Effect of groundwater composition on arsenic detection by bacterial biosensors.

A luminescent bacterial biosensor was used to quantify bioavailable arsenic in artificial groundwater. Its light production above the background emission was proportional to the arsenite concentration in the toxicologically relevant range of 0 to 0.5 mu M. Effects of the inorganic solutes phosphate, Fe(II) and silicate on the biosensor signal were studied. Phosphate at a concentration of 0.25 g L-1 phosphate slightly stimulated the light emission, but much less than toxicologically relevant concentrations of the much stronger inducer arsenite. No effect of phosphate was oberved in the presence of arsenite. Freshly prepared sodium silicate solution at a concentration of 10 g L-1 Si reduced the arsenite-induced light production by roughly 37%, which can be explained by transient polymerization leading to sequestration of some arsenic. After three days of incubation, silicate did not have this effect anymore, probably because depolymerization occurred. In the presence of 0.4 g L-1 Fe(II), the arsenite-induced light emission was reduced by up to 90%, probably due to iron oxidation followed by arsenite adsorption on the less soluble Fe(III) possibly along with some oxidation to the stronger adsorbing As(V). Addition of 100 mu M EDTA was capable of releasing all arsenic from the precipitate and to transform it into the biologically measurable, dissolved state. The biosensor also proved valuable for monitoring the effectiveness of an arsenic removal procedure based on water filtration through a mixture of sand and iron granules.

Detection of neuronal activity and metabolism in a model of dehydration-induced anorexia in rats at 14.1 T using manganese-enhanced MRI and 1H MRS.

In this study, hypothalamic activation was performed by dehydration-induced anorexia (DIA) and overnight food suppression (OFS) in female rats. The assessment of the hypothalamic response to these challenges by manganese-enhanced MRI showed increased neuronal activity in the paraventricular nuclei (PVN) and lateral hypothalamus (LH), both known to be areas involved in the regulation of food intake. The effects of DIA and OFS were compared by generating T-score maps. Increased neuronal activation was detected in the PVN and LH of DIA rats relative to OFS rats. In addition, the neurochemical profile of the PVN and LH were measured by (1) H MRS at 14.1T. Significant increases in metabolite levels were measured in DIA and OFS relative to control rats. Statistically significant increases in γ-aminobutyric acid were found in DIA (p=0.0007) and OFS (p<0.001) relative to control rats. Lactate increased significantly in DIA (p=0.03), but not in OFS, rats. This work shows that manganese-enhanced MRI coupled to (1) H MRS at high field is a promising noninvasive method for the investigation of the neural pathways and mechanisms involved in the control of food intake, in the autonomic and endocrine control of energy metabolism and in the regulation of body weight.

Illuminating the detection chain of bacterial bioreporters.

Engineering bacteria for measuring chemicals of environmental or toxicological concern (bioreporter bacteria) has grown slowly into a mature research area. Despite many potential advantages, current bioreporters do not perform well enough to comply with environmental detection standards. Basically, the reasons for this are the lack of engineering principles in the detection chain in the bioreporters. Here, we dissect critical steps in the detection chain and illustrate how bioreporter design could be improved by mutagenizing specificity and selectivity of the sensing and regulatory proteins, by newer expression strategies and application of different signalling networks. Furthermore, we describe how redesigning bioreporter assays with respect to pollutant transport into the cells and application of other detection devices can decrease detection limits and increase the speed of detection.

Tunable reporter signal production in feedback-uncoupled arsenic bioreporters.

Escherichia coli-based bioreporters for arsenic detection are typically based on the natural feedback loop that controls ars operon transcription. Feedback loops are known to show a wide range linear response to the detriment of the overall amplification of the incoming signal. While being a favourable feature in controlling arsenic detoxification for the cell, a feedback loop is not necessarily the most optimal for obtaining highest sensitivity and response in a designed cellular reporter for arsenic detection. Here we systematically explore the effects of uncoupling the topology of arsenic sensing circuitry on the developed reporter signal as a function of arsenite concentration input. A model was developed to describe relative ArsR and GFP levels in feedback and uncoupled circuitry, which was used to explore new ArsR-based synthetic circuits. The expression of arsR was then placed under the control of a series of constitutive promoters, which differed in promoter strength, and which could be further modulated by TetR repression. Expression of the reporter gene was maintained under the ArsR-controlled Pars promoter. ArsR expression in the systems was measured by using ArsR-mCherry fusion proteins. We find that stronger constitutive ArsR production decreases arsenite-dependent EGFP output from Pars and vice versa. This leads to a tunable series of arsenite-dependent EGFP outputs in a variety of systematically characterized circuitries. The higher expression levels and sensitivities of the response curves in the uncoupled circuits may be useful for improving field-test assays using arsenic bioreporters.

Capacity-approaching rate function for layered multiantenna architectures

The simultaneous use of multiple transmit and receive antennas can unleash very large capacity increases in rich multipath environments. Although such capacities can be approached by layered multi-antenna architectures with per-antenna rate control, the need for short-term feedback arises as a potential impediment, in particular as the number of antennas—and thus the number of rates to be controlled—increases. What we show, however, is that the need for short-term feedback in fact vanishes as the number of antennas and/or the diversity order increases. Specifically, the rate supported by each transmit antenna becomes deterministic and a sole function of the signal-to-noise, the ratio of transmit and receive antennas, and the decoding order, all of which are either fixed or slowly varying. More generally, we illustrate -through this specific derivation— the relevance of some established random CDMA results to the single-user multi-antenna problem.

On high-rate full-diversity 2x2 space-time codes with low-complexity optimum detection

The 2×2 MIMO profiles included in Mobile WiMAX specifications are Alamouti’s space-time code (STC) fortransmit diversity and spatial multiplexing (SM). The former hasfull diversity and the latter has full rate, but neither of them hasboth of these desired features. An alternative 2×2 STC, which is both full rate and full diversity, is the Golden code. It is the best known 2×2 STC, but it has a high decoding complexity. Recently, the attention was turned to the decoder complexity, this issue wasincluded in the STC design criteria, and different STCs wereproposed. In this paper, we first present a full-rate full-diversity2×2 STC design leading to substantially lower complexity ofthe optimum detector compared to the Golden code with only a slight performance loss. We provide the general optimized form of this STC and show that this scheme achieves the diversitymultiplexing frontier for square QAM signal constellations. Then, we present a variant of the proposed STC, which provides a further decrease in the detection complexity with a rate reduction of 25% and show that this provides an interesting trade-off between the Alamouti scheme and SM.

Multiuser detection in a dynamic environment — Part II: Joint user identification and parameter estimation

The problem of jointly estimating the number, the identities, and the data of active users in a time-varying multiuser environment was examined in a companion paper (IEEE Trans. Information Theory, vol. 53, no. 9, September 2007), at whose core was the use of the theory of finite random sets on countable spaces. Here we extend that theory to encompass the more general problem of estimating unknown continuous parameters of the active-user signals. This problem is solved here by applying the theory of random finite sets constructed on hybrid spaces. We doso deriving Bayesian recursions that describe the evolution withtime of a posteriori densities of the unknown parameters and data.Unlike in the above cited paper, wherein one could evaluate theexact multiuser set posterior density, here the continuous-parameter Bayesian recursions do not admit closed-form expressions. To circumvent this difficulty, we develop numerical approximationsfor the receivers that are based on Sequential Monte Carlo (SMC)methods (“particle filtering”). Simulation results, referring to acode-divisin multiple-access (CDMA) system, are presented toillustrate the theory.

A systolic array for linear MIMO detection based on an all-swap lattice reduction algorithm

A systolic array to implement lattice-reduction-aided lineardetection is proposed for a MIMO receiver. The lattice reductionalgorithm and the ensuing linear detections are operated in the same array, which can be hardware-efficient. All-swap lattice reduction algorithm (ASLR) is considered for the systolic design.ASLR is a variant of the LLL algorithm, which processes all lattice basis vectors within one iteration. Lattice-reduction-aided linear detection based on ASLR and LLL algorithms have very similarbit-error-rate performance, while ASLR is more time efficient inthe systolic array, especially for systems with a large number ofantennas.

Enhanced sensitivity detection of protein immobilization by fluorescent interference on oxidized silicon.

We present a silicon chip-based approach for the enhanced sensitivity detection of surface-immobilized fluorescent molecules. Green fluorescent protein (GFP) is bound to the silicon substrate by a disuccinimidyl terephtalate-aminosilane immobilization procedure. The immobilized organic layers are characterized by surface analysis techniques, like ellipsometry, atomic force microscopy (AFM) and X-ray induced photoelectron spectroscopy. We obtain a 20-fold enhancement of the fluorescent signal, using constructive interference effects in a fused silica dielectric layer, deposited before immobilization onto the silicon. Our method opens perspectives to increase by an order of magnitude the fluorescent response of surface immobilized DNA- or protein-based layers for a variety of biosensor applications.

Signal search analysis server.

Signal search analysis is a general method to discover and characterize sequence motifs that are positionally correlated with a functional site (e.g. a transcription or translation start site). The method has played an instrumental role in the analysis of eukaryotic promoter elements. The signal search analysis server provides access to four different computer programs as well as to a large number of precompiled functional site collections. The programs offered allow: (i) the identification of non-random sequence regions under evolutionary constraint; (ii) the detection of consensus sequence-based motifs that are over- or under-represented at a particular distance from a functional site; (iii) the analysis of the positional distribution of a consensus sequence- or weight matrix-based sequence motif around a functional site; and (iv) the optimization of a weight matrix description of a locally over-represented sequence motif. These programs can be accessed at: http://www.isrec.isb-sib.ch/ssa/.

A leverage theory of reputation building with co-branding: Complementarity in reputation building

We present a leverage theory of reputation building with co-branding. We showthat under certain conditions, co-branding that links unknown firms in a new sectorwith established firms in a mature sector allows the unknown firms to signal a highproduct quality and establish their own reputation. We compare this situationwith a benchmark in which both sectors are new and firms signal their qualityonly with prices. We investigate how this comparison is affected by the nature ofthe technology linking the two sectors and a cross-sector inference problem thatconsumers might face in identifying the true cause of product failure. We find thatco-branding facilitates the process in which a Þrm in the new sector to signal itsproduct quality only if the co-branding sectors produce complementary inputs andconsumers face a cross-sector inference problem. We apply our insight to economicsof superstars, multinational firms and co-authorship.

Self-paced Movement Intention Detection from Human Brain Signals: Invasive and Non-invasive EEG

Neural signatures of humans' movement intention can be exploited by future neuroprosthesis. We propose a method for detecting self-paced upper limb movement intention from brain signals acquired with both invasive and noninvasive methods. In the first study with scalp electroencephalograph (EEG) signals from healthy controls, we report single trial detection of movement intention using movement related potentials (MRPs) in a frequency range between 0.1 to 1 Hz. Movement intention can be detected above chance level (p<0.05) on average 460 ms before the movement onset with low detection rate during the on-movement intention period. Using intracranial EEG (iEEG) from one epileptic subject, we detect movement intention as early as 1500 ms before movement onset with accuracy above 90% using electrodes implanted in the bilateral supplementary motor area (SMA). The coherent results obtained with non-invasive and invasive method and its generalization capabilities across different days of recording, strengthened the theory that self-paced movement intention can be detected before movement initiation for the advancement in robot-assisted neurorehabilitation.