Multi-agent Simulation of Bilateral Contracting in Competitive Electricity Markets

Traditional vertically integrated power utilities around the world have evolved from monopoly structures to open markets that promote competition among suppliers and provide consumers with a choice of services. Market forces drive the price of electricity and reduce the net cost through increased competition. Electricity can be traded in both organized markets or using forward bilateral contracts. This article focuses on bilateral contracts and describes some important features of an agent-based system for bilateral trading in competitive markets. Special attention is devoted to the negotiation process, demand response in bilateral contracting, and risk management. The article also presents a case study on forward bilateral contracting: a retailer agent and a customer agent negotiate a 24h-rate tariff.

Hybrid systems biology: application to Escherichia coli

Dissertation presented to obtain a Master degree in Biotechnology

Mesenchymal Stem Cell Therapy in Heart Disease

Cardiovascular disease is among the main causes of mortality and morbidity worldwide. Despite significant advances in medical and interventional therapy, the prognosis of conditions such as ischemic heart disease is still dismal. There is thus a need to investigate new therapeutic tools, one of which is stem cell therapy. Hematopoietic stem cells are the most studied type, and the fact that their biology is relatively well understood has led to their being used in preclinical research and clinical trials. However, the results of some of these studies have been controversial, which has opened the way for studies on other cell types, such as mesenchymal stem cells. These cells have immunomodulatory properties which suggest that they have therapeutic potential in cardiology. In the present article, the authors review the state of the art regarding mesenchymal stem cells, from basic and translational research to their use in clinical trials on ischemic heart disease, heart failure and arrhythmias, and discuss possible future uses.

Integration of a mobile autonomous robot in a surveillance multi-agent system

This dissertation aims to guarantee the integration of a mobile autonomous robot equipped with many sensors in a multi-agent distributed and georeferenced surveillance system. The integration of a mobile autonomous robot in this system leads to new features that will be available to clients of surveillance system may use. These features may be of two types: using the robot as an agent that will act in the environment or by using the robot as a mobile set of sensors. As an agent in the system, the robot can move to certain locations when alerts are received, in order to acknowledge the underlying events or take to action in order to assist in resolving this event. As a sensor platform in the system, it is possible to access information that is read from the sensors of the robot and access complementary measurements to the ones taken by other sensors in the multi-agent system. To integrate this mobile robot in an effective way it is necessary to extend the current multi-agent system architecture to make the connection between the two systems and to integrate the functionalities provided by the robot into the multi-agent system.

Development of process control strategies exploiting knowledge from systems biology: application to MDCK suspension cells

Madine Darby Canine Kidney (MDCK) cell lines have been extensively evaluated for their potential as host cells for influenza vaccine production. Recent studies allowed the cultivation of these cells in a fully defined medium and in suspension. However, reaching high cell densities in animal cell cultures still remains a challenge. To address this shortcoming, a combined methodology allied with knowledge from systems biology was reported to study the impact of the cell environment on the flux distribution. An optimization of the medium composition was proposed for both a batch and a continuous system in order to reach higher cell densities. To obtain insight into the metabolic activity of these cells, a detailed metabolic model previously developed by Wahl A. et. al was used. The experimental data of four cultivations of MDCK suspension cells, grown under different conditions and used in this work came from the Max Planck Institute, Magdeburg, Germany. Classical metabolic flux analysis (MFA) was used to estimate the intracellular flux distribution of each cultivation and then combined with partial least squares (PLS) method to establish a link between the estimated metabolic state and the cell environment. The validation of the MFA model was made and its consistency checked. The resulted PLS model explained almost 70% of the variance present in the flux distribution. The medium optimization for the continuous system and for the batch system resulted in higher biomass growth rates than the ones obtained experimentally, 0.034 h-1 and 0.030 h-1, respectively, thus reducing in almost 10 hours the duplication time. Additionally, the optimal medium obtained for the continuous system almost did not consider pyruvate. Overall the proposed methodology seems to be effective and both proposed medium optimizations seem to be promising to reach high cell densities.

Systems biology approaches for the design of novel Saccharomyces cerevisiae winemaking strains for enhanced flavour compounds synthesis

Tese de Doutoramento em Biologia Ambiental e Molecular

Stem cell transplantation in brain tumors: a new field for molecular imaging?

Neural stem cells have been proposed as a new and promising treatment modality in various pathologies of the central nervous system, including malignant brain tumors. However, the underlying mechanism by which neural stem cells target tumor areas remains elusive. Monitoring of these cells is currently done by use of various modes of molecular imaging, such as optical imaging, magnetic resonance imaging and positron emission tomography, which is a novel technology for visualizing metabolism and signal transduction to gene expression. In this new context, the microenvironment of (malignant) brain tumors and the blood-brain barrier gains increased interest. The authors of this review give a unique overview of the current molecular-imaging techniques used in different therapeutic experimental brain tumor models in relation to neural stem cells. Such methods for molecular imaging of gene-engineered neural stem/progenitor cells are currently used to trace the location and temporal level of expression of therapeutic and endogenous genes in malignant brain tumors, closing the gap between in vitro and in vivo integrative biology of disease in neural stem cell transplantation.

Artificial Snow Optimization in Winter Sport Destinations Using a Multi-agent Simulation

This paper presents the Juste-Neige system for predicting the snow height on the ski runs of a resort using a multi-agent simulation software. Its aim is to facilitate snow cover management in order to i) reduce the production cost of artificial snow and to improve the profit margin for the companies managing the ski resorts; and ii) to reduce the water and energy consumption, and thus to reduce the environmental impact, by producing only the snow needed for a good skiing experience. The software provides maps with the predicted snow heights for up to 13 days. On these maps, the areas most exposed to snow erosion are highlighted. The software proceeds in three steps: i) interpolation of snow height measurements with a neural network; ii) local meteorological forecasts for every ski resort; iii) simulation of the impact caused by skiers using a multi-agent system. The software has been evaluated in the Swiss ski resort of Verbier and provides useful predictions.

Plerixafor and granulocyte colony-stimulating factor for first-line steady-state autologous peripheral blood stem cell mobilization in lymphoma and multiple myeloma: results of the prospective PREDICT trial.

In Europe, the combination of plerixafor + granulocyte colony-stimulating factor is approved for the mobilization of hematopoietic stem cells for autologous transplantation in patients with lymphoma and myeloma whose cells mobilize poorly. The purpose of this study was to further assess the safety and efficacy of plerixafor + granulocyte colony-stimulating factor for front-line mobilization in European patients with lymphoma or myeloma. In this multicenter, open label, single-arm study, patients received granulocyte colony-stimulating factor (10 μg/kg/day) subcutaneously for 4 days; on the evening of day 4 they were given plerixafor (0.24 mg/kg) subcutaneously. Patients underwent apheresis on day 5 after a morning dose of granulocyte colony-stimulating factor. The primary study objective was to confirm the safety of mobilization with plerixafor. Secondary objectives included assessment of efficacy (apheresis yield, time to engraftment). The combination of plerixafor + granulocyte colony-stimulating factor was used to mobilize hematopoietic stem cells in 118 patients (90 with myeloma, 25 with non-Hodgkin's lymphoma, 3 with Hodgkin's disease). Treatment-emergent plerixafor-related adverse events were reported in 24 patients. Most adverse events occurred within 1 hour after injection, were grade 1 or 2 in severity and included gastrointestinal disorders or injection-site reactions. The minimum cell yield (≥ 2 × 10(6) CD34(+) cells/kg) was harvested in 98% of patients with myeloma and in 80% of those with non-Hodgkin's lymphoma in a median of one apheresis. The optimum cell dose (≥ 5 × 10(6) CD34(+) cells/kg for non-Hodgkin's lymphoma or ≥ 6 × 10(6) CD34(+) cells/kg for myeloma) was harvested in 89% of myeloma patients and 48% of non-Hodgkin's lymphoma patients. In this prospective, multicenter European study, mobilization with plerixafor + granulocyte colony-stimulating factor allowed the majority of patients with myeloma or non-Hodgkin's lymphoma to undergo transplantation with minimal toxicity, providing further data supporting the safety and efficacy of plerixafor + granulocyte colony-stimulating factor for front-line mobilization of hematopoietic stem cells in patients with non-Hodgkin's lymphoma or myeloma.

Colorectal Cancer Classification and Cell Heterogeneity: A Systems Oncology Approach.

Colorectal cancer is a heterogeneous disease that manifests through diverse clinical scenarios. During many years, our knowledge about the variability of colorectal tumors was limited to the histopathological analysis from which generic classifications associated with different clinical expectations are derived. However, currently we are beginning to understand that under the intense pathological and clinical variability of these tumors there underlies strong genetic and biological heterogeneity. Thus, with the increasing available information of inter-tumor and intra-tumor heterogeneity, the classical pathological approach is being displaced in favor of novel molecular classifications. In the present article, we summarize the most relevant proposals of molecular classifications obtained from the analysis of colorectal tumors using powerful high throughput techniques and devices. We also discuss the role that cancer systems biology may play in the integration and interpretation of the high amount of data generated and the challenges to be addressed in the future development of precision oncology. In addition, we review the current state of implementation of these novel tools in the pathological laboratory and in clinical practice.

Generation of cardiomyocytes from new human embrionic stem cell lines derived from poor-quanlity blastocysts

Human embryonic stem (hES) cells represent a potential source for cell replacement therapy of many degenerative diseases. Most frequently, hES cell lines are derived from surplus embryos from assisted reproduction cycles, independent of their quality or morphology. Here, we show that hES cell lines can be obtained from poor-quality blastocysts with the same efficiency as that obtained from good- or intermediate-quality blastocysts. Furthermore, we show that the self-renewal, pluripotency, and differentiation ability of hES cell lines derived from either source are comparable. Finally, we present a simple and reproducible embryoid body-based protocol for the differentiation of hES cells into functional cardiomyocytes. The five new hES cell lines derived here should widen the spectrum of available resources for investigating the biology of hES cells and advancing toward efficient strategies of regenerative medicine.

Towards robust network based complex systems : from evolutionary cellular automata to biological models

Abstract Sitting between your past and your future doesn't mean you are in the present. Dakota Skye Complex systems science is an interdisciplinary field grouping under the same umbrella dynamical phenomena from social, natural or mathematical sciences. The emergence of a higher order organization or behavior, transcending that expected of the linear addition of the parts, is a key factor shared by all these systems. Most complex systems can be modeled as networks that represent the interactions amongst the system's components. In addition to the actual nature of the part's interactions, the intrinsic topological structure of underlying network is believed to play a crucial role in the remarkable emergent behaviors exhibited by the systems. Moreover, the topology is also a key a factor to explain the extraordinary flexibility and resilience to perturbations when applied to transmission and diffusion phenomena. In this work, we study the effect of different network structures on the performance and on the fault tolerance of systems in two different contexts. In the first part, we study cellular automata, which are a simple paradigm for distributed computation. Cellular automata are made of basic Boolean computational units, the cells; relying on simple rules and information from- the surrounding cells to perform a global task. The limited visibility of the cells can be modeled as a network, where interactions amongst cells are governed by an underlying structure, usually a regular one. In order to increase the performance of cellular automata, we chose to change its topology. We applied computational principles inspired by Darwinian evolution, called evolutionary algorithms, to alter the system's topological structure starting from either a regular or a random one. The outcome is remarkable, as the resulting topologies find themselves sharing properties of both regular and random network, and display similitudes Watts-Strogtz's small-world network found in social systems. Moreover, the performance and tolerance to probabilistic faults of our small-world like cellular automata surpasses that of regular ones. In the second part, we use the context of biological genetic regulatory networks and, in particular, Kauffman's random Boolean networks model. In some ways, this model is close to cellular automata, although is not expected to perform any task. Instead, it simulates the time-evolution of genetic regulation within living organisms under strict conditions. The original model, though very attractive by it's simplicity, suffered from important shortcomings unveiled by the recent advances in genetics and biology. We propose to use these new discoveries to improve the original model. Firstly, we have used artificial topologies believed to be closer to that of gene regulatory networks. We have also studied actual biological organisms, and used parts of their genetic regulatory networks in our models. Secondly, we have addressed the improbable full synchronicity of the event taking place on. Boolean networks and proposed a more biologically plausible cascading scheme. Finally, we tackled the actual Boolean functions of the model, i.e. the specifics of how genes activate according to the activity of upstream genes, and presented a new update function that takes into account the actual promoting and repressing effects of one gene on another. Our improved models demonstrate the expected, biologically sound, behavior of previous GRN model, yet with superior resistance to perturbations. We believe they are one step closer to the biological reality.

A dynamic model for stem cell homeostasis and patterning in Arabidopsis meristems.

Plants maintain stem cells in their meristems as a source for new undifferentiated cells throughout their life. Meristems are small groups of cells that provide the microenvironment that allows stem cells to prosper. Homeostasis of a stem cell domain within a growing meristem is achieved by signalling between stem cells and surrounding cells. We have here simulated the origin and maintenance of a defined stem cell domain at the tip of Arabidopsis shoot meristems, based on the assumption that meristems are self-organizing systems. The model comprises two coupled feedback regulated genetic systems that control stem cell behaviour. Using a minimal set of spatial parameters, the mathematical model allows to predict the generation, shape and size of the stem cell domain, and the underlying organizing centre. We use the model to explore the parameter space that allows stem cell maintenance, and to simulate the consequences of mutations, gene misexpression and cell ablations.

Estimating dormant and active hematopoietic stem cell kinetics through extensive modeling of bromodeoxyuridine label-retaining cell dynamics.

Bone marrow hematopoietic stem cells (HSCs) are responsible for both lifelong daily maintenance of all blood cells and for repair after cell loss. Until recently the cellular mechanisms by which HSCs accomplish these two very different tasks remained an open question. Biological evidence has now been found for the existence of two related mouse HSC populations. First, a dormant HSC (d-HSC) population which harbors the highest self-renewal potential of all blood cells but is only induced into active self-renewal in response to hematopoietic stress. And second, an active HSC (a-HSC) subset that by and large produces the progenitors and mature cells required for maintenance of day-to-day hematopoiesis. Here we present computational analyses further supporting the d-HSC concept through extensive modeling of experimental DNA label-retaining cell (LRC) data. Our conclusion that the presence of a slowly dividing subpopulation of HSCs is the most likely explanation (amongst the various possible causes including stochastic cellular variation) of the observed long term Bromodeoxyuridine (BrdU) retention, is confirmed by the deterministic and stochastic models presented here. Moreover, modeling both HSC BrdU uptake and dilution in three stages and careful treatment of the BrdU detection sensitivity permitted improved estimates of HSC turnover rates. This analysis predicts that d-HSCs cycle about once every 149-193 days and a-HSCs about once every 28-36 days. We further predict that, using LRC assays, a 75%-92.5% purification of d-HSCs can be achieved after 59-130 days of chase. Interestingly, the d-HSC proportion is now estimated to be around 30-45% of total HSCs - more than twice that of our previous estimate.

Stem cell-related "self-renewal" signature and high epidermal growth factor receptor expression associated with resistance to concomitant chemoradiotherapy in glioblastoma.

PURPOSE: Glioblastomas are notorious for resistance to therapy, which has been attributed to DNA-repair proficiency, a multitude of deregulated molecular pathways, and, more recently, to the particular biologic behavior of tumor stem-like cells. Here, we aimed to identify molecular profiles specific for treatment resistance to the current standard of care of concomitant chemoradiotherapy with the alkylating agent temozolomide. PATIENTS AND METHODS: Gene expression profiles of 80 glioblastomas were interrogated for associations with resistance to therapy. Patients were treated within clinical trials testing the addition of concomitant and adjuvant temozolomide to radiotherapy. RESULTS: An expression signature dominated by HOX genes, which comprises Prominin-1 (CD133), emerged as a predictor for poor survival in patients treated with concomitant chemoradiotherapy (n = 42; hazard ratio = 2.69; 95% CI, 1.38 to 5.26; P = .004). This association could be validated in an independent data set. Provocatively, the HOX cluster was reminiscent of a "self-renewal" signature (P = .008; Gene Set Enrichment Analysis) recently characterized in a mouse leukemia model. The HOX signature and EGFR expression were independent prognostic factors in multivariate analysis, adjusted for the O-6-methylguanine-DNA methyltransferase (MGMT) methylation status, a known predictive factor for benefit from temozolomide, and age. Better outcome was associated with gene clusters characterizing features of tumor-host interaction including tumor vascularization and cell adhesion, and innate immune response. CONCLUSION: This study provides first clinical evidence for the implication of a "glioma stem cell" or "self-renewal" phenotype in treatment resistance of glioblastoma. Biologic mechanisms identified here to be relevant for resistance will guide future targeted therapies and respective marker development for individualized treatment and patient selection.