Acyl exchange between oleoyl-CoA and phosphatidylcholine in microsomes of developing soya bean cotyledons and its role in fatty acid desaturation

Microsomes of developing soya bean cotyledons transfer oleate from oleoyl-CoA to phosphatidylcholine (PC) by two different mechanisms: one in which oleate transfer is accompanied by the release of free CoA and another which results in the exchange of oleate from oleoyl-CoA for unsaturated 18-carbon fatty acids of PC. The acyl exchange can be demonstrated only when bovine serum albumin is present in the incubation medium. ATP-dependent acyl-CoA synthetase is not involved in the exchange process, which apparently does not require any cofactors. In light of this exchange process, the oleate desaturase system was reinvestigated in order to determine what the actual substrate for this system is. Upon incubation of microsomes with high concentrations of [¹⁴C] oleoyl-CoA, bovine serum albumin and NADH, it could be conclusively demonstrated that most oleic acid is desaturated while part of the PC molecule. The amounts of [¹⁴C] linoleoyl-CoA formed could be explained entirely by the acyl exchange. The physiological significance of the acyl exchange system is discussed. A new method for separation of acyl-CoA from other lipids and free CoA using reversed phase column chromatography also is described.     

Filters of residuated lattices and triangle algebras

An important concept in the theory of residuated lattices and other algebraic structures used for formal fuzzy logic, is that of a filter. Filters can be used, amongst others, to define congruence relations. Specific kinds of filters include Boolean filters and prime filters.In this paper, we define several different filters of residuated lattices and triangle algebras and examine their mutual dependencies and connections. Triangle algebras characterize interval-valued residuated lattices.     

The pseudo-linear semantics of interval-valued fuzzy logics

Triangle algebras are equationally defined structures that are equivalent with certain residuated lattices on a set of intervals, which are called interval-valued residuated lattices (IVRLs). Triangle algebras have been used to construct triangle logic (TL), a formal fuzzy logic that is sound and complete w.r.t. the class of IVRLs.In this paper, we prove that the so-called pseudo-prelinear triangle algebras are subdirect products of pseudo-linear triangle algebras. This can be compared with MTL-algebras (prelinear residuated lattices) being subdirect products of linear residuated lattices.As a consequence, we are able to prove the pseudo-chain completeness of pseudo-linear triangle logic (PTL), an axiomatic extension of TL introduced in this paper. This kind of completeness is the analogue of the chain completeness of monoidal T-norm based logic (MTL).This result also provides a better insight in the structure of triangle algebras; it enables us, amongst others, to prove properties of pseudo-prelinear triangle algebras more easily. It is known that there is a one-to-one correspondence between triangle algebras and couples (L,α), in which L is a residuated lattice and α an element in that residuated lattice. We give a schematic overview of some properties of pseudo-prelinear triangle algebras (and a number of others that can be imposed on a triangle algebra), and the according necessary and sufficient conditions on L and α.     

Difference algebra and system identification

The framework of differential algebra, especially Ritt’s algorithm, has turned out to be a useful tool when analyzing the identifiability of certain nonlinear continuous-time model structures. This framework provides conceptually interesting means to analyze complex nonlinear model structures via the much simpler linear regression models. One difficulty when working with continuous-time signals is dealing with white noise in nonlinear systems. In this paper, difference algebraic techniques, which mimic the differential-algebraic techniques, are presented. Besides making it possible to analyze discrete-time model structures, this opens up the possibility of dealing with noise. Unfortunately, the corresponding discrete-time identifiability results are not as conclusive as in continuous time. In addition, an alternative elimination scheme to Ritt’s algorithm will be formalized and the resulting algorithm is analyzed when applied to a special form of the nfir model structure.     

Highly Porous Geopolymers Through Templating and Surface Interactions

The natural porosity of geopolymers and the simplicity of geopolymer synthesis make them a potential candidate for the formation of highly porous ceramics. Here, the synthesis of highly porous (≈70 vol% or more) metakaolin geopolymer is demonstrated using a novel emulsion preparation with one‐pot curing and hydrophobization of the interior pores with alkylalkoxysilanes. Using mercury intrusion porosimetry, tailoring of the characteristic percolation pore size is demonstrated over a range of ≈200 nm to 10 μm. Using powder X‐ray diffraction, reactivity was shown to be decreased versus typical geopolymers, but substantial geopolymerization still occurred and the samples formed cohesive monoliths. Optional calcination under inert conditions allowed for formation of a glassy ceramic with a notable SiC phase, as well as further increasing the porosity by removing the hydrophobic pore coatings.     

Identification of quasi-optimal regions in the design space using surrogate modeling

The use of Surrogate Based Optimization (SBO) is widely spread in engineering design to find optimal performance characteristics of expensive simulations (forward analysis: from input to optimal output). However, often the practitioner knows a priori the desired performance and is interested in finding the associated input parameters (reverse analysis: from desired output to input). A popular method to solve such reverse (inverse) problems is to minimize the error between the simulated performance and the desired goal. However, there might be multiple quasi-optimal solutions to the problem. In this paper, the authors propose a novel method to efficiently solve inverse problems and to sample Quasi-Optimal Regions (QORs) in the input (design) space more densely. The development of this technique, based on the probability of improvement criterion and kriging models, is driven by a real-life problem from bio-mechanics, i.e., determining the elasticity of the (rabbit) tympanic membrane, a membrane that converts acoustic sound wave into vibrations of the middle ear ossicular bones.     

Single-step formation of a biorecognition layer for assaying histidine-tagged proteins

The purpose of this work was to develop a simple procedure for the creation of a specific biorecognition layer for histidine-tagged (His-tagged) molecules. Such a layer was prepared by the spontaneous fusion of vesicles containing readily available plain (DOPC) and iminodiacetic acid (DOGS-NTA) phospholipids on a silica surface resulting in the formation of an NTA-containing supported lipid bilayer. The frequency surface acoustic waveguide device which supports Love waves was used to follow the real-time formation of the biorecognition layer. The mole percent of the DOGS-NTA phospholipids in the supported bilayer was optimized by following the kinetics of the fusion for the different NTA-containing lipids. Fluorescently labeled lipids were used with observations of the fluorescence recovery after photobleaching to confirm the presence of lipid bilayers. After saturating all NTA-molecules with Ni(2+), the binding of a His-tagged protein fragment within the concentration range of 0.04 and 0.4 mM to a 5 mol % DOGS-NTA/DOPC was detected; binding curves were used to calculate the apparent association constant k(on) = 2.56 x 10(4) M(-)(1) s(-)(1), dissociation constant k(off) = 1.3 x 10(-)(3) s(-)(1), and equilibrium constant k(eq) = 1.97 x 10(7) M(-)(1). The described method could find significant applications as a generic technique for preparing biorecognition layers for His-tagged proteins. In addition, the acoustic waveguide device, which provides high sensitivity together with flexibility in terms of the substrate material used, is shown to be an attractive alternative to direct optical biosensors.     

Broadband macromodelling of passive components using orthonormal vector fitting

Vector fitting is widely accepted as a robust macromodelling tool for efficient frequency domain identification of passive components. The orthonormal vector fitting technique is introduced, which improves the numerical stability of the method, by using orthonormal rational functions. This leads to better conditioned equations, reduces the numerical sensitivity to the choice of starting poles significantly, limits the number of required iterations, and reduces the overall computation time.     

Accurate macromodeling algorithm for time domain identification of transient port responses

Orthonormal vector fitting is a robust method for broadband macromodeling of frequency domain responses. The use of orthonormal rational basis functions makes the conditioning of the system equations less sensitive to the initial pole specification when compared with the classical Vector Fitting procedure. This paper presents a time domain generalization of the technique to compute broadband rational macromodels from transient input–output port responses. The efficacy of the approach is illustrated by two numerical examples. Copyright © 2011 John Wiley & Sons, Ltd.