114 research outputs found
Networks from gene expression time series: characterization of correlation patterns
This paper describes characteristic features of networks reconstructed from
gene expression time series data. Several null models are considered in order
to discriminate between informations embedded in the network that are related
to real data, and features that are due to the method used for network
reconstruction (time correlation).Comment: 10 pages, 3 BMP figures, 1 Table. To appear in Int. J. Bif. Chaos,
July 2007, Volume 17, Issue
Statistical ensemble of gene regulatory networks of macrophage differentiation
Background: Macrophages cover a major role in the immune system, being the most plastic cell yielding several key immune functions. Methods: Here we derived a minimalistic gene regulatory network model for the differentiation of macrophages into the two phenotypes M1 (pro-) and M2 (anti-inflammatory). Results: To test the model, we simulated a large number of such networks as in a statistical ensemble. In other words, to enable the inter-cellular crosstalk required to obtain an immune activation in which the macrophage plays its role, the simulated networks are not taken in isolation but combined with other cellular agents, thus setting up a discrete minimalistic model of the immune system at the microscopic/intracellular (i.e., genetic regulation) and mesoscopic/intercellular scale. Conclusions: We show that within the mesoscopic level description of cellular interaction and cooperation, the gene regulatory logic is coherent and contributes to the overall dynamics of the ensembles that shows, statistically, the expected behaviour
Heterosexual, gay, and lesbian people’s reactivity to virtual caresses on their embodied avatars’ taboo zones
Embodying an artificial agent through immersive virtual reality (IVR) may lead to feeling vicariously somatosensory stimuli on one’s body which are in fact never delivered. To explore whether vicarious touch in IVR reflects the basic individual and social features of real-life interpersonal interactions we tested heterosexual men/women and gay men/lesbian women reacting subjectively and physiologically to the observation of a gender-matched virtual body being touched on intimate taboo zones (like genitalia) by male and female avatars. All participants rated as most erogenous caresses on their embodied avatar taboo zones. Crucially, heterosexual men/women and gay men/lesbian women rated as most erogenous taboo touches delivered by their opposite and same gender avatar, respectively. Skin conductance was maximal when taboo touches were delivered by female avatars. Our study shows that IVR may trigger realistic experiences and ultimately allow the direct exploration of sensitive societal and individual issues that can otherwise be explored only through imagination
Gene regulatory network modeling of macrophage differentiation corroborates the continuum hypothesis of polarization states
Macrophages derived from monocyte precursors undergo specific polarization processes which are influenced by the local tissue environment: classically activated (M1) macrophages, with a pro-inflammatory activity and a role of effector cells in Th1 cellular immune responses, and alternatively activated (M2) macrophages, with anti-inflammatory functions and involved in immunosuppression and tissue repair. At least three different subsets of M2 macrophages, namely, M2a, M2b, and M2c, are characterized in the literature based on their eliciting signals. The activation and polarization of macrophages is achieved through many, often intertwined, signaling pathways. To describe the logical relationships among the genes involved in macrophage polarization, we used a computational modeling methodology, namely, logical (Boolean) modeling of gene regulation. We integrated experimental data and knowledge available in the literature to construct a logical network model for the gene regulation driving macrophage polarization to the M1, M2a, M2b, and M2c phenotypes. Using the software GINsim and BoolNet, we analyzed the network dynamics under different conditions and perturbations to understand how they affect cell polarization. Dynamic simulations of the network model, enacting the most relevant biological conditions, showed coherence with the observed behavior of in vivo macrophages. The model could correctly reproduce the polarization toward the four main phenotypes as well as to several hybrid phenotypes, which are known to be experimentally associated to physiological and pathological conditions. We surmise that shifts among different phenotypes in the model mimic the hypothetical continuum of macrophage polarization, with M1 and M2 being the extremes of an uninterrupted sequence of states. Furthermore, model simulations suggest that anti-inflammatory macrophages are resilient to shift back to the pro-inflammatory phenotype
Direct and indirect use of water in a dairy system
La gestión de los recursos hÃdricos se ha convertido en un tema de suma importancia a nivel mundial. El objetivo del trabajo fue evaluar el uso del agua en un sistema de producción de leche Se evaluó el uso directo e indirecto del agua en un sistema de base pastoril (40%), con una carga de 2 VT/ha, contemplando el alimento importado al sistema versus el suministrado a los animales. El periodo evaluado fue desde junio de 2011 hasta julio de 2012. El agua directa es aquella usada en las tareas de higiene de la máquina de ordeño (MqO) y del equipo de frÃo (EF), en la placa de refrescado (PR) y como bebida animal. Los consumos de agua para la limpieza de la instalación de ordeño, corrales anexos y el agua de bebida se obtuvieron por caudalÃmetro y por fórmula para: MqO, litros/dÃa (l/d)=27,75*número de unidades de ordeño+134,4 y EF, l/d=0,0403*capacidad tanque (l)+11,153. Para la PR se utilizó un valor promedio de 2,75 l agua/l leche a refrescar. El agua indirecta es la necesaria para producir los alimentos importados (balanceado, grano maÃz, semilla algodón y pellet soja) y propios (pasturas y cultivos anuales en secano). Para su cálculo se utilizaron los programas CLIMWAT 2.0 y CROPWAT de la FAO, adaptando los ciclos de los cultivos con datos del sistema y regionales. En el Cuadro se observa que el consumo de agua total en el sistema considerando el alimento suministrado fue de 951,2 y con alimento importado fue 1.151,5 l/l (21,1% mayor). El consumo directo de agua solo representó menos del 1% de la cantidad total utilizada en el sistema, siendo el agua de bebida y la de PR las principales contribuyentes. El consumo indirecto representó más del 99%, compuesto mayoritariamente por el agua utilizada por las pasturas y por los alimentos importados. El análisis más detallado de esta fracción permitirÃa detectar las variables de mayor peso en el uso del agua, mejorando el manejo de este recurso en un sistema de producción lechero.Fil: Tieri, M. P.. Instituto Nacional de TecnologÃa Agropecuaria. Centro Regional Santa Fe. Estación Experimental Agropecuaria, Rafaela; Argentina;Fil: Pece, Marta Graciela del Valle. Instituto Nacional de TecnologÃa Agropecuaria. Centro Regional Santa Fe. Estación Experimental Agropecuaria, Rafaela; Argentina;Fil: Charlon, Veronica. Instituto Nacional de TecnologÃa Agropecuaria. Centro Regional Santa Fe. Estación Experimental Agropecuaria, Rafaela; Argentina;Fil: Comerón, E.. Instituto Nacional de TecnologÃa Agropecuaria. Centro Regional Santa Fe. Estación Experimental Agropecuaria, Rafaela; Argentina;Fil: Civit, Bárbara MarÃa. Universidad Tecnológica Nacional. Facultad Regional de Mendoza; Argentina; Consejo Nacional de Investigaciones CientÃficas y Técnicas. Centro CientÃfico Tecnológico - CONICET - Mendoza. Instituto de Ciencias Humanas, Sociales y Ambientales; Argentina
X-chromosome-linked miR548am-5p is a key regulator of sex disparity in the susceptibility to mitochondria-mediated apoptosis.
Sex dimorphism in cell response to stress has previously been investigated by different research groups. This dimorphism could be at least in part accounted for by sex-biased expression of regulatory elements such as microRNAs (miRs). In order to spot previously unknown miR expression differences we took advantage of prior knowledge on specialized databases to identify X chromosome-encoded miRs potentially escaping X chromosome inactivation (XCI). MiR-548am-5p emerged as potentially XCI escaper and was experimentally verified to be significantly up-regulated in human XX primary dermal fibroblasts (DFs) compared to XY ones. Accordingly, miR-548am-5p target mRNAs, e.g. the transcript for Bax, was differently modulated in XX and XY DFs. Functional analyses indicated that XY DFs were more prone to mitochondria-mediated apoptosis than XX ones. Experimentally induced overexpression of miR548am-5p in XY cells by lentivirus vector transduction decreased apoptosis susceptibility, whereas its down-regulation in XX cells enhanced apoptosis susceptibility. These data indicate that this approach could be used to identify previously unreported sex-biased differences in miR expression and that a miR identified with this approach, miR548am-5p, can account for sex-dependent differences observed in the susceptibility to mitochondrial apoptosis of human DFs
On dynamic network entropy in cancer
The cellular phenotype is described by a complex network of molecular
interactions. Elucidating network properties that distinguish disease from the
healthy cellular state is therefore of critical importance for gaining
systems-level insights into disease mechanisms and ultimately for developing
improved therapies. By integrating gene expression data with a protein
interaction network to induce a stochastic dynamics on the network, we here
demonstrate that cancer cells are characterised by an increase in the dynamic
network entropy, compared to cells of normal physiology. Using a fundamental
relation between the macroscopic resilience of a dynamical system and the
uncertainty (entropy) in the underlying microscopic processes, we argue that
cancer cells will be more robust to random gene perturbations. In addition, we
formally demonstrate that gene expression differences between normal and cancer
tissue are anticorrelated with local dynamic entropy changes, thus providing a
systemic link between gene expression changes at the nodes and their local
network dynamics. In particular, we also find that genes which drive
cell-proliferation in cancer cells and which often encode oncogenes are
associated with reductions in the dynamic network entropy. In summary, our
results support the view that the observed increased robustness of cancer cells
to perturbation and therapy may be due to an increase in the dynamic network
entropy that allows cells to adapt to the new cellular stresses. Conversely,
genes that exhibit local flux entropy decreases in cancer may render cancer
cells more susceptible to targeted intervention and may therefore represent
promising drug targets.Comment: 10 pages, 3 figures, 4 tables. Submitte
Networked buffering: a basic mechanism for distributed robustness in complex adaptive systems
A generic mechanism - networked buffering - is proposed for the generation of robust traits in complex systems. It requires two basic conditions to be satisfied: 1) agents are versatile enough to perform more than one single functional role within a system and 2) agents are degenerate, i.e. there exists partial overlap in the functional capabilities of agents. Given these prerequisites, degenerate systems can readily produce a distributed systemic response to local perturbations. Reciprocally, excess resources related to a single function can indirectly support multiple unrelated functions within a degenerate system. In models of genome:proteome mappings for which localized decision-making and modularity of genetic functions are assumed, we verify that such distributed compensatory effects cause enhanced robustness of system traits. The conditions needed for networked buffering to occur are neither demanding nor rare, supporting the conjecture that degeneracy may fundamentally underpin distributed robustness within several biotic and abiotic systems. For instance, networked buffering offers new insights into systems engineering and planning activities that occur under high uncertainty. It may also help explain recent developments in understanding the origins of resilience within complex ecosystems. \ud
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Community effort endorsing multiscale modelling, multiscale data science and multiscale computing for systems medicine
© 2017 The Author 2017. Published by Oxford University Press. Systems medicine holds many promises, but has so far provided only a limited number of proofs of principle. To address this road block, possible barriers and challenges of translating systems medicine into clinical practice need to be identified and addressed. The members of the European Cooperation in Science and Technology COST) Action CA15120 Open Multiscale Systems Medicine OpenMultiMed) wish to engage the scientific community of systems medicine and multiscale modelling, data science and computing, to provide their feedback in a structured manner. This will result in follow-up white papers and open access resources to accelerate the clinical translation of systems medicine.Austrian Science Fund: Special Research Program SFB-F54. The European Cooperation in Science and Technology (COST) Action CA15120 OpenMultiMed (http://openmultimed.net)
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