The Emperor’s Dilemma: A Computational Model of Self-Enforcing Norms

The authors demonstrate the uses of agent‐based computational models in an application to a social enigma they call the “emperor’s dilemma,” based on the Hans Christian Andersen fable. In this model, agents must decide whether to comply with and enforce a norm that is supported by a few fanatics and opposed by the vast majority. They find that cascades of self‐reinforcing support for a highly unpopular norm cannot occur in a fully connected social network. However, if agents’ horizons are limited to immediate neighbors, highly unpopular norms can emerge locally and then spread. One might expect these cascades to be more likely as the number of “true believers” increases, and bridge ties are created between otherwise distant actors. Surprisingly, the authors observed quite the opposite effects

Statistical monitoring of weak spots for improvement of normalization and ratio estimates in microarrays

BACKGROUND: Several aspects of microarray data analysis are dependent on identification of genes expressed at or near the limits of detection. For example, regression-based normalization methods rely on the premise that most genes in compared samples are expressed at similar levels and therefore require accurate identification of nonexpressed genes (additive noise) so that they can be excluded from the normalization procedure. Moreover, key regulatory genes can maintain stringent control of a given response at low expression levels. If arbitrary cutoffs are used for distinguishing expressed from nonexpressed genes, some of these key regulatory genes may be unnecessarily excluded from the analysis. Unfortunately, no accurate method for differentiating additive noise from genes expressed at low levels is currently available. RESULTS: We developed a multistep procedure for analysis of mRNA expression data that robustly identifies the additive noise in a microarray experiment. This analysis is predicated on the fact that additive noise signals can be accurately identified by both distribution and statistical analysis. CONCLUSIONS: Identification of additive noise in this manner allows exclusion of noncorrelated weak signals from regression-based normalization of compared profiles thus maximizing the accuracy of these methods. Moreover, genes expressed at very low levels can be clearly identified due to the fact that their expression distribution is stable and distinguishable from the random pattern of additive noise

Cascade Dynamics of Multiplex Propagation

Random links between otherwise distant nodes can greatly facilitate the propagation of disease or information, provided contagion can be transmitted by a single active node. However we show that when the propagation requires simultaneous exposure to multiple sources of activation, called multiplex propagation, the effect of random links is just the opposite: it makes the propagation more difficult to achieve. We calculate analytical and numerically critical points for a threshold model in several classes of complex networks, including an empirical social network.Comment: 4 pages, 5 figures, for similar work visit http://hsd.soc.cornell.edu and http://www.imedea.uib.es/physdep

Temporal dynamics of gene expression in the lung in a baboon model of E. coli sepsis

BACKGROUND: Bacterial invasion during sepsis induces disregulated systemic responses that could lead to fatal lung failure. The purpose of this study was to relate the temporal dynamics of gene expression to the pathophysiological changes in the lung during the first and second stages of E. coli sepsis in baboons. RESULTS: Using human oligonucleotide microarrays, we have explored the temporal changes of gene expression in the lung of baboons challenged with sublethal doses of E. coli. Temporal expression pattern and biological significance of the differentially expressed genes were explored using clustering and pathway analysis software. Expression of selected genes was validated by real-time PCR. Cytokine levels in tissue and plasma were assayed by multiplex ELISA. Changes in lung ultrastructure were visualized by electron microscopy. We found that genes involved in primary inflammation, innate immune response, and apoptosis peaked at 2 hrs. Inflammatory and immune response genes that function in the stimulation of monocytes, natural killer and T-cells, and in the modulation of cell adhesion peaked at 8 hrs, while genes involved in wound healing and functional recovery were upregulated at 24 hrs. CONCLUSION: The analysis of gene expression modulation in response to sepsis provides the baseline information that is crucial for the understanding of the pathophysiology of systemic inflammation and may facilitate the development of future approaches for sepsis therapy

Systems biology approach for mapping the response of human urothelial cells to infection by Enterococcus faecalis

<p>Abstract</p> <p>Background</p> <p>To better understand the response of urinary epithelial (urothelial) cells to <it>Enterococcus faecalis</it>, a uropathogen that exhibits resistance to multiple antibiotics, a genome-wide scan of gene expression was obtained as a time series from urothelial cells growing as a layered 3-dimensional culture similar to normal urothelium. We herein describe a novel means of analysis that is based on deconvolution of gene variability into technical and biological components.</p> <p>Results</p> <p>Analysis of the expression of 21,521 genes from 30 minutes to 10 hours post infection, showed 9553 genes were expressed 3 standard deviations (SD) above the system zero-point noise in at least 1 time point. The asymmetric distribution of relative variances of the expressed genes was deconvoluted into technical variation (with a 6.5% relative SD) and biological variation components (>3 SD above the mode technical variability). These 1409 hypervariable (HV) genes encapsulated the effect of infection on gene expression. Pathway analysis of the HV genes revealed an orchestrated response to infection in which early events included initiation of immune response, cytoskeletal rearrangement and cell signaling followed at the end by apoptosis and shutting down cell metabolism. The number of poorly annotated genes in the earliest time points suggests heretofore unknown processes likely also are involved.</p> <p>Conclusion</p> <p><it>Enterococcus </it>infection produced an orchestrated response by the host cells involving several pathways and transcription factors that potentially drive these pathways. The early time points potentially identify novel targets for enhancing the host response. These approaches combine rigorous statistical principles with a biological context and are readily applied by biologists.</p

A dynamic model of gene expression in monocytes reveals differences in immediate/early response genes between adult and neonatal cells

Neonatal monocytes display immaturity of numerous functions compared with adult cells. Gene expression arrays provide a promising tool for elucidating mechanisms underlying neonatal immune function. We used a well-established microarray to analyze differences between LPS-stimulated human cord blood and adult monocytes to create dynamic models for interactions to elucidate observed deficiencies in neonatal immune responses. We identified 168 genes that were differentially expressed between adult and cord monocytes after 45 min incubation with LPS. Of these genes, 95% (159 of 167) were over-expressed in adult relative to cord monocytes. Differentially expressed genes could be sorted into nine groups according to their kinetics of activation. Functional modelling suggested differences between adult and cord blood in the regulation of apoptosis, a finding confirmed using annexin binding assays. We conclude that kinetic studies of gene expression reveal potentially important differences in gene expression dynamics that may provide insight into neonatal innate immunity

The inflammatory and normal transcriptome of mouse bladder detrusor and mucosa

BACKGROUND: An organ such as the bladder consists of complex, interacting set of tissues and cells. Inflammation has been implicated in every major disease of the bladder, including cancer, interstitial cystitis, and infection. However, scanty is the information about individual detrusor and urothelium transcriptomes in response to inflammation. Here, we used suppression subtractive hybridizations (SSH) to determine bladder tissue- and disease-specific genes and transcriptional regulatory elements (TRE)s. Unique TREs and genes were assembled into putative networks. RESULTS: It was found that the control bladder mucosa presented regulatory elements driving genes such as myosin light chain phosphatase and calponin 1 that influence the smooth muscle phenotype. In the control detrusor network the Pax-3 TRE was significantly over-represented. During development, the Pax-3 transcription factor (TF) maintains progenitor cells in an undifferentiated state whereas, during inflammation, Pax-3 was suppressed and genes involved in neuronal development (synapsin I) were up-regulated. Therefore, during inflammation, an increased maturation of neural progenitor cells in the muscle may underlie detrusor instability. NF-κB was specifically over-represented in the inflamed mucosa regulatory network. When the inflamed detrusor was compared to control, two major pathways were found, one encoding synapsin I, a neuron-specific phosphoprotein, and the other an important apoptotic protein, siva. In response to LPS-induced inflammation, the liver X receptor was over-represented in both mucosa and detrusor regulatory networks confirming a role for this nuclear receptor in LPS-induced gene expression. CONCLUSION: A new approach for understanding bladder muscle-urothelium interaction was developed by assembling SSH, real time PCR, and TRE analysis results into regulatory networks. Interestingly, some of the TREs and their downstream transcripts originally involved in organogenesis and oncogenesis were also activated during inflammation. The latter represents an additional link between inflammation and cancer. The regulatory networks represent key targets for development of novel drugs targeting bladder diseases

Discriminators of mouse bladder response to intravesical Bacillus Calmette-Guerin (BCG)

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Internal standard-based analysis of microarray data2—Analysis of functional associations between HVE-genes

In this work we apply the Internal Standard-based analytical approach that we described in an earlier communication and here we demonstrate experimental results on functional associations among the hypervariably-expressed genes (HVE-genes). Our working assumption was that those genetic components, which initiate the disease, involve HVE-genes for which the level of expression is undistinguishable among healthy individuals and individuals with pathology. We show that analysis of the functional associations of the HVE-genes is indeed suitable to revealing disease-specific differences. We show also that another possible exploit of HVE-genes for characterization of pathological alterations is by using multivariate classification methods. This in turn offers important clues on naturally occurring dynamic processes in the organism and is further used for dynamic discrimination of groups of compared samples. We conclude that our approach can uncover principally new collective differences that cannot be discerned by individual gene analysi