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There are contradictory requirements on the A-pillar of a modern passenger vehicle. The A-pillar needs to be strong to help withstand the forces, as in a rollover situation, and maintain the occupant cell integrity in rollover and high-speed offset frontal crashes. The A-pillar needs to be slim to ensure good visibility for the driver and should be light to contribute to lower fuel consumption. An ideal A-pillar, which is folded during normal operation but is expanded by high-pressure gas in a crash, resulting in a signficant increase in cross-section and strength, should combine these contradictory requirements. Such an A-pillar was developed in this project. The A-pillar was initially folded and sealed. The goal was to develop an A-pillar that was lighter, had a smaller obscuration angle and had the same level of safety for the occupant as a state-of-the-art A-pillar. Expansion and pressurisation of the folded sealed A-pillar was accomplished by generating a high internal pressure using pyrotechnics, which is a cost- and weight-efficient way to generate high pressures. The development was carried out by combining full-vehicle crash simulations with mechanical tests. The load cases used in the development of the expandable A-pillar were an offset deformable barrier crash at 64 km/h and a roof crush test according to FMVSS 216. The expandable A-pillar concept was subsequently built and mechanically tested. The A-pillar model was validated by means of mechanical testing. Generally, there was a clear correlation between the predicted A-pillar shape and the shape of the expanded mechanical A-pillar. The developed expandable A-pillar combined the goals of high strength, smaller cross-section and lower mass. The developed A-pillar reduced the obscuration angle by 25% and the mass by 8% (excluding brackets and gas generator) relative to a state-of-the-art A-pillar, while maintaining the level of safety for the occupant.

The quest to determine cause from effect is often referred to as reverse engineering in the context of cellular networks. Here we propose and evaluate an algorithm for reverse engineering a gene regulatory network from time-series kind steady-state data. Our algorithmic pipeline, which is rather standard in its parts but not in its integrative composition, combines ordinary differential equations, parameter estimations by least angle regression, and cross-validation procedures for determining the in-degrees and selection of nonlinear transfer functions. The result of the algorithm is a complete directed net-work, in which each edge has been assigned a score front it bootstrap procedure. To evaluate the performance, we submitted the outcome of the algorithm to the reverse engineering assessment competition DREAM2, where we used the data corresponding to the InSillico1 and InSilico2 networks as input. Our algorithm outperformed all other algorithms when inferring one of the directed gene-to-gene networks. This is the authors’ version of the following article:Mika Gustafsson, Michael Hörnquist, Jesper Lundstrom, Johan Bjorkegren and Jesper Tegnér, Reverse Engineering of Gene Networks with LASSO and Nonlinear Basis Functions, 2009, Annals of the New York Academy of Sciences, Volume 1158 Issue, The Challenges of Systems Biology Community Efforts to Harness Biological Complexity, 265-275.which has been published in final form at: http://dx.doi.org/10.1111/j.1749-6632.2008.03764.xCopyright: Blackwell Publishing Ltdhttp://www.blackwellpublishing.com/

During recent years many protein fold recognition methods have been developed, based on different algorithms and using various kinds of information. To examine the performance of these methods several evaluation experiments have been conducted. These include blind tests in CASP/CAFASP, large scale benchmarks, and long-term, continuous assessment with newly solved protein structures. These studies confirm the expectation that for different targets different methods produce the best predictions, and the final prediction accuracy could be improved if the available methods were combined in a perfect manner. In this article a neural-network-based consensus predictor, Pcons, is presented that attempts this task. Pcons attempts to select the best model out of those produced by six prediction servers, each using different methods. Pcons translates the confidence scores reported by each server into uniformly scaled values corresponding to the expected accuracy of each model. The translated scores as well as the similarity between models produced by different servers is used in the final selection. According to the analysis based on two unrelated sets of newly solved proteins, Pcons outperforms any single server by generating approximately 8%-10% more correct predictions. Furthermore, the specificity of Pcons is significantly higher than for any individual server. From analyzing different input data to Pcons it can be shown that the improvement is mainly attributable to measurement of the similarity between the different models. Pcons is freely accessible for the academic community through the protein structure-prediction metaserver at http://bioinfo.pl/meta/.

Background: The stability of atherosclerotic plaques determines the risk for rupture, which may lead to thrombus formation and potentially severe clinical complications such as myocardial infarction and stroke. Although the rate of plaque formation may be important for plaque stability, this process is not well understood. We took advantage of the atmospheric C-14-declination curve (a result of the atomic bomb tests in the 1950s and 1960s) to determine the average biological age of carotid plaques. Methodology/Principal Finding: The cores of carotid plaques were dissected from 29 well-characterized, symptomatic patients with carotid stenosis and analyzed for C-14 content by accelerator mass spectrometry. The average plaque age (i.e. formation time) was 9.6+/-3.3 years. All but two plaques had formed within 5-15 years before surgery. Plaque age was not associated with the chronological ages of the patients but was inversely related to plasma insulin levels (p=0.0014). Most plaques were echo-lucent rather than echo-rich (2.2460.97, range 1-5). However, plaques in the lowest tercile of plaque age (most recently formed) were characterized by further instability with a higher content of lipids and macrophages (67.8+/-12.4 vs. 50.4+/-6.2, p=0.00005; 57.6+/-26.1 vs. 39.8+/-25.7, p

Environmental exposures filtered through the genetic make-up of each individual alter the transcriptional repertoire in organs central to metabolic homeostasis, thereby affecting arterial lipid accumulation, inflammation, and the development of coronary artery disease (CAD). The primary aim of the Stockholm Atherosclerosis Gene Expression (STAGE) study was to determine whether there are functionally associated genes (rather than individual genes) important for CAD development. To this end, two-way clustering was used on 278 transcriptional profiles of liver, skeletal muscle, and visceral fat (n = 66/tissue) and atherosclerotic and unaffected arterial wall (n = 40/tissue) isolated from CAD patients during coronary artery bypass surgery. The first step, across all mRNA signals (n = 15,042/12,621 RefSeqs/genes) in each tissue, resulted in a total of 60 tissue clusters (n = 3958 genes). In the second step (performed within tissue clusters), one atherosclerotic lesion (n = 49/48) and one visceral fat (n = 59) cluster segregated the patients into two groups that differed in the extent of coronary stenosis (P = 0.008 and P = 0.00015). The associations of these clusters with coronary atherosclerosis were validated by analyzing carotid atherosclerosis expression profiles. Remarkably, in one cluster (n = 55/54) relating to carotid stenosis (P = 0.04), 27 genes in the two clusters relating to coronary stenosis were confirmed (n = 16/17, P, Author Summary The WHO predicts that coronary artery disease (CAD) will become the leading cause of death worldwide in 2010. Currently, major research efforts are focused on understanding the genetics of CAD through multi-center, genome-wide association studies of tens of thousands of patients and controls. Such studies can identify common variants of general importance throughout the entire population, which are likely relatively few. The number of rare genetic variants and variants that act in the context of environmental risk factors for CAD is probably much higher. We performed whole-genome expression analyses in several organs to identify functionally associated genes important for CAD development. We found an atherosclerosis module (A-module) consisting of 128 genes, enriched with genetic risk for CAD, involving transendothelial migration of leukocytes (TEML) and LIM domain binding 2 (LDB2) as its high-hierarchy regulator. Our study design represents a novel way of understanding the molecular underpinnings of CAD, focusing on genome-wide expression sensing both environmental and genetic influences. Investigating the relative enrichment of genetic CAD risk in functional groups (modules and networks) is an alternative approach to extract additional relevant information from genome-wide association studies. The A-module and LDB2 are attractive targets for treatments to modulate TEML and atherosclerosis development.

Despite the well-documented effects of plasma lipid lowering regimes halting atherosclerosis lesion development and reducing morbidity and mortality of coronary artery disease and stroke, the transcriptional response in the atherosclerotic lesion mediating these beneficial effects has not yet been carefully investigated. We performed transcriptional profiling at 10-week intervals in atherosclerosis-prone mice with human-like hypercholesterolemia and a genetic switch to lower plasma lipoproteins (Ldlr −/− Apo 100/100 Mttp flox/flox Mx1-Cre). Atherosclerotic lesions progressed slowly at first, then expanded rapidly, and plateaued after advanced lesions formed. Analysis of lesion expression profiles indicated that accumulation of lipid-poor macrophages reached a point that led to the rapid expansion phase with accelerated foam-cell formation and inflammation, an interpretation supported by lesion histology. Genetic lowering of plasma cholesterol (e.g., lipoproteins) at this point all together prevented the formation of advanced plaques and parallel transcriptional profiling of the atherosclerotic arterial wall identified 37 cholesterol-responsive genes mediating this effect. Validation by siRNA-inhibition in macrophages incubated with acetylated-LDL revealed a network of eight cholesterol-responsive atherosclerosis genes regulating cholesterol-ester accumulation. Taken together, we have identified a network of atherosclerosis genes that in response to plasma cholesterol-lowering prevents the formation of advanced plaques. This network should be of interest for the development of novel atherosclerosis therapies., Author Summary Atherosclerosis is present in the major arteries of all adults. In industrial societies, atherosclerosis progression in ∼50% of adults leads to clinical manifestations such as stroke and myocardial infarction, and eventually death. Lowering circulating LDL-cholesterol levels can slow atherosclerosis progression and even cause regression. Yet, little is known about the genes in the atherosclerotic arterial wall that mediate those effects. To identify such genes, we studied genetically modified mice in which high levels of human-like LDL-cholesterol cause rapid progression of atherosclerosis; the mice also had a genetic “switch” to lower LDL-cholesterol. Lowering LDL-cholesterol at a critical point before advanced plaques developed stopped lesion progression. Analysis of gene expression in response to the lowering of plasma LDL-cholesterol revealed 37 lesion genes as possible mediators of this effect. We validated some of these genes in macrophages using siRNA incubated with acetylated-LDL to mimic foam cells, which are central to atherosclerosis progression. “Reverse engineering” of whole-genome expression data from these experiments revealed a regulatory gene network of cholesterol-responsive atherosclerosis genes that control foam cell formation. This network and the individual genes within it merit further attention as targets for drugs to prevent the transformation of early harmless lesions into advanced, clinically significant plaques.