Responsive Urban Models by Processing Sets of Heterogeneous Data

This paper presents some steps in experimentation aimed at describing urban spaces made following the series of earthquakes that affected a vast area of central Italy starting on 24 August 2016. More specifically, these spaces pertain to historical centres of limited size and case studies that can be called "problematic" (due to complex morphological and settlement conditions, because they are difficult to access, or because they have been affected by calamitous events, etc.). The main objectives were to verify the use of sets of heterogeneous data that are already largely available to define a workflow and develop procedures that would allow some of the steps to be automated as much as possible. The most general goal was to use the experimentation to define a methodology to approach the problem aimed at developing descriptive responsive models of the urban space, that is, morphological and computer-based models capable of being modified in relation to the constantly updated flow of input data

Measurement and simulation of reflector antenna

Well-established procedures are consolidated to determine the associated measurement uncertainty for a given antenna and measurements scenario [1-2]. Similar criteria for establishing uncertainties in numerical modelling of the same antenna are still to be established. In this paper, we investigate the achievable agreement between antenna measurement and simulation when external error sources are minimized. The test object, is a reflector fed by a wideband dual ridge horn (SR40-A and SH4000). The highly stable reference antenna has been selected to minimize uncertainty related to finite manufacturing and material parameter accuracy. Two frequencies, 10.7GHz and 18GHz have been selected for detailed investigation

A Digital Pattern Methodology supporting Railway Industries in Portfolio Management

The object of this paper is the development of a decision support system involved in the bidding for invitations to tender in the railway field. The proposed methodology is based on the characterization of the whole train and its components, through several attributes according to a digital pattern approach. In particular some key components were chosen such as the traction motor, the bogie and the auxiliary equipment converter. The system measures the extent to which the products offered by the company fit the one required by the customer, comparing the homologous attributes. Such analysis is called ‘adopt/adapt/innovate’ (AAI). In this way it is possible to identify products already designed that fully or partly fit what required, obtaining huge benefits in terms of effectiveness and efficiency

The Evolving Transcriptome of Head and Neck Squamous Cell Carcinoma: A Systematic Review

BACKGROUND: Numerous studies were performed to illuminate mechanisms of tumorigenesis and metastases from gene expression profiles of Head and Neck Squamous Cell Carcinoma (HNSCC). The objective of this review is to conduct a network-based meta-analysis to identify the underlying biological signatures of the HNSCC transcriptome. METHODS AND FINDINGS: We included 63 HNSCC transcriptomic studies into three specific categories of comparisons: Pre, premalignant lesions v.s. normal; TvN, primary tumors v.s. normal; and Meta, metastatic or invasive v.s. primary tumors. Reported genes extracted from the literature were systematically analyzed. Participation of differential gene activities across three progressive stages deciphered the evolving nature of HNSCC. In total, 1442 genes were verified, i.e. reported at least twice, with ECM1, EMP1, CXCL10 and POSTN shown to be highly reported across all three stages. Knowledge-based networks of the HNSCC transcriptome were constructed, demonstrating integrin signaling and antigen presentation pathways as highly enriched. Notably, functional estimates derived from topological characteristics of integrin signaling networks identified such important genes as ITGA3 and ITGA5, which were supported by findings of invasiveness in vitro. Moreover, we computed genome-wide probabilities of reporting differential gene activities for the Pre, TvN, and Meta stages, respectively. Results highlighted chromosomal regions of 6p21, 19p13 and 19q13, where genomic alterations were shown to be correlated with the nodal status of HNSCC. CONCLUSIONS: By means of a systems-biology approach via network-based meta-analyses, we provided a deeper insight into the evolving nature of the HNSCC transcriptome. Enriched canonical signaling pathways, hot-spots of transcriptional profiles across the genome, as well as topologically significant genes derived from network analyses were highlighted for each of the three progressive stages, Pre, TvN, and Meta, respectively

Immunological network signatures of cancer progression and survival

<p>Abstract</p> <p>Background</p> <p>The immune contribution to cancer progression is complex and difficult to characterize. For example in tumors, immune gene expression is detected from the combination of normal, tumor and immune cells in the tumor microenvironment. Profiling the immune component of tumors may facilitate the characterization of the poorly understood roles immunity plays in cancer progression. However, the current approaches to analyze the immune component of a tumor rely on incomplete identification of immune factors.</p> <p>Methods</p> <p>To facilitate a more comprehensive approach, we created a ranked immunological relevance score for all human genes, developed using a novel strategy that combines text mining and information theory. We used this score to assign an immunological grade to gene expression profiles, and thereby quantify the immunological component of tumors. This immunological relevance score was benchmarked against existing manually curated immune resources as well as high-throughput studies. To further characterize immunological relevance for genes, the relevance score was charted against both the human interactome and cancer information, forming an expanded interactome landscape of tumor immunity. We applied this approach to expression profiles in melanomas, thus identifying and grading their immunological components, followed by identification of their associated protein interactions.</p> <p>Results</p> <p>The power of this strategy was demonstrated by the observation of early activation of the adaptive immune response and the diversity of the immune component during melanoma progression. Furthermore, the genome-wide immunological relevance score classified melanoma patient groups, whose immunological grade correlated with clinical features, such as immune phenotypes and survival.</p> <p>Conclusions</p> <p>The assignment of a ranked immunological relevance score to all human genes extends the content of existing immune gene resources and enriches our understanding of immune involvement in complex biological networks. The application of this approach to tumor immunity represents an automated systems strategy that quantifies the immunological component in complex disease. In so doing, it stratifies patients according to their immune profiles, which may lead to effective computational prognostic and clinical guides.</p

Gene Expression Profiles Characterize Inflammation Stages in the Acute Lung Injury in Mice

Acute Lung Injury (ALI) carries about 50 percent mortality and is frequently associated with an infection (sepsis). Life-support treatment with mechanical ventilation rescues many patients, although superimposed infection or multiple organ failure can result in death. The outcome of a patient developing sepsis depends on two factors: the infection and the pre-existing inflammation. In this study, we described each stage of the inflammation process using a transcriptional approach and an animal model. Female C57BL6/J mice received an intravenous oleic acid injection to induce an acute lung injury (ALI). Lung expression patterns were analyzed using a 9900 cDNA mouse microarray (MUSV29K). Our gene-expression analysis revealed marked changes in the immune and inflammatory response metabolic pathways, notably lipid metabolism and transcription. The early stage (1 hour–1.5 hours) is characterized by a pro-inflammatory immune response. Later (3 hours–4 hours), the immune cells migrate into inflamed tissues through interaction with vascular endothelial cells. Finally, at late stages of lung inflammation (18 hours–24 hours), metabolism is deeply disturbed. Highly expressed pro-inflammatory cytokines activate transcription of many genes and lipid metabolism. In this study, we described a global overview of critical events occurring during lung inflammation which is essential to understand infectious pathologies such as sepsis where inflammation and infection are intertwined. Based on these data, it becomes possible to isolate the impact of a pathogen at the transcriptional level from the global gene expression modifications resulting from the infection associated with the inflammation

Agent-Based Modeling of Endotoxin-Induced Acute Inflammatory Response in Human Blood Leukocytes

Inflammation is a highly complex biological response evoked by many stimuli. A persistent challenge in modeling this dynamic process has been the (nonlinear) nature of the response that precludes the single-variable assumption. Systems-based approaches offer a promising possibility for understanding inflammation in its homeostatic context. In order to study the underlying complexity of the acute inflammatory response, an agent-based framework is developed that models the emerging host response as the outcome of orchestrated interactions associated with intricate signaling cascades and intercellular immune system interactions.An agent-based modeling (ABM) framework is proposed to study the nonlinear dynamics of acute human inflammation. The model is implemented using NetLogo software. Interacting agents involve either inflammation-specific molecules or cells essential for the propagation of the inflammatory reaction across the system. Spatial orientation of molecule interactions involved in signaling cascades coupled with the cellular heterogeneity are further taken into account. The proposed in silico model is evaluated through its ability to successfully reproduce a self-limited inflammatory response as well as a series of scenarios indicative of the nonlinear dynamics of the response. Such scenarios involve either a persistent (non)infectious response or innate immune tolerance and potentiation effects followed by perturbations in intracellular signaling molecules and cascades.The ABM framework developed in this study provides insight on the stochastic interactions of the mediators involved in the propagation of endotoxin signaling at the cellular response level. The simulation results are in accordance with our prior research effort associated with the development of deterministic human inflammation models that include transcriptional dynamics, signaling, and physiological components. The hypothetical scenarios explored in this study would potentially improve our understanding of how manipulating the behavior of the molecular species could manifest into emergent behavior of the overall system

Is human blood a good surrogate for brain tissue in transcriptional studies?

Abstract Background Since human brain tissue is often unavailable for transcriptional profiling studies, blood expression data is frequently used as a substitute. The underlying hypothesis in such studies is that genes expressed in brain tissue leave a transcriptional footprint in blood. We tested this hypothesis by relating three human brain expression data sets (from cortex, cerebellum and caudate nucleus) to two large human blood expression data sets (comprised of 1463 individuals). Results We found mean expression levels were weakly correlated between the brain and blood data (r range: [0.24,0.32]). Further, we tested whether co-expression relationships were preserved between the three brain regions and blood. Only a handful of brain co-expression modules showed strong evidence of preservation and these modules could be combined into a single large blood module. We also identified highly connected intramodular "hub" genes inside preserved modules. These preserved intramodular hub genes had the following properties: first, their expression levels tended to be significantly more heritable than those from non-preserved intramodular hub genes (p &lt; 10-90); second, they had highly significant positive correlations with the following cluster of differentiation genes: CD58, CD47, CD48, CD53 and CD164; third, a significant number of them were known to be involved in infection mechanisms, post-transcriptional and post-translational modification and other basic processes. Conclusions Overall, we find transcriptome organization is poorly preserved between brain and blood. However, the subset of preserved co-expression relationships characterized here may aid future efforts to identify blood biomarkers for neurological and neuropsychiatric diseases when brain tissue samples are unavailable

Comparison of reflector antenna measurements and simulations

In antenna measurement, well-established procedures are consolidated to determine the associated measurement uncertainty for a given antenna and measurements scenario [1-2]. Similar criteria for establishing uncertainties in numerical modeling of the same antenna are still to be established. In this paper, we investigate the achievable agreement between antenna measurement and simulation when external error sources are minimized. The test object, is a reflector fed by a wideband dual ridge horn (SR40-A and SH4000) manufactured by MVG. This highly stable reference antenna has been selected to minimize uncertainty related to finite manufacturing and material parameter accuracy. Two frequencies, 10.7GHz and 18GHz have been selected for detailed investigation. The antenna has been measured by several measurement facilities (spherical, cylindrical and planar near field ranges) across Europe in the ? ? ? ? ? ? ? ? activity. The purpose of this intercomparison campaign is the comparison of the different antenna measurement facilities, throughout Europe, considering measurement procedures and uncertainty estimates. The antenna has been simulated using a full CAD model, in step compatible format and using different numerical methods from different software vendor