A novel multi-network approach reveals tissue-specific cellular modulators of fibrosis in systemic sclerosis

BACKGROUND: Systemic sclerosis (SSc) is a multi-organ autoimmune disease characterized by skin fibrosis. Internal organ involvement is heterogeneous. It is unknown whether disease mechanisms are common across all involved affected tissues or if each manifestation has a distinct underlying pathology. METHODS: We used consensus clustering to compare gene expression profiles of biopsies from four SSc-affected tissues (skin, lung, esophagus, and peripheral blood) from patients with SSc, and the related conditions pulmonary fibrosis (PF) and pulmonary arterial hypertension, and derived a consensus disease-associate signature across all tissues. We used this signature to query tissue-specific functional genomic networks. We performed novel network analyses to contrast the skin and lung microenvironments and to assess the functional role of the inflammatory and fibrotic genes in each organ. Lastly, we tested the expression of macrophage activation state-associated gene sets for enrichment in skin and lung using a Wilcoxon rank sum test. RESULTS: We identified a common pathogenic gene expression signature-an immune-fibrotic axis-indicative of pro-fibrotic macrophages (MØs) in multiple tissues (skin, lung, esophagus, and peripheral blood mononuclear cells) affected by SSc. While the co-expression of these genes is common to all tissues, the functional consequences of this upregulation differ by organ. We used this disease-associated signature to query tissue-specific functional genomic networks to identify common and tissue-specific pathologies of SSc and related conditions. In contrast to skin, in the lung-specific functional network we identify a distinct lung-resident MØ signature associated with lipid stimulation and alternative activation. In keeping with our network results, we find distinct MØ alternative activation transcriptional programs in SSc-associated PF lung and in the skin of patients with an "inflammatory" SSc gene expression signature. CONCLUSIONS: Our results suggest that the innate immune system is central to SSc disease processes but that subtle distinctions exist between tissues. Our approach provides a framework for examining molecular signatures of disease in fibrosis and autoimmune diseases and for leveraging publicly available data to understand common and tissue-specific disease processes in complex human diseases

Addressing the sample size problem in behavioural operational research: simulating the newsvendor problem

Laboratory-based experimental studies with human participants are beneficial for testing hypotheses in behavioural operational research. However, such experiments are not without their problems. One specific problem is obtaining a sufficient sample size, not only in terms of the number of participants but also the time they are willing to devote to an experiment. In this paper, we explore how agent-based simulation (ABS) can be used to address the sample size problem and demonstrate the approach in the newsvendor setting. The decision-making strategies of a small sample of individual decision-makers are determined through laboratory experiments. The interactions of these suppliers and retailers are then simulated using an ABS to generate a large sample set of decisions. With only a small number of participants, we demonstrate that it is possible to produce similar results to previous experimental studies that involved much larger sample sizes. We conclude that ABS provides the potential to extend the scope of experimental research in behavioural operational research

Spatially Uniform ReliefF (SURF) for computationally-efficient filtering of gene-gene interactions

<p>Abstract</p> <p>Background</p> <p>Genome-wide association studies are becoming the de facto standard in the genetic analysis of common human diseases. Given the complexity and robustness of biological networks such diseases are unlikely to be the result of single points of failure but instead likely arise from the joint failure of two or more interacting components. The hope in genome-wide screens is that these points of failure can be linked to single nucleotide polymorphisms (SNPs) which confer disease susceptibility. Detecting interacting variants that lead to disease in the absence of single-gene effects is difficult however, and methods to exhaustively analyze sets of these variants for interactions are combinatorial in nature thus making them computationally infeasible. Efficient algorithms which can detect interacting SNPs are needed. ReliefF is one such promising algorithm, although it has low success rate for noisy datasets when the interaction effect is small. ReliefF has been paired with an iterative approach, Tuned ReliefF (TuRF), which improves the estimation of weights in noisy data but does not fundamentally change the underlying ReliefF algorithm. To improve the sensitivity of studies using these methods to detect small effects we introduce Spatially Uniform ReliefF (SURF).</p> <p>Results</p> <p>SURF's ability to detect interactions in this domain is significantly greater than that of ReliefF. Similarly SURF, in combination with the TuRF strategy significantly outperforms TuRF alone for SNP selection under an epistasis model. It is important to note that this success rate increase does not require an increase in algorithmic complexity and allows for increased success rate, even with the removal of a nuisance parameter from the algorithm.</p> <p>Conclusion</p> <p>Researchers performing genetic association studies and aiming to discover gene-gene interactions associated with increased disease susceptibility should use SURF in place of ReliefF. For instance, SURF should be used instead of ReliefF to filter a dataset before an exhaustive MDR analysis. This change increases the ability of a study to detect gene-gene interactions. The SURF algorithm is implemented in the open source Multifactor Dimensionality Reduction (MDR) software package available from <url>http://www.epistasis.org</url>.</p

Convergent extension analysis in mouse whole embryo culture

Mutations have been identified in a non-canonical Wnt signalling cascade (the planar cell polarity pathway) in several mouse genetic models of severe neural tube defects. In each of these models, neurulation fails to be initiated at the 3-4 somite stage, leading to an almost entirely open neural tube (termed craniorachischisis). Studies in whole embryo culture have identified a defect in the morphogenetic process of convergent extension during gastrulation, preceding the onset of neural tube closure. The principal defect is a failure of midline extension, both in the neural plate and axial mesoderm. This leads to an abnormally wide neural plate in which the elevating neural folds are too far apart to achieve closure. In this chapter, we provide details of several experimental methods that can be used to evaluate convergent extension in cultured mouse embryos. We describe analytical methods that can reveal the abnormalities that characterise neurulation-stage embryos with defective planar cell polarity signalling, in particular the loop-tail (Lp; Vangl2) mutant

Face-selective electrostatic control of hydrothermal zinc oxide nanowire synthesis

Rational control over the morphology and the functional properties of inorganic nanostructures has been a long-standing goal in the development of bottom-up device fabrication processes. We report that the geometry of hydrothermally grown zinc oxide nanowires can be tuned from platelets to needles, covering more than three orders of magnitude in aspect ratio (~0.1–100). We introduce a classical thermodynamics-based model to explain the underlying growth inhibition mechanism by means of the competitive and face-selective electrostatic adsorption of non-zinc complex ions at alkaline conditions. The performance of these nanowires rivals that of vapour-phase-grown nanostructures and their low-temperature synthesis (<60 °C) is favourable to the integration and in situ fabrication of complex and polymer-supported devices. We illustrate this capability by fabricating an all-inorganic light-emitting diode in a polymeric microfluidic manifold. Our findings indicate that electrostatic interactions in aqueous crystal growth may be systematically manipulated to synthesize nanostructures and devices with enhanced structural control.National Science Foundation (U.S.) (MIT Center for Bits and Atoms (NSF CCR0122419))Massachusetts Institute of Technology. Media LaboratoryKorea Foundation for Advanced StudiesSamsung Electronics Co. (research internship)Harvard University. Society of FellowsWallace H. Coulter Foundation (Early Career Award)Brain & Behavior Research Foundation (Young Investigator Award)National Science Foundation (U.S.)National Institutes of Health (U.S.) (Director’s New Innovator Award

Analytic philosophy for biomedical research: the imperative of applying yesterday's timeless messages to today's impasses

The mantra that "the best way to predict the future is to invent it" (attributed to the computer scientist Alan Kay) exemplifies some of the expectations from the technical and innovative sides of biomedical research at present. However, for technical advancements to make real impacts both on patient health and genuine scientific understanding, quite a number of lingering challenges facing the entire spectrum from protein biology all the way to randomized controlled trials should start to be overcome. The proposal in this chapter is that philosophy is essential in this process. By reviewing select examples from the history of science and philosophy, disciplines which were indistinguishable until the mid-nineteenth century, I argue that progress toward the many impasses in biomedicine can be achieved by emphasizing theoretical work (in the true sense of the word 'theory') as a vital foundation for experimental biology. Furthermore, a philosophical biology program that could provide a framework for theoretical investigations is outlined