Miscibility of Quillaja Saponins with other Co‐surfactants under Different pH Values

The miscibility behavior of mixed surfactant systems and the influence of extrinsic parameters are crucial for their application as emulsifiers. Therefore, the objective of this study was to evaluate the miscibility behavior of mixed systems composed of commercial Quillaja saponin and a co‐surfactant, namely sodium caseinate, pea protein, rapeseed lecithin, or egg lecithin. These mixtures were evaluated macro‐ and microscopically at different concentration ratios (maximum concentration 5% w/v) at pH 3, 5, and 7 at 25 °C. The individual ingredients were also assessed for their charge properties and surface hydrophobicity. The results showed that Quillaja saponin–caseinate mixtures were miscible only at pH 7, and showed aggregation and precipitation at lower pH due to increasing electrostatic attraction forces. Rheological measurements showed that Quillaja saponin‐pea protein mixtures formed gelled structures at all tested pH values mainly via association of hydrophobic patches. Quillaja saponins mixed with rapeseed lecithin were miscible at all tested pH values due to electrostatic repulsion. Quillaja saponin–egg lecithin mixtures aggregated independent of pH and concentration ratio. The microscopic analysis revealed that the lower the pH and the higher the Quillaja saponin ratio, the denser were the formed Quillaja saponin–egg lecithin aggregates. The results are summarized in ternary phase diagrams that provide a useful tool in selecting a surfactant system for food applications.     

Deep Blue's contribution to AI

Deep Blue's defeat of World Chess Champion Garry Kasparov in 1997 marked one of the great accomplishments in artificial intelligence during the previous century. It was the result of work by thousands of researchers beginning in the late 1950s and of the great support given to the project by IBM during the final decade of the century. The achievement suggests great progress can be expected in other related AI problems in this current century. This revised version was published online in June 2006 with corrections to the Cover Date.     

Network formation by aza‐Michael addition of primary amines to vinyl end groups of enzymatically synthesized poly(glycerol adipate)

A highly efficient approach for the synthesis of polyester‐based networks via aza‐Michael addition of primary amines to α,β‐unsaturated (vinyl) end groups of poly(glycerol adipate) (PGA) was achieved. By acylation of PGA with 6‐(Fmoc‐amino)hexanoic acid side chains via Steglich esterification, protected amine‐functionalized PGA was obtained. This was followed by the removal of fluorenylmethyloxycarbonyl (Fmoc) protecting groups and the synthesis of PGA‐based networks under catalyst‐free conditions. The successful conjugate addition of primary amines to vinyl end groups and network formation were confirmed using ¹³C magic angle spinning NMR and Fourier transform infrared spectroscopy. Network heterogeneity and defects were quantitatively investigated using ¹H double‐quantum NMR spectroscopy. Finally, a hydrogel was prepared with potential biomedical applications.     

New expression method and characterization of recombinant human granulocyte colony stimulating factor in a stable protein formulation

Human recombinant granulocyte colony stimulating factor (rhG-CSF) is widely used in hematology and oncology for the treatment of neutropenia, for the restoration of neutrophil production after bone marrow transplantation, for myelodysplastic syndromes, and aplastic anemia. The E. coli expression system is commonly used for fast recombinant production of rhG-CSF at a large scale. We have applied a novel autoinduction method for the batch expression of rhG-CSF to study whether this new system would increase cell mass and target-protein yield compared to conventional E. coli cell culture and induction with isopropyl β-D-thiogalactopyranoside (IPTG). We could demonstrate 3-fold higher culture densities and a 5-fold higher protein yield compared to IPTG induction without the need to monitor cell growth in a shortened 24 h expression procedure. rhG-CSF expressed in autoinduction media was successfully extracted from E. coli inclusion bodies and refolded by dialysis. After size exclusion chromatography (SEC) purification, rhG-CSF showed similar conformation, biological activity and aggregation profile compared to the commercially available biosimilar TEVAgrastim(?) (TEVA Pharma AG). Expression by autoinduction is suggested as a cost- and time-effective method for rhG-CSF production.     

Zur Kinetik der stabilisierten Fällungs-polymerisation eines Kationischen Monomeren in wäßrigen Natriumchlorid-Lösungen

The stabilized free-radical precipitation polymerization of the cationic monomer N-(2-methacryloyloxyethyl)-N,N-dimethylbenzylammonium chloride (MADAMBQ) in aqueous solutions of sodium chloride was studied by reaction calorimetry. Poly(ethylene oxide) was used as stabilizer. The rate of polymerization reaches its maximum immediately after initiation and remains nearly constant up to 50 % conversion followed by a decrease that could be described by a first order kinetics. The particles formed are approximately 1 to 30 μm in diameter and are stable over a period of several months. A model based on the theory of homogeneous particle nucleation is suggested to describe the kinetic course of polymerization, taking into account the rate of polymerization in both phases. With the assumption that the concentration of monomer in the phases is determined by a Nernst distribution law, the kinetics of the early stage of polymerization can be modelled reasonably well. The solution polymerization and the unstabilized precipitation polymerization of MADAMBQ was also studied.     

Predicting the morphological and hydraulic consequences of river rehabilitation

Decisions about reach‐scale river rehabilitation for the purposes of flood protection and ecological enhancement require prediction of the possible consequences of management alternatives. To provide such predictions, an integrative model is necessary that represents the cause–effect relations between rehabilitation options and morphological, hydraulic and ecological consequences. This paper describes the morphological and hydraulic submodel of such an integrative model. This submodel is further subdivided into four modules predicting: (1) channel morphology, (2) flooding (dike overtopping, floodplain flooding and bed moving floods), (3) velocity and depth distribution and (4) riverbed siltation. Model relationships come from results reported in the literature and new data analyses. By using quantities that are all either readily available or easily predictable for changed conditions, the model should be widely applicable, even for data‐limited situations. The overall model is implemented as a probability network to facilitate estimation of uncertainties in model results. An application of the model to a reach of the Thur River in Switzerland demonstrates its utility for predicting morphological and hydraulic consequences of a planned river widening. The full integrative model, including ecological endpoints, will be used together with quantitative assessments of stakeholder preferences to support rehabilitation decisions for a number of Swiss rivers. Copyright © 2007 John Wiley & Sons, Ltd.     

State estimate recovery via nonlinear transforms during periods of destabilisation initiated by measurement uncertainty

A parallel approach is being proposed for the construction of a nonlinear-based state estimator for closed-loop systems failing the Hurwitz criteria during finite time intervals. The instability originates from sensor errors, and it is assumed that a Kalman–Bucy/Luenberger estimator is being processed in closed loop. It is shown that a bounded nonlinear state estimator can be constructed via nonlinear state transforms over a finite time interval, and makes use of the control input and the measured output of the destabilised closed-loop system. The filter presented provides an interesting new approach for the correction of state estimation due to sensor bias. In cases where the closed-loop plant remains stable, this approach is useful for dealing with pure sensor bias without the need for high gain filtering. The original uncontrolled open-loop system is assumed stable as a preemptive criterion throughout this study.