Inflammatory Gene Regulatory Networks in Amnion Cells Following Cytokine Stimulation: Translational Systems Approach to Modeling Human Parturition

A majority of the studies examining the molecular regulation of human labor have been conducted using single gene approaches. While the technology to produce multi-dimensional datasets is readily available, the means for facile analysis of such data are limited. The objective of this study was to develop a systems approach to infer regulatory mechanisms governing global gene expression in cytokine-challenged cells in vitro, and to apply these methods to predict gene regulatory networks (GRNs) in intrauterine tissues during term parturition. To this end, microarray analysis was applied to human amnion mesenchymal cells (AMCs) stimulated with interleukin-1β, and differentially expressed transcripts were subjected to hierarchical clustering, temporal expression profiling, and motif enrichment analysis, from which a GRN was constructed. These methods were then applied to fetal membrane specimens collected in the absence or presence of spontaneous term labor. Analysis of cytokine-responsive genes in AMCs revealed a sterile immune response signature, with promoters enriched in response elements for several inflammation-associated transcription factors. In comparison to the fetal membrane dataset, there were 34 genes commonly upregulated, many of which were part of an acute inflammation gene expression signature. Binding motifs for nuclear factor-κB were prominent in the gene interaction and regulatory networks for both datasets; however, we found little evidence to support the utilization of pathogen-associated molecular pattern (PAMP) signaling. The tissue specimens were also enriched for transcripts governed by hypoxia-inducible factor. The approach presented here provides an uncomplicated means to infer global relationships among gene clusters involved in cellular responses to labor-associated signals

Four types of scrapie in goats differentiated from each other and bovine spongiform encephalopathy by biochemical methods

Scrapie in goats has been known since 1942, the archetype of prion diseases in which only prion protein (PrP) in misfolded state (PrPSc) acts as infectious agent with fatal consequence. Emergence of bovine spongiform encephalopathy (BSE) with its zoonotic behaviour and detection in goats enhanced fears that its source was located in small ruminants. However, in goats knowledge on prion strain typing is limited. A European-wide study is presented concerning the biochemical phenotypes of the protease resistant fraction of PrPSc (PrPres) in over thirty brain isolates from transmissible spongiform encephalopathy (TSE) affected goats collected in seven countries. Three different scrapie forms were found: classical scrapie (CS), Nor98/atypical scrapie and one case of CH1641 scrapie. In addition, CS was found in two variants—CS-1 and CS-2 (mainly Italy)—which differed in proteolytic resistance of the PrPres N-terminus. Suitable PrPres markers for discriminating CH1641 from BSE (C-type) appeared to be glycoprofile pattern, presence of two triplets instead of one, and structural (in)stability of its core amino acid region. None of the samples exhibited BSE like features. BSE and these four scrapie types, of which CS-2 is new, can be recognized in goats with combinations of a set of nine biochemical parameters

Participatory Modeling and Community Dialog About Vulnerability of Lobster Fishing to Climate Change

The US National Research Council has repeatedly called for an analytic-deliberative process to make environmental decisions. Such a process should bring together experts, local citizens, stakeholders, and decision makers in venues where they investigate, discuss and learn together, make decisions, and follow up with monitoring, evaluation, and adjustment. In this spirit, we have developed a community-based participatory modeling experience that gathers and organizes local and expert knowledge and then uses the model to inform public policy dialog. This chapter tells the story of how, over 24 months, we engaged a group of lobstermen and community members in South Thomaston, Maine. The group characterized how climate change is impacting the lobster fishery and the community. It also identified resilience actions they could take to better understand the complex connections between fishing effort, timing of lobster molting, and the price of lobster. We used system dynamics modeling to estimate these connections using available data from participants, scientific reports and publications, and data gathered by regulatory authorities. The model lets participants run scenarios that characterize how different resilience action strategies affect landings and fishermen’s income. We met with individual lobstermen to fine-tune the model and to explore its applications and then presented the model and its simulations back to the community. We also prepared a booklet that summarized NOAA data about ocean temperatures and distributed it in the community. These products helped promote community deliberation about how to enhance resilience to climate change