Formation of dityrosine cross-links during breadmaking

To establish its significance during commercial breadmaking, dityrosine formation was quantified in flours and doughs of six commercial wheat types at various stages of the Chorleywood Bread Process. Dityrosine was formed mainly during mixing and baking, at the levels of nmol/g dry weight. Good breadmaking flours tended to exhibit higher dityrosine content in the final bread than low quality ones, but no relationship was found for dityrosine as a proportion of flour protein content, indicating that the latter was still a dominant factor in the analysis. There was no correlation between gluten yield of the six wheat types and their typical dityrosine concentrations, suggesting that dityrosine crosslinks were not a determinant factor for gluten formation. Ascorbic acid was found to inhibit dityrosine formation during mixing and proving, and have no significant effect on dityrosine in the final bread. Hydrogen peroxide promoted dityrosine formation, which suggests a radical mechanism involving endogenous peroxidases might be the responsible for dityrosine formation during breadmaking.

Supramolecular helix and beta-sheet through self-assembly of two isomeric tetrapeptides in crystals and formation of filaments and ribbons in the solid state

Single crystal X-ray diffraction studies show that the beta-turn structure of tetrapeptide I, Boc-Gly-Phe-Aib-Leu-OMe (Aib: alpha-amino isobutyric acid) self-assembles to a supramolecular helix through intermolecular hydrogen bonding along the crystallographic a axis. By contrast the beta-turn structure of an isomeric tetrapeptide II, Boc-Gly-Leu-Aib-Phe-OMe self-assembles to a supramolecular beta-sheet-like structure via a two-dimensional (a, b axis) intermolecular hydrogen bonding network and pi-pi interactions. FT-IR studies of the peptides revealed that both of them form intermolecularly hydrogen bonded supramolecular structures in the solid state. Field emission scanning electron micrographs (FE-SEM) of the dried fibrous materials of the peptides show different morphologies, non-twisted filaments in case of peptide I and non-twisted filaments and ribbon-like structures in case of peptide II.

Inhibition of the formation of the neurotoxin 5-S-cysteinyl-dopamine by polyphenols

The death of nigral neurons in Parkinson's disease is thought to involve the formation of the endogenous neurotoxin, 5-S-cysteinyl-dopamine. In the present study, we show that the polyphenols, (+)-catechin and caffeic acid, which contain a catechol moiety, inhibit tyrosinase-induced formation of 5-S-eysteinyl-dopamine via their capacity to undergo tyro sina se-induced oxidation to yield cysteinyl-polyphenol adducts. In contrast, the inhibition afforded by the flavanone, hesperetin, was not accompanied by the formation of cysteinyl-hesperetin adducts, indicating that it may inhibit via direct interaction with tyrosinase. Whilst the stilbene resveratrol also inhibited 5-S-eysteinyl-dopamine formation, this was accompanied by the formation of dihydrobenzothiazine, a strong neurotoxin. Our data indicate that the inhibitory effects of polyphenols against 5-S-cysteinyl-dopamine formation are structure-dependent and shed further light on the mechanisms by which polyphenols exert protection against neuronal injury relevant to neurodegenerative diseases. (C) 2007 Elsevier Inc. All rights reserved.

Peroxynitrite induced formation of the neurotoxins 5-S-cysteinyl-dopamine and DHBT-1: implications for Parkinson's disease and protection by polyphenols

Mechanisms of nigral cell injury in Parkinson's disease remain unclear, although a combination of increased oxidative stress, the formation of catecholamine-quinones and the subsequent formation of neurotoxic cysteinyl-catecholamine conjugates may contribute. In the present study, peroxynitrite was observed to generate both 2-S- and 5-S-cysteinyl-dopamine and a dihydrobenzothiazine species, DHBT-1, following the reaction of dopamine with L-cysteine. The formation of 5-S-cysteinyl-dopamine and DHBT-1 in the presence of peroxynitrite induced significant neuronal injury. Pre-treatment of cortical neurons with pelargonidin, quercetin, hesperetin, caffeic acid, the 4'-O-Me derivatives of catechin and epicatechin (0.1-3.0 mu M) resulted in concentration dependant protection against 5-S-cysteinyl-dopamine-induced neurotoxicity. These data suggest that polyphenols may protect against neuronal injury induced by endogenous neurotoxins relevant to the aetiology of the Parkinson disease. (C) 2008 Elsevier Inc. All rights reserved.

pH-mediated interactions between poly(acrylic acid) and methylcellulose in the formation of ultrathin multilayered hydrogels and spherical nanoparticles

Poly(acrylic acid) forms insoluble hydrogen-bonded interpolymer complexes with methylcellulose in aqueous solutions under acidic conditions. In this work the reaction heats and binding constants were determined for the complexation between poly(acrylic acid) and methylcellulose by isothermal titration calorimetry at different pH and findings are correlated with the aggregation processes occurring in this system. The principal contribution to the complexation heat results from primary polycomplex particle aggregation. Transmission electron microscopy of nanoparticles produced at pH 1.4 and 2.4 demonstrated that they are spherical and dense structures. The nanoparticles ranged from 80 to 200 nm, whereas particles formed at pH 3.2 were 20-30 nm and were stabilized against aggregation by a network of uncomplexed macromolecules. For the first time, multilayered materials were developed on the basis of hydrogen-bonded complexes of poly(acrylic acid) and methylcellulose using layer-by-layer deposition on a glass surface. The thickness of these films was a linear function of the number of deposition cycles. The materials were subsequently cross-linked by thermal treatment, resulting in ultrathin hydrogels which detached from the glass substrate upon swelling. The swelling capacity of ultrathin hydrogels differed from the swelling of the thicker films of a similar chemical composition.

Prefrontal social cognition network dysfunction underlying face encoding and social anxiety in fragile X syndrome

Individuals with fragile X syndrome (FXS) commonly display characteristics of social anxiety, including gaze aversion, increased time to initiate social interaction, and difficulty forming meaningful peer relationships. While neural correlates of face processing, an important component of social interaction, are altered in FXS, studies have not examined whether social anxiety in this population is related to higher cognitive processes, such as memory. This study aimed to determine whether the neural circuitry involved in face encoding was disrupted in individuals with FXS, and whether brain activity during face encoding was related to levels of social anxiety. A group of 11 individuals with FXS (5 M) and 11 age-and gender-matched control participants underwent fMRI scanning while performing a face encoding task with onlineeye-tracking. Results indicate that compared to the control group, individuals with FXS exhibited decreased activation of prefrontal regions associated with complex social cognition, including the medial and superior frontal cortex, during successful face encoding. Further, the FXS and control groups showed significantly different relationships between measures of social anxiety (including gaze-fixation) and brain activity during face encoding. These data indicate that social anxiety in FXS may be related to the inability to successfully recruit higher level social cognition regions during the initial phases of memory formation. (C) 2008 Elsevier Inc. All rights reserved.

Generalized neurofuzzy network modeling algorithms using Bezier-Bernstein polynomial functions and additive decomposition

This paper introduces a new neurofuzzy model construction algorithm for nonlinear dynamic systems based upon basis functions that are Bezier-Bernstein polynomial functions. This paper is generalized in that it copes with n-dimensional inputs by utilising an additive decomposition construction to overcome the curse of dimensionality associated with high n. This new construction algorithm also introduces univariate Bezier-Bernstein polynomial functions for the completeness of the generalized procedure. Like the B-spline expansion based neurofuzzy systems, Bezier-Bernstein polynomial function based neurofuzzy networks hold desirable properties such as nonnegativity of the basis functions, unity of support, and interpretability of basis function as fuzzy membership functions, moreover with the additional advantages of structural parsimony and Delaunay input space partition, essentially overcoming the curse of dimensionality associated with conventional fuzzy and RBF networks. This new modeling network is based on additive decomposition approach together with two separate basis function formation approaches for both univariate and bivariate Bezier-Bernstein polynomial functions used in model construction. The overall network weights are then learnt using conventional least squares methods. Numerical examples are included to demonstrate the effectiveness of this new data based modeling approach.

A thermoresponsive supramolecular polymer network comprising pyrene-functionalized gold nano-particles and a chain-folding polydiimide.

A thermoresponsive, supramolecular nanocomposite has been prepared by the addition of pyrenyl functionalized gold nanoparticles (AuNPs) to a polydiimide that contains receptor residues designed to form defined complexes with pyrene. The novel pyrenyl-functionalized AuNPs (P-AuNPs) were characterized by transmission electron microscopy, with surface functionalization confirmed by infrared and UV–visible spectroscopic analyses. Mixing solutions of the P-AuNPs and a π-electron-deficient polydiimide resulted in the formation of electronically complementary, chain-folded and π–π-stacked complexes, so affording a new supramolecular nanocomposite network which precipitated from solution. The P-AuNPs bind to the polydiimide via π–π stacking interactions to create supramolecular cross-links. UV–visible spectroscopic analysis confirmed the thermally reversible nature of the complexation process, and transmission electron microscopy (TEM), infrared spectroscopy (IR), and differential scanning calorimetry (DSC) were used to characterize the supramolecular-nanocomposite material. The supramolecular polymer network is insoluble at room temperature, yet may be dissolved at temperatures above 60 °C. The thermal reversibility of this system is maintained over five heat/cool cycles without diminishment of the network characteristics. In contrast to the individual components, the nanocomposite formed self-supporting films, demonstrating the benefit of the supramolecular network in terms of mechanical properties. Control experiments probing the interactions between a model diimide compound that can also form a π-stacked complex with the π-electron rich pyrene units on P-AuNPs showed that, while complexation was readily apparent, precipitation did not occur because a supramolecular cross-linked network system could not be formed with this system.

Hypoxia suppresses astrocyte glutamate transport independently of amyloid formation

Sustained hypoxia alters the expression of numerous proteins and predisposes individuals to Alzheimer's disease (AD). We have previously shown that hypoxia in vitro alters Ca2+ homeostasis in astrocytes and promotes increased production of amyloid beta peptides (Abeta) of AD. Indeed, alteration of Ca2+ homeostasis requires amyloid formation. Here, we show that electrogenic glutamate uptake by astrocytes is suppressed by hypoxia (1% O2, 24h) in a manner that is independent of amyloid beta peptide formation. Thus, hypoxic suppression of glutamate uptake and expression levels of glutamate transporter proteins EAAT1 and EAAT2 were not mimicked by exogenous application of amyloid beta peptide, or by prevention of endogenous amyloid peptide formation (using inhibitors of either beta or gamma secretase). Thus, dysfunction in glutamate homeostasis in hypoxic conditions is independent of Abeta production, but will likely contribute to neuronal damage and death associated with AD following hypoxic events.

Observing wind, aerosol particles, clouds and precipitation: Finland's new ground-based remote-sensing network

The Finnish Meteorological Institute, in collaboration with the University of Helsinki, has established a new ground-based remote-sensing network in Finland. The network consists of five topographically, ecologically and climatically different sites distributed from southern to northern Finland. The main goal of the network is to monitor air pollution and boundary layer properties in near real time, with a Doppler lidar and ceilometer at each site. In addition to these operational tasks, two sites are members of the Aerosols, Clouds and Trace gases Research InfraStructure Network (ACTRIS); a Ka band cloud radar at Sodankylä will provide cloud retrievals within CloudNet, and a multi-wavelength Raman lidar, PollyXT (POrtabLe Lidar sYstem eXTended), in Kuopio provides optical and microphysical aerosol properties through EARLINET (the European Aerosol Research Lidar Network). Three C-band weather radars are located in the Helsinki metropolitan area and are deployed for operational and research applications. We performed two inter-comparison campaigns to investigate the Doppler lidar performance, compare the backscatter signal and wind profiles, and to optimize the lidar sensitivity through adjusting the telescope focus length and data-integration time to ensure sufficient signal-to-noise ratio (SNR) in low-aerosol-content environments. In terms of statistical characterization, the wind-profile comparison showed good agreement between different lidars. Initially, there was a discrepancy in the SNR and attenuated backscatter coefficient profiles which arose from an incorrectly reported telescope focus setting from one instrument, together with the need to calibrate. After diagnosing the true telescope focus length, calculating a new attenuated backscatter coefficient profile with the new telescope function and taking into account calibration, the resulting attenuated backscatter profiles all showed good agreement with each other. It was thought that harsh Finnish winters could pose problems, but, due to the built-in heating systems, low ambient temperatures had no, or only a minor, impact on the lidar operation – including scanning-head motion. However, accumulation of snow and ice on the lens has been observed, which can lead to the formation of a water/ice layer thus attenuating the signal inconsistently. Thus, care must be taken to ensure continuous snow removal.

Optimized hash for network path encoding with minimized false positives

The Bloom filter is a space efficient randomized data structure for representing a set and supporting membership queries. Bloom filters intrinsically allow false positives. However, the space savings they offer outweigh the disadvantage if the false positive rates are kept sufficiently low. Inspired by the recent application of the Bloom filter in a novel multicast forwarding fabric, this paper proposes a variant of the Bloom filter, the optihash. The optihash introduces an optimization for the false positive rate at the stage of Bloom filter formation using the same amount of space at the cost of slightly more processing than the classic Bloom filter. Often Bloom filters are used in situations where a fixed amount of space is a primary constraint. We present the optihash as a good alternative to Bloom filters since the amount of space is the same and the improvements in false positives can justify the additional processing. Specifically, we show via simulations and numerical analysis that using the optihash the false positives occurrences can be reduced and controlled at a cost of small additional processing. The simulations are carried out for in-packet forwarding. In this framework, the Bloom filter is used as a compact link/route identifier and it is placed in the packet header to encode the route. At each node, the Bloom filter is queried for membership in order to make forwarding decisions. A false positive in the forwarding decision is translated into packets forwarded along an unintended outgoing link. By using the optihash, false positives can be reduced. The optimization processing is carried out in an entity termed the Topology Manger which is part of the control plane of the multicast forwarding fabric. This processing is only carried out on a per-session basis, not for every packet. The aim of this paper is to present the optihash and evaluate its false positive performances via simulations in order to measure the influence of different parameters on the false positive rate. The false positive rate for the optihash is then compared with the false positive probability of the classic Bloom filter.

The multiple team formation problem using sociometry

The Team Formation problem (TFP) has become a well-known problem in the OR literature over the last few years. In this problem, the allocation of multiple individuals that match a required set of skills as a group must be chosen to maximise one or several social positive attributes. Speci�cally, the aim of the current research is two-fold. First, two new dimensions of the TFP are added by considering multiple projects and fractions of people's dedication. This new problem is named the Multiple Team Formation Problem (MTFP). Second, an optimization model consisting in a quadratic objective function, linear constraints and integer variables is proposed for the problem. The optimization model is solved by three algorithms: a Constraint Programming approach provided by a commercial solver, a Local Search heuristic and a Variable Neighbourhood Search metaheuristic. These three algorithms constitute the first attempt to solve the MTFP, being a variable neighbourhood local search metaheuristic the most effi�cient in almost all cases. Applications of this problem commonly appear in real-life situations, particularly with the current and ongoing development of social network analysis. Therefore, this work opens multiple paths for future research.