A longitudinal study of gene expression in healthy individuals

<p>Abstract</p> <p>Background</p> <p>The use of gene expression in venous blood either as a pharmacodynamic marker in clinical trials of drugs or as a diagnostic test requires knowledge of the variability in expression over time in healthy volunteers. Here we defined a normal range of gene expression over 6 months in the blood of four cohorts of healthy men and women who were stratified by age (22–55 years and > 55 years) and gender.</p> <p>Methods</p> <p>Eleven immunomodulatory genes likely to play important roles in inflammatory conditions such as rheumatoid arthritis and infection in addition to four genes typically used as reference genes were examined by quantitative reverse transcription-polymerase chain reaction (qRT-PCR), as well as the full genome as represented by Affymetrix HG U133 Plus 2.0 microarrays.</p> <p>Results</p> <p>Gene expression levels as assessed by qRT-PCR and microarray were relatively stable over time with ~2% of genes as measured by microarray showing intra-subject differences over time periods longer than one month. Fifteen genes varied by gender. The eleven genes examined by qRT-PCR remained within a limited dynamic range for all individuals. Specifically, for the seven most stably expressed genes (CXCL1, HMOX1, IL1RN, IL1B, IL6R, PTGS2, and TNF), 95% of all samples profiled fell within 1.5–2.5 Ct, the equivalent of a 4- to 6-fold dynamic range. Two subjects who experienced severe adverse events of cancer and anemia, had microarray gene expression profiles that were distinct from normal while subjects who experienced an infection had only slightly elevated levels of inflammatory markers.</p> <p>Conclusion</p> <p>This study defines the range and variability of gene expression in healthy men and women over a six-month period. These parameters can be used to estimate the number of subjects needed to observe significant differences from normal gene expression in clinical studies. A set of genes that varied by gender was also identified as were a set of genes with elevated expression in a subject with iron deficiency anemia and another subject being treated for lung cancer.</p

Societies, Cultures and Fisheries from a Modeling Perspective

Cultures can be viewed as sets of beliefs and techniques allowing societies to cope with their environment. We here propose simple and explicit schemes showing how fishermen could encode beliefs about a renewable resource, fish. We then discuss the dynamics of the society, represented by economic and cultural variables, coupled to the fishery represented by fish abundance. According to different coding schemes and sets of parameters, several dynamical regimes are observed, including one with endogenous crises.Fisheries, Learning, Institutions, Beliefs, Dynamics, Environment

Dynamics Of Economic Choices Involving Pollution

Economic choices involving pollution, like those concerning common resources, relate to the emergence of cooperation among actors. Since pollution propagates in space, the temporal dynamics of economic choices is coupled to the spatial dynamics of pollution. We start from a simple description of the internal representations of the agents proposed by Arthur and Lane (1993) to describe information contagion. The simulations done in this paper allow us to discuss the maximum price that the agents agree to pay for non-polluting devices as a function of pollution, propagation of information and memory characteristics of the agents. We also characterize the spatio-temporal dynamics of choices, market shares and pollution. 1. INTRODUCTION The purpose of the present study is to determine under which conditions economic agents would agree to pay the extra cost of devices that prevent polluting the environment, such as catalytic converters for cars. We depart from the conventional view of one pe..

Towards a computational model for-1 eukaryotic frameshifting sites

Motivation: Unconventional decoding events are now well acknowledged, but not yet well formalized. In this study, we present a bioinformatics analysis of eukaryotic &minus;1 frameshifting, in order to model this event.Results: A consensus model has already been established for -1 frameshifting sites. Our purpose here is to provide new constraints which make the model more precise. We show how a machine learning approach can be used to refine the current model. We identify new properties that may be involved in frameshifting. Each of the properties found was experimentally validated. Initially, we identify features of the overall model that are to be simultaneously satisfied. We then focus on the following two components: the spacer and the slippery sequence. As a main result, we point out that the identity of the primary structure of the so-called spacer is of great importance

Towards implementing virtual control groups in nonclinical safety studies: Workshop report and roadmap to implementation

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