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D Sasselov - One of the best experts on this subject based on the ideXlab platform.
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a Detailed Model grid for solid planets from 0 1 through 100 earth masses
2013Co-Authors: Li Zeng, D SasselovAbstract:This article describes a new grid for the mass-radius relation of three-layer exoplanets within the mass range of 0.1-100 M⊕. The three layers are: Fe (-phase of iron), MgSiO3 (including both the perovskite phase, post-perovskite phase, and its dissociation at ultrahigh pressures), and H2O (including Ices Ih, III, V, VI, VII, X, and the superionic phase along the melting curve). We discuss the current state of knowledge about the equations of state (EOS) that influence these calculations and the improvements used in the new grid. For the two-layer Model, we demonstrate the utility of contours on the mass-radius diagrams. Given the mass and radius input, these contours can be used to quickly determine the important physical properties of a planet including its p0 (central pressure), p1/p0 (core-mantle boundary pressure over central pressure), CMF (core mass fraction) or CRF (core radius fraction). For the three-layer Model, a curve segment on the ternary diagram represents all possible relative mass proportions of the three layers for a given mass-radius input. These ternary diagrams are tabulated with the intent to make comparison to observations easier. How the presence of Fe in the mantle affects the mass-radius relations is also discussed in a separate section. A dynamic and interactive tool to characterize and illustrate the interior structure of exoplanets built upon Models in this article is available online.
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a Detailed Model grid for solid planets from 0 1 through 100 earth masses
2013Co-Authors: Li Zeng, D SasselovAbstract:This paper describes a new grid for the mass-radius relation of 3-layer exoplanets within the mass range of 0.1 through 100 Earth Masses. The 3 layers are: Fe (epsilon iron), MgSiO3 (including both the perovskite phase, post-perovskite phase, and its dissociation at ultra-high pressures), and H2O (including Ices Ih, III, V, VI, VII, X, and the superionic phase along the melting curve). We discuss the current state of knowledge about the equations of state (EOS) that influence these calculations and the improvements used in the new grid. For the 2-layer Model, we demonstrate the utility of contours on the mass-radius diagrams. Given the mass and radius input, these contours can be used to quickly determine the important physical properties of a planet including its p0 (central pressure), p1/p0 (core-mantle boundary pressure over central pressure), CMF (core mass fraction) or CRF (core radius fraction). For the 3-layer Model, a curve segment on the ternary diagram represents all possible relative mass proportions of the 3 layers for a given mass-radius input. These ternary diagrams are tabulated into Table3 with the intent to make comparison to observations easier. How the presence of Fe in the mantle affects the mass-radius relations is also discussed in a separate section. A dynamic and interactive tool to characterize and illustrate the interior structure of exoplanets built upon Models in this paper is available on the website: this http URL
Li Zeng - One of the best experts on this subject based on the ideXlab platform.
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a Detailed Model grid for solid planets from 0 1 through 100 earth masses
2013Co-Authors: Li Zeng, D SasselovAbstract:This article describes a new grid for the mass-radius relation of three-layer exoplanets within the mass range of 0.1-100 M⊕. The three layers are: Fe (-phase of iron), MgSiO3 (including both the perovskite phase, post-perovskite phase, and its dissociation at ultrahigh pressures), and H2O (including Ices Ih, III, V, VI, VII, X, and the superionic phase along the melting curve). We discuss the current state of knowledge about the equations of state (EOS) that influence these calculations and the improvements used in the new grid. For the two-layer Model, we demonstrate the utility of contours on the mass-radius diagrams. Given the mass and radius input, these contours can be used to quickly determine the important physical properties of a planet including its p0 (central pressure), p1/p0 (core-mantle boundary pressure over central pressure), CMF (core mass fraction) or CRF (core radius fraction). For the three-layer Model, a curve segment on the ternary diagram represents all possible relative mass proportions of the three layers for a given mass-radius input. These ternary diagrams are tabulated with the intent to make comparison to observations easier. How the presence of Fe in the mantle affects the mass-radius relations is also discussed in a separate section. A dynamic and interactive tool to characterize and illustrate the interior structure of exoplanets built upon Models in this article is available online.
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a Detailed Model grid for solid planets from 0 1 through 100 earth masses
2013Co-Authors: Li Zeng, D SasselovAbstract:This paper describes a new grid for the mass-radius relation of 3-layer exoplanets within the mass range of 0.1 through 100 Earth Masses. The 3 layers are: Fe (epsilon iron), MgSiO3 (including both the perovskite phase, post-perovskite phase, and its dissociation at ultra-high pressures), and H2O (including Ices Ih, III, V, VI, VII, X, and the superionic phase along the melting curve). We discuss the current state of knowledge about the equations of state (EOS) that influence these calculations and the improvements used in the new grid. For the 2-layer Model, we demonstrate the utility of contours on the mass-radius diagrams. Given the mass and radius input, these contours can be used to quickly determine the important physical properties of a planet including its p0 (central pressure), p1/p0 (core-mantle boundary pressure over central pressure), CMF (core mass fraction) or CRF (core radius fraction). For the 3-layer Model, a curve segment on the ternary diagram represents all possible relative mass proportions of the 3 layers for a given mass-radius input. These ternary diagrams are tabulated into Table3 with the intent to make comparison to observations easier. How the presence of Fe in the mantle affects the mass-radius relations is also discussed in a separate section. A dynamic and interactive tool to characterize and illustrate the interior structure of exoplanets built upon Models in this paper is available on the website: this http URL
Sara Checa - One of the best experts on this subject based on the ideXlab platform.
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Data_Sheet_2_Computational Modeling to Quantify the Contributions of VEGFR1, VEGFR2, and Lateral Inhibition in Sprouting Angiogenesis.ZIP
2019Co-Authors: Clemens Kühn, Sara ChecaAbstract:Sprouting angiogenesis is a necessary process in regeneration and development as well as in tumorigenesis. VEGF-A is the main pro-angiogenic chemoattractant and it can bind to the decoy receptor VEGFR1 or to VEGFR2 to induce sprouting. Active sprout cells express Dll4, which binds to Notch1 on neighboring cells, in turn inhibiting VEGFR2 expression. It is known that the balance between VEGFR2 and VEGFR1 determines tip selection and network architecture, however the quantitative interrelationship of the receptors and their interrelated balances, also with relation to Dll4-Notch1 signaling, remains yet largely unknown. Here, we present an agent-based computer Model of sprouting angiogenesis, integrating VEGFR1 and VEGFR2 in a Detailed Model of cellular signaling. Our Model reproduces experimental data on VEGFR1 knockout. We show that soluble VEGFR1 improves the efficiency of angiogenesis by directing sprouts away from existing cells over a wide range of parameters. Our analysis unravels the relevance of the stability of the active notch intracellular domain as a dominating hub in this regulatory network. Our analysis quantitatively dissects the regulatory interactions in sprouting angiogenesis. Because we use a Detailed Model of intracellular signaling, the results of our analysis are directly linked to biological entities. We provide our computational Model and simulation engine for integration in complementary Modeling approaches.
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Computational Modeling to Quantify the Contributions of VEGFR1, VEGFR2, and Lateral Inhibition in Sprouting Angiogenesis
2019Co-Authors: Clemens Kühn, Sara ChecaAbstract:Sprouting angiogenesis is a necessary process in regeneration and development as well as in tumorigenesis. VEGF-A is the main pro-angiogenic chemoattractant and it can bind to the decoy receptor VEGFR1 or to VEGFR2 to induce sprouting. Active sprout cells express Dll4, which binds to Notch1 on neighboring cells, in turn inhibiting VEGFR2 expression. It is known that the balance between VEGFR2 and VEGFR1 determines tip selection and network architecture, however the quantitative interrelationship of the receptors and their interrelated balances, also with relation to Dll4-Notch1 signaling, remains yet largely unknown. Here, we present an agent-based computer Model of sprouting angiogenesis, integrating VEGFR1 and VEGFR2 in a Detailed Model of cellular signaling. Our Model reproduces experimental data on VEGFR1 knockout. We show that soluble VEGFR1 improves the efficiency of angiogenesis by directing sprouts away from existing cells over a wide range of parameters. Our analysis unravels the relevance of the stability of the active notch intracellular domain as a dominating hub in this regulatory network. Our analysis quantitatively dissects the regulatory interactions in sprouting angiogenesis. Because we use a Detailed Model of intracellular signaling, the results of our analysis are directly linked to biological entities. We provide our computational Model and simulation engine for integration in complementary Modeling approaches
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Video_6_Computational Modeling to Quantify the Contributions of VEGFR1, VEGFR2, and Lateral Inhibition in Sprouting Angiogenesis.MP4
2019Co-Authors: Clemens Kühn, Sara ChecaAbstract:Sprouting angiogenesis is a necessary process in regeneration and development as well as in tumorigenesis. VEGF-A is the main pro-angiogenic chemoattractant and it can bind to the decoy receptor VEGFR1 or to VEGFR2 to induce sprouting. Active sprout cells express Dll4, which binds to Notch1 on neighboring cells, in turn inhibiting VEGFR2 expression. It is known that the balance between VEGFR2 and VEGFR1 determines tip selection and network architecture, however the quantitative interrelationship of the receptors and their interrelated balances, also with relation to Dll4-Notch1 signaling, remains yet largely unknown. Here, we present an agent-based computer Model of sprouting angiogenesis, integrating VEGFR1 and VEGFR2 in a Detailed Model of cellular signaling. Our Model reproduces experimental data on VEGFR1 knockout. We show that soluble VEGFR1 improves the efficiency of angiogenesis by directing sprouts away from existing cells over a wide range of parameters. Our analysis unravels the relevance of the stability of the active notch intracellular domain as a dominating hub in this regulatory network. Our analysis quantitatively dissects the regulatory interactions in sprouting angiogenesis. Because we use a Detailed Model of intracellular signaling, the results of our analysis are directly linked to biological entities. We provide our computational Model and simulation engine for integration in complementary Modeling approaches.
Christof Koch - One of the best experts on this subject based on the ideXlab platform.
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a biophysically Detailed Model of neocortical local field potentials predicts the critical role of active membrane currents
2013Co-Authors: Michael W Reimann, Christof Koch, Costas A Anastassiou, Rodrigo Perin, Sean Hill, Henry MarkramAbstract:Brain activity generates extracellular voltage fluctuations recorded as local field potentials (LFPs). It is known that the relevant microvariables, the ionic currents across membranes, jointly generate the macrovariables, the extracellular voltage, but neither the Detailed biophysical knowledge nor the required computational power have been available to Model these processes. We simulated the LFP in a Model of the rodent neocortical column composed of >12,000 reconstructed, multicompartmental, and spiking cortical layer 4 and 5 pyramidal neurons and basket cells, including five million dendritic and somatic compartments with voltage- and ion-dependent currents, realistic connectivity, and probabilistic AMPA, NMDA, and GABA synapses. We found that, depending on a number of factors, the LFP reflects local and cross-layer processing. Active currents dominate the generation of LFPs, not synaptic ones. Spike-related currents impact the LFP not only at higher frequencies but below 50 Hz. This work calls for re-evaluating the genesis of LFPs.
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a Detailed Model of the primary visual pathway in the cat comparison of afferent excitatory and intracortical inhibitory connection schemes for orientation selectivity
1991Co-Authors: Florentin Worgotter, Christof KochAbstract:In order to arrive at a quantitative understanding of the dynamics of cortical neuronal networks, we simulated a Detailed Model of the primary visual pathway of the adult cat. This computer Model comprises a 5 degrees x 5 degrees patch of the visual field at a retinal eccentricity of 4.5 degrees and includes 2048 ON- and OFF-center retinal beta-ganglion cells, 8192 geniculate X-cells, and 4096 simple cells in layer IV in area 17. The neurons are implemented as improved integrate-and-fire units. Cortical receptive fields are determined by the pattern of afferent convergence and by inhibitory intracortical connections. Orientation columns are implemented continuously with a realistic receptive field scatter and jitter in the preferred orientations. We first show that realistic ON-OFF-responses, orientation selectivity, velocity low-pass behaviour, null response, and responses to spot stimuli can be obtained with an appropriate alignment of geniculate neurons converging onto the cortical simple cell (Hubel and Wiesel, 1962) and in the absence of intracortical connections. However, the average receptive field elongation (length to width) required to obtain realistic orientation tuning is 4.0, much higher than the average observed elongation. This strongly argues for additional intracortical mechanisms sharpening orientation selectivity. In the second stage, we simulated five different inhibitory intracortical connection patterns (random, local, sparse-local, circular, and cross-orientation) in order to investigate the connection specificity necessary to achieve orientation tuning. Inhibitory connection schemes were superimposed onto Hubel and Wiesel-type receptive fields with an elongation of 1.78. Cross-orientation inhibition gave rise to different horizontal and vertical orientation tuning curves, something not observed experimentally. A combination of two inhibitory schemes, local and circular inhibition (a weak form of cross-orientation inhibition), is in good agreement with observed receptive field properties. The specificity required to establish these connections during development is low. We propose that orientation selectivity is caused by at least three different mechanisms (“eclectic” Model): a weak afferent geniculate bias, broadly tuned cross-orientation inhibition, and some iso-orientation inhibition. The most surprising finding is that an isotropic connection scheme, circular inhibition, in which a cell inhibits all of its postsynaptic target cells at a distance of approximately 500 microns, enhances orientation tuning and leads to a significant directional bias. This is caused by the embedding of cortical cells within a columnar structure and does not depend on our specific assumptions.
Javier Lafuente - One of the best experts on this subject based on the ideXlab platform.
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a Detailed Model of a biofilter for ammonia removal Model parameters analysis and Model validation
2005Co-Authors: Guillermo Baquerizo, Juan P Maestre, Takeyuki Sakuma, Marc A Deshusses, Xavier Gamisans, David Gabriel, Javier LafuenteAbstract:A dynamic Model to describe ammonia removal in a gas-phase biofilter was developed. The mathematical Model is based on discretized mass balances and Detailed nitrification kinetics that include inhibitory effects caused by free ammonia (FA) and free nitrous acid (FNA). The Model has been able to predict experimental results for dynamic operation under different loading rates (from 3.2 to 17.2 g NH 3 h −1 m −3 ). In particular the Model was capable of predicting the outlet ammonia gas concentrations as well as reproducing satisfactorily the gaseous ammonia concentration profile with time under FA inhibition and under non-inhibitory conditions. A sensitivity analysis showed that pH strongly influences the results of the Model. © 2005 Elsevier B.V. All rights reserved.