Size control and growth process of alkylamine-stabilized platinum nanocrystals: a comparison between the phase transfer and reverse micelles methods

Alkylamine-stabilized platinum nanoparticles are synthesized either by the phase-transfer method or in reverse micelles. The phase-transfer method produces nanocrystals that are quite spherical whereas the synthesis in reverse micelles generates a large number of wormlike structures. An alkylamine is used as a stabilizing agent to prevent nanoparticle coalescence, and it is shown that there is an inverse relationship between the alkylamine chain length and the platinum nanoparticle diameter. By comparing alkylamine and alkylthiol analogues, it is found that the integrity of the different crystallites depends on the strength of the interaction between the stabilizing agent and the platinum nanocrystals. The results obtained and the comparison made between the two synthesis methods improve the understanding of the growth mechanisms of platinum nanocrystals in disperse media.     

Development of a new protein labeling strategy, oxidation labeling. part 1: Preliminary evaluation and synthesis of tautomycin containing a metal coordinating unit

In the current work we present our preliminary evaluation of a new protein labeling strategy, namely oxidation labeling. We found that a bis(2-picolyl) amine analogue coordinating Cu⁺ was able to oxidize histidine to oxo-histedine in a small peptide by generating reactive oxygen species upon exposure to hydrogen peroxide. The bis(2-picolyl) amine unit was then incorporated into the natural product tautomycin via an oxime linker. The compound, which showed good activity toward protein phosphatase 1γ (PP1γ), will be used in oxidation labeling studies with PP1γ.     

Positive shrinkage, improved pretest and absolute penalty estimators in partially linear models

Shrinkage estimators of a partially linear regression parameter vector are constructed by shrinking estimators in the direction of the estimate which is appropriate when the regression parameters are restricted to a linear subspace. We investigate the asymptotic properties of positive Stein-type and improved pretest semiparametric estimators under quadratic loss. Under an asymptotic distributional quadratic risk criterion, their relative dominance picture is explored analytically. It is shown that positive Stein-type semiparametric estimators perform better than the usual Stein-type and least square semiparametric estimators and that an improved pretest semiparametric estimator is superior to the usual pretest semiparametric estimator. We also consider an absolute penalty type estimator for partially linear models and give a Monte Carlo simulation comparisons of positive shrinkage, improved pretest and the absolute penalty type estimators. The comparison shows that the shrinkage method performs better than the absolute penalty type estimation method when the dimension of the parameter space is much larger than that of the linear subspace.     

A unifying coordinate family for the Kerr–Newman metric

A new unified metric form is presented for the Kerr–Newman geometry. The new form is a generalization of the Boyer–Lindquist metric involving an arbitrary gauge function of the spheroidal radial variable. Each choice of the gauge function corresponds to a coordinate system including four of the most important coordinate systems for Kerr–Newman (Boyer–Lindquist, Kerr, Kerr–Schild and Doran coordinates). The representation is given in terms of a single Minkowski frame together with the gauge function. This Minkowski frame arises by boosting a static orthonormal frame which is adapted to spheroidal coordinates. Properties of the boost reflect the rotating nature of the Kerr–Newman solution including an identification of the angular velocities of the disk and the horizon matching previously known values obtained in other ways.     

Solid-State P and H NMR Investigations of Amorphous and Crystalline Calcium Phosphates Grown Biomimetically From a Mesoporous Bioactive Glass

By exploiting (1)H and (31)P magic-angle spinning nuclear magnetic resonance (NMR) spectroscopy, we explore the proton and orthophosphate environments in biomimetic amorphous calcium phosphate (ACP) and hydroxy-apatite (HA), as grown in vitro at the surface of a 10CaO-85SiO(2)-5P(2)O(5) mesoporous bioactive glass (MBG) in either a simulated body fluid or buffered water. Transmission electron microscopy confirmed the presence of a calcium phosphate layer comprising nanocrystalline HA. Two-dimensional (1)H-(31)P heteronuclear correlation NMR established predominantly (1)H(2)O?(31)PO(4) (3-) and O(1)H?(31)PO(4) (3-) contacts in the amorphous and crystalline component, respectively, of the MBG surface-layer; these two pairs exhibit distinctly different (1)H→(31)P cross-polarization dynamics, revealing a twice as large squared effective (1)H-(31)P dipolar coupling constant in ACP compared with HA. These respective observations are mirrored in synthetic (well-crystalline) HA, and the amorphous calcium orthophosphate (CaP) clusters that are present in the pristine MBG pore walls: besides highlighting very similar local (1)H and (31)P environments in synthetic and biomimetic HA, our findings evidence closely related NMR characteristics, and thereby similar local structures, of the CaP clusters in the pristine MBG relative to biomimetic ACP.     

Identifying promising compounds in drug discovery: genetic algorithms and some new statistical techniques

Throughout the drug discovery process, discovery teams are compelled to use statistics for making decisions using data from a variety of inputs. For instance, teams are asked to prioritize compounds for subsequent stages of the drug discovery process, given results from multiple screens. To assist in the prioritization process, we propose a desirability function to account for a priori scientific knowledge; compounds can then be prioritized based on their desirability scores. In addition to identifying existing desirable compounds, teams often use prior knowledge to suggest new, potentially promising compounds to be created in the laboratory. Because the chemistry space to search can be dauntingly large, we propose the sequential elimination of level combinations (SELC) method for identifying new optimal compounds. We illustrate this method on a combinatorial chemistry example.     

Incorporation of platinum nanoparticles in ordered mesoporous carbon

Platinum nanoparticles were incorporated within the pore system of ordered mesoporous carbon (OMC) by impregnating the carbon with a water-in-oil (w/o) microemulsion containing dissolved platinum salt followed by reduction of the platinum ions in situ inside the carbon pore system. The procedure provides preparation of metallic nanoparticles from hydrophilic precursors inside the hydrophobic carbon support structure with simultaneous control of the maximum metal particle size. Electron tomography was used to verify the presence of platinum nanoparticles inside the carbon material.     

On the relationship between fluorescence and molecular geometry solvent-assisted formation of luminescent intramolecular exciplexes from anthronyl-substituted anthracenes

The fluorescence efficiency of 1′,2′-dihydro-spiro[anthracene-9(10H),3′-[3H]benz[de]anthracen]-10-one in 10 solvents of varying dielectric constant has been investigated. The observed exciplex luminescence is attributed to a solvent-assisted intramolecular charge-transfer interaction between the ground-state anthrone and excited-state anthracene moietis. The geometry of the exciplex is suggested to resemble that of a σ-π complex.     

Optimal Solutions in the Multi-location Inventory System with Transshipments

We consider a single-period multi-location inventory system where inventory choices at each location are centrally coordinated. Transshipments are allowed as recourse actions in order to reduce the cost of shortage or surplus inventory after demands are realized. This problem has not been solved to optimality before for more than two locations with general cost parameters. In this paper we present a simple and intuitive model that enables us to characterize optimal inventory and transshipment policies for three and four locations as well. The insight gained from these analytical results leads us to examine the optimality conditions of a greedy transshipment policy. We show that this policy will be optimal for two and three locations. For the n location model we characterize the necessary and sufficient conditions on the cost structure for which the greedy transshipment policy will be optimal.      

Covariate Selection in High-Dimensional Generalized Linear Models With Measurement Error

In many problems involving generalized linear models, the covariates are subject to measurement error. When the number of covariates p exceeds the sample size n, regularized methods like the lasso or Dantzig selector are required. Several recent papers have studied methods which correct for measurement error in the lasso or Dantzig selector for linear models in the p > n setting. We study a correction for generalized linear models, based on Rosenbaum and Tsybakov’s matrix uncertainty selector. By not requiring an estimate of the measurement error covariance matrix, this generalized matrix uncertainty selector has a great practical advantage in problems involving high-dimensional data. We further derive an alternative method based on the lasso, and develop efficient algorithms for both methods. In our simulation studies of logistic and Poisson regression with measurement error, the proposed methods outperform the standard lasso and Dantzig selector with respect to covariate selection, by reducing the number of false positives considerably. We also consider classification of patients on the basis of gene expression data with noisy measurements. Supplementary materials for this article are available online.