Up-regulation of GABA transporters and GABAA Receptor α1 subunit in tremor rat hippocampus

The loss of GABAergic neurotransmission has been closely linked with epileptogenesis. The modulation of the synaptic activity occurs both via the removal of GABA from the synaptic cleft and by GABA transporters (GATs) and by modulation of GABA receptors. The tremor rat (TRM; tm/tm) is the parent strain of the spontaneously epileptic rat (SER; zi/zi, tm/tm), which exhibits absence-like seizure after 8 weeks of age. However, there are no reports that can elucidate the effects of GATs and GABAA receptors (GABARs) on TRMs. The present study was conducted to detect GATs and GABAR a1 subunit in TRMs hippocampus at mRNA and protein levels. In this study, total synaptosomal GABA content was significantly decreased in TRMs hippocampus compared with control Wistar rats by high performance liquid chromatography (HPLC); mRNA and protein expressions of GAT-1, GAT-3 and GABAR a1 subunit were all significantly increased in TRMs hippocampus by real time PCR and western blot, respectively; GAT-1 and GABAR a1 subunit proteins were localized widely in TRMs and control rats hippocampus including CA1, CA3 and dentate gyrus (DG) regions whereas only a wide distribution of GAT-3 was observed in CA1 region by immunohistochemistry. These data demonstrate that excessive expressions of GAT-1 as well as GAT-3 and GABAR a1 subunit in TRMs hippocampus may provide the potential therapeutic targets for genetic epilepsy.

Commonality in Returns, Order Flows, and Liquidity in the Greek Stock Market

Using a unique high-frequency data-set on a comprehensive sample of Greek blue-chip stocks, spanning from September 2003 through March 2006, this note assesses the extent and role of commonality in returns, order flows (OFs), and liquidity. It also formally models aggregate equity returns in terms of aggregate equity OF, in an effort to clarify OF's importance in explaining returns for the Athens Exchange market. Almost a quarter of the daily returns in the FTSE/ATHEX20 index is explained by aggregate own OF. In a second step, using principal components and canonical correlation analyses, we document substantial common movements in returns, OFs, and liquidity, both on a market-wide basis and on an individual security basis. These results emphasize that asset pricing and liquidity cannot be analyzed in isolation from each other.

Behavioral plasticity allows short-term adjustment to a novel environment

Many species are currently experiencing anthropogenically driven environmental changes. Among these changes, increasing noise levels are specifically a problem for species relying on acoustic communication. Recent evidence suggests that some species adjust their acoustic signals to man-made noise. However, it is unknown whether these changes occur through short-term and reversible adjustments by behavioral plasticity or through long-term adaptations by evolutionary change. Using behavioral observations and playback experiments, we show that male reed buntings (Emberiza schoeniclus) adjusted their songs immediately, singing at a higher minimum frequency and at a lower rate when noise levels were high. Our data showed that these changes in singing behavior were short-term adjustments of signal characteristics resulting from behavioral plasticity, rather than a long-term adaptation. However, more males remained unpaired at a noisy location than at a quiet location throughout the breeding season. Thus, phenotypic plasticity enables individuals to respond to environmental changes, but whether these short-term adjustments are beneficial remains to be seen.

Inferring the conservative causal core of gene regulatory networks

Background
Inferring gene regulatory networks from large-scale expression data is an important problem that received much attention in recent years. These networks have the potential to gain insights into causal molecular interactions of biological processes. Hence, from a methodological point of view, reliable estimation methods based on observational data are needed to approach this problem practically.

Results
In this paper, we introduce a novel gene regulatory network inference (GRNI) algorithm, called C3NET. We compare C3NET with four well known methods, ARACNE, CLR, MRNET and RN, conducting in-depth numerical ensemble simulations and demonstrate also for biological expression data from E. coli that C3NET performs consistently better than the best known GRNI methods in the literature. In addition, it has also a low computational complexity. Since C3NET is based on estimates of mutual information values in conjunction with a maximization step, our numerical investigations demonstrate that our inference algorithm exploits causal structural information in the data efficiently.

Conclusions
For systems biology to succeed in the long run, it is of crucial importance to establish methods that extract large-scale gene networks from high-throughput data that reflect the underlying causal interactions among genes or gene products. Our method can contribute to this endeavor by demonstrating that an inference algorithm with a neat design permits not only a more intuitive and possibly biological interpretation of its working mechanism but can also result in superior results.

QR decomposition-based matrix inversion for high performance embedded MIMO receivers

Real-time matrix inversion is a key enabling technology in multiple-input multiple-output (MIMO) communications systems, such as 802.11n. To date, however, no matrix inversion implementation has been devised which supports real-time operation for these standards. In this paper, we overcome this barrier by presenting a novel matrix inversion algorithm which is ideally suited to high performance floating-point implementation. We show how the resulting architecture offers fundamentally higher performance than currently published matrix inversion approaches and we use it to create the first reported architecture capable of supporting real-time 802.11n operation. Specifically, we present a matrix inversion approach based on modified squared Givens rotations (MSGR). This is a new QR decomposition algorithm which overcomes critical limitations in other QR algorithms that prohibits their application to MIMO systems. In addition, we present a novel modification that further reduces the complexity of MSGR by almost 20%. This enables real-time implementation with negligible reduction in the accuracy of the inversion operation, or the BER of a MIMO receiver based on this.

Real-valued fixed-complexity sphere decoder for high dimensional QAM-MIMO systems

The development of high performance, low computational complexity detection algorithms is a key challenge for real-time Multiple-Input Multiple-Output (MIMO) communication system design. The Fixed-Complexity Sphere Decoder (FSD) algorithm is one of the most promising approaches, enabling quasi-ML decoding accuracy and high performance implementation due to its deterministic, highly parallel structure. However, it suffers from exponential growth in computational complexity as the number of MIMO transmit antennas increases, critically limiting its scalability to larger MIMO system topologies. In this paper, we present a solution to this problem by applying a novel cutting protocol to the decoding tree of a real-valued FSD algorithm. The new Real-valued Fixed-Complexity Sphere Decoder (RFSD) algorithm derived achieves similar quasi-ML decoding performance as FSD, but with an average 70% reduction in computational complexity, as we demonstrate from both theoretical and implementation perspectives for Quadrature Amplitude Modulation (QAM)-MIMO systems.

A Pipeline Interleaved Heterogeneous SIMD Soft Processor Array Architecture for MIMO-OFDM Detection

The most promising way to maintain reliable data transfer across the rapidly fluctuating channels used by next generation multiple-input multiple-output communications schemes is to exploit run-time variable modulation and antenna configurations. This demands that the baseband signal processing architectures employed in the communications terminals must provide low cost and high performance with runtime reconfigurability. We present a softcore-processor based solution to this issue, and show for the first time, that such programmable architectures can enable real-time data operation for cutting-edge standards
such as 802.11n; furthermore, by exploiting deep processing pipelines and interleaved task execution, the cost and performance of these architectures is shown to be on a par with traditional dedicated circuit based solutions. We believe this to be the first such programmable architecture to achieve this, and the combination of implementation efficiency and programmability makes this implementation style the most promising approach for hosting such dynamic architectures.

Structural influence of gene networks on their inference: analysis of C3NET

Background: The availability of large-scale high-throughput data possesses considerable challenges toward their functional analysis. For this reason gene network inference methods gained considerable interest. However, our current knowledge, especially about the influence of the structure of a gene network on its inference, is limited.

Raman spectroscopic studies of the cure of dicyclopentadiene (DCPD)

The cure of polydicyclopentadiene conducted by ring-opening metathesis polymerisation in the presence of a Grubbs catalyst was studied using non-invasive Raman spectroscopy. The spectra of the monomer precursor and polymerised product were fully characterised and all stages of polymerisation monitored. Because of the monomer's high reactivity, the cure process is adaptable to reaction injection moulding and reactive rotational moulding. The viscosity of the dicyclopentadiene undergoes a rapid change at the beginning of the polymerisation process and it is critical that the induction time of the viscosity increase is determined and controlled for successful manufacturing. The results from this work show non-invasive Raman spectroscopic monitoring to be an effective method for monitoring the degree of cure, paving the way for possible implementation of the technique as a method of real-time analysis for control and optimisation during reactive processing. Agreement is shown between Raman measurements and ultrasonic time of flight data acquired during the initial induction period of the curing process. (c) 2004 Elsevier B.V. All rights reserved.

Developments in Performance Monitoring of Concrete Exposed to Extreme Environments

The performance of the surface zone of concrete is acknowledged as a major factor governing the rate of deterioration of reinforced concrete structures as it provides the only barrier to the ingress of water containing dissolved ionic species such as chlorides which, ultimately, initiate corrosion of the reinforcement. In-situ monitoring of cover-zone concrete is therefore critical in attempting to make realistic predictions as to the in-service performance of the structure. To this end, this paper presents developments in a remote interrogation system to allow continuous, real-time monitoring of the cover-zone concrete from an office setting. Use is made of a multi-electrode array embedded within cover-zone concrete to acquire discretized electrical resistivity and temperature measurements, with both parameters monitored spatially and temporally. On-site instrumentation, which allows remote interrogation of concrete samples placed at a marine exposure site, is detailed, together with data handling and processing procedures. Site-measurements highlight the influence of temperature on electrical resistivity and an Arrhenius-based temperature correction protocol is developed using on-site measurements to standardize resistivity data to a reference temperature; this is an advancement over the use of laboratory-based procedures. The testing methodology and interrogation system represents a robust, low-cost and high-value technique which could be deployed for intelligent monitoring of reinforced concrete structures.

Detection of Voigt Spectral Line Profiles of Hydrogen Radio Recombination Lines toward Sagittarius B2(N)

We report the detection of Voigt spectral line profiles of radio recombination lines (RRLs) toward Sagittarius B2(N) with the 100 m Green Bank Telescope (GBT). At radio wavelengths, astronomical spectra are highly populated with RRLs, which serve as ideal probes of the physical conditions in molecular cloud complexes. An analysis of the Hn alpha lines presented herein shows that RRLs of higher principal quantum number (n > 90) are generally divergent from their expected Gaussian profiles and, moreover, are well described by their respective Voigt profiles. This is in agreement with the theory that spectral lines experience pressure broadening as a result of electron collisions at lower radio frequencies. Given the inherent technical difficulties regarding the detection and profiling of true RRL wing spans and shapes, it is crucial that the observing instrumentation produce flat baselines as well as high-sensitivity, high-resolution data. The GBT has demonstrated its capabilities regarding all of these aspects, and we believe that future observations of RRL emission via the GBT will be crucial toward advancing our knowledge of the larger-scale extended structures of ionized gas in the interstellar medium (ISM).

FPGA based Soft-core SIMD Processing: A MIMO-OFDM Fixed-Complexity Sphere Decoder Case Study

To enable reliable data transfer in next generation Multiple-Input Multiple-Output (MIMO) communication systems, terminals must be able to react to fluctuating channel conditions by having flexible modulation schemes and antenna configurations. This creates a challenging real-time implementation problem: to provide the high performance required of cutting edge MIMO standards, such as 802.11n, with the flexibility for this behavioural variability. FPGA softcore processors offer a solution to this problem, and in this paper we show how heterogeneous SISD/SIMD/MIMD architectures can enable programmable multicore architectures on FPGA with similar performance and cost as traditional dedicated circuit-based architectures. When applied to a 4×4 16-QAM Fixed-Complexity Sphere Decoder (FSD) detector we present the first soft-processor based solution for real-time 802.11n MIMO.

A Kernel Interleaved Scheduling Method for Streaming Applications on Soft-core Vector Processors

Massively parallel networks of highly efficient, high performance Single Instruction Multiple Data (SIMD) processors have been shown to enable FPGA-based implementation of real-time signal processing applications with performance and
cost comparable to dedicated hardware architectures. This is achieved by exploiting simple datapath units with deep processing pipelines. However, these architectures are highly susceptible to pipeline bubbles resulting from data and control hazards; the only way to mitigate against these is manual interleaving of
application tasks on each datapath, since no suitable automated interleaving approach exists. In this paper we describe a new automated integrated mapping/scheduling approach to map algorithm tasks to processors and a new low-complexity list scheduling technique to generate the interleaved schedules. When applied to a spatial Fixed-Complexity Sphere Decoding (FSD) detector
for next-generation Multiple-Input Multiple-Output (MIMO) systems, the resulting schedules achieve real-time performance for IEEE 802.11n systems on a network of 16-way SIMD processors on FPGA, enable better performance/complexity balance than current approaches and produce results comparable to handcrafted implementations.

First report of the use of a saxitoxin-protein conjugate to develop a DNA aptamer to a small molecule toxin

Saxitoxin (STX) is a low molecular weight neurotoxin mainly produced by certain marine dinoflagellates that, along with its family of similarly related paralytic shellfish toxins, may cause the potentially fatal intoxication known as paralytic shellfish poisoning. Illness and fatality rates are low due to the effective monitoring programs that determine when toxins exceed the established regulatory action level and effectuate shellfish harvesting closures accordingly. Such monitoring programs rely on the ability to rapidly screen large volumes of samples. Many of the screening assays currently available employ antibodies or live animals. This research focused on developing an analytical recognition element that would eliminate the challenges associated with the limited availability of antibodies and the use of animals. Here we report the discovery of a DNA aptamer that targets STX. Concentration-dependent and selective binding of the aptamer to STX was determined using a surface plasmon resonance sensor. Not only does this work represent the first reported aptamer to STX, but also the first aptamer to any marine biotoxin. A novel strategy of using a toxin-protein conjugate for DNA aptamer selection was successfully implemented to overcome the challenges associated with aptamer selection to small molecules. Taking advantage of such an approach could lead to increased diversity and accessibility of aptamers to low molecular weight toxins, which could then be incorporated as analytical recognition elements in diagnostic assays for foodborne toxin detection. The selected STX aptamer sequence is provided here, making it available to any investigator for use in assay development for the detection of STX.

VQ tree search system based on bit level systolic arrays

A bit-level systolic array system for performing a binary tree vector quantization (VQ) codebook search is described. This is based on a highly regular VLSI building block circuit. The system in question exhibits a very high data rate suitable for a range of real-time applications. A technique is described which reduces the storage requirements of such a system by 50%, with a corresponding decrease in hardware complexity.