Molecular basis of Yersinia enterocolitica temperature-dependent resistance to antimicrobial peptides

Antimicrobial peptides (APs) belong to the arsenal of weapons of the innate immune system against infections. In the case of gram-negative bacteria, APs interact with the anionic lipid A moiety of the lipopolysaccharide (LPS). In yersiniae most virulence factors are temperature regulated. Studies from our laboratory demonstrated that Yersinia enterocolitica is more susceptible to polymyxin B, a model AP, when grown at 37°C than at 22°C (J. A. Bengoechea, R. Díaz, and I. Moriyón, Infect. Immun. 64:4891-4899, 1996), and here we have extended this observation to other APs, not structurally related to polymyxin B. Mechanistically, we demonstrate that the lipid A modifications with aminoarabinose and palmitate are downregulated at 37°C and that they contribute to AP resistance together with the LPS O-polysaccharide. Bacterial loads of lipid A mutants in Peyer's patches, liver, and spleen of orogastrically infected mice were lower than those of the wild-type strain at 3 and 7 days postinfection. PhoPQ and PmrAB two-component systems govern the expression of the loci required to modify lipid A with aminoarabinose and palmitate, and their expressions are also temperature regulated. Our findings support the notion that the temperature-dependent regulation of loci controlling lipid A modifications could be explained by H-NS-dependent negative regulation alleviated by RovA. In turn, our data also demonstrate that PhoPQ and PmrAB regulate positively the expression of rovA, the effect of PhoPQ being more important. However, rovA expression reached wild-type levels in the phoPQ pmrAB mutant background, hence indicating the existence of an unknown regulatory network controlling rovA expression in this background.

Resolution theory, and static and frequency-dependent cross-talk in piezoresponse force microscopy

Probing the functionality of materials locally by means of scanning probe microscopy (SPM) requires a reliable framework for identifying the target signal and separating it from the effects of surface morphology and instrument non-idealities, e.g. instrumental and topographical cross-talk. Here we develop a linear resolution theory framework in order to describe the cross-talk effects, and apply it for elucidation of frequency-dependent cross-talk mechanisms in piezoresponse force microscopy. The use of a band excitation method allows electromechanical/electrical and mechanical/topographic signals to be unambiguously separated. The applicability of a functional fit approach and multivariate statistical analysis methods for identification of data in band excitation SPM is explored.

Abnormal changes in voltage-gated sodium channels NaV1.1, NaV1.2, NaV1.3, NaV1.6 and in Calmodulin/calmodulin-dependent protein kinase II, within the brains of spontaneously epileptic rats and tremor rats

Voltage-gated sodium channels (VGSCs) play a crucial role in epilepsy. The expressions of different VGSCs subtypes are varied in diverse animal models of epilepsy that may reflect their multiple phenotypes or the complexity of the mechanisms of epilepsy. In a previous study, we reported that NaV1.1 and NaV1.3 were up-regulated in the hippocampus of the spontaneously epileptic rat (SER). In this study, we further analyzed both the expression and distribution of the typical VGSC subtypes NaV1.1, NaV1.2, NaV1.3 and NaV1.6 in the hippocampus and in the cortex of the temporal lobe of two genetic epileptic animal models: the SER and the tremor rat (TRM). The expressions of calmodulin (CaM) and calmodulin-dependent protein kinase II (CaMKII) were also analyzed with the purpose of assessing the effect of the CaM/CaMKII pathway in these two models of epilepsy. Increased expression of the four VGSC subtypes and CaM, accompanied by a decrease in CaMKII was observed in the hippocampus of both the SERs and the TRM rats. However, the changes observed in the expression of VGSC subtypes and CaM were decreased with an elevated CaMKII in the cortex of their temporal lobes. Double-labeled immunofluorescence data suggested that in SERs and TRM rats, the four subtypes of the VGSC proteins were present throughout the CA1, CA3 and dentate gyrus regions of the hippocampus and temporal lobe cortex and these were co-localized in neurons with CaM. These data represent the first evidence of abnormal changes in expression of four VGSC subtypes (NaV1.1, NaV1.2, NaV1.3 and NaV1.6) and CaM/CaMKII in the hippocampus and temporal lobe cortex of SERs and TRM rats. These changes may be involved in the generation of epileptiform activity and underlie the observed seizure phenotype in these rat models of genetic epilepsy.

Connectivity Mapping for Candidate Therapeutics Identification Using Next Generation Sequencing RNA-Seq Data

The advent of next generation sequencing technologies (NGS) has expanded the area of genomic research, offering high coverage and increased sensitivity over older microarray platforms. Although the current cost of next generation sequencing is still exceeding that of microarray approaches, the rapid advances in NGS will likely make it the platform of choice for future research in differential gene expression. Connectivity mapping is a procedure for examining the connections among diseases, genes and drugs by differential gene expression initially based on microarray technology, with which a large collection of compound-induced reference gene expression profiles have been accumulated. In this work, we aim to test the feasibility of incorporating NGS RNA-Seq data into the current connectivity mapping framework by utilizing the microarray based reference profiles and the construction of a differentially expressed gene signature from a NGS dataset. This would allow for the establishment of connections between the NGS gene signature and those microarray reference profiles, alleviating the associated incurring cost of re-creating drug profiles with NGS technology. We examined the connectivity mapping approach on a publicly available NGS dataset with androgen stimulation of LNCaP cells in order to extract candidate compounds that could inhibit the proliferative phenotype of LNCaP cells and to elucidate their potential in a laboratory setting. In addition, we also analyzed an independent microarray dataset of similar experimental settings. We found a high level of concordance between the top compounds identified using the gene signatures from the two datasets. The nicotine derivative cotinine was returned as the top candidate among the overlapping compounds with potential to suppress this proliferative phenotype. Subsequent lab experiments validated this connectivity mapping hit, showing that cotinine inhibits cell proliferation in an androgen dependent manner. Thus the results in this study suggest a promising prospect of integrating NGS data with connectivity mapping. © 2013 McArt et al.

Maillard reaction products and their relation to complications in insulin-dependent diabetes mellitus

Glycation, oxidation, and browning of proteins have all been implicated in the development of diabetic complications. We measured the initial Amadori adduct, fructoselysine (FL); two Maillard products, N epsilon-(carboxymethyl) lysine (CML) and pentosidine; and fluorescence (excitation = 328 nm, emission = 378 nm) in skin collagen from 39 type 1 diabetic patients (aged 41.5 +/- 15.3 [17-73] yr; duration of diabetes 17.9 +/- 11.5 [0-46] yr, [mean +/- SD, range]). The measurements were related to the presence of background (n = 9) or proliferative (n = 16) retinopathy; early nephropathy (24-h albumin excretion rate [AER24] > or = 20 micrograms/min; n = 9); and limited joint mobility (LJM; n = 20). FL, CML, pentosidine, and fluorescence increased progressively across diabetic retinopathy (P <0.05, P <0.001, P <0.05, P <0.01, respectively). FL, CML, pentosidine, and fluorescence were also elevated in patients with early nephropathy (P <0.05, P <0.001, P <0.01, P <0.01, respectively). There was no association with LJM. Controlling for age, sex, and duration of diabetes using logistic regression, FL and CML were independently associated with retinopathy (FL odds ratio (OR) = 1.06, 95% confidence interval (CI) = 1.01-1.12, P <0.05; CML OR = 6.77, 95% CI = 1.33-34.56, P <0.05) and with early nephropathy (FL OR = 1.05, 95% CI = 1.01-1.10, P <0.05; CML OR = 13.44, 95% CI = 2.00-93.30, P <0.01). The associations between fluorescence and retinopathy and between pentosidine and nephropathy approached significance (P = 0.05). These data show that FL and Maillard products in skin correlate with functional abnormalities in other tissues and suggest that protein glycation and oxidation (glycoxidation) may be implicated in the development of diabetic retinopathy and early nephropathy.

Quantum chemistry and in situ FTir spectroscopy studies on potential-dependent properties of CO adsorbed on Pt electrodes

The electronic and vibrational properties of CO adsorbed on Pt electrodes at different potentials have been studied, by using methods of self-consistent-charge discrete variational Xa (SCC-DV-Xa) cluster calculations and in situ FTir spectroscopy. Two new models have been developed and verified to be successful: (1) using a "metallic state cluster" to imitate a metal (electrode) surface; and (2) charging the cluster and shifting its Fermi level (e{lunate}) to simulate, according to the relation of -d e{lunate}e dE, quantitatively the variation of the electrode potential (E). It is shown that the binding of PtCO is dominated by the electric charge transfer of dp ? 2p, while that of s ? Pt is less important in this binding. The electron occupancy of the 2p orbital of CO weakens the CO bond and decreases the v. Variation of E mainly influences the charge transfer process of dp ? 2p, but hardly influences that of s ? Pt. A linear potential-dependence of v has been shown and the calculated dv/dE = 35.0 cm V. All results of calculations coincide with the ir experimental data. © 1993.

Harnessing the complexity of gene expression data from cancer: from single gene to structural pathway methods

High-dimensional gene expression data provide a rich source of information because they capture the expression level of genes in dynamic states that reflect the biological functioning of a cell. For this reason, such data are suitable to reveal systems related properties inside a cell, e.g., in order to elucidate molecular mechanisms of complex diseases like breast or prostate cancer. However, this is not only strongly dependent on the sample size and the correlation structure of a data set, but also on the statistical hypotheses tested. Many different approaches have been developed over the years to analyze gene expression data to (I) identify changes in single genes, (II) identify changes in gene sets or pathways, and (III) identify changes in the correlation structure in pathways. In this paper, we review statistical methods for all three types of approaches, including subtypes, in the context of cancer data and provide links to software implementations and tools and address also the general problem of multiple hypotheses testing. Further, we provide recommendations for the selection of such analysis methods.

Nonlinear numerical modelling of lightning strike effect on composite panels with temperature dependent material properties

This paper presents a physics based modelling procedure to predict the thermal damage of composite material when struck by lightning. The procedure uses the Finite Element Method with non-linear material models to represent the extreme thermal material behaviour of the composite material (carbon/epoxy) and an embedded copper mesh protection system. Simulation predictions are compared against published experimental data, illustrating the potential accuracy and computational cost of virtual lightning strike tests and the requirement for temperature dependent material modelling. The modelling procedure is then used to examine and explain a number of practical solutions to minimize thermal material damage. © 2013 Elsevier Ltd.

A highly potent and specific MET therapeutic protein antagonist with both ligand-dependent and ligand-independent activity

Activation of the MET oncogenic pathway has been implicated in the development of aggressive cancers that are difficult to treat with current chemotherapies. This has led to an increased interest in developing novel therapies that target the MET pathway. However, most existing drug modalities are confounded by their inability to specifically target and/or antagonize this pathway. Anticalins, a novel class of monovalent small biologics, are hypothesized to be "fit for purpose" for developing highly specific and potent antagonists of cancer pathways. Here, we describe a monovalent full MET antagonist, PRS-110, displaying efficacy in both ligand-dependent and ligand-independent cancer models. PRS-110 specifically binds to MET with high affinity and blocks hepatocyte growth factor (HGF) interaction. Phosphorylation assays show that PRS-110 efficiently inhibits HGF-mediated signaling of MET receptor and has no agonistic activity. Confocal microscopy shows that PRS-110 results in the trafficking of MET to late endosomal/lysosomal compartments in the absence of HGF. In vivo administration of PRS-110 resulted in significant, dose-dependent tumor growth inhibition in ligand-dependent (U87-MG) and ligand-independent (Caki-1) xenograft models. Analysis of MET protein levels on xenograft biopsy samples show a significant reduction in total MET following therapy with PRS-110 supporting its ligand-independent mechanism of action. Taken together, these data indicate that the MET inhibitor PRS-110 has potentially broad anticancer activity that warrants evaluation in patients.

VDR and MEK-ERK dependent induction of the antimicrobial peptide cathelicidin in keratinocytes by lithocholic acid

Cathelicidin is an antimicrobial peptide (AMP) and signaling molecule in innate immunity and a direct target of 1,25-dihydroxyvitamin D3 (1,25D3) in primary human keratinocytes (NHEK). The expression of cathelicidin is dysregulated in various skin diseases and its regulation differs depending on the epithelial cell type. The secondary bile acid lithocholic acid (LCA) is a ligand of the vitamin D receptor (VDR) and can carry out in vivo functions of vitamin D3. Therefore we analyzed cathelicidin mRNA- and peptide expression levels in NHEK and colonic epithelial cells (Caco-2) after stimulation with LCA. We found increased expression of cathelicidin mRNA and peptide in NHEK, in Caco-2 colon cells no effect was observed after LCA stimulation. The VDR as well as MEK-ERK signaled the upregulation of cathelicidin in NHEK induced by LCA. Collectively, our data indicate that cathelicidin induction upon LCA treatment differs in keratinocytes and colonic epithelial cells. Based on these observations LCA-like molecules targeting cathelicidin could be designed for the treatment of cutaneous diseases that are characterized by disturbed cathelicidin expression.

Autonomic scheduling of tasks from data parallel patterns to CPU/GPU core mixes

We propose a methodology for optimizing the execution of data parallel (sub-)tasks on CPU and GPU cores of the same heterogeneous architecture. The methodology is based on two main components: i) an analytical performance model for scheduling tasks among CPU and GPU cores, such that the global execution time of the overall data parallel pattern is optimized; and ii) an autonomic module which uses the analytical performance model to implement the data parallel computations in a completely autonomic way, requiring no programmer intervention to optimize the computation across CPU and GPU cores. The analytical performance model uses a small set of simple parameters to devise a partitioning-between CPU and GPU cores-of the tasks derived from structured data parallel patterns/algorithmic skeletons. The model takes into account both hardware related and application dependent parameters. It computes the percentage of tasks to be executed on CPU and GPU cores such that both kinds of cores are exploited and performance figures are optimized. The autonomic module, implemented in FastFlow, executes a generic map (reduce) data parallel pattern scheduling part of the tasks to the GPU and part to CPU cores so as to achieve optimal execution time. Experimental results on state-of-the-art CPU/GPU architectures are shown that assess both performance model properties and autonomic module effectiveness. © 2013 IEEE.

Resistance to chemotherapy in ovarian cancer is miRrored by the microRNA miR-433-dependent dysregulation of the cell cycle.

An understanding of the mechanisms underlying the development of resistance to chemotherapy treatment is a gateway to the introduction of novel therapies and improved outcomes for women presenting with ovarian cancer (OC). The desired apoptotic death post-chemotherapy depends on an intact and fully functioning cell cycle machinery.

In this study we demonstrate that stable expression of miR-433 renders OC cells more resistant to paclitaxel treatment. Interestingly, only cells with the highest miR-433 survived paclitaxel suggesting the possible role of miR-433 in cancer recurrence. Importantly, for the first time we demonstrate that miR 433 induces cellular senescence, exemplified by a flattened morphology, the downregulation of phosphorylated Retinoblastoma (p Rb) and increased β galactosidase activity. Surprisingly, miR 433 induced senescence was independent of two well recognised senescent drivers: p21 and p16. Further in silico analysis followed by in vitro experiments identified CKD6 as a novel miR-433 target gene possibly explaining the observed p21 and p16-independent induction of cellular senescence. Another in silico identified miR-433 target gene was CDC27, a protein involved in the regulation of the cell cycle during mitosis. We demonstrate that the overexpression of pre-miR-433 leads to the downregulation of CDC27 in vitro revealing a novel interaction between miR-433 and CDC27, an integral cell cycle regulating protein.

Interestingly, miR-433 expressing cells also demonstrated an ability to impact their tumour microenvironment. We show that miR-433 is present in exosomes released from miR-433 overexpressing and high miR-433 naïve cells. Moreover, growth condition media (GCM) harvested from cells with high miR-433 have higher levels of IL-6 and IL-8, two key cytokines involved in the senescence associated secretory phenotype (SASP). Importantly, GCM from miR-433-enriched cells repressed the growth of co-cultured cells with initial studies showing a GCM-dependent induction of chemoresistance.

In conclusion, data in this study highlights how the aberrant expression miR-433 contributes to chemoresistance in OC cells. We postulate that standard chemotherapy, particularly paclitaxel, used to treat women with OC may have an attenuated ability to kill cells harbouring increased levels of miR-433, allowing for a subsequent chemoresistant phenotype post-therapy.

Supervised Aggregative Feature Extraction for Big Data Time Series Regression

In many applications, and especially those where batch processes are involved, a target scalar output of interest is often dependent on one or more time series of data. With the exponential growth in data logging in modern industries such time series are increasingly available for statistical modeling in soft sensing applications. In order to exploit time series data for predictive modelling, it is necessary to summarise the information they contain as a set of features to use as model regressors. Typically this is done in an unsupervised fashion using simple techniques such as computing statistical moments, principal components or wavelet decompositions, often leading to significant information loss and hence suboptimal predictive models. In this paper, a functional learning paradigm is exploited in a supervised fashion to derive continuous, smooth estimates of time series data (yielding aggregated local information), while simultaneously estimating a continuous shape function yielding optimal predictions. The proposed Supervised Aggregative Feature Extraction (SAFE) methodology can be extended to support nonlinear predictive models by embedding the functional learning framework in a Reproducing Kernel Hilbert Spaces setting. SAFE has a number of attractive features including closed form solution and the ability to explicitly incorporate first and second order derivative information. Using simulation studies and a practical semiconductor manufacturing case study we highlight the strengths of the new methodology with respect to standard unsupervised feature extraction approaches.

Generalized collisional radiative model for light elements: C: Data for the B isonuclear sequence

A first stage collision database is assembled which contains electron-impact excitation, ionization,\r and recombination rate coefficients for B, B + , B 2+ , B 3+ , and B 4+ . The first stage database\r is constructed using the R-matrix with pseudostates, time-dependent close-coupling, and perturbative\r distorted-wave methods. A second stage collision database is then assembled which contains\r generalized collisional-radiative ionization, recombination, and power loss rate coefficients as a\r function of both temperature and density. The second stage database is constructed by solution of\r the collisional-radiative equations in the quasi-static equilibrium approximation using the first\r stage database. Both collision database stages reside in electronic form at the IAEA Labeled Atomic\r Data Interface (ALADDIN) database and the Atomic Data Analysis Structure (ADAS) open database.

Generalized collisional radiative model for light elements. Part B: Data for the Be isonuclear sequence

A first-stage collision database is assembled which contains electron-impact excitation, ionization, and recombination rate coefficients for Be, Be+, Be2+, and Be3+. The first-stage database is constructed using the R-matrix with pseudo-states, time-dependent close-coupling, and perturbative, distorted-wave methods. A second-stage collision database is then assembled which contains generalized collisional-radiative and radiated power loss coefficients. The second-stage database is constructed by solution of collisional-radiative equations in the quasi-static equilibrium approximation using the first-stage database. Both collision database stages reside in electronic form at the ORNL Controlled Fusion Atomic Data Center and in the ADAS database, and are easily accessed over the worldwide internet. © 2007 Elsevier Inc. All rights reserved.