Elucidating the role of mesenchymal stem cell participation in the tumor microenvironment

To meet the requirements for rapid tumor growth, a complex array of non-neoplastic vascular, fibroblastic, and immune cells are recruited to the tumor microenvironment. Understanding the origin, composition, and mechanism(s) for recruitment of these stromal components will help identify areas for therapeutic intervention. Previous findings have suggested that ex-vivo expanded bone marrow-derived MSC home to the sites of tumor development, responding to inflammatory signals and can serve as effective drug delivery vehicles. Therefore, we first sought to fully assess conditions under which MSC migrate to and incorporate into inflammatory microenvironments and the consequences of modulated inflammation. MSC delivered to animals bearing inflammatory insults were monitored by bioluminescence imaging and displayed specific tropism and selective incorporation into all tumor and wound sites. These findings were consistent across routes of tumor establishment, MSC administration, and immunocompetence. MSC were then used as drug delivery vehicles, transporting Interferon β to sites of pancreatic tumors. This therapy was effective at inhibiting pancreatic tumor growth under homeostatic conditions, but inhibition was lost when inflammation was decreased with CDDO-Me combination treatment. Next, to examine the endogenous tumor microenvironment, a series of tissue transplant experiments were carried out in which tissues were genetically labeled and engrafted in recipients prior to tumor establishment. Tumors were then analyzed for markers of tumor associated fibroblasts (TAF): α-smooth muscle actin (α-SMA), nerve glia antigen 2 (NG2), fibroblast activation protein (FAP), and fibroblast specific protein (FSP) as well as endothelial marker CD31 and macrophage marker F4/80. We determined the majority of α-SMA+, NG2+ and CD31+ cells were non-bone marrow derived, while most FAP+, FSP+, and F4/80+ cells were recruited from the bone marrow. In accord, transplants of prospectively isolated BM MSC prior to tumor development indicated that these cells were recruited to the tumor microenvironment and co-expressed FAP and FSP. In contrast, fat transplant experiments revealed recruited fat derived cells co-expressed α-SMA, NG2, and CD31. These results indicate TAF are a heterogeneous population composed of subpopulations with distinct tissues of origin. These models have provided a platform upon which further investigation into tumor microenvironment composition and tests for candidate drugs can be performed. ^

Behaviour Driven Development for Multi-Agent Systems

This paper presents a testing methodology to apply Behaviour Driven Development (BDD) techniques while developing Multi-Agent Systems (MAS), so called BEhavioural Agent Simple Testing (BEAST) methodology. It is supported by the developed open source framework (BEAST Tool) which automatically generates test cases skeletons from BDD scenarios specifications. The developed framework allows testing MASs based on JADE or JADEX platforms and offers a set of configurable Mock Agents which allow the execution of tests while the system is under development. BEAST tool has been validated in the development of a MAS for fault diagnosis in FTTH (Fiber To The Home) networks.

Cooperative Learning Model based on Multi-Agent Architecture for Embedded Intelligent Systems

Cooperative systems are suitable for many types of applications and nowadays these system are vastly used to improve a previously defined system or to coordinate multiple devices working together. This paper provides an alternative to improve the reliability of a previous intelligent identification system. The proposed approach implements a cooperative model based on multi-agent architecture. This new system is composed of several radar-based systems which identify a detected object and transmit its own partial result by implementing several agents and by using a wireless network to transfer data. The proposed topology is a centralized architecture where the coordinator device is in charge of providing the final identification result depending on the group behavior. In order to find the final outcome, three different mechanisms are introduced. The simplest one is based on majority voting whereas the others use two different weighting voting procedures, both providing the system with learning capabilities. Using an appropriate network configuration, the success rate can be improved from the initial 80% up to more than 90%.

GERp95, a Membrane-associated Protein that Belongs to a Family of Proteins Involved in Stem Cell Differentiation

A panel of mAbs was elicited against intracellular membrane fractions from rat pancreas. One of the antibodies reacted with a 95-kDa protein that localizes primarily to the Golgi complex or the endoplasmic reticulum (ER), depending on cell type. The corresponding cDNA was cloned and sequenced and found to encode a protein of 97.6 kDa that we call GERp95 (Golgi ER protein 95 kDa). The protein copurifies with intracellular membranes but does not contain hydrophobic regions that could function as signal peptides or transmembrane domains. Biochemical analysis suggests that GERp95 is a cytoplasmically exposed peripheral membrane protein that exists in a protease-resistant complex. GERp95 belongs to a family of highly conserved proteins in metazoans and Schizosaccharomyces pombe. It has recently been determined that plant and Drosophila homologues of GERp95 are important for controlling the differentiation of stem cells (Bohmert et al., 1998; Cox et al., 1998; Moussian et al., 1998). In Caenorhabditis elegans, there are at least 20 members of this protein family. To this end, we have used RNA interference to show that the GERp95 orthologue in C. elegans is important for maturation of germ-line stem cells in the gonad. GERp95 and related proteins are an emerging new family of proteins that have important roles in metazoan development. The present study suggests that these proteins may exert their effects on cell differentiation from the level of intracellular membranes.

Increasing DNA repair methyltransferase levels via bone marrow stem cell transduction rescues mice from the toxic effects of 1,3-bis(2-chloroethyl)-1-nitrosourea, a chemotherapeutic alkylating agent.

The chloroethylnitrosourea (CNU) alkylating agents are commonly used for cancer chemotherapy, but their usefulness is limited by severe bone marrow toxicity that causes the cumulative depletion of all hematopoietic lineages (pancytopenia). Bone marrow CNU sensitivity is probably due to the inefficient repair of CNU-induced DNA damage; relative to other tissues, bone marrow cells express extremely low levels of the O6-methylguanine DNA methyltransferase (MGMT) protein that repairs cytotoxic O6-chloroethylguanine DNA lesions. Using a simplified recombinant retroviral vector expressing the human MGMT gene under control of the phosphoglycerate kinase promoter (PGK-MGMT) we increased the capacity of murine bone marrow-derived cells to repair CNU-induced DNA damage. Stable reconstitution of mouse bone marrow with genetically modified, MGMT-expressing hematopoietic stem cells conferred considerable resistance to the cytotoxic effects of 1,3-bis(2-chloroethyl)-1-nitrosourea (BCNU), a CNU commonly used for chemotherapy. Bone marrow harvested from mice transplanted with PGK-MGMT-transduced cells showed extensive in vitro BCNU resistance. Moreover, MGMT expression in mouse bone marrow conferred in vivo resistance to BCNU-induced pancytopenia and significantly reduced BCNU-induced mortality due to bone marrow hypoplasia. These data demonstrate that increased DNA alkylation repair in primitive hematopoietic stem cells confers multilineage protection from the myelosuppressive effects of BCNU and suggest a possible approach to protecting cancer patients from CNU chemotherapy-related toxicity.

Robotic control systems based on bioinspired multi-agent systems: application of the principles of neuroscience to robotics

Robotics is a field that presents a large number of problems because it depends on a large number of disciplines, devices, technologies and tasks. Its expansion from perfectly controlled industrial environments toward open and dynamic environment presents a many new challenges, such as robots household robots or professional robots. To facilitate the rapid development of robotic systems, low cost, reusability of code, its medium and long term maintainability and robustness are required novel approaches to provide generic models and software systems who develop paradigms capable of solving these problems. For this purpose, in this paper we propose a model based on multi-agent systems inspired by the human nervous system able to transfer the control characteristics of the biological system and able to take advantage of the best properties of distributed software systems.

Stability of multi-agent systems

This work attempts to shed light to the fundamental concepts behind the stability of Multi-Agent Systems. We view the system as a discrete time Markov chain with a potentially unknown transitional probability distribution. The system will be considered to be stable when its state has converged to an equilibrium distribution. Faced with the non-trivial task of establishing the convergence to such a distribution, we propose a hypothesis testing approach according to which we test whether the convergence of a particular system metric has occurred. We describe some artificial multi-agent ecosystems that were developed and we present results based on these systems which confirm that this approach qualitatively agrees with our intuition.

Education Complex "Multi-agent Technologies for Parallel and Distributed Information Processing in Telecommunication Networks"

The paper describes education complex "Multi-agent Technologies for Parallel and Distributed Information Processing in Telecommunication Networks".

Formalization of Interaction Events in Multi-agent Systems

The problem of the description of interaction between spatially divided agents in the form of dialogues is explored. The concept of processes synchronization is analyzed to formalize the specification of interaction at the level of events constituting the processes. The approach to formalization of the description of conditions of synchronization when both the independent behavior and the communications of agents can be presented at a logic level is offered. It is shown, that the collective behavior of agents can be specified by the synthetic temporal logic that unites linear and branching time temporal logics.

A Multi-agent Framework for Distributed Decision-making Systems

An approach of building distributed decision support systems is proposed. There is defined a framework of a distributed DSS and examined questions of problem formulation and solving using artificial intellectual agents in system core.

Multi-agent Systems in the Harvest Prognosis

The paper presents a case study of geo-monitoring a region consisting in the capturing and encoding of human expertise into a knowledge-based system. As soon as the maps have been processed, the data patterns are detected using knowledge-based agents for the harvest prognosis.

Adaptive Control and Multi-agent Interface for Infotelecommunication Systems of New Generation

Problems for intellectualisation for man-machine interface and methods of self-organization for network control in multi-agent infotelecommunication systems have been discussed. Architecture and principles for construction of network and neural agents for telecommunication systems of new generation have been suggested. Methods for adaptive and multi-agent routing for information flows by requests of external agents- users of global telecommunication systems and computer networks have been described.

Stem cell-derived astrocytes:are they physiologically credible?

Astrocytes are now increasingly acknowledged as having fundamental and sophisticated roles in brain function and dysfunction. Unravelling the complex mechanisms that underlie human brain astrocyte-neuron interactions is therefore an essential step on the way to understanding how the brain operates. Insights into astrocyte function to date, have almost exclusively been derived from studies conducted using murine or rodent models. Whilst these have led to significant discoveries, preliminary work with human astrocytes has revealed a hitherto unknown range of astrocyte types with potentially greater functional complexity and increased neuronal interaction with respect to animal astrocytes. It is becoming apparent, therefore, that many important functions of astrocytes will only be discovered by direct physiological interrogation of human astrocytes. Recent advancements in the field of stem cell biology have provided a source of human based models. These will provide a platform to facilitate our understanding of normal astrocyte functions as well as their role in CNS pathology. A number of recent studies have demonstrated that stem cell derived astrocytes exhibit a range of properties, suggesting that they may be functionally equivalent to their in vivo counterparts. Further validation against in vivo models will ultimately confirm the future utility of these stem-cell based approaches in fulfilling the need for human- based cellular models for basic and clinical research. In this review we discuss the roles of astrocytes in the brain and highlight the extent to which human stem cell derived astrocytes have demonstrated functional activities that are equivalent to that observed in vivo.