The 3'-terminal exon of the family of steroid and phenol sulfotransferase genes is spliced at the N-terminal glycine of the universally conserved GXXGXXK motif that forms the sulfonate donor binding site.

The guinea pig estrogen sulfotransferase gene has been cloned and compared to three other cloned steroid and phenol sulfotransferase genes (human estrogen sulfotransferase, human phenol sulfotransferase, and guinea pig 3 alpha-hydroxysteroid sulfotransferase). The four sulfotransferase genes demonstrate a common outstanding feature: the splice sites for their 3'-terminal exons are identically located. That is, the 3'-terminal exon splice sites involve a glycine that constitutes the N-terminal glycine of an invariably conserved GXXGXXK motif present in all steroid and phenol sulfotransferases for which primary structures are known. This consistency strongly suggests that all steroid and phenol sulfotransferase genes will be similarly spliced. The GXXGXXK motif forms the active binding site for the universal sulfonate donor 3'-phosphoadenosine 5'-phosphosulfate. Amino acid sequence alignment of 19 cloned steroid and phenol sulfotransferases starting with the GXXGXXK motif indicates that the 3'-terminal exon for each steroid and phenol sulfotransferase gene encodes a similarly sized C-terminal fragment of the protein. Interestingly, on further analysis of the alignment, three distinct amino acid sequence patterns emerge. The presence of the conserved functional GXXGXXK motif suggests that the protein domains encoded by steroid and phenol sulfotransferase 3'-terminal exons have evolved from a common ancestor. Furthermore, it is hypothesized that during the course of evolution, the 3'-terminal exon further diverged into at least three sulfotransferase subdivisions: a phenol or aryl group, an estrogen or phenolic steroid group, and a neutral steroid group.

Analysis of the interaction of ZAP-70 and syk protein-tyrosine kinases with the T-cell antigen receptor by plasmon resonance.

Tyrosine phosphorylation of a 17-amino acid immunoreceptor tyrosine-based activation motif (ITAM), conserved in each of the signaling subunits of the T-cell antigen receptor (TCR), mediates the recruitment of ZAP-70 and syk protein-tyrosine kinases (PTKs) to the activated receptor. The interaction between the two tandemly arranged Src-homology 2 (SH2) domains of this family of PTKs and each of the phosphotyrosine-containing ITAMs was examined by real-time measurements of kinetic parameters. The association rate and equilibrium binding constants for the ZAP-70 and syk SH2 domains were determined for the CD3 epsilon ITAM. Both PTKs bound with ka and Kd values of 5 x 10(6) M-1.sec-1 and approximately 25 nM, respectively. Bindings to the other TCR ITAMs (zeta 1, zeta 2, gamma, and delta ITAMs) were comparable, although the zeta 3 ITAM bound approximately 2.5-fold less well. Studies of the affinity of a single functional SH2 domain of ZAP-70 provided evidence for the cooperative nature of binding of the dual SH2 domains. Mutation of either single SH2 domain decreased the Kd by > 100-fold. Finally, the critical features of the ITAM for syk binding were found to be similar to those required for ZAP-70 binding. These data provide insight into the mechanism by which the multisubunit TCR interacts with downstream effector molecules.

Reduced expression of chemokine (C-C motif) ligand-2 (CCL2) in ovarian adenocarcinoma

Chemokine (C-C motif) ligand-2 (CCL2) is a chemoattractant and activator of macrophages and is a key determinant of the macrophage infiltrate into tumours. We demonstrate here that CCL2 is expressed in normal human ovarian surface epithelium ( HOSE) cells and is silenced in most ovarian cancer cell lines, and silenced or downregulated in the majority of primary ovarian adenocarcinomas. Analysis of the CCL2 locus at 17q11.2-q12 showed loss of heterozygosity (LOH) in 70% of primary tumours, and this was significantly more common in tumours of advanced stage or grade. However, we did not detect any mutations in the CCL2 coding sequence in 94 primary ovarian adenocarcinomas. These data support the hypothesis that CCL2 may play a role in the pathobiology of ovarian cancers, but additional studies will be required to evaluate this possibility.

The applicability of recurrent neural networks for biological sequence analysis

Selection of machine learning techniques requires a certain sensitivity to the requirements of the problem. In particular, the problem can be made more tractable by deliberately using algorithms that are biased toward solutions of the requisite kind. In this paper, we argue that recurrent neural networks have a natural bias toward a problem domain of which biological sequence analysis tasks are a subset. We use experiments with synthetic data to illustrate this bias. We then demonstrate that this bias can be exploitable using a data set of protein sequences containing several classes of subcellular localization targeting peptides. The results show that, compared with feed forward, recurrent neural networks will generally perform better on sequence analysis tasks. Furthermore, as the patterns within the sequence become more ambiguous, the choice of specific recurrent architecture becomes more critical.

In vivo effects of tailored laminin-332 α3 conjugated scaffolds enhances wound healing:a histomorphometric analysis

Surface modification techniques have been used to develop biomimetic scaffolds by incorporating cell adhesion peptides. In our previous work, we have shown the tethering of laminin-332 α3 chain to type I collagen scaffold using microbial transglutaminase (mTGase), promotes cell adhesion, migration, and proliferation. In this study, we evaluated the wound healing properties of tailored laminin-332 α3 chain (peptide A: PPFLMLLKGSTR) tethered to a type I collagen scaffold using mTGase by incorporating transglutaminase substrate peptide sequences containing either glutamine (peptide B: PPFLMLLKGSTREAQQIVM) or lysine (peptide C: PPFLMLLKGSTRKKKKG) in rat full-thickness wound model at two different time points (7 and 21 days). Histological evaluations were assessed for wound closure, epithelialization, angiogenesis, inflammatory, fibroblastic cellular infiltrations, and quantified using stereological methods (p < 0.05). Peptide A and B tethered to collagen scaffold using mTGase stimulated neovascularization, decreased the inflammatory cell infiltration and prominently enhanced the fibroblast proliferation which significantly accelerated the wound healing process. We conclude that surface modification by incorporating motif of laminin-332 α3 chain (peptide A: PPFLMLLK GSTR) domain and transglutaminase substrate to the laminin-332 α3 chain (peptide B: PPFLMLLKGSTREAQQIVM) using mTGase may be a potential candidate for tissue engineering applications and skin regeneration. © 2013 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 101A:2788-2795, 2013. Copyright © 2013 Wiley Periodicals, Inc., a Wiley Company.

Modeling the peptide-T cell receptor interaction by the comparative molecular similarity indices analysis-soft independent modeling of class analogy technique

A set of 38 epitopes and 183 non-epitopes, which bind to alleles of the HLA-A3 supertype, was subjected to a combination of comparative molecular similarity indices analysis (CoMSIA) and soft independent modeling of class analogy (SIMCA). During the process of T cell recognition, T cell receptors (TCR) interact with the central section of the bound nonamer peptide; thus only positions 4−8 were considered in the study. The derived model distinguished 82% of the epitopes and 73% of the non-epitopes after cross-validation in five groups. The overall preference from the model is for polar amino acids with high electron density and the ability to form hydrogen bonds. These so-called “aggressive” amino acids are flanked by small-sized residues, which enable such residues to protrude from the binding cleft and take an active role in TCR-mediated T cell recognition. Combinations of “aggressive” and “passive” amino acids in the middle part of epitopes constitute a putative TCR binding motif

Conformational analysis of the natural iron chelator myo-inositol 1,2,3-trisphosphate using a pyrene-based fluorescent mimic

myo-Inositol phosphates possessing the 1,2,3-trisphosphate motif share the remarkable ability to completely inhibit iron-catalysed hydroxyl radical formation. The simplest derivative, myo-inositol 1,2,3-trisphosphate [Ins(1,2,3)P3], has been proposed as an intracellular iron chelator involved in iron transport. The binding conformation of Ins(1,2,3)P3 is considered to be important to complex Fe3+ in a 'safe' manner. Here, a pyrene-based fluorescent probe, 4,6-bispyrenoyl-myo-inositol 1,2,3,5-tetrakisphosphate [4,6-bispyrenoyl Ins(1,2,3,5)P4], has been synthesised and used to monitor the conformation of the 1,2,3-trisphosphate motif using excimer fluorescence emission. Ring-flip of the cyclohexane chair to the penta-axial conformation occurs upon association with Fe3+, evident from excimer fluorescence induced by π-π stacking of the pyrene reporter groups, accompanied by excimer formation by excitation at 351 nm. This effect is unique amongst biologically relevant metal cations, except for Ca 2+ cations exceeding a 1:1 molar ratio. In addition, the thermodynamic constants for the interaction of the fluorescent probe with Fe3+ have been determined. The complexes formed between Fe 3+ and 4,6-bispyrenoyl Ins(1,2,3,5)P4 display similar stability to those formed with Ins(1,2,3)P3, indicating that the fluorescent probe acts as a good model for the 1,2,3-trisphosphate motif. This is further supported by the antioxidant properties of 4,6-bispyrenoyl Ins(1,2,3,5)P4, which closely resemble those obtained for Ins(1,2,3)P3. The data presented confirms that Fe3+ binds tightly to the unstable penta-axial conformation of myo-inositol phosphates possessing the 1,2,3-trisphosphate motif. © 2010 The Royal Society of Chemistry.

Computational Analysis of Intelligent Agents: Social and Strategic Settings

The central motif of this work is prediction and optimization in presence of multiple interacting intelligent agents. We use the phrase `intelligent agents' to imply in some sense, a `bounded rationality', the exact meaning of which varies depending on the setting. Our agents may not be `rational' in the classical game theoretic sense, in that they don't always optimize a global objective. Rather, they rely on heuristics, as is natural for human agents or even software agents operating in the real-world. Within this broad framework we study the problem of influence maximization in social networks where behavior of agents is myopic, but complication stems from the structure of interaction networks. In this setting, we generalize two well-known models and give new algorithms and hardness results for our models. Then we move on to models where the agents reason strategically but are faced with considerable uncertainty. For such games, we give a new solution concept and analyze a real-world game using out techniques. Finally, the richest model we consider is that of Network Cournot Competition which deals with strategic resource allocation in hypergraphs, where agents reason strategically and their interaction is specified indirectly via player's utility functions. For this model, we give the first equilibrium computability results. In all of the above problems, we assume that payoffs for the agents are known. However, for real-world games, getting the payoffs can be quite challenging. To this end, we also study the inverse problem of inferring payoffs, given game history. We propose and evaluate a data analytic framework and we show that it is fast and performant.

Raman microscopy of formamide-intercalated kaolinites treated by controlled-rate thermal analysis technology

Raman spectroscopy of formamide-intercalated kaolinites treated using controlled-rate thermal analysis technology (CRTA), allowing the separation of adsorbed formamide from intercalated formamide in formamide-intercalated kaolinites, is reported. The Raman spectra of the CRTA-treated formamide-intercalated kaolinites are significantly different from those of the intercalated kaolinites, which display a combination of both intercalated and adsorbed formamide. An intense band is observed at 3629 cm-1, attributed to the inner surface hydroxyls hydrogen bonded to the formamide. Broad bands are observed at 3600 and 3639 cm-1, assigned to the inner surface hydroxyls, which are hydrogen bonded to the adsorbed water molecules. The hydroxyl-stretching band of the inner hydroxyl is observed at 3621 cm-1 in the Raman spectra of the CRTA-treated formamide-intercalated kaolinites. The results of thermal analysis show that the amount of intercalated formamide between the kaolinite layers is independent of the presence of water. Significant differences are observed in the CO stretching region between the adsorbed and intercalated formamide.

Detailed analysis of a conservative difference approximation for the time fractional diffusion equation

Diffusion equations that use time fractional derivatives are attractive because they describe a wealth of problems involving non-Markovian Random walks. The time fractional diffusion equation (TFDE) is obtained from the standard diffusion equation by replacing the first-order time derivative with a fractional derivative of order α ∈ (0, 1). Developing numerical methods for solving fractional partial differential equations is a new research field and the theoretical analysis of the numerical methods associated with them is not fully developed. In this paper an explicit conservative difference approximation (ECDA) for TFDE is proposed. We give a detailed analysis for this ECDA and generate discrete models of random walk suitable for simulating random variables whose spatial probability density evolves in time according to this fractional diffusion equation. The stability and convergence of the ECDA for TFDE in a bounded domain are discussed. Finally, some numerical examples are presented to show the application of the present technique.

Determination of preventive maintenance lead time using hybrid analysis

The time for conducting Preventive Maintenance (PM) on an asset is often determined using a predefined alarm limit based on trends of a hazard function. In this paper, the authors propose using both hazard and reliability functions to improve the accuracy of the prediction particularly when the failure characteristic of the asset whole life is modelled using different failure distributions for the different stages of the life of the asset. The proposed method is validated using simulations and case studies.