Metamaterials Nanosensor for Label-free Analysis of Conformation and Molecular Interaction of Biomolecules

Analysis of molecular interaction and conformational dynamics of biomolecules is of paramount importance in understanding of their vital functions in complex biological systems, disease detection, and new drug development. Plasmonic biosensors based upon surface plasmon resonance and localized surface plasmon resonance have become the predominant workhorse for detecting accumulated biomass caused by molecular binding events. However, unlike surface-enhanced Raman spectroscopy (SERS), the plasmonic biosensors indeed are not suitable tools to interrogate vibrational signatures of conformational transitions required for biomolecules to interact. Here, we show that plasmonic metamaterials can offer two transducing channels for parallel acquisition of optical transmission and sensitive SERS spectra at the biointerface, simultaneously probing the conformational states and binding affinity of biomolecules, e.g. G-quadruplexes, in different environments (Fig. 1). We further demonstrate the use of the metamaterials for fingerprinting and detection of arginine-glycine-glycine domain of nucleolin, a cancer biomarker which specifically binds to a G-quadruplex, with the picomolar sensitivity. The dual-mode nanosensor will significantly contribute to unraveling the complexes of the conformational dynamics of biomolecules as well as to improving specificity of biodetection assays.

Association Study of 167 Candidate Genes for Schizophrenia Selected by a Multi-Domain Evidence-Based Prioritization Algorithm and Neurodevelopmental Hypothesis

Integrating evidence from multiple domains is useful in prioritizing disease candidate genes for subsequent testing. We ranked all known human genes (n = 3819) under linkage peaks in the Irish Study of High-Density Schizophrenia Families using three different evidence domains: 1) a meta-analysis of microarray gene expression results using the Stanley Brain collection, 2) a schizophrenia protein-protein interaction network, and 3) a systematic literature search. Each gene was assigned a domain-specific p-value and ranked after evaluating the evidence within each domain. For comparison to this
ranking process, a large-scale candidate gene hypothesis was also tested by including genes with Gene Ontology terms related to neurodevelopment. Subsequently, genotypes of 3725 SNPs in 167 genes from a custom Illumina iSelect array were used to evaluate the top ranked vs. hypothesis selected genes. Seventy-three genes were both highly ranked and involved in neurodevelopment (category 1) while 42 and 52 genes were exclusive to neurodevelopment (category 2) or highly ranked (category 3), respectively. The most significant associations were observed in genes PRKG1, PRKCE, and CNTN4 but no individual SNPs were significant after correction for multiple testing. Comparison of the approaches showed an excess of significant tests using the hypothesis-driven neurodevelopment category. Random selection of similar sized genes from two independent genome-wide association studies (GWAS) of schizophrenia showed the excess was unlikely by chance. In a further meta-analysis of three GWAS datasets, four candidate SNPs reached nominal significance. Although gene ranking using integrated sources of prior information did not enrich for significant results in the current experiment, gene selection using an a priori hypothesis (neurodevelopment) was superior to random selection. As such, further development of gene ranking strategies using more carefully selected sources of information is warranted.

Prediction of failure and fracture mechanisms of polymeric composites using finite element analysis. Part 2:Fiber reinforced composites

A robust finite element scheme for the micro-mechanical modeling of the behavior of fiber reinforced polymeric composites under external loads is developed. The developed model is used to simulate stress distribution throughout the composite domain and to identify the locations where maximum stress concentrations occur. This information is used as a guide to predict dominant failure and crack growth mechanisms in fiber reinforced composites. The differences between continuous fibers, which are susceptible to unidirectional transverse fracture, and short fibers have been demonstrated. To assess the validity and range of applicability of the developed scheme, numerical results obtained by the model are compared with the available experimental data and also with the values found using other methods reported in the literature. These comparisons show that the present finite element scheme can generate meaningful results in the analysis of fiber reinforced composites.

Towards utilizing Model-Driven Engineering of Composite Applications for business performance analysis

Composite Applications on top of SAPs implementation of SOA (Enterprise SOA) enable the extension of already existing business logic. In this paper we show, based on a case study, how Model-Driven Engineering concepts are applied in the development of such Composite Applications. Our Case Study extends a back-end business process which is required for the specific needs of a demo company selling wine. We use this to describe how the business centric models specifying the modified business behaviour of our case study can be utilized for business performance analysis where most of the actions are performed by humans. In particular, we apply a refined version of Model-Driven Performance Engineering that we proposed in our previous work and motivate which business domain specifics have to be taken into account for business performance analysis. We additionally motivate the need for performance related decision support for domain experts, who generally lack performance related skills. Such a support should offer visual guidance about what should be changed in the design and resource mapping to get improved results with respect to modification constraints and performance objectives, or objectives for time.

Comparative biochemical analysis of three members of the Schistosoma mansoni TAL family: Differences in ion and drug binding properties

The tegumental allergen-like (TAL) proteins from Schistosoma mansoni are part of a family of calcium binding proteins found only in parasitic flatworms. These proteins have attracted interest as potential drug or vaccine targets, yet comparatively little is known about their biochemistry. Here, we compared the biochemical properties of three members of this family: SmTAL1 (Sm22.6), SmTAL2 (Sm21.7) and SmTAL3 (Sm20.8). Molecular modelling suggested that, despite similarities in domain organisation, there are differences in the three proteins’ structures. SmTAL1 was predicted to have two functional calcium binding sites and SmTAL2 was predicted to have one. Despite the presence of two EF-hand-like structures in SmTAL3, neither was predicted to be functional. These predictions were confirmed by native gel electrophoresis, intrinsic fluorescence and differential scanning fluorimetry: both SmTAL1 and SmTAL2 are able to bind calcium ions reversibly, but SmTAL3 is not. SmTAL1 is also able to interact with manganese, strontium, iron(II) and nickel ions. SmTAL2 has a different ion binding profile interacting with cadmium, manganese, magnesium, strontium and barium ions in addition to calcium. All three proteins form dimers and, in contrast to some Fasciola hepatica proteins from the same family; dimerization is not affected by calcium ions. SmTAL1 interacts with the anti-schistosomal drug praziquantel and the calmodulin antagonists trifluoperazine, chlorpromazine and W7. SmTAL2 interacts only with W7. SmTAL3 interacts with the aforementioned calmodulin antagonists and thiamylal, but not praziquantel. Overall, these data suggest that the proteins have different biochemical properties and thus, most likely, different in vivo functions.

Identification and Functional Analysis of a Novel Tryptophyllin Peptide from the Skin of the Red-eye Leaf Frog, Agalychnis callidryas

Amphibian skin has proved repeatedly to be a largely untapped source of bioactive peptides and this is especially true of members of the Phyllomedusinae subfamily of frogs native to South and Central America. Tryptophyllins are a group of peptides mainly found in the skin of members of this genus. In this study, a novel tryptophyllin (TPH) type 3 peptide, named AcT-3, has been isolated and structurally-characterised from the skin secretion and lyophilised skin extract of the red-eye leaf frog, Agalychnis callidryas. The peptide was identified in and purified from the skin secretion by reverse-phase HPLC. MALDI-TOF mass spectrometry and MS/MS fragmentation sequencing established its primary structure as: pGlu-Gly-Lys-Pro-Tyr-Trp-Pro-Pro-Pro-Phe-Leu-Pro-Glu, with a non-protonated molecular mass of 1538.19Da. The mature peptide possessed the canonical N-terminal pGlu residue that arises from post-translational modification of a Gln residue. The deduced open-reading frame consisted of 63 amino acid residues encoding a highly-conserved signal peptide of approximately 22 amino acid residues, an intervening acidic spacer peptide domain, a single AcT-3 encoding domain and a C terminal processing site. A synthetic replicate of AcT-3 was found to antagonise the effect of BK on rat tail artery smooth muscle and to contract the intestinal smooth muscle preparations. It was also found that AcT-3 could dose-dependently inhibit the proliferation of human prostate cancer cell lines after 72h incubation.

Using Brain Data for Sentiment Analysis

We present the results of exploratory experiments using lexical valence extracted from brain using electroencephalography (EEG) for sentiment analysis. We selected 78 English words (36 for training and 42 for testing), presented as stimuli to 3 English native speakers. EEG signals were recorded from the subjects while they performed a mental imaging task for each word stimulus. Wavelet decomposition was employed to extract EEG features from the time-frequency domain. The extracted features were used as inputs to a sparse multinomial logistic regression (SMLR) classifier for valence classification, after univariate ANOVA feature selection. After mapping EEG signals to sentiment valences, we exploited the lexical polarity extracted from brain data for the prediction of the valence of 12 sentences taken from the SemEval-2007 shared task, and compared it against existing lexical resources.

Topological analysis of the Escherichia coli WcaJ protein reveals a new conserved configuration for the polyisoprenyl-phosphate hexose-1-phosphate transferase family

WcaJ is an Escherichia coli membrane enzyme catalysing the biosynthesis of undecaprenyl-diphosphate-glucose, the first step in the assembly of colanic acid exopolysaccharide. WcaJ belongs to a large family of polyisoprenyl-phosphate hexose-1-phosphate transferases (PHPTs) sharing a similar predicted topology consisting of an N-terminal domain containing four transmembrane helices (TMHs), a large central periplasmic loop, and a C-terminal domain containing the fifth TMH (TMH-V) and a cytosolic tail. However, the topology of PHPTs has not been experimentally validated. Here, we investigated the topology of WcaJ using a combination of LacZ/PhoA reporter fusions and sulfhydryl
labelling by PEGylation of novel cysteine residues introduced into a cysteine-less WcaJ. The results showed that the large central loop and the C-terminal tail both reside in the cytoplasm and are separated by TMH-V, which does not fully span the membrane, likely forming a "hairpin" structure. Modelling of TMH-V revealed that a highly conserved proline might contribute to a helix-break-helix structure in all PHPT members. Bioinformatic analyses show that all of these features are conserved in PHPT homologues from
Gram-negative and Gram-positive bacteria. Our data demonstrate a novel topological configuration for PHPTs, which is proposed as a signature for all members of this enzyme family

Bayesian network data imputation with application to survival tree analysis

Retrospective clinical datasets are often characterized by a relatively small sample size and many missing data. In this case, a common way for handling the missingness consists in discarding from the analysis patients with missing covariates, further reducing the sample size. Alternatively, if the mechanism that generated the missing allows, incomplete data can be imputed on the basis of the observed data, avoiding the reduction of the sample size and allowing methods to deal with complete data later on. Moreover, methodologies for data imputation might depend on the particular purpose and might achieve better results by considering specific characteristics of the domain. The problem of missing data treatment is studied in the context of survival tree analysis for the estimation of a prognostic patient stratification. Survival tree methods usually address this problem by using surrogate splits, that is, splitting rules that use other variables yielding similar results to the original ones. Instead, our methodology consists in modeling the dependencies among the clinical variables with a Bayesian network, which is then used to perform data imputation, thus allowing the survival tree to be applied on the completed dataset. The Bayesian network is directly learned from the incomplete data using a structural expectation–maximization (EM) procedure in which the maximization step is performed with an exact anytime method, so that the only source of approximation is due to the EM formulation itself. On both simulated and real data, our proposed methodology usually outperformed several existing methods for data imputation and the imputation so obtained improved the stratification estimated by the survival tree (especially with respect to using surrogate splits).

Comparative analysis of Klebsiella pneumoniae genomes identifies a phospholipase D family protein as a novel virulence factor

BACKGROUND: Klebsiella pneumoniae strains are pathogenic to animals and humans, in which they are both a frequent cause of nosocomial infections and a re-emerging cause of severe community-acquired infections. K. pneumoniae isolates of the capsular serotype K2 are among the most virulent. In order to identify novel putative virulence factors that may account for the severity of K2 infections, the genome sequence of the K2 reference strain Kp52.145 was determined and compared to two K1 and K2 strains of low virulence and to the reference strains MGH 78578 and NTUH-K2044.

RESULTS: In addition to diverse functions related to host colonization and virulence encoded in genomic regions common to the four strains, four genomic islands specific for Kp52.145 were identified. These regions encoded genes for the synthesis of colibactin toxin, a putative cytotoxin outer membrane protein, secretion systems, nucleases and eukaryotic-like proteins. In addition, an insertion within a type VI secretion system locus included sel1 domain containing proteins and a phospholipase D family protein (PLD1). The pld1 mutant was avirulent in a pneumonia model in mouse. The pld1 mRNA was expressed in vivo and the pld1 gene was associated with K. pneumoniae isolates from severe infections. Analysis of lipid composition of a defective E. coli strain complemented with pld1 suggests an involvement of PLD1 in cardiolipin metabolism.

CONCLUSIONS: Determination of the complete genome of the K2 reference strain identified several genomic islands comprising putative elements of pathogenicity. The role of PLD1 in pathogenesis was demonstrated for the first time and suggests that lipid metabolism is a novel virulence mechanism of K. pneumoniae.

Inactivating mutations in an SH2 domain-encoding gene in X-linked lymphoproliferative syndrome

X-linked lymphoproliferative syndrome (XLP) is an inherited immunodeficiency characterized by increased susceptibility to Epstein-Barr virus (EBV). In affected males, primary EBV infection leads to the uncontrolled proliferation of virus-containing B cells and reactive cytotoxic T cells, often culminating in the development of high-grade lymphoma. The XLP gene has been mapped to chromosome band Xq25 through linkage analysis and the discovery of patients harboring large constitutional genomic deletions. We describe here the presence of small deletions and intragenic mutations that specifically disrupt a gene named DSHP in 6 of 10 unrelated patients with XLP. This gene encodes a predicted protein of 128 amino acids composing a single SH2 domain with extensive homology to the SH2 domain of SHIP, an inositol polyphosphate 5-phosphatase that functions as a negative regulator of lymphocyte activation. DSHP is expressed in transformed T cell lines and is induced following in vitro activation of peripheral blood T lymphocytes. Expression of DSHP is restricted in vivo to lymphoid tissues, and RNA in situ hybridization demonstrates DSHP expression in activated T and B cell regions of reactive lymph nodes and in both T and B cell neoplasms. These observations confirm the identity of DSHP as the gene responsible for XLP, and suggest a role in the regulation of lymphocyte activation and proliferation. Induction of DSHP may sustain the immune response by interfering with SHIP-mediated inhibition of lymphocyte activation, while its inactivation in XLP patients results in a selective immunodeficiency to EBV.

Generating analysis topology using virtual topology operators

Virtual topology operations have been utilized to generate an analysis topology definition suitable for downstream mesh generation. Detailed descriptions are provided for virtual topology merge and split operations for all topological entities, where virtual decompositions are robustly linked to the underlying geometry. Current virtual topology technology is extended to allow the virtual partitioning of volume cells. A valid description of the topology, including relative orientations, is maintained which enables downstream interrogations to be performed on the analysis topology description, such as determining if a specific meshing strategy can be applied to the virtual volume cells. As the virtual representation is a true non-manifold description of the sub-divided domain the interfaces between cells are recorded automatically. Therefore, the advantages of non-manifold modelling are exploited within the manifold modelling environment of a major commercial CAD system without any adaptation of the underlying CAD model. A hierarchical virtual structure is maintained where virtual entities are merged or partitioned. This has a major benefit over existing solutions as the virtual dependencies here are stored in an open and accessible manner, providing the analyst with the freedom to create, modify and edit the analysis topology in any preferred sequence.

Geostatistical Fisher discriminant analysis

A geostatistical version of the classical Fisher rule (linear discriminant analysis) is presented.This method is applicable when a large dataset of multivariate observations is available within a domain split in several known subdomains, and it assumes that the variograms (or covariance functions) are comparable between subdomains, which only differ in the mean values of the available variables. The method consists on finding the eigen-decomposition of the matrix W-1B, where W is the matrix of sills of all direct- and cross-variograms, and B is the covariance matrix of the vectors of weighted means within each subdomain, obtained by generalized least squares. The method is used to map peat blanket occurrence in Northern Ireland, with data from the Tellus
survey, which requires a minimal change to the general recipe: to use compositionally-compliant variogram tools and models, and work with log-ratio transformed data.

A Cyber-Physical Security Analysis of Synchronous-Islanded Microgrid Operation

Cyber-security research in the field of smart grids is often performed with a focus on either the power and control domain or the Information and Communications Technology (ICT) domain. The characteristics of the power equipment or ICT domain are commonly not collectively considered. This work provides an analysis of the physical effects of cyber-attacks on microgrids – a smart grid construct that allows continued power supply when disconnected from a main grid. Different types of microgrid operations are explained (connected, islanded and synchronous-islanding) and potential cyber-attacks and their physical effects are analyzed. A testbed that is based on physical power and ICT equipment is presented to validate the results in both the physical and ICT domain.

Tumor suppressor Ras-association domain family 1 isoform A is a novel regulator of cardiac hypertrophy

BACKGROUND: Ras signaling regulates a number of important processes in the heart, including cell growth and hypertrophy. Although it is known that defective Ras signaling is associated with Noonan, Costello, and other syndromes that are characterized by tumor formation and cardiac hypertrophy, little is known about factors that may control it. Here we investigate the role of Ras effector Ras-association domain family 1 isoform A (RASSF1A) in regulating myocardial hypertrophy.

METHODS AND RESULTS: A significant downregulation of RASSF1A expression was observed in hypertrophic mouse hearts, as well as in failing human hearts. To further investigate the role of RASSF1A in cardiac (patho)physiology, we used RASSF1A knock-out (RASSF1A(-)(/)(-)) mice and neonatal rat cardiomyocytes with adenoviral overexpression of RASSF1A. Ablation of RASSF1A in mice significantly enhanced the hypertrophic response to transverse aortic constriction (64.2% increase in heart weight/body weight ratio in RASSF1A(-)(/)(-) mice compared with 32.4% in wild type). Consistent with the in vivo data, overexpression of RASSF1A in cardiomyocytes markedly reduced the cellular hypertrophic response to phenylephrine stimulation. Analysis of molecular signaling events in isolated cardiomyocytes indicated that RASSF1A inhibited extracellular regulated kinase 1/2 activation, likely by blocking the binding of Raf1 to active Ras.

CONCLUSIONS: Our data establish RASSF1A as a novel inhibitor of cardiac hypertrophy by modulating the extracellular regulated kinase 1/2 pathway.