Reduced pancreatic β-cell mass is associated with decreased FoxO1 and Erk1/2 protein phosphorylation in low-protein malnourished rats

A low-protein diet leads to functional and structural pancreatic islet alterations, including islet hypotrophy. Insulin-signaling pathways are involved in several adaptive responses by pancreatic islets. We determined the levels of some insulin-signaling proteins related to pancreatic islet function and growth in malnourished rats. Adult male Wistar rats (N = 20 per group) were fed a 17% protein (normal-protein diet; NP) or 6% protein (low-protein diet; LP), for 8 weeks. At the end of this period, blood glucose and serum insulin and albumin levels were measured. The morphometric parameters of the endocrine pancreas and the content of some proteins in islet lysates were determined. The β-cell mass was significantly reduced (≅65%) in normoglycemic but hypoinsulinemic LP rats compared to NP rats. Associated with these alterations, a significant 30% reduction in insulin receptor substrate-1 and a 70% increase in insulin receptor substrate-2 protein content were observed in LP islets compared to NP islets. The phosphorylated serine-threonine protein kinase (pAkt)/Akt protein ratio was similar in LP and NP islets. The phosphorylated forkhead-O1 (pFoxO1)/FoxO1 protein ratio was decreased by 43% in LP islets compared to NP islets (P < 0.05). Finally, the ratio of phosphorylated-extracellular signal-related kinase 1/2 (pErk1/2) to total Erk1/2 protein levels was decreased by 71% in LP islets compared to NP islets (P < 0.05). Therefore, the reduced β-cell mass observed in LP rats is associated with the reduction of phosphorylation in mitogenic-related signals, FoxO1 and Erk proteins. The cause/effect basis of this association remains to be determined.

Sleep pattern and learning in knockdown mice with reduced cholinergic neurotransmission

Impaired cholinergic neurotransmission can affect memory formation and influence sleep-wake cycles (SWC). In the present study, we describe the SWC in mice with a deficient vesicular acetylcholine transporter (VAChT) system, previously characterized as presenting reduced acetylcholine release and cognitive and behavioral dysfunctions. Continuous, chronic ECoG and EMG recordings were used to evaluate the SWC pattern during light and dark phases in VAChT knockdown heterozygous (VAChT-KDHET, n=7) and wild-type (WT, n=7) mice. SWC were evaluated for sleep efficiency, total amount and mean duration of slow-wave, intermediate and paradoxical sleep, as well as the number of awakenings from sleep. After recording SWC, contextual fear-conditioning tests were used as an acetylcholine-dependent learning paradigm. The results showed that sleep efficiency in VAChT-KDHET animals was similar to that of WT mice, but that the SWC was more fragmented. Fragmentation was characterized by an increase in the number of awakenings, mainly during intermediate sleep. VAChT-KDHET animals performed poorly in the contextual fear-conditioning paradigm (mean freezing time: 34.4±3.1 and 44.5±3.3 s for WT and VAChT-KDHET animals, respectively), which was followed by a 45% reduction in the number of paradoxical sleep episodes after the training session. Taken together, the results show that reduced cholinergic transmission led to sleep fragmentation and learning impairment. We discuss the results on the basis of cholinergic plasticity and its relevance to sleep homeostasis. We suggest that VAChT-KDHET mice could be a useful model to test cholinergic drugs used to treat sleep dysfunction in neurodegenerative disorders.

Mikrostrukturierte Sensoren für die pH-Wert-Bestimung auf Basis von dünnen, intrinisch leitfähigen Polyanilinschichten

Der pH-Wert stellt in der Chemie, Physik, Biologie, Pharmazie und Medizin eine wichtige Meßgröße dar, da eine Vielzahl von Reaktionen durch den pH-Wert bestimmt wird. In der Regel werden zur pH-Wert-Messung Glaselektroden eingesetzt. Hierbei konnte der pH-sensitive Bereich zwar bis auf einige Mikrometer reduziert werden, aber die Gesamtab-messungen betragen immer noch 15-20 cm. Mit der Einführung miniaturisierter Reaktionsgefäße ist daher der Bedarf an miniaturisierten Sensoren enorm gestiegen. Um in solchen Gefäßen Reaktionsparameter wie z. B. den pH-Wert zu kontrollieren, müssen die Gesamtabmessungen der Sensoren verringert werden. Dies lässt sich mit Hilfe der Mikrostrukturtechnik von Silizium realisieren. Hiermit lassen sich Strukturen und ganze Systeme bis in den Nanometerbereich herstellen. Basierend auf Silizium und Gold als Elektrodenmaterial wurden im Rahmen dieser Arbeit verschiedene Interdigitalstrukturen hergestellt. Um diese Strukturen zur pH-Wert-Messungen einsetzen zu können, müssen sie mit einer pH-sensitiven Schicht versehen werden. Hierbei wurde Polyanilin, ein intrinsisch leitendes Polymer, aufgrund seine pH-abhängigen elektrischen und optischen Verhaltens eingesetzt. Die Beschichtung dieser Sensoren mit Polyanilin erfolgte vorwiegend elektrochemisch mit Hilfe der Zyklovoltammetrie. Neben der Herstellung reiner Polyanilinfilme wurden auch Kopolymerisationen von Anilin und seinen entsprechenden Aminobenzoesäure- bzw. Aminobenzensulfonsäurederivaten durchgeführt. Ergebnisse dazu werden vorgestellt und diskutiert. Zur Charakterisierung der resultierenden Polyanilin- und Kopolymerfilme auf den Inter-digitalstrukturen wurden mit Hilfe der ATR-FT-IR-Spektroskopie Spektren aufgenommen, die gezeigt und diskutiert werden. Eine elektrochemische Charakterisierung der Polymere erfolgte mittels der Zyklovoltammetrie. Die mit Polyanilin bzw. seinen Kopolymeren beschichteten Sensoren wurden dann für Widerstandsmessungen an den Polymerfilmen in wässrigen Medien eingesetzt. Polyanilin zeigt lediglich eine pH-Sensitivität in einem pH-Bereich von pH 2 bis pH 4. Durch den Einsatz der Kopolymere konnte dieser pH-sensitive Bereich jedoch bis zu einem pH-Wert von 10 ausgeweitet werden. Zur weiteren Miniaturisierung der Sensoren wurde das Konzept der interdigitalen Elektroden-paare auf Cantilever übertragen. Die pH-sensitive Zone konnte dabei auf 500 µm2 bei einer Gesamtlänge des Sensors (Halter mit integriertem Cantilever) von 4 mm reduziert werden. Neben den elektrischen pH-abhängigen Eigenschaften können auch die optischen Eigen-schaften des Polyanilins zur pH-Detektion herangezogen werden. Diese wurden zunächst mit Hilfe der UV-VIS-Spektroskopie untersucht. Die erhaltenen Spektren werden gezeigt und kurz diskutiert. Mit Hilfe eines Raster-Sonden-Mikroskops (a-SNOM, Firma WITec) wurden Reflexionsmessungen an Polyanilinschichten durchgeführt. Zur weiteren Miniaturisierung wurden Siliziumdioxidhohlpyramiden (Basisfläche 400 µm2) mit Spitzenöffnungen in einem Bereich von 50-150 nm mit Polyanilin beschichtet. Auch hier sollten die optischen Eigenschaften des Polyanilins zur pH-Wert-Sensorik ausgenutzt werden. Es werden erste Messungen an diesen Strukturen in Transmission diskutiert.

Priors Stabilizers and Basis Functions: From Regularization to Radial, Tensor and Additive Splines

We had previously shown that regularization principles lead to approximation schemes, as Radial Basis Functions, which are equivalent to networks with one layer of hidden units, called Regularization Networks. In this paper we show that regularization networks encompass a much broader range of approximation schemes, including many of the popular general additive models, Breiman's hinge functions and some forms of Projection Pursuit Regression. In the probabilistic interpretation of regularization, the different classes of basis functions correspond to different classes of prior probabilities on the approximating function spaces, and therefore to different types of smoothness assumptions. In the final part of the paper, we also show a relation between activation functions of the Gaussian and sigmoidal type.

An Equivalence Between Sparse Approximation and Support Vector Machines

In the first part of this paper we show a similarity between the principle of Structural Risk Minimization Principle (SRM) (Vapnik, 1982) and the idea of Sparse Approximation, as defined in (Chen, Donoho and Saunders, 1995) and Olshausen and Field (1996). Then we focus on two specific (approximate) implementations of SRM and Sparse Approximation, which have been used to solve the problem of function approximation. For SRM we consider the Support Vector Machine technique proposed by V. Vapnik and his team at AT&T Bell Labs, and for Sparse Approximation we consider a modification of the Basis Pursuit De-Noising algorithm proposed by Chen, Donoho and Saunders (1995). We show that, under certain conditions, these two techniques are equivalent: they give the same solution and they require the solution of the same quadratic programming problem.

Ab initio benchmark study for the oxidative addition of CH4 to Pd: importance of basis-set flexibility and polarization

To obtain a state-of-the-art benchmark potential energy surface (PES) for the archetypal oxidative addition of the methane C-H bond to the palladium atom, we have explored this PES using a hierarchical series of ab initio methods (Hartree-Fock, second-order Møller-Plesset perturbation theory, fourth-order Møller-Plesset perturbation theory with single, double and quadruple excitations, coupled cluster theory with single and double excitations (CCSD), and with triple excitations treated perturbatively [CCSD(T)]) and hybrid density functional theory using the B3LYP functional, in combination with a hierarchical series of ten Gaussian-type basis sets, up to g polarization. Relativistic effects are taken into account either through a relativistic effective core potential for palladium or through a full four-component all-electron approach. Counterpoise corrected relative energies of stationary points are converged to within 0.1-0.2 kcal/mol as a function of the basis-set size. Our best estimate of kinetic and thermodynamic parameters is -8.1 (-8.3) kcal/mol for the formation of the reactant complex, 5.8 (3.1) kcal/mol for the activation energy relative to the separate reactants, and 0.8 (-1.2) kcal/mol for the reaction energy (zero-point vibrational energy-corrected values in parentheses). This agrees well with available experimental data. Our work highlights the importance of sufficient higher angular momentum polarization functions, f and g, for correctly describing metal-d-electron correlation and, thus, for obtaining reliable relative energies. We show that standard basis sets, such as LANL2DZ+ 1f for palladium, are not sufficiently polarized for this purpose and lead to erroneous CCSD(T) results. B3LYP is associated with smaller basis set superposition errors and shows faster convergence with basis-set size but yields relative energies (in particular, a reaction barrier) that are ca. 3.5 kcal/mol higher than the corresponding CCSD(T) values

Simplification, approximation and deformation of large models

The high level of realism and interaction in many computer graphic applications requires techniques for processing complex geometric models. First, we present a method that provides an accurate low-resolution approximation from a multi-chart textured model that guarantees geometric fidelity and correct preservation of the appearance attributes. Then, we introduce a mesh structure called Compact Model that approximates dense triangular meshes while preserving sharp features, allowing adaptive reconstructions and supporting textured models. Next, we design a new space deformation technique called *Cages based on a multi-level system of cages that preserves the smoothness of the mesh between neighbouring cages and is extremely versatile, allowing the use of heterogeneous sets of coordinates and different levels of deformation. Finally, we propose a hybrid method that allows to apply any deformation technique on large models obtaining high quality results with a reduced memory footprint and a high performance.

A collocation method for high frequency scattering by convex polygons

We consider the problem of scattering of a time-harmonic acoustic incident plane wave by a sound soft convex polygon. For standard boundary or finite element methods, with a piecewise polynomial approximation space, the computational cost required to achieve a prescribed level of accuracy grows linearly with respect to the frequency of the incident wave. Recently Chandler–Wilde and Langdon proposed a novel Galerkin boundary element method for this problem for which, by incorporating the products of plane wave basis functions with piecewise polynomials supported on a graded mesh into the approximation space, they were able to demonstrate that the number of degrees of freedom required to achieve a prescribed level of accuracy grows only logarithmically with respect to the frequency. Here we propose a related collocation method, using the same approximation space, for which we demonstrate via numerical experiments a convergence rate identical to that achieved with the Galerkin scheme, but with a substantially reduced computational cost.

Analysis of shade and temperature effects on assimilate partitioning in the everbearing strawberry 'Everest' as the basis for optimised long-season fruit production

Growth patterns and cropping were evaluated over the season for the everbearing strawberry 'Everest' at a range of temperatures (15-27degreesC) in two light environments (ambient and 50% shade). The highest yield was recorded for unshaded plants grown at 23degreesC, but the optimum temperature for vegetative growth was 15degreesC. With increasing temperature fruit number increased, but fruit weight decreased. Fruit weight was also significantly reduced by shade, and although 'Everest' showed a degree of shade tolerance in vegetative growth, yield was consistently reduced by shade. Shade also reduced the number of crowns developed by the plants over the course of the season, emphasising that crown number was ultimately the limiting factor for yield potential. We conclude that, in contrast to Junebearers which partition more assimilates to fruit at temperatures around 15degreesC (Le Miere et al., 1998), optimised cropping in the everbearer 'Everest' is achieved at the significantly higher temperature of 23degreesC. These findings have significance for commercial production, in which protection tends to reduce light levels but increase average temperature throughout the season.

Sparse model identification using orthogonal forward regression with basis pursuit and D-optimality

An efficient model identification algorithm for a large class of linear-in-the-parameters models is introduced that simultaneously optimises the model approximation ability, sparsity and robustness. The derived model parameters in each forward regression step are initially estimated via the orthogonal least squares (OLS), followed by being tuned with a new gradient-descent learning algorithm based on the basis pursuit that minimises the l(1) norm of the parameter estimate vector. The model subset selection cost function includes a D-optimality design criterion that maximises the determinant of the design matrix of the subset to ensure model robustness and to enable the model selection procedure to automatically terminate at a sparse model. The proposed approach is based on the forward OLS algorithm using the modified Gram-Schmidt procedure. Both the parameter tuning procedure, based on basis pursuit, and the model selection criterion, based on the D-optimality that is effective in ensuring model robustness, are integrated with the forward regression. As a consequence the inherent computational efficiency associated with the conventional forward OLS approach is maintained in the proposed algorithm. Examples demonstrate the effectiveness of the new approach.

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.

Scenarios as the basis for assessment of mitigation and adaptation

The possibilities and need for adaptation and mitigation depends on uncertain future developments with respect to socio-economic factors and the climate system. Scenarios are used to explore the impacts of different strategies under uncertainty. In this chapter, some scenarios are presented that are used in the ADAM project for this purpose. One scenario explores developments with no mitigation, and thus with high temperature increase and high reliance on adaptation (leading to 4oC increase by 2100 compared to pre-industrial levels). A second scenario explores an ambitious mitigation strategy (leading to 2oC increase by 2100 compared to pre-industrial levels). In the latter scenario, stringent mitigation strategies effectively reduces the risks of climate change, but based on uncertainties in the climate system a temperature increase of 3oC or more cannot be excluded. The analysis shows that, in many cases, adaptation and mitigation are not trade-offs but supplements. For example, the number of people exposed to increased water resource stress due to climate change can be substantially reduced in the mitigation scenario, but even then adaptation will be required for the remaining large numbers of people exposed to increased stress. Another example is sea level rise, for which adaptation is more cost-effective than mitigation, but mitigation can help reduce damages and the cost of adaptation. For agriculture, finally, only the scenario based on a combination of adaptation and mitigation is able to avoid serious climate change impacts.

A structural basis for the inhibition of collagen-stimulated platelet function by quercetin and structurally related flavonoids

Background and purpose: Molecular mechanisms underlying the links between dietary intake of flavonoids and reduced cardiovascular disease risk are only partially understood. Key events in the pathogenesis of cardiovascular disease, particularly thrombosis, are inhibited by these polyphenolic compounds via mechanisms such as inhibition of platelet activation and associated signal transduction, attenuation of generation of reactive oxygen species, enhancement of nitric oxide production and binding to thromboxane A2 receptors. In vivo, effects of flavonoids are mediated by their metabolites, but the effects and modes of action of these compounds are not well-characterized. A good understanding of flavonoid structure–activity relationships with regard to platelet function is also lacking. Experimental approach: Inhibitory potencies of structurally distinct flavonoids (quercetin, apigenin and catechin) and plasma metabolites (tamarixetin, quercetin-3′-sulphate and quercetin-3-glucuronide) for collagen-stimulated platelet aggregation and 5-hydroxytryptamine secretion were measured in human platelets. Tyrosine phosphorylation of total protein, Syk and PLCγ2 (immunoprecipitation and Western blot analyses), and Fyn kinase activity were also measured in platelets. Internalization of flavonoids and metabolites in a megakaryocytic cell line (MEG-01 cells) was studied by fluorescence confocal microscopy. Key results: The inhibitory mechanisms of these compounds included blocking Fyn kinase activity and the tyrosine phosphorylation of Syk and PLCγ2 following internalization. Principal functional groups attributed to potent inhibition were a planar, C-4 carbonyl substituted and C-3 hydroxylated C ring in addition to a B ring catechol moiety. Conclusions and implications: The structure–activity relationship for flavonoids on platelet function presented here may be exploited to design selective inhibitors of cell signalling.

Use of a reduced Schiff-Base ligand to prepare novel chloro-bridged chains of rare Cu(II) trinuclear complexes with mixed azido/oxo and chloro/oxo bridges

Two mixed bridged one-dimensional (1D) polynuclear complexes, [Cu3L2(mu(1,1)-N-3)(2)(mu-Cl)Cl](n) (1) and {[Cu3L2(mu-Cl)(3)Cl]center dot 0.46CH(3)OH}(n), (2), have been synthesized using the tridentate reduced Schiff-base ligand HL (2-[(2-dimethylamino-ethylamino)-methyl]-phenol). The complexes have been characterized by X-ray structural analyses and variable-temperature magnetic susceptibility measurements. In both complexes the basic trinuclear angular units are joined together by weak chloro bridges to form a 1D chain. The trinuclear structure of 1 is composed of two terminal square planar [Cu(L)(mu(1,1)-N-3)] units connected by a central Cu(II) atom through bridging nitrogen atoms of end-on azido ligands and the phenoxo oxygen atom of the tridentate ligand. These four coordinating atoms along with a chloride ion form a distorted trigonal bipyramidal geometry around the central Cu(II). The structure of 2 is similar; the only difference being a Cl bridge replacing the mu(1,1)-N-3 bridge in the trinuclear unit. The magnetic properties of both trinuclear complexes can be very well reproduced with a simple linear symmetrical trimer model (H = JS(i)S(i+1)) with only one intracluster exchange coupling (J) including a weak intertrimer interaction (.j) reproduced with the molecular field approximation. This model provides very satisfactory fits for both complexes in the whole temperature range with the following parameters: g = 2.136(3), J = 93.9(3) cm(-1) and zj= -0.90(3) cm(-1) (z = 2) for 1 and g = 2.073(7), J = -44.9(4) cm(-1) and zJ = -1.26(6) cm(-1) (z = 2) for 2.

Unit-cell approximation for diblock−copolymer brushes grafted to spherical particles

This paper examines the equilibrium phase behavior of thin diblock-copolymer films tethered to a spherical core, using numerical self-consistent field theory (SCFT). The computational cost of the calculation is greatly reduced by implementing the unit-cell approximation (UCA) routinely used in the study of bulk systems. This provides a tremendous reduction in computational time, permitting us to map out the phase behavior more extensively and allowing us to consider far larger particles. The main consequence of the UCA is that it omits packing frustration, but evidently the effect is minor for large particles. On the other hand, when the particles are small, the UCA calculation can be readily followed up with the full SCFT, the comparison to which conveniently allows one to quantitatively assess the effect of packing frustration.