Systems biology and translational research

The microcirculation: linking trauma and coagulopathy

Survival after severe traumatic shock can be complicated by a number of pathophysiologic processes that ensue after the initial trauma. One of these is trauma-induced coagulopathy (TIC) whose onset may occur before initial fluid resuscitation. The pathogenesis of TIC has not yet been fully elaborated, but evolving evidence appears to link severe tissue hypoxia and damage to the endothelium as key factors, which evolve into measurable structural and biochemical changes of the endothelium resulting in a coagulopathic state. This paper will provide a general review of these linkages and identify knowledge gaps as well as suggest new approaches and areas of investigation, which may both limit the development of TIC as well as produce insights into its pathophysiology. A better understanding of these issues will be necessary in order to advance the practice of remote damage control resuscitation.

Pathway analysis in microarray data: a comparison of two different pathway analysis devices in the same data set

Oligonucleotide microarray technology has been developed to a very powerful and favorable biotechnique. However, it is an explicit challenge to judge the potential biological meaning of such extensive amounts of data. There are various-commercially available or free-software applications for pathway analyses on microarray data on the market. The aim of the present study was to test whether pathway analyses on the same data set using different commercially available devices lead to roughly comparable or massively diverging results and, if so, to give potential explanations. Two different commercially available pathway analysis programs (GeneGo and Pathway Studio 6) have been elected. The programs have been compared concerning their different analyses tools, underlying databases, database constructions, and network-building algorithms. The same data set has been uploaded into two different programs. Pathway analysis was performed according to the following three criteria: the five top networks, the five top diseases, and the five top canonical networks that are associated with the uploaded gene list. The different programs differ in extracting their information from the literature, in database construction, and network-building algorithms. The "top networks," as suggested by the programs as to be "most important," substantially differ from each other and share only one same gene. Concerning the most represented diseases in the data set, there are certain overlaps but no uniform results in the different applications. Pathway analyses of microarray data using preformed software devices offer valuable options for investigating on the biological relevance and function of a focus gene set. However, there is no standard in constructing such programs. This leads to substantial differences when investigating on the same data set using different devices. The intention of this work is to sensitize for the potentialities and also pitfalls doing pathway analysis using automated software tools.

In Silico Modeling in Infectious Disease

Infectious disease has witnessed the emergence of mathematical modeling a tool of synthesizing data of growing complexity now available to clinicians and basic scientists alike. The purpose of this review is to introduce mathematical tools commonly used to model infectious disease. We will illustrate the use of equation-based, agent-based or statistical modeling approaches to a variety of examples pertaining to acute inflammation, bacterial dynamics, viral dynamics, and signaling pathways, focusing of host-pathogen interactions rather than population models. We will discuss the strengths and weaknesses of these approaches and offer future perspectives for this rapidly evolving field.

Trevor Trust – AstraZeneca R&D Boston, 35 Gatehouse Drive, Waltham, MA 02451, USA