Scanning and transmission electron microscopy studies on a model series of spherulitic segmented polyurethanes

Scanning (SEM) and transmission (TEM) electron microscopy studies were made on a model series of four segmented polyurethanes. The morphologies of both the homopolymers and of their mixtures were made by SEM while TEM was utilized to study only ultrathin films of the homopolymers. It was found that well-structured spherulitic morphologies could be induced in these systems and their mixtures, and that control over the textures could be maintained by solution casting conditions. The domains were observable via TEM, and the general orientation of this structure within the spherulites was noted. Deformation studies of the spherulitic textures were followed by both SEM and small-angle light scattering. It was concluded that, in general, the spherulites deform in a nonaffine manner–this is particularly true for the systems possessing a porous texture.     

High-spin structure of yrast-band in 78Kr

Lifetime of levels up to 22⁺, have been measured in ⁷⁸Kr and an oblate shape is assigned to the ground state using the CSM and the configuration dependent shell correction calculations. Calculations further show that ⁷⁸Kr is highly γ-soft nucleus. The experimental Q _t values coupled with theoretical calculations indicate an oblate shape for ⁷⁸Kr at low spins and triaxial shape at higher spins     

Tetrahydrofuran-based amino acids as library scaffolds

A furanose sugar amino acid (SAA) has been utilized as a library scaffold for the first time. Two furanose SAA scaffolds were examined to illustrate their potential for derivatization. The resulting 99-member library contained three orthogonal points of diversification that allowed easy access to ethers and carbamates from a hydroxyl moiety, a range of ureas from an azide (via an amine), and a range of amides from a methyl ester. The novel amide formation (by displacement of the methoxide from the methyl ester moiety) was achieved in good yield and purity with high structural confidence. Full characterization of several library intermediates (including a crystal structure) was obtained. The library was submitted for antibacterial screening.     

Use of 13C NMR spectrometric data to produce a predictive model of estrogen receptor binding activity

We have developed a spectroscopic data-activity relationship (SDAR) model based on 13C NMR spectral data for 30 estrogenic chemicals whose relative binding affinities (RBA) are available for the alpha (ERalpha) and beta (ERbeta) estrogen receptors. The SDAR models segregated the 30 compounds into strong and medium binding affinities. The SDAR model gave a leave-one-out (LOO) cross-validation of 90%. Two compounds that were classified incorrectly in the SDAR model were in the transition zone between classifications. Real and predicted 13C NMR chemical shifts were used with test compounds to evaluate the predictive behavior of the SDAR model. The 13C NMR SDAR model using predicted 13C NMR data for the test compounds provides a rapid, reliable, and simple way to screen whether a compound binds to the estrogen receptors.     

Routine analysis by high precision gas chromatography/mass selective detector/isotope ratio mass spectrometry to 0.1 parts per mil

Stable isotope methods are potentially quite useful for validating natural or enhanced mineral degradation of contaminants. For this reason, a continuous flow gas chromatograph (GC), isotope ratio mass spectrometer (IRMS) has been coupled with a quadrupole mass selective detector (MSD) to allow simultaneous mass spectral and stable carbon isotope ratio data to be obtained from a single chromatographic analysis. This allows the target contaminant and any extra-cellular degradation intermediates to be both qualified and quantified. Previously acceptable limits of precision (0.3 parts per mil) are undesirable given the small fractionation observed during aerobic degradation. To further understand the fate of organic contaminants and to gain information about the metabolic degradative pathway employed by a microorganism, routine isotopic analyses on a range of analytes have been performed. Quantities of sample producing mass-44 ion beam signal (I(44)) of 2 x 10(-10) to 1 x 10(-8) A were analysed. When the IRMS was tuned for high sensitivity, ion source nonlinearities were overcome by peak height correction from an algorithm that was produced using known isotopic standards of varying concentrations. This led to sample accuracy of <0.01 per thousand and sample precision of 0.1 per thousand. Copyright 1999 John Wiley & Sons, Ltd.     

Producing 13C NMR, infrared absorption, and electron ionization mass spectrometric data models of the monodechlorination of chlorobenzenes, chlorophenols, and chloroanilines

We have developed four spectroscopic data-activity relationship (SDAR) models of monodechlorination of 32 chlorinated benzene compounds in anaerobic estuarine sediment. The SDAR models were based on combinations of 13C nuclear magnetic resonance (NMR), infrared absorption (IR), and electron ionization mass spectrometric (EI MS) data. The SDAR models segregated the 32 compounds into 17 readily monodechlorinated compounds and 15 not readily monodechlorinated compounds. The SDAR model based on 13C NMR, IR, and EI MS data gave a leave-one-out cross-validation of 93.8%. The SDAR model based on a composite of 13C NMR and IR data gave a leave-one-out cross-validation of 90.6%. The SDAR model based on a composite of IR and EI MS data gave a leave-one-out cross-validation of 84.4%. The SDAR model based on a composite of 13C NMR and EI MS data gave a leave-one-out cross-validation of 84.4%. These reliable SDAR models provide a rapid and simple way to predict whether a chlorinated benzene compound will readily go through monodechlorination. The FDA has filed a patent application on methods of using any combination of spectral data (NMR, MS, UV-vis, IR, and fluorescence, phosphorescence) to model a chemical, physical, or biological endpoint.