Quantitation of angiogenesis in vitro induced by VEGF-A and FGF-2 in two different human endothelial cultures : an all-in-one assay

Angiogenic therapy is considered to be a promising tool for treatment of ischemic diseases. Many in vivo and in vitro assays have been developed to identify potential proangiogenic drugs and to investigate their mode of action. However, until now no validated system exists that would allow quantitation of angiogenesis in vitro in only one assay. Here, a previously established all-in-one in vitro assay based on staging of the angiogenic cascade was validated by quantitation of the effects of the known proangiogenic factors VEGF-A and FGF-2. Both growth factors were applied separately or in combination to human endothelial cell cultures derived from the heart and the foreskin, and angiogenesis was quantitated over 30 days of culture. Additionally, gene expression of VEGFR-1, VEGFR-2 and FGFR-1 at 3, 10, 20 or 40 days of cultivation was quantitated by RT-qPCR. In both cultures, VEGF-A as well as FGF-2 induced a run through all defined stages of angiogenesis in vitro. Application of VEGF-A only led to formation of irregular globular endothelial structures, while FGF-2 resulted in development of regular capillary-like structures. Quantitation of the angiogenic effects of VEGF-A and transcripts of VEGFR-1 and VEGFR-2 showed that a high VEGFR-1/VEGFR-2 ratio evoked deceleration of angiogenesis

High Speed Solution of Spacecraft Trajectory Problems Using Taylor Series Integration

Taylor series integration is implemented in a spacecraft trajectory analysis code-the Spacecraft N-body Analysis Program (SNAP) - and compared with the code s existing eighth-order Runge-Kutta Fehlberg time integration scheme. Nine trajectory problems, including near Earth, lunar, Mars and Europa missions, are analyzed. Head-to-head comparison at five different error tolerances shows that, on average, Taylor series is faster than Runge-Kutta Fehlberg by a factor of 15.8. Results further show that Taylor series has superior convergence properties. Taylor series integration proves that it can provide rapid, highly accurate solutions to spacecraft trajectory problems

Temporal patterns in artificial reaction networks.

The Artificial Reaction Network (ARN) is a bio-inspired connectionist paradigm based on the emerging field of Cellular Intelligence. It has properties in common with both AI and Systems Biology techniques including Artificial Neural Networks, Petri Nets, and S-Systems. This paper discusses the temporal aspects of the ARN model using robotic gaits as an example and compares it with properties of Artificial Neural Networks. The comparison shows that the ARN based network has similar functionality

A critical review on modelling formalisms and simulation tools in computational biosystems

Integration of different kinds of biological processes is an ultimate goal for whole-cell modelling. We briefly review modelling formalisms that have been used in Systems Biology and identify the criteria that must be addressed by an integrating framework capable of modelling, analysing and simulating different biological networks. Aware that no formalism can fit all purposes we realize Petri nets as a suitable model for Metabolic Engineering and take a deeper perspective on the role of this formalism as an integrating framework for regulatory and metabolic networks.Research supported by PhD grant SFRH/BD/35215/2007 from the Fundacao para a Ciencia e a Tecnologia (FCT) and the MIT-Portugal program

Optimal design of feedback control by inhibition

The local stability of unbranched biosynthetic pathways is examined by mathematical analysis and computer simulation using a novel nonlinear formalism that appears to accurately describe biochemical systems. Four factors affecting the stability are examined: strength of feedback inhibition, equalization of the values among the corresponding kinetic parameters for the reactions of the pathway, pathway length, and alternative patterns of feedback interaction. The strength of inhibition and the pattern of feedback interactions are important determinants of steady-state behavior. The simple pattern of end-product inhibition in unbranched pathways may have evolved because it optimizes the steady-state behavior and is temporally most responsive to change. Stability in these simple systems is achieved by shortening pathway length either physically or, in the case of necessarily long pathways, kinetically by a wide divergence in the values of the corresponding kinetic parameters for the reactions of the pathway. These conclusions are discussed in the light of available experimental evidence.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/48053/1/239_2005_Article_BF01741242.pd

Petri net based model validation in systems biology

Abstract. This paper describes the thriving application of Petri net theory for model validation of different types of molecular biological systems. After a short introduction into systems biology we demonstrate how to develop and validate qualitative models of biological pathways in a systematic manner using the well-established Petri net analysis technique of place and transition invariants. We discuss special properties, which are characteristic ones for biological pathways, and give three representative case studies, which we model and analyse in more detail. The examples used in this paper cover signal transduction pathways as well as metabolic pathways.