Taking enzyme kinetics out of control; putting control into regulation

The matrix formulation of metabolic control analysis, which states that multiplying the elasticity matrix for any system by the corresponding control matrix yields an identity matrix, can be transformed into a statement that multiplying a matrix expressing internal regulatory properties by a matrix expressing external regulatory properties also yields an identity matrix. This transformation supplies the formal basis for metabolic regulation analysis, and provides the key to determining the control structure of a system without the need to know the exact changes in enzyme activities that are made to measure control coefficients.     

Functional Characterisation of Three Glycine N-Acyltransferase Variants and the Effect on Glycine Conjugation to Benzoyl–CoA

The glycine conjugation pathway in humans is involved in the metabolism of natural substrates and the detoxification of xenobiotics. The interactions between the various substrates in this pathway and their competition for the pathway enzymes are currently unknown. The pathway consists of a mitochondrial xenobiotic/medium-chain fatty acid: coenzyme A (CoA) ligase (ACSM2B) and glycine N-acyltransferase (GLYAT). The catalytic mechanism and substrate specificity of both of these enzymes have not been thoroughly characterised. In this study, the level of evolutionary conservation of GLYAT missense variants and haplotypes were analysed. From these data, haplotype variants were selected (156Asn > Ser, [17Ser > Thr,156Asn > Ser] and [156Asn > Ser,199Arg > Cys]) in order to characterise the kinetic mechanism of the enzyme over a wide range of substrate concentrations. The 156Asn > Ser haplotype has the highest frequency and the highest relative enzyme activity in all populations studied, and hence was used as the reference in this study. Cooperative substrate binding was observed, and the kinetic data were fitted to a two-substrate Hill equation. The coding region of the GLYAT gene was found to be highly conserved and the rare 156Asn > Ser,199Arg > Cys variant negatively affected the relative enzyme activity. Even though the 156Asn > Ser,199Arg > Cys variant had a higher affinity for benzoyl-CoA (s_0.5,benz = 61.2 µM), k_cat was reduced to 9.8% of the most abundant haplotype 156Asn > Ser (s_0.5,benz = 96.6 µM), while the activity of 17Ser > Thr,156Asn > Ser (s_0.5,benz = 118 µM) was 73% of 156Asn > Ser. The in vitro kinetic analyses of the effect of the 156Asn > Ser,199Arg > Cys variant on human GLYAT enzyme activity indicated that individuals with this haplotype might have a decreased ability to metabolise benzoate when compared to individuals with the 156Asn > Ser variant. Furthermore, the accumulation of acyl-CoA intermediates can inhibit ACSM2B leading to a reduction in mitochondrial energy production.     

In-line catalytic derivatization method for selective detection of chlorinated aromatics with a hyphenated gas chromatography/laser mass spectrometry technique: a concept for comprehensive detection of isomeric ensembles

The combination of gas chromatography (GC) and laser-based resonance-enhanced multiphoton ionization-time-of-flight mass spectrometry (REMPI-TOFMS) represents a three-dimensional analytical method, using the gas chromatographic retention time, the wavelength of the ionization laser for REMPI, and the molecular mass as analytical parameters. In this work, a novel analytical scheme for detection of chlorinated aromatic compounds, including isomeric ensembles, by GC/REMPI-TOFMS is presented. The concept uses an in-line hydrodechlorination catalyst for post- or precolumn derivatization of chlorinated aromatic compounds. The chlorinated aromatics are quantitatively reduced, forming their respective aromatic skeletons. These aromatic skeletons are detected selectively by REMPI-TOFMS. The first results for substance class selective detection of chlorinated benzene isomers are given, and potential applications in the field of the analysis of compounds such as polychlorinated dibenzo-p-dioxins and -furans are discussed.     

Age and individual differences in the learning of a memorization procedure.

Age differences in memory performance have been ascribed to corresponding differences in the effectiveness of mental memorization procedures. The present authors challenge the sufficiency of this explanation by raising the issue of how to account for age differences in memorization procedures themselves. Two hypotheses are evaluated with reference to the results of previous studies of procedural maintenance and transfer following instruction. Although these results provide more support for a capability than for an opportunity hypothesis, they pertain mainly to rehearsal procedures in the preadolescent age range. Corroborative evidence is reported from a new study of maintenance of an elaborative procedure following instruction given to 216 11- and 17-yr-olds. Whereas maintenance was equivalent across age on a task of low processing demand, it was more complete among older Ss on a more demanding task. Obstacles to adducing conclusive evidence on the issue are underlined. (29 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Bayesian invariant measurements of generalization

The problem of evaluating different learning rules and other statistical estimators is analysed. A new general theory of statistical inference is developed by combining Bayesian decision theory with information geometry. It is coherent and invariant. For each sample a unique ideal estimate exists and is given by an average over the posterior. An optimal estimate within a model is given by a projection of the ideal estimate. The ideal estimate is a sufficient statistic of the posterior, so practical learning rules are functions of the ideal estimator. If the sole purpose of learning is to extract information from the data, the learning rule must also approximate the ideal estimator. This framework is applicable to both Bayesian and non-Bayesian methods, with arbitrary statistical models, and to supervised, unsupervised and reinforcement learning schemes.     

Investigations on imperfection sensitivity and deduction of improved knock-down factors for unstiffened CFRP cylindrical shells

In the field of aerospace engineering but also in the fields of civil and mechanical engineering the industry demands for significantly reduced costs for development and operating. Reduction of structural weight at safe design is one avenue to achieve this objective. In many cases it results in thin-walled structures, which are prone to buckling if subjected to compression or shear. The presented paper is based on a recent European Space Agency (ESA) study, conducted at DLR Braunschweig, on Probabilistic Aspects of Buckling Knock-Down Factors and contributes to this goal by striving for an improved buckling knock-down factor (the ratio of buckling loads of imperfect and perfect structures) for unstiffened CFRP cylindrical shells. Buckling tests and buckling simulations were performed to investigate the imperfection sensitivity and to validate the applied simulation methodologies. Test results as well as deterministic and probabilistic buckling simulation results are presented and compared. Finally, improved knock-down factors are deduced and discussed.