A low-temperature ammonium ylid rearrangement: enhanced reactivity engendered by rigidity

Sigmatropic rearrangement of tetrahydropyridine-derived ammonium is a valuable method for the preparation of substituted prolines. These reaction normally require elevated temperatures to proceed, but bicyclic tetrahydropyridine-like ylid I undergoes rearrangement at -15 degrees C; the extra rigidity of the azabicyclo[3.3.0]octene system preorganizes the transition state and lowers the activation energy for rearrangement.

Copper(II) complexes of tetradentate N2S2 donor sets: synthesis, crystal structure characterization and reactivity

Two mononuclear and one dinuclear copper(II) complexes, containing neutral tetradentate NSSN type ligands, of formulation [Cu-II(L-1)Cl]ClO4 (1), [Cu-II(L-2)Cl]ClO4 (2) and [Cu-2(II)(L-3)(2)Cl-2](ClO4)(2) (3) were synthesized and isolated in pure form [where L-1 = 1,2-bis(2-pyridylmethylthio)ethane, L-2 = 1,3-bis(2-pyridylmethylthio)propane and L-3 = 1,4-bis(2-pyridylmethylthio)butane]. All these green colored copper(II) complexes were characterized by physicochemical and spectroscopic methods. The dinuclear copper(II) complex 3 changed to a colorless dinuclear copper(I) species of formula [Cu-2(1)(L-3)(2)](ClO4)(2),0.5H(2)O (4) in dimethylformamide even in the presence of air at ambient temperature, while complexes I and 2 showed no change under similar conditions. The solid-state structures of complexes 1, 2 and 4 were established by X-ray crystallography. The geometry about the copper in complexes 1 and 2 is trigonal bipyramidal whereas the coordination environment about the copper(I) in dinuclear complex 4 is distorted tetrahedral. (C) 2008 Elsevier Ltd. All rights reserved.

Synthesis, crystal structure and reactivity of copper(II) complexes of tetradentate N2S2 donor ligands

Two new hexa-coordinated mononuclear copper(II) complexes of two ligands L-1 and L-2 containing NSSN donor sets formulated as [Cu(L)(H2O)(2)](NO3)(2) [1a, L = 1,2-bis(2-pyridylmethylthio)ethane (L-1), 1b L = 1,3-bis(2-pyridyl-methylthio)propane (L-2)] were synthesized and characterized by physico-chemical and spectroscopic methods. In 1a the single crystal X-ray crystallography analysis showed a distorted octahedral geometry about copper(II) ion. The crystal packing evidences pairs of complexes arranged about a center of symmetry and connected through a H-bond occurring between aquo ligands and nitrate anions. On reaction with chloride and pseudohalides (N-3(-) and SCN-), in acetonitrile at ambient temperature. complexes 1 changed to monocationic penta-coordinated mononuclear copper(H) species formulated as [Cu(L)(Cl)]NO3 (2), [Cu(L)(N-3)]NO3 (3). and [Cu(L)(SCN)]NO3 (4). These copper(II) complexes have been isolated in pure form from the reaction mixtures and characterized by physico-chemical and spectroscopic tools. The solid-state structure of 2a, established by X-ray crystallography, shows a trigonal bipyramidal geometry about the metal ion with a trigonality index (tau) of 0.561. (C) 2009 Elsevier B.V. All rights reserved.

Chemical composition and reactivity of water on hexagonal Pt-group metal surfaces

The dissociation behaviour and valence-electronic structure of water adsorbed on clean and oxygen-covered Ru{0001}, Rh{111}, Pd{111}, Ir{111} and Pt{111} surfaces has been studied by high-resolution X-ray photoelectron spectroscopy with the aim of identifying similarities and trends within the Pt-group metals. On average, we find higher reactivity for the 4d metals (Ru, Rh, Pd) as compared to 5d (Ir, Pt), which is correlated with characteristic shifts in the 1b(1) and 3a(1) molecular orbitals of water. Small amounts of oxygen (<0.2 ML) induce dissociation of water on all five surfaces, for higher coverages (>0.25 ML) only intact water is observed. Under UHV conditions these higher coverages can only be reached on the 4d metals, the 5d metals are, therefore, not passivated.

Synthesis, reactivity, and X-ray crystal structure of some mixed-ligand oxovanadium(V) complexes: first report of binuclear oxovanadium(V) complexes containing 4,4 '-Bipyridine type bridge

Reaction of the tridentate ONO Schiff-base ligand 2-hydroxybenzoylhydrazone of 2-hydroxybenzoylhydrazine (H2L) with VO(acac)(2) in ethanol medium produces the oxoethoxovanadium(V) complex [VO(OEt)L] (A), which reacts with pyridine to form [VO(OEt)L center dot(py)] (1). Complex 1 is structurally characterized. It has a distorted octahedral O4N2 coordination environment around the V(V) acceptor center. Both complexes A and 1 in ethanol medium react with neutral monodentate Lewis bases 2-picoline, 3-picoline, 4-picoline, 4-amino pyridine, imidazole, and 4-methyl imidazole, all of which are stronger bases than pyridine, to produce dioxovanadium(V) complexes of general formula BH[VO2L]. Most of these dioxo complexes are structurally characterized, and the complex anion [VO2L](-) is found to possess a distorted square pyramidal structure. When a solution/suspension of a BH[VO2L] complex in an alcohol (ROH) is treated with HCl in the same alcohol, it is converted into the corresponding monooxoalkoxo complex [ O(OR)L], where R comes from the alcohol used as the reaction medium. Both complexes A and 1 produce the 4,4'-bipyridine-bridged binuclear complex [VO(OEt)L](2)(mu-4,4'-bipy) (2), which, to the best of our knowledge, represents the first report of a structurally characterized 4,4'-bipyridine-bridged oxovanadium(V) binuclear complex. Two similar binuclear oxovanadium(V) complexes 3 and 4 are also synthesized and characterized. All these binuclear complexes (2-4), on treatment with base B, produce the corresponding mononuclear dioxovanadium(V) complexes (5-10).

Ligand-centred reactivity of bis(picolyl)amine iridium: sequential deprotonation, oxidation and oxygenation of a "non-innocent" ligand

Treatment of [Ir(bpa)(cod)](+) complex [1](+) with a strong base (e.g., tBuO(-)) led to unexpected double deprotonation to form the anionic [Ir-(bpa-2H)(cod)](-) species [3](-), via the mono-deprotonated neutral amido complex [Ir(bpa-H)(cod)] as an isolable intermediate. A certain degree of aromaticity of the obtained metal-chelate ring may explain the favourable double deprotonation. The rhodium analogue [4](-) was prepared in situ. The new species [M(bpa-2H)(cod)](-) (M = Rh, Ir) are best described as two-electron reduced analogues of the cationic imine complexes [M-I(cod)(Py-CH2-N=CH-Py)](+). One-electron oxidation of [3](-) and [4](-) produced the ligand radical complexes [3]* and [4]*. Oxygenation of [3](-) with O-2 gave the neutral carboxamido complex [Ir(cod)(py-CH2-N-CO-py)] via the ligand radical complex [3]* as a detectable intermediate.

Meal fatty acids and postprandial vascular reactivity

With increasing recognition of the pivotal role of vascular dysfunction in the progression of atherosclerosis, the vasculature has emerged as an important target for dietary therapies. Recent studies have indicated that chronic fatty acid manipulation alters vascular reactivity, when measured after an overnight fast. However, individuals spend a large proportion of the day in the postprandial (non-fasted) state. Several studies have shown that high fat meals can impair endothelial function within 3-4 h, a time period often associated with peak postprandial lipaemia. Although the impact of meal fatty acids on the magnitude and duration of the postprandial lipaemic response has been extensively studied, very little is known about their impact on vascular reactivity after a meal.

Fish oil fatty acids improve postprandial vascular reactivity in healthy men

Chronic fish oil intervention had been shown to have a positive impact on endothelial function. Although high-fat meals have often been associated with a loss of postprandial vascular reactivity, studies examining the effects of fish oil fatty acids on vascular function in the postprandial phase are limited. The aim of the present study was to examine the impact of the addition of fish oil fatty acids to a standard test meal on postprandial vascular reactivity. A total of 25 men received in a random order either a placebo oil meal (40 g of mixed fat; fatty acid profile representative of the U.K. diet) or a fish oil meal (31 g of mixed fat and 9 g of fish oil) on two occasions. Vascular reactivity was measured at baseline (0 h) and 4 h after the meal by laser Doppler iontophoresis, and blood samples were taken for the measurement of plasma lipids, total nitrite, glucose and insulin. eNOS (endothelial NO synthase) and NADPH oxidase gene expression were determined in endothelial cells after incubation with TRLs (triacylglycerol-rich lipoproteins) isolated from the plasma samples taken at 4 h. Compared with baseline, sodium nitroprusside (an endothelium-independent vasodilator)-induced reactivity (P = 0.024) and plasma nitrite levels (P = 0.001) were increased after the fish oil meal. In endothelial cells, postprandial TRLs isolated after the fish oil meal increased eNOS and decreased NADPH oxidase gene expression compared with TRLs isolated following the placebo oil meal (P <= 0.03). In conclusion, meal fatty acids appear to be an important determinant of vascular reactivity, with fish oils significantly improving postprandial endothelium-independent vasodilation.

Probability density function estimation using orthogonal forward regression

Using the classical Parzen window estimate as the target function, the kernel density estimation is formulated as a regression problem and the orthogonal forward regression technique is adopted to construct sparse kernel density estimates. The proposed algorithm incrementally minimises a leave-one-out test error score to select a sparse kernel model, and a local regularisation method is incorporated into the density construction process to further enforce sparsity. The kernel weights are finally updated using the multiplicative nonnegative quadratic programming algorithm, which has the ability to reduce the model size further. Except for the kernel width, the proposed algorithm has no other parameters that need tuning, and the user is not required to specify any additional criterion to terminate the density construction procedure. Two examples are used to demonstrate the ability of this regression-based approach to effectively construct a sparse kernel density estimate with comparable accuracy to that of the full-sample optimised Parzen window density estimate.

Fully complex-valued radial basis function networks for orthogonal least squares regression

We consider a fully complex-valued radial basis function (RBF) network for regression application. The locally regularised orthogonal least squares (LROLS) algorithm with the D-optimality experimental design, originally derived for constructing parsimonious real-valued RBF network models, is extended to the fully complex-valued RBF network. Like its real-valued counterpart, the proposed algorithm aims to achieve maximised model robustness and sparsity by combining two effective and complementary approaches. The LROLS algorithm alone is capable of producing a very parsimonious model with excellent generalisation performance while the D-optimality design criterion further enhances the model efficiency and robustness. By specifying an appropriate weighting for the D-optimality cost in the combined model selecting criterion, the entire model construction procedure becomes automatic. An example of identifying a complex-valued nonlinear channel is used to illustrate the regression application of the proposed fully complex-valued RBF network.

Sparse kernel density estimator using orthogonal regression based on D-optimality experimental design

A novel sparse kernel density estimator is derived based on a regression approach, which selects a very small subset of significant kernels by means of the D-optimality experimental design criterion using an orthogonal forward selection procedure. The weights of the resulting sparse kernel model are calculated using the multiplicative nonnegative quadratic programming algorithm. The proposed method is computationally attractive, in comparison with many existing kernel density estimation algorithms. Our numerical results also show that the proposed method compares favourably with other existing methods, in terms of both test accuracy and model sparsity, for constructing kernel density estimates.

Sparse multioutput radial basis function network construction using combined locally regularised orthogonal least square and D-optimality experimental design

A construction algorithm for multioutput radial basis function (RBF) network modelling is introduced by combining a locally regularised orthogonal least squares (LROLS) model selection with a D-optimality experimental design. The proposed algorithm aims to achieve maximised model robustness and sparsity via two effective and complementary approaches. The LROLS method alone is capable of producing a very parsimonious RBF network model with excellent generalisation performance. The D-optimality design criterion enhances the model efficiency and robustness. A further advantage of the combined approach is that the user only needs to specify a weighting for the D-optimality cost in the combined RBF model selecting criterion and the entire model construction procedure becomes automatic. The value of this weighting does not influence the model selection procedure critically and it can be chosen with ease from a wide range of values.

Sparse kernel regression modeling using combined locally regularized orthogonal least squares and D-optimality experimental design

The note proposes an efficient nonlinear identification algorithm by combining a locally regularized orthogonal least squares (LROLS) model selection with a D-optimality experimental design. The proposed algorithm aims to achieve maximized model robustness and sparsity via two effective and complementary approaches. The LROLS method alone is capable of producing a very parsimonious model with excellent generalization performance. The D-optimality design criterion further enhances the model efficiency and robustness. An added advantage is that the user only needs to specify a weighting for the D-optimality cost in the combined model selecting criterion and the entire model construction procedure becomes automatic. The value of this weighting does not influence the model selection procedure critically and it can be chosen with ease from a wide range of values.

Kernel density construction using orthogonal forward regression

An automatic algorithm is derived for constructing kernel density estimates based on a regression approach that directly optimizes generalization capability. Computational efficiency of the density construction is ensured using an orthogonal forward regression, and the algorithm incrementally minimizes the leave-one-out test score. Local regularization is incorporated into the density construction process to further enforce sparsity. Examples are included to demonstrate the ability of the proposed algorithm to effectively construct a very sparse kernel density estimate with comparable accuracy to that of the full sample Parzen window density estimate.