The design of an agent for modelling supply chain network dynamics

A useful insight into managerial decision making can be found from simulation of business systems, but existing work on simulation of supply chain behaviour has largely considered non-competitive chains. Where competitive agents have been examined, they have generally had a simple structure and been used for fundamental examination of stability and equilibria rather than providing practical guidance to managers. In this paper, a new agent for the study of competitive supply chain network dynamics is proposed. The novel features of the agent include the ability to select between competing vendors, distribute orders preferentially among many customers, manage production and inventory, and determine price based on competitive behaviour. The structure of the agent is related to existing business models and sufficient details are provided to allow implementation. The agent is tested to demonstrate that it recreates the main results of the existing modelling and management literature on supply chain dynamics. A brief exploration of competitive dynamics is given to confirm that the proposed agent can respond to competition. The results demonstrate that overall profitability for a supply chain network is maximised when businesses operate collectively. It is possible for an individual business to achieve higher profits by adopting a more competitive stance, but the consequence of this is that the overall profitability of the network is reduced. The agent will be of use for a broad range of studies on the long-run effect of management decisions on their network of suppliers and customers.

Quantifying Cell Binding Kinetics Mediated By Surface-Bound Blood Type B Antigen To Immobilized Antibodies

Cell adhesion is crucial to many biological processes, such as inflammatory responses, tumor metastasis and thrombosis formation. Recently a commercial surface plasmon resonance (SPR)-based BIAcore biosensor has been extended to determine cell binding mediated by surface-bound biomolecular interactions. How such cell binding is quantitatively governed by kinetic rates and regulating factors, however, has been poorly understood. Here we developed a novel assay to determine the binding kinetics of surface-bound biomolecular interactions using a commercial BIAcore 3000 biosensor. Human red blood cells (RBCs) presenting blood group B antigen and CM5 chip bearing immobilized anti-B monoclonal antibody (mAb) were used to obtain the time courses of response unit, or sensorgrams, when flowing RBCs over the chip surface. A cellular kinetic model was proposed to correlate the sensorgrams with kinetic rates. Impacts of regulating factors, such as cell concentration, flow duration and rate, antibody-presenting level, as well as pH value and osmotic pressure of suspending medium were tested systematically, which imparted the confidence that the approach can be applied to kinetic measurements of cell adhesion mediated by surface-bound biomolecular interactions. These results provided a new insight into quantifying cell binding using a commercial SPR-based BIAcore biosensor.

Measuring Binding Kinetics Of Surface-Bound Molecules Using The Surface Plasmon Resonance Technique

Surface plasmon resonance (SPR) technology and the Biacore biosensor have been widely used to measure the kinetics of biomolecular interactions in the fluid phase. In the past decade, the assay was further extended to measure reaction kinetics when two counterpart molecules are anchored on apposed surfaces. However, the cell binding kinetics has not been well quantified. Here we report development of a cellular kinetic model, combined with experimental procedures for cell binding kinetic measurements, to predict kinetic rates per cell. Human red blood cells coated with bovine serum albumin and anti-BSA monoclonal antibodies (mAbs) immobilized on the chip were used to conduct the measurements. Sensor-grams for BSA-coated RBC binding onto and debinding from the anti-BSA mAb-immobilized chip were obtained using a commercial Biacore 3000 biosensor, and analyzed with the cellular kinetic model developed. Not only did the model fit the data well, but it also predicted cellular on and off-rates as well as binding affinities from curve fitting. The dependence of flow duration, flow rate, and site density of BSA on binding kinetics was tested systematically, which further validated the feasibility and reliability of the new approach. Crown copyright (c) 2008 Published by Elsevier Inc. All rights reserved.

Compatibility of Glyphosate with Galerucella calmariensis; a Biological Control Agent for Purple Loosestrife (Lythrum salicaria)

By integrating Galerucella calmariensis with glyphosate there is potential to achieve both immediate and sustained control of purple loosestrife (Lythrum salicaria). The objective of this study was to determine the compatibility of glyphosate on the oviposition and survival of adult G. Calmariensis and on the ability of G. calmariensis third instar larvae to pupate to teneral adults. Our results revealed glyphosate (formulated as Roundup) at a concentration of 2% (2.43L/acre) and 4% solution (4.86 L/acre) had no impact on the ability of G. calmariensis third instar larvae to pupate to new generation adults. To examine the effect of a 2% solution of glyphosate on adult G. calmariensis oviposition and survival, adults were randomly divided between a direct contact group (adults sprayed directly), an indirect contact group (host plants with adults were sprayed), and a control group. Our results revealed that glyphosate does not impact G. calmariensis oviposition or adult survival. The results of this study indicate that G. calmariensis is compatible with glyphosate indicating that further field studies examining integrated control strategies for purple loosestrife are warranted.

New Oncogenic Drivers in Hepatocellular Carcinoma: Role of the RNA Binding Protein Hu antigen R

156 p. : graf.

Role of G protein coupled inwardly rectifier K+ channels (GIRK) on the neurobiology depression

353 págs.