Yuri Mansury

Simulating the impact of a molecular 'decision-process' on cellular phenotype and multicellular patterns in brain tumors

Experimental evidence indicates that human brain cancer cells proliferate or migrate, yet do not display both phenotypes at the same time. Here, we present a novel computational model simulating this cellular decision-process leading up to either phenotype based on a molecular interaction network of genes and proteins. The models regulatory network consists of the epidermal growth factor receptor (EGFR), its ligand transforming growth factor-alpha (TGF alpha), the downstream enzyme phospholipaseC-gamma (PLC gamma) and a mitosis-associated response pathway. This network is activated by autocrine TGF alpha secretion, and the EGFR-dependent downstream signaling this step triggers, as well as modulated by an extrinsic nutritive glucose gradient. Employing a framework of mass action kinetics within a multiscale agent-based environment, we analyse both the emergent multicellular behavior of tumor growth and the single-cell molecular profiles that change over time and space. Our results show that one can indeed simulate the dichotomy between cell migration and proliferation based solely on an EGFR decision network. It turns out that these behavioral decisions on the single cell level impact the spatial dynamics of the entire cancerous system. Furthermore, the simulation results yield intriguing experimentally testable hypotheses also on the sub-cellular level such as spatial cytosolic polarization of PLC gamma towards an extrinsic chemotactic gradient. Implications of these results for future works, both on the modeling and experimental side are discussed.

Growth model for multicellular tumor spheroids

Most organisms grow according to simple laws, which in principle can be derived from energy conservation and scaling arguments, critically dependent on the relation between the metabolic rate B of energy flow and the organism mass m. Although this relation is generally recognized to be of the form B(m)=mp, the specific value of the exponent p is the object of an ongoing debate, with many mechanisms being postulated to support different predictions. We propose that multicellular tumor spheroids provide an ideal experimental model system for testing these allometric growth theories, especially under controlled conditions of malnourishment and applied mechanical stress.

Simulating the time series of a selected gene expression profile in an agent-based tumor model

Abstract To elucidate the role of environmental conditions in molecular-level dynamics and to study their impact on macroscopic brain tumor growth patterns, the expression of the genes Tenascin C and PCNA in a 2D agent-based model for the migratory trait is calibrated using experimental data from the literature, while the expression of these genes for the proliferative trait is obtained as the model output. Numerical results confirm that the gene expression of Tenascin C is indeed consistently higher in the migratory glioma cell phenotype and show that the expression of PCNA is consistently higher among proliferating tumor cells. Intriguingly, the time series of the tumor cells’ gene expression exhibit a sudden change in behavior during the invasion of the tumor into a nutrient-abundant region, showing a robust positive correlation between the expression of Tenascin C and the tumor’s diameter, yet a strong negative correlation between the expression of PCNA and the diameter. These molecular-level dynamics correspond to the emergence of a structural asymmetry in the form of a bulging tumor rim in the nutrient-abundant region. The simulated time series thus supports the critical role of the migratory cell phenotype during both the tumor system’s overall macroscopic expansion and the evolvement of regional growth patterns, particularly in the later stages. Furthermore, detrended fluctuation analysis (DFA) suggests that for prediction purposes, the simulated gene expression profiles of Tenascin C and PCNA that were determined separately for the migrating and proliferating phenotypes exhibit lesser predictability than those of the phenotypic mixture combining all viable tumor cells typically found in clinical biopsies. Finally, partitioning the tumor into distinct geographic regions of interest (ROI) reveals that the gene expression profile of tumor cells in the quadrant close to the nutrient-abundant region is representative for the entire tumor whereas the expression profile of tumor cells in the geographically opposite ROI is not. Potential implications of these modeling results for experimental and clinical cancer research are discussed.

Measuring Economy-wide Impacts of a Financial Shock

This article analyses the transmission of financial shock to household income distribution using the case of Indonesia. Presumably, those benefiting from currency depreciation and high interest rate during the crisis are the high-income groups. However, the same groups might lose since they were employed in sectors that are highly import-dependent. On the production side, construction was the hardest-hit sector during the crisis, and thus the low-income non-agricultural households were more susceptible due to their heavy reliance on manual work in construction. This sector also proves to be instrumental in transmitting the shock from the credit crunch to the fall in household income. To the extent that a formal social safety net is lacking, an informal system of inter-household network is expected to mitigate the impact on the poor. However, we found that there is no convincing evidence that households acted altruistically to assist their distressed neighbours during the crisis.

Assessing the Economic Impacts of Local Food System Producers by Scale

Policy makers and economic developers are increasingly interested in the impacts of local food systems, yet attempts to obtain accurate estimates are often complicated by a lack of available data. Utilizing a unique data set from producers in New York, the authors examine the extent of differential purchasing and sales patterns for small-scale direct agriculture (SDA) producers. The supplemental data are integrated into a regional input–output model to assess the total effects and distributional implications of equivalent policies targeted to agriculture sectors. The authors demonstrate that SDA producers have different expenditure patterns than other agricultural producers and, for equivalent policy shocks targeted toward agriculture industry expansion, have lower total employment and output impacts but higher effects on labor income and total value added than non-SDA producers. The results underscore the importance of collecting appropriate data for analysis and outline the local economic benefits of small-scale local food system participants.

Impacts of Organic Food Agritourism on a Small Rural Economy: A Social Accounting Matrix Approach

The U.S. organic food market recently experienced a rapid expansion, and yet this industrys potential to promote economic development remains largely unexplored. This paper proposes the introduction of organic-food agritourism as a sustainable development strategy for a distressed rural community. In contrast to conventional impact studies that emphasize final demand shocks, this study examines the impact of higher regional purchase coefficients (RPCs) based on the hypothesis that agritourism promotion will attract nature-oriented tourists inclined to spend more on organic produce. Using a social accounting matrix (SAM) model, we found that a successful campaign to promote organic agriculture not only delivers higher production output, but also generates a more egalitarian distribution of income.

Modeling Tumors as Complex Biosystems: An Agent-Based Approach

We argue that tumors behave as complex dynamic self-organizing and adaptive biosystems. In this chapter, we present a numerical agent-based model of malignant brain tumor cells in which both time and space are discrete yet environmental variables are treated as a continuum. Simulations of this multiscale algorithm allow us to investigate the molecular, microscopic, and multicellular patterns that emerge from various interactions among cells and between the cells and their environments.

Size, connectivity, and tipping in spatial networks: Theory and empirics

Abstract We study the impact of settlement sizes on network connectivity in a spatial setting. First, we develop a model of geometric urban networks that posits a positive relationship between connectivity and size. Empirical evidence is then presented validating the model prediction that local links exhibit super-linear scaling with the exponent greater than 1, while long-range connections scale linearly with the unit exponent. The scaling exponents thus suggest that the impact of population size on connectivity is stronger within cities than between cities. We next combine the geometric framework with a computational model of interacting agents to generate a realistic settlement distribution and urban networks from the bottom-up. Calibrated simulation results demonstrate the consistency between hierarchical rank-size distribution and scale-free connectivity. Finally, coupling the spatial network with a tipping diffusion model allows us to consolidate the evolution of network connectivity, city sizes, and social practices in a unified computational framework.

An Economic Development Road Map for Promoting Israeli-Palestinian Cooperation

In this paper we propose an interregional framework as a policy tool for identifying sectors that can stimulate Palestinian economic development while recognizing the reality of the Israeli-Palestinian economic interdependencies. Specifically, this paper emphasizes the potential role of bi-national trade channels to promote Israeli-Palestinian cooperation. To that end, we apply an interregional input-output model to 14 sectors of the Palestinian and Israeli economies and their trading relationships. We then investigate the impact of an exogenous foreign injection under alternative trade scenarios. The results suggest that foreign aid injections to the Banking and Construction sectors in Palestine make the highest impact on Palestinian output. On the other hand, if the primary objective is to promote employment, then injections should be concentrated on the Community, Social, Personal and Household Services sectors.

Economic Impact of High-Speed Rail on Household Income in China

Although developed only in the past 20 years, Chinese high-speed rail (HSR) has overtaken many of its forerunners in its unprecedented scale. However, such a scale raises questions about its implications for regional economic development. Previous studies have discussed the impact of HSR at the regional and city levels, but few have addressed its impact on the individual level, which is crucial for understanding the distribution of the impact. To fill the gap, this study focused on the economic impact of recent HSR development between 2009 and 2012 on Chinese household income and discussed its significance, magnitude, and distribution. The survey data from the China Family Panel Survey were used and a difference-in-differences approach was implemented. Two key explanatory variables, weighted average travel time and probability of living proximate to HSR stations, were included in the models to examine the direct and spillover impacts of HSR. The study shows that these impacts both contribute to the HSR impact but affect urban and rural regions and production sectors differently. In particular, the spillover effect or the agglomeration effect contributes the most and favors more urbanized regions with stronger service sectors. As a consequence, although HSR plays a positive role in stimulating the regional economy, it may further widen the gap between developed regions and underdeveloped regions. From the analyses, it is concluded that HSR projects need more comprehensive studies of the full spectrum of its impact to ensure both economic growth and regional balance and coordination.