DNA interaction and phosphotransfer of the C-4-dicarboxylate-responsive DcuS-DcuR two-component regulatory system from Escherichia coli

The DcuS-DcuR system of Escherichia coli is a two-component sensor-regulator that controls gene expression in response to external C-4-dicarboxylates and citrate. The DcuS protein is particularly interesting since it contains two PAS domains, namely a periplasmic C-4-dicarboxylate-sensing PAS domain (PASp) and a cytosolic PAS domain (PASc) of uncertain function. For a study of the role of the PASc domain, three different fragments of DcuS were overproduced and examined: they were PASc-kinase, PASc, and kinase. The two kinase-domain-containing fragments were autophosphorylated by [gamma-P-32]ATP. The rate was not affected by fumarate or succinate, supporting the role of the PASp domain in C-4-dicarboxylate sensing. Both of the phosphorylated DcuS constructs were able to rapidly pass their phosphoryl groups to DcuR, and after phosphorylation, DcuR dephosphorylated rapidly. No prosthetic group or significant quantity of metal was found associated with either of the PASc-containing proteins. The DNA-binding specificity of DcuR was studied by use of the pure protein. It was found to be converted from a monomer to a dimer upon acetylphosphate treatment, and native polyacrylamide gel electrophoresis suggested that it can oligomerize. DcuR specifically bound to the promoters of the three known DcuSR-regulated genes (dctA, dcuB, and frdA), with apparent K(D)s of 6 to 32 muM for untreated DcuR and less than or equal to1 to 2 muM for the acetylphosphate-treated form. The binding sites were located by DNase I footprinting, allowing a putative DcuR-binding motif [tandemly repeated (T/A)(A/T)(T/C)(A/T)AA sequences] to be identified. The DcuR-binding sites of the dcuB, dctA, and frdA genes were located 27, 94, and 86 bp, respectively, upstream of the corresponding +1 sites, and a new promoter was identified for dcuB that responds to DcuR.

A system for studying epithelial-stromal interactions reveals distinct inductive abilities of stromal cells from benign prostatic hyperplasia and prostate cancer

The development of normal and abnormal glandular structures in the prostate is controlled at the endocrine and paracrine levels by reciprocal interactions between epithelium and stroma. To study these processes it is useful to have an efficient method of tissue acquisition for reproducible isolation of cells from defined histologies. Here we assessed the utility of a standardized system for acquisition and growth of prostatic cells from different regions of the prostate with different pathologies, and we compared the abilities of stromal cells from normal peripheral zone (PZ-S), benign prostatic hyperplasia (BPH-S), and cancer (CA-S) to induce the growth of a human prostatic epithelial cell line (BPH-1) in vivo. Using the tissue recombination method, we showed that grafting stromal cells (from any histology) alone, or BPH-1 epithelial cells alone produced no visible grafts. Recombining PZ-S with BPH-1 cells also produced no visible grafts (n = 15). Recombining BPH-S with BPH-1 cells generated small, well-organized and sharply demarcated grafts approximately 3-4 mm in diameter (n = 9), demonstrating a moderate inductive ability of BPH-S. Recombining CA-S with BPH-1 cells generated highly disorganized grafts that completely surrounded the host kidney and invaded into adjacent renal tissue, demonstrating induction of an aggressive phenotype. We conclude that acquisition of tissue from toluidine blue dye stained specimens is an efficient method to generate high quality epithelial and/or stromal cultures. Stromal cells derived by this method from areas of BPH and cancer induce epithelial cell growth in vivo which mimics the natural history of these diseases.

Tachykinins regulate the function of platelets

Evidence has been mounting for peripheral functions for tachykinins, a family of neuropeptides including substance P (SP), neurokinin A, and neurokinin B, which are recognized for their roles in the central and peripheral nervous system. The recent discovery of 4 new members of this family, the endokinins (EKA, B, C, and 13), which are distributed peripherally, adds support to the notion that tachykinins have physiologic/endocrine roles in the periphery. In the present study we report a fundamental new function for tachykinins in the regulation of platelet function. We show that SP stimulates platelet aggregation, and underlying this is the intracellular mobilization of calcium and degranulation. We demonstrate the presence of the tachykinin receptors NK1 and NK3 in platelets and present evidence for the involvement of NK1 in SP-mediated platelet aggregation. Platelets were found to contain SP-like immunoreactivity that is secreted upon activation implicating SP-like substances in the autocrine/paracrine regulation of these cells. Indeed, NK1-blocking antibodies inhibited aggregation in response to other agonists. Of particular note is the observation that EKA/B cross-react in the SP immunoassay and are also able to stimulate platelet activation. Together our data implicate tachykinins, specifically SP and EKA/B, in the regulation of platelet function. (C) 2004 by The American Society of Hematology.

Extraction behavior of the synergistic system 2,6-bis-(benzoxazolyl)-4-dodecyloxylpyridine and 2-bromodecanoic acid using Am and Eu as radioactive tracers

In this study, the extraction properties of a synergistic system consisting of 2,6-bis-(benzoxazolyl)-4-dodecyloxylpyridine (BODO) and 2-bromodecanoic acid (HA) in tert-butyl benzene (TBB) have been investigated as a function of ionic strength by varying the nitrate ion and perchlorate ion concentrations. The influence of the hydrogen ion concentration has also been investigated. Distribution ratios between 0.03-12 and 0.003-0.8 have been found for Am(III) and Eu(HI), respectively, but there were no attempts to maximize these values. It has been shown that the distribution ratios decrease with increasing amounts of ClO4-, NO3-, and H+. The mechanisms, however, by which the decrease occurs, are different. In the case of increasing perchlorate ion concentration, the decrease in extraction is linear in a log-log plot of the distribution ratio vs. the ionic strength, while in the nitrate case the complexation between nitrate and Am or Eu increases at high nitrate ion concentrations and thereby decreases the distribution ratio in a non-linearway. The decrease in extraction could be caused by changes in activity coefficients that can be explained with specific ion interaction theory (SIT); shielding of the metal ions, and by nitrate complexation with Am and Eu as competing mechanism at high ionic strengths. The separation factor between Am and Eu reaches a maximum at similar to1 M nitrate ion concentration. Thereafter the values decrease with increasing nitrate ion concentrations.

Commentary on 'Prebiotics, immune function, infection and inflammation: a review of the evidence'

There is a growing awareness that the gut microbiota and an appropriately functioning immune system play an important role in maintaining human health. Recent population statistics have highlighted some worrying trends, specifically that there is a growing burden of immunological disease in Western populations, that Western populations are ageing, and that obesity, with its strong inflammatory component, is reaching epidemic proportions.

Hypothesis about mechanisms through which nicotine might exert its effect on the interdependence of inflammation and gut barrier function in ulcerative colitis

Ulcerative colitis (UC) is characterized by impairment of the epithelial barrier and the formation of ulcer-type lesions, which result in local leaks and generalized alterations of mucosal tight junctions. Ultimately, this results in increased basal permeability. Although disruption of the epithelial barrier in the gut is a hallmark of inflammatory bowel disease and intestinal infections, it remains unclear whether barrier breakdown is an initiating event of UC or rather a consequence of an underlying inflammation, evidenced by increased production of proinflammatory cytokines. UC is less common in smokers, suggesting that the nicotine in cigarettes may ameliorate disease severity. The mechanism behind this therapeutic effect is still not fully understood, and indeed it remains unclear if nicotine is the true protective agent in cigarettes. Nicotine is metabolized in the body into a variety of metabolites and can also be degraded to form various breakdown products. It is possible these metabolites or degradation products may be the true protective or curative agents. A greater understanding of the pharmacodynamics and kinetics of nicotine in relation to the immune system and enhanced knowledge of out permeability defects in UC are required to establish the exact protective nature of nicotine and its metabolites in UC. This review suggests possible hypotheses for the protective mechanism of nicotine in UC, highlighting the relationship between gut permeability and inflammation, and indicates where in the pathogenesis of the disease nicotine may mediate its effect.

Modelling the interdependence between the stoichiometry of receptor oligomerization and ligand binding for a coexisting dimer/tetramer receptor system

Many G protein-coupled receptors have been shown to exist as oligomers, but the oligomerization state and the effects of this on receptor function are unclear. For some G protein-coupled receptors, in ligand binding assays, different radioligands provide different maximal binding capacities. Here we have developed mathematical models for co-expressed dimeric and tetrameric species of receptors. We have considered models where the dimers and tetramers are in equilibrium and where they do not interconvert and we have also considered the potential influence of the ligands on the degree of oligomerization. By analogy with agonist efficacy, we have considered ligands that promote, inhibit or have no effect on oligomerization. Cell surface receptor expression and the intrinsic capacity of receptors to oligomerize are quantitative parameters of the equations. The models can account for differences in the maximal binding capacities of radioligands in different preparations of receptors and provide a conceptual framework for simulation and data fitting in complex oligomeric receptor situations.

Performance of GPRS coding scheme detection under severe multipath and co-channel interference as a function of soft-bit width

The General Packet Radio Service (GPRS) has been developed for the mobile radio environment to allow the migration from the traditional circuit switched connection to a more efficient packet based communication link particularly for data transfer. GPRS requires the addition of not only the GPRS software protocol stack, but also more baseband functionality for the mobile as new coding schemes have be en defined, uplink status flag detection, multislot operation and dynamic coding scheme detect. This paper concentrates on evaluating the performance of the GPRS coding scheme detection methods in the presence of a multipath fading channel with a single co-channel interferer as a function of various soft-bit data widths. It has been found that compressing the soft-bit data widths from the output of the equalizer to save memory can influence the likelihood decision of the coding scheme detect function and hence contribute to the overall performance loss of the system. Coding scheme detection errors can therefore force the channel decoder to either select the incorrect decoding scheme or have no clear decision which coding scheme to use resulting in the decoded radio block failing the block check sequence and contribute to the block error rate. For correct performance simulation, the performance of the full coding scheme detection must be taken into account.

Apodisation, denoising and system identification techniques for THz transients in the wavelet domain

This work describes the use of a quadratic programming optimization procedure for designing asymmetric apodization windows to de-noise THz transient interferograms and compares these results to those obtained when wavelet signal processing algorithms are adopted. A systems identification technique in the wavelet domain is also proposed for the estimation of the complex insertion loss function. The proposed techniques can enhance the frequency dependent dynamic range of an experiment and should be of particular interest to the THz imaging and tomography community. Future advances in THz sources and detectors are likely to increase the signal-to-noise ratio of the recorded THz transients and high quality apodization techniques will become more important, and may set the limit on the achievable accuracy of the deduced spectrum.

A fast identification algorithm for Box-Cox transformation based radial basis function neural network

In this letter, a Box-Cox transformation-based radial basis function (RBF) neural network is introduced using the RBF neural network to represent the transformed system output. Initially a fixed and moderate sized RBF model base is derived based on a rank revealing orthogonal matrix triangularization (QR decomposition). Then a new fast identification algorithm is introduced using Gauss-Newton algorithm to derive the required Box-Cox transformation, based on a maximum likelihood estimator. The main contribution of this letter is to explore the special structure of the proposed RBF neural network for computational efficiency by utilizing the inverse of matrix block decomposition lemma. Finally, the Box-Cox transformation-based RBF neural network, with good generalization and sparsity, is identified based on the derived optimal Box-Cox transformation and a D-optimality-based orthogonal forward regression algorithm. The proposed algorithm and its efficacy are demonstrated with an illustrative example in comparison with support vector machine regression.

Modified radial basis function neural network using output transformation

A modified radial basis function (RBF) neural network and its identification algorithm based on observational data with heterogeneous noise are introduced. The transformed system output of Box-Cox is represented by the RBF neural network. To identify the model from observational data, the singular value decomposition of the full regression matrix consisting of basis functions formed by system input data is initially carried out and a new fast identification method is then developed using Gauss-Newton algorithm to derive the required Box-Cox transformation, based on a maximum likelihood estimator (MLE) for a model base spanned by the largest eigenvectors. Finally, the Box-Cox transformation-based RBF neural network, with good generalisation and sparsity, is identified based on the derived optimal Box-Cox transformation and an orthogonal forward regression algorithm using a pseudo-PRESS statistic to select a sparse RBF model with good generalisation. The proposed algorithm and its efficacy are demonstrated with numerical examples.

Experimental design and model construction algorithms for radial basis function networks

New construction algorithms for radial basis function (RBF) network modelling are introduced based on the A-optimality and D-optimality experimental design criteria respectively. We utilize new cost functions, based on experimental design criteria, for model selection that simultaneously optimizes model approximation, parameter variance (A-optimality) or model robustness (D-optimality). The proposed approaches are based on the forward orthogonal least-squares (OLS) algorithm, such that the new A-optimality- and D-optimality-based cost functions are constructed on the basis of an orthogonalization process that gains computational advantages and hence maintains the inherent computational efficiency associated with the conventional forward OLS approach. The proposed approach enhances the very popular forward OLS-algorithm-based RBF model construction method since the resultant RBF models are constructed in a manner that the system dynamics approximation capability, model adequacy and robustness are optimized simultaneously. The numerical examples provided show significant improvement based on the D-optimality design criterion, demonstrating that there is significant room for improvement in modelling via the popular RBF neural network.

A model for self-directed problem-based learning for renal therapeutics

Objective To introduce a new approach to problem-based learning (PBL) for self-directed learning in renal therapeutics. Design This 5-week course, designed for large student cohorts using minimal teaching resources, was based on a series of case studies and subsequent pharmaceutical care plans, followed by intensive and regular feedback from the instructor. Assessment Assessment of achievement of the learning outcomes was based on weekly-graded care plans and peer review assessment, allowing each student to judge the contributions of each group member and their own, along with a written case-study based examination. The pharmaceutical care plan template, designed using a “tick-box” system, significantly reduced staff time for feedback and scoring. Conclusion The proposed instructional model achieved the desired learning outcomes with appropriate student feedback, while promoting skills that are essential for the students' future careers as health care professionals.

Dual-orthogonal radial basis function networks for nonlinear time series prediction

A new structure of Radial Basis Function (RBF) neural network called the Dual-orthogonal RBF Network (DRBF) is introduced for nonlinear time series prediction. The hidden nodes of a conventional RBF network compare the Euclidean distance between the network input vector and the centres, and the node responses are radially symmetrical. But in time series prediction where the system input vectors are lagged system outputs, which are usually highly correlated, the Euclidean distance measure may not be appropriate. The DRBF network modifies the distance metric by introducing a classification function which is based on the estimation data set. Training the DRBF networks consists of two stages. Learning the classification related basis functions and the important input nodes, followed by selecting the regressors and learning the weights of the hidden nodes. In both cases, a forward Orthogonal Least Squares (OLS) selection procedure is applied, initially to select the important input nodes and then to select the important centres. Simulation results of single-step and multi-step ahead predictions over a test data set are included to demonstrate the effectiveness of the new approach.

Effect of olive oil on immune function in middle-aged men

Consumption of diets rich in monounsaturated fatty acids (MUFAs) has been linked with a low prevalence of atherosclerosis and there has been great interest in the effects of MUFAs on lipoprotein metabolism. Less attention has been paid to the effects of MUFAs on the immune system, yet cells of the immune system are an inherent part of the inflammatory events involved in atherosclerosis and several animal studies showed that olive oil has some potent immunomodulatory actions. We therefore considered it important to investigate the effects of chronic consumption of MUFAs on several immune cell functions in healthy humans. Healthy middle-aged males entered a doubleblind, randomized, controlled trial in which they consumed either a MUFA diet or a control diet for 2 mo. There was a significant decrease in the expression of intercellular adhesion molecule 1 by peripheral blood mononuclear cells from subjects consuming the MUFA diet. Consumption of the MUFA diet did not affect natural killer cell activity or proliferation of mitogen-stimulated leukocytes. The effects of a MUFA-rich diet on adhesion molecule expression may have implications for the influence of dietary fat on inflammatory diseases, including atherosclerosis.