liquid culture, impaired colony formation and loss of the leukemia initiating cell. Furthermore, in vivo treatment with Entinostat resulted in prolonged survival of leukemic mice. This study demonstrates that the HDAC inhibitor Entinostat inhibits disease maintenance and prolongs survival in a clinically relevant murine model of cytogenetically normal AML. © 2013 AlphaMed Press

Klebsiella pneumoniae targets an EGF receptor-dependent pathway to subvert inflammation

The NF-kB transcriptional factor plays a key role governing the activation of immune responses. Klebsiella pneumoniae is an important cause of community-acquired and nosocomial pneumonia. Evidence indicates that K. pneumoniae infections are characterized by lacking an early in?ammatory response. Recently, we have demonstrated that Klebsiella antagonizes the activation of NF-kB via the deubiquitinase CYLD. In this work, by applying a high-throughput siRNA gain-of-function screen interrogating the human kinome, we identi?ed 17 kinases that when targeted by siRNA restored IL-1b-dependent NF-kB translocation in infected cells. Further characterization revealed that K. pneumoniae activates an EGF receptor (EGFR)- phosphatidylinositol 3-OH kinase (PI3K)–AKT–PAK4–ERK–GSK3b signalling pathway to attenuate the cytokine-dependent nuclear translocation of NF-kB. Our data also revealed that CYLD is a downstream effector of K. pneumoniae-induced EGFR–
PI3K–AKT–PAK4–ERK–GSK3b signalling pathway. Our efforts to identify the bacterial factor(s) responsible for EGFR activation demonstrate that a capsule (CPS) mutant did not activate EGFR hence
suggesting that CPS could mediate the activation of EGFR. Supporting this notion, puri?ed CPS did activate EGFR as well as the EGFR-dependent PI3K–AKT–PAK4–ERK–GSK3b signalling pathway. CPS-mediated EGFR activation was dependent on a TLR4–MyD88–c-SRC-dependent pathway. Several promising drugs have been developed to antagonize this cascade. We propose that agents targeting this signalling pathway might provide selective alternatives for the management of K. pneumoniae pneumonias.

The topography of DNA methylation in the non-neoplastic colonic mucosa surrounding colorectal cancers

The degree of gene hypermethylation in non-neoplastic colonic mucosa (NNCM) is a potentially important event in the development of colorectal cancer (CRC), particularly for the subgroup with a CpG island methylator phenotype (CIMP). In this study, we aimed to use an unbiased and high-throughput approach to evaluate the topography of DNA methylation in the non-neoplastic colonic mucosa (NNCM) surrounding colorectal cancer (CRC). A total of 61 tissue samples comprising 53 NNCM and 8 tumor samples were obtained from hemicolectomy specimens of two CRC patients (Cases 1 and 2). NNCM was stripped from the underlying colonic wall and samples taken at varying distances from the tumor. The level of DNA methylation in NNCM and tumor tissues was assessed at 1,505 CpG sites in 807 cancer-related genes using Illumina GoldenGate® methylation arrays. Case 1 tumor showed significantly higher levels of methylation compared to surrounding NNCM samples (P?

Development of a Portable Tissue Micro Array Instrument

Tissue micro array (TMA) is based on the idea of applying miniaturization and a high throughput approach to hybridization-based analyses of tissues. It facilitates biomedical research on a large scale in a single experiment; thus representing one of the most commonly used technologies in translational research. A critical analysis of the existing TMA instruments indicates that there are potential constraints in terms of portability, apart from costs and complexity. This paper will present the development of an affordable, configurable, and portable TMA instrument to allow an efficient collection of tissues, especially in instrument-to-tissue scenarios. The purely mechanical instrument requires no energy sources other than the user, is light weight, portable, and simple to use. [DOI: 10.1115/1.4004922]

Genetic and Epigenetic Risk Factors for Diabetic Kidney Disease

Diabetes is increasing at daunting rates worldwide, and approximately 40% of affected individuals will develop kidney complications. Diabetic kidney disease (DKD) is the leading cause of end-stage kidney disease, and there are significant healthcare costs providing appropriate renal replacement therapies to affected individuals. For several decades, investigators have sought to discover inherited risk factors and biomarkers for DKD. In recent years, advances in high-throughput laboratory techniques and computational analyses, coupled with the establishment of multicenter consortia, have helped to identify genetic loci that are replicated across multiple populations. Several genome-wide association studies (GWAS) have been conducted for DKD with further meta-analysis of GWAS and comprehensive ”single gene” meta-analyses now published. Despite these efforts, much of the inherited predisposition to DKD remains unexplained. Meta-analyses and integrated–omics pathway studies are being used to help elucidate underlying genetic risks. Epigenetic phenomena are increasingly recognized as important drivers of disease risk, and several epigenome-wide association studies have now been completed. This review describes key findings and ongoing genetic and epigenetic initiatives for DKD.

Personalized medicine: Has it started yet? A reconstruction of the early history

Within the last few years the field personalized medicine entered the stage. Accompanied with great hopes and expectations it is believed that this field may have the potential to revolutionize medical and clinical care by utilizing genomics information about the individual patients themselves. In this paper, we reconstruct the early footprints of personalized medicine as reflected by information retrieved from PubMed and Google Scholar. That means we are providing a data-driven perspective of this field to estimate its current status and potential problems.

cudaMap: a GPU accelerated program for gene expression connectivity mapping

Background: Modern cancer research often involves large datasets and the use of sophisticated statistical techniques. Together these add a heavy computational load to the analysis, which is often coupled with issues surrounding data accessibility. Connectivity mapping is an advanced bioinformatic and computational technique dedicated to therapeutics discovery and drug re-purposing around differential gene expression analysis. On a normal desktop PC, it is common for the connectivity mapping task with a single gene signature to take >2h to complete using sscMap, a popular Java application that runs on standard CPUs (Central Processing Units). Here, we describe new software, cudaMap, which has been implemented using CUDA C/C++ to harness the computational power of NVIDIA GPUs (Graphics Processing Units) to greatly reduce processing times for connectivity mapping.

Results: cudaMap can identify candidate therapeutics from the same signature in just over thirty seconds when using an NVIDIA Tesla C2050 GPU. Results from the analysis of multiple gene signatures, which would previously have taken several days, can now be obtained in as little as 10 minutes, greatly facilitating candidate therapeutics discovery with high throughput. We are able to demonstrate dramatic speed differentials between GPU assisted performance and CPU executions as the computational load increases for high accuracy evaluation of statistical significance.

Conclusion: Emerging 'omics' technologies are constantly increasing the volume of data and information to be processed in all areas of biomedical research. Embracing the multicore functionality of GPUs represents a major avenue of local accelerated computing. cudaMap will make a strong contribution in the discovery of candidate therapeutics by enabling speedy execution of heavy duty connectivity mapping tasks, which are increasingly required in modern cancer research. cudaMap is open source and can be freely downloaded from http://purl.oclc.org/NET/cudaMap.

Cancer drug resistance:an evolving paradigm

Resistance to chemotherapy and molecularly targeted therapies is a major problem facing current cancer research. The mechanisms of resistance to 'classical' cytotoxic chemotherapeutics and to therapies that are designed to be selective for specific molecular targets share many features, such as alterations in the drug target, activation of prosurvival pathways and ineffective induction of cell death. With the increasing arsenal of anticancer agents, improving preclinical models and the advent of powerful high-throughput screening techniques, there are now unprecedented opportunities to understand and overcome drug resistance through the clinical assessment of rational therapeutic drug combinations and the use of predictive biomarkers to enable patient stratification.

Multi-standard sub-pixel interpolation architecture for video motion estimation

A new domain-specific reconfigurable sub-pixel interpolation architecture for multi-standard video Motion Estimation (ME) is presented. The mixed use of parallel and serial-input FIR filters achieves high throughput rate and efficient silicon utilisation. Flexibility has been achieved by using a multiplexed reconfigurable data-path controlled by a selection signal. Silicon design studies show that this can be implemented using 34.8K gates with area and performance that compares very favourably with existing fixed solutions based solely on the H.264 standard. ©2008 IEEE.

qPCR utilization for the study of RNA Polymerase I transcription

Ribosome biogenesis is a fundamental cellular process tightly linked to cell growth and proliferation, which requires the coordinated transcription of all three nuclear polymerases. Synthesis of ribosomal RNA (rRNA) by RNA polymerase I (Pol I) has been suggested as a key regulator of ribosome biogenesis, and there is a strong link between transcription of ribosomal RNAs and cellular proliferation. This makes Pol I transcription a valid and attractive target for anticancer therapy. At the moment however there are only a small number of compounds that act as specific inhibitors of Pol I transcription and this makes it very difficult for the development of drugs which would target rRNA transcription and consequently ribosome biogenesis. Therefore, to aid in the development of new inhibitors of Pol I, high-throughput methods to monitor and detect changes in Pol I activity need to be developed. This current study aimed to address the question of whether or not quantitative PCR (qPCR) could be used to detect changes in rRNA production in cells under different conditions that repress Pol I activity i.e. serum starvation and drug treatment. Our results have shown that using primers and a hydrolysis probe designed for the 5’ETS region of the pre-rRNA molecule, rRNA levels in both treated and untreated cells could be determined by using qPCR.
Amplification resulted in formation of a single product and S1 nuclease protection assay confirmed the down-regulation of Pol I transcription. Following serum-starvation and drug treatment there was a dramatic reduction in the amount of 5’ETS transcript quantitated by both Sybr Green chemistry and the use of a fluorescently labelled hydrolysis probe. The optimization of the qPCR strategy will be discussed.

Improved Detection of Mycobacterium bovis in Bovine Tissues Using Immunomagnetic Separation Approaches

Immunomagnetic separation (IMS) represents a simple but effective method of selectively capturing and concentrating Mycobacterium bovis, the causative agent of bovine tuberculosis (bTB), from tissue samples. It is a physical cell separation technique that does not impact cell viability, unlike traditional chemical decontamination prior to culture. IMS is performed with paramagnetic beads coated with M. bovis-specific antibody and peptide binders. Once captured by IMS, M. bovis cells can be detected by either PCR or cultural detection methods. Increased detection rates of M. bovis, particularly from non-visibly lesioned lymph node tissues from bTB reactor animals, have recently been reported when IMS-based methods were employed.

Multimedia Resource Allocation in mmWave 5G Networks

The 5G network infrastructure is driven by the evolution of today's most demanding applications. Already, multimedia applications such as on-demand HD video and IPTV require gigabit- per-second throughput and low delay, while future technologies include ultra HDTV and machine-to-machine communication. Mm-Wave technologies such as IEEE 802.15.3c and IEEE 802.11ad are ideal candidates to deliver high throughput to multiple users demanding differentiated QoS. Optimization is often used as a methodology to meet throughput and delay constraints. However, traditional optimization techniques are not suited to a mixed set of multimedia applications. Particle swarm optimization (PSO) is shown as a promising technique in this context. Channel-time allocation PSO (CTA-PSO) is successfully shown here to allocate resource even in scenarios where blockage of the 60 GHz signal poses significant challenges.