A Biosilification Fusion Protein for a ‘Self‐immobilising’ Sarcosine Oxidase Amperometric Enzyme Biosensor

Monomeric sarcosine oxidase (mSOx) fusion with the silaffin peptide, R5, designed previously for easy protein production in low resource areas, was used in a biosilification process to form an enzyme layer electrode biosensor. mSOx is a low activity enzyme (10–20 U/mg) requiring high amounts of enzyme to obtain an amperometric biosensor signal, in the clinically useful range <1 mM sarcosine, especially since the K_m is >10 mM. An amperometric biosensor model was fitted to experimental data to investigate dynamic range. mSOx constructs were designed with 6H (6×histidine) and R5 (silaffin) peptide tags and compared with native mSOx. Glutaraldehyde (GA) cross‐linked proteins retained ～5 % activity for mSOx and mSOx‐6H and only 0.5 % for mSOx‐R5. In contrast R5 catalysed biosilification on (3‐mercaptopropyl) trimethoxysilane (MPTMS) and tetramethyl orthosilicate (TMOS) particles created a ‘self‐immobilisation’ matrix retaining 40 % and 76 % activity respectively. The TMOS matrix produced a thick layer (>500 μm) on a glassy carbon electrode with a mediated current due to sarcosine in the clinical range for sarcosinemia (0–1 mM). The mSOx‐R5 fusion protein was also used to catalyse biosilification in the presence of creatinase and creatininase, entrapping all three enzymes. A mediated GC enzyme linked current was obtained with dynamic range available for creatinine determination of 0.1–2 mM for an enzyme layer ～800 nm.     

Holographic sensors for the determination of ionic strength

Holographic sensors for monitoring ionic strength have been fabricated from charged sulphonate and quaternary ammonium monomers, incorporated into thin, polymeric hydrogel films which were transformed into volume holograms. The diffraction wavelength or reflected colour of the holograms was used to characterise their swelling or de-swelling behaviour as a function of ionic strength in various media. The effects of co-monomer structure, buffer composition, ion composition, pH and temperature were evaluated, whilst the reversibility and reproducibility of the sensor was also assessed. An acrylamide-based hologram containing equal molar amounts of negatively and positively charged monomers was shown to be able to quantify ionic strength independent of the identity of the ionic species present in the test solution. The sensor was fully reversible, free of hysteresis and exhibited little response to pH between 3 and 9 and temperature within the range 20-45 °C. The system was successfully used to quantify the ionic strength of milk solutions, which contain a complex mixture of ions and biological components.     

Benzotriazole is thermally more stable than 1,2,3-triazole

TGA, DTA and DSC analyses indicate that benzotriazole is significantly more stable thermally than 1,2,3-triazole.     

Anionic iron(II) alkoxides as initiators for the controlled ring‐opening polymerization of lactide

Hetero‐bimetallic Fe(II) alkoxide/aryloxides were evaluated as initiators for the ring‐opening polymerization of rac‐lactide. [(THF)NaFe(O^tBu)₃]₂ ( 1 ) and [(THF)₄Na₂Fe(2,6‐diisopropylphenolate)₄] ( 2 ) (THF = tetrahydrofuran) both polymerized lactide efficiently at room temperature, with complex 1 affording better control over the molecular weight parameters of the resultant polymer. At conversions below 70%, a linear increase in molecular weight with conversion was observed, indicative of a well‐controlled polymerization process. Complex 2 is the first example of a dianionic Fe(II) alkoxide and has been structurally characterized to reveal a distorted square planar FeO₄ array in which both Na counterions bridge two aryloxide ligands and are further complexed by two THF ligands. © 2003 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 41: 3798–3803, 2003     

The structure of students' emotions experienced during a mathematical achievement test

Several models have been developed in order to categorize the numerous expressions that people use in order to describe their emotional experiences. The focus of the present study is on one of these theoretical classifications proposed by Pekrun (1992) specifically concerning emotions which are directly related to learning and achievement in mathematics. In his model, emotions are classified according to their valence (positive vs. negative) and their level of activation. In testing the assumptions of this model, we investigated students' enjoyment, anxiety, anger and boredom experienced before, during, and after the completion of a math test. Correspondence analyses which were used to generate a graphical illustration of structural interrelationships between these emotions provide empirical support for the theoretical classification.     

Magnetic resonance imaging: a new window into industrial processing.

Although the most important use of nuclear magnetic resonance imaging (MRI) continues to be for diagnostic medicine, recognition is being gained for many nonmedical applications. Examples include the following areas: petrogeology, food, agriculture, polymers and polymer-composites, and pharmaceuticals. These areas all involve studies of species that have short spin-spin relaxation times, and consequently need far fast gradient switching. These technical details are discussed and typical applications given.     

Properties of nonparametric estimators of autocovariance for stationary random fields

Summary We introduce nonparametric estimators of the autocovariance of a stationary random field. One of our estimators has the property that it is itself an autocovatiance. This feature enables the estimator to be used as the basis of simulation studies such as those which are necessary when constructing bootstrap confidence intervals for unknown parameters. Unlike estimators proposed recently by other authors, our own do not require assumptions such as isotropy or monotonicity. Indeed, like nonparametric function estimators considered more widely in the context of curve estimation, our approach demands only smoothness and tail conditions on the underlying curve or surface (here, the autocovariance), and moment and mixing conditions on the random field. We show that by imposing the condition that the estimator be a covariance function we actually reduce the numerical value of integrated squared error.