Simplified analysis of organic compounds in headspace and aqueous samples by high-capacity sample enrichment probe

A sample enrichment probe (SEP) consisting of a thin rod of an inert material and provided at one end with a short sleeve of polydimethylsilicone rubber was used for the high-capacity sample enrichment of analytes from gaseous and aqueous samples for analysis by gas chromatography (GC) and its hyphenated techniques. The silicone rubber was exposed to the analytical sample, after which the end of the rod carrying the silicone rubber was introduced into the injector and the analytes thermally desorbed and analysed by GC. This technique is similar to, but differs from, solid-phase microextraction (SPME) in that a much larger volume of the sorptive phase is employed, the sorptive phase is not introduced into the inlet of the GC via a needle and the injector is opened to the atmosphere for the introduction and removal of the SEP. In the determination of volatile and semi-volatile organic compounds in gaseous and aqueous media, the SEP technique gave results comparable with those obtained by the stir-bar-sorptive extraction (SBSE) and high-capacity sorption probe (HCSP) techniques. Implementation of the SEP technique requires only minor adaptations to the gas chromatograph and does not require any auxiliary thermal desorption and cryotrapping equipment.     

Automatic integration of the reaction path using diagonally implicit Runge-Kutta methods

The diagonally implicit Runge-Kutta framework is shown to be a general form for constructing stable, efficient steepest descent reaction path integrators, of any order. With this framework tolerance driven, adaptive step-size methods can be constructed by embedding methods to obtain error estimates of each step without additional computational cost. There are many embedded and nonembedded, diagonally implicit Runge-Kutta methods available from the numerical analysis literature and these are reviewed for orders two, three, and four. New embedded methods are also developed which are tailored to the application of reaction path following. All integrators are summarized and compared for three systems: the Muller-Brown [Theor. Chem. Acta 53, 75 (1979)] potential and two gas phase chemical reactions. The results show that many of the methods are capable of integrating efficiently while reliably keeping the error bound within the desired tolerance. This allows the reaction path to be determined through automatic integration by only specifying the desired accuracy and transition state.     

A combined explicit-implicit method for high accuracy reaction path integration

We present the use of an optimal combined explicit-implicit method for following the reaction path to high accuracy. This is in contrast to most purely implicit reaction path integration algorithms, which are only efficient on stiff ordinary differential equations. The defining equation for the reaction path is considered to be stiff, however, we show here that the reaction path is not uniformly stiff and instead is only stiff near stationary points. The optimal algorithm developed in this work is a combination of explicit and implicit methods with a simple criterion to switch between the two. Using three different chemical reactions, we combine and compare three different integration methods: the implicit trapezoidal method, an explicit stabilized third order algorithm implemented in the code DUMKA3 and the traditional explicit fourth order Runge-Kutta method written in the code RKSUITE. The results for high accuracy show that when the implicit trapezoidal method is combined with either explicit method the number of energy and gradient calculations can potentially be reduced by almost a half compared with integrating either method alone. Finally, to explain the improvements of the combined method we expand on the concepts of stability and stiffness and relate them to the efficiency of integration methods.     

Effect of sialic acid content on glycoprotein pI analyzed by two‐dimensional electrophoresis

2‐DE is broadly used for quantitative analysis of differential protein expression in complex mixtures such as serum samples or cell lysates. PTMs directly influence the 2‐DE pattern, and knowledge of the rules of protein separation is required in order to understand the protein distribution in a 2‐DE gel. Glycosylation is the most common PTM and can modify both the molecular weight and the pI of a protein. In particular, the effect of charged monosaccharides (mainly sialic acids, SAs) on the 2‐DE pattern of a protein is of major interest since changes in sialylation are regularly observed in comparative studies. Little is known about the pI shift of a glycoprotein induced by the presence of SAs, or whether this shift is the same for all glycoproteins. To address this issue, this study examined the influence of SA on the 2‐DE pattern of three serum glycoproteins (haptoglobin, α1‐antitrypsin and ribonuclease 1), which N‐glycan chains had been previously characterised, and reviewed existing bibliographic data. The SA content of the different glycoforms of a glycoprotein showed a negative linear correlation with the pI, although the slope varied among the studied glycoproteins. We also described a positive correlation between the protein pI and the pI decrease per SA molecule.     

Raman Spectra of Poly(p‐phenylenevinylene)s with Fluorinated Vinylene Units: Evidence of Inter‐ring Distortion

Ring the changes : Experimental Raman spectra of fluorinated and non‐fluorinated polyphenylenevinylenes are assigned according to quantum chemical calculations for oligomer model systems (see picture). Characteristic differences in the spectra can be traced back to strong inter‐ring distortion of the fluorinated compounds.