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.

Behavioural queueing : cellular automata and a laboratory experiment

Dans cette thèse, nous étudions les aspects comportementaux d'agents qui interagissent dans des systèmes de files d'attente à l'aide de modèles de simulation et de méthodologies expérimentales. Chaque période les clients doivent choisir un prestataire de servivce. L'objectif est d'analyser l'impact des décisions des clients et des prestataires sur la formation des files d'attente. Dans un premier cas nous considérons des clients ayant un certain degré d'aversion au risque. Sur la base de leur perception de l'attente moyenne et de la variabilité de cette attente, ils forment une estimation de la limite supérieure de l'attente chez chacun des prestataires. Chaque période, ils choisissent le prestataire pour lequel cette estimation est la plus basse. Nos résultats indiquent qu'il n'y a pas de relation monotone entre le degré d'aversion au risque et la performance globale. En effet, une population de clients ayant un degré d'aversion au risque intermédiaire encoure généralement une attente moyenne plus élevée qu'une population d'agents indifférents au risque ou très averses au risque. Ensuite, nous incorporons les décisions des prestataires en leur permettant d'ajuster leur capacité de service sur la base de leur perception de la fréquence moyenne d'arrivées. Les résultats montrent que le comportement des clients et les décisions des prestataires présentent une forte "dépendance au sentier". En outre, nous montrons que les décisions des prestataires font converger l'attente moyenne pondérée vers l'attente de référence du marché. Finalement, une expérience de laboratoire dans laquelle des sujets jouent le rôle de prestataire de service nous a permis de conclure que les délais d'installation et de démantèlement de capacité affectent de manière significative la performance et les décisions des sujets. En particulier, les décisions du prestataire, sont influencées par ses commandes en carnet, sa capacité de service actuellement disponible et les décisions d'ajustement de capacité qu'il a prises, mais pas encore implémentées. - Queuing is a fact of life that we witness daily. We all have had the experience of waiting in line for some reason and we also know that it is an annoying situation. As the adage says "time is money"; this is perhaps the best way of stating what queuing problems mean for customers. Human beings are not very tolerant, but they are even less so when having to wait in line for service. Banks, roads, post offices and restaurants are just some examples where people must wait for service. Studies of queuing phenomena have typically addressed the optimisation of performance measures (e.g. average waiting time, queue length and server utilisation rates) and the analysis of equilibrium solutions. The individual behaviour of the agents involved in queueing systems and their decision making process have received little attention. Although this work has been useful to improve the efficiency of many queueing systems, or to design new processes in social and physical systems, it has only provided us with a limited ability to explain the behaviour observed in many real queues. In this dissertation we differ from this traditional research by analysing how the agents involved in the system make decisions instead of focusing on optimising performance measures or analysing an equilibrium solution. This dissertation builds on and extends the framework proposed by van Ackere and Larsen (2004) and van Ackere et al. (2010). We focus on studying behavioural aspects in queueing systems and incorporate this still underdeveloped framework into the operations management field. In the first chapter of this thesis we provide a general introduction to the area, as well as an overview of the results. In Chapters 2 and 3, we use Cellular Automata (CA) to model service systems where captive interacting customers must decide each period which facility to join for service. They base this decision on their expectations of sojourn times. Each period, customers use new information (their most recent experience and that of their best performing neighbour) to form expectations of sojourn time at the different facilities. Customers update their expectations using an adaptive expectations process to combine their memory and their new information. We label "conservative" those customers who give more weight to their memory than to the xiv Summary new information. In contrast, when they give more weight to new information, we call them "reactive". In Chapter 2, we consider customers with different degree of risk-aversion who take into account uncertainty. They choose which facility to join based on an estimated upper-bound of the sojourn time which they compute using their perceptions of the average sojourn time and the level of uncertainty. We assume the same exogenous service capacity for all facilities, which remains constant throughout. We first analyse the collective behaviour generated by the customers' decisions. We show that the system achieves low weighted average sojourn times when the collective behaviour results in neighbourhoods of customers loyal to a facility and the customers are approximately equally split among all facilities. The lowest weighted average sojourn time is achieved when exactly the same number of customers patronises each facility, implying that they do not wish to switch facility. In this case, the system has achieved the Nash equilibrium. We show that there is a non-monotonic relationship between the degree of risk-aversion and system performance. Customers with an intermediate degree of riskaversion typically achieve higher sojourn times; in particular they rarely achieve the Nash equilibrium. Risk-neutral customers have the highest probability of achieving the Nash Equilibrium. Chapter 3 considers a service system similar to the previous one but with risk-neutral customers, and relaxes the assumption of exogenous service rates. In this sense, we model a queueing system with endogenous service rates by enabling managers to adjust the service capacity of the facilities. We assume that managers do so based on their perceptions of the arrival rates and use the same principle of adaptive expectations to model these perceptions. We consider service systems in which the managers' decisions take time to be implemented. Managers are characterised by a profile which is determined by the speed at which they update their perceptions, the speed at which they take decisions, and how coherent they are when accounting for their previous decisions still to be implemented when taking their next decision. We find that the managers' decisions exhibit a strong path-dependence: owing to the initial conditions of the model, the facilities of managers with identical profiles can evolve completely differently. In some cases the system becomes "locked-in" into a monopoly or duopoly situation. The competition between managers causes the weighted average sojourn time of the system to converge to the exogenous benchmark value which they use to estimate their desired capacity. Concerning the managers' profile, we found that the more conservative Summary xv a manager is regarding new information, the larger the market share his facility achieves. Additionally, the faster he takes decisions, the higher the probability that he achieves a monopoly position. In Chapter 4 we consider a one-server queueing system with non-captive customers. We carry out an experiment aimed at analysing the way human subjects, taking on the role of the manager, take decisions in a laboratory regarding the capacity of a service facility. We adapt the model proposed by van Ackere et al (2010). This model relaxes the assumption of a captive market and allows current customers to decide whether or not to use the facility. Additionally the facility also has potential customers who currently do not patronise it, but might consider doing so in the future. We identify three groups of subjects whose decisions cause similar behavioural patterns. These groups are labelled: gradual investors, lumpy investors, and random investor. Using an autocorrelation analysis of the subjects' decisions, we illustrate that these decisions are positively correlated to the decisions taken one period early. Subsequently we formulate a heuristic to model the decision rule considered by subjects in the laboratory. We found that this decision rule fits very well for those subjects who gradually adjust capacity, but it does not capture the behaviour of the subjects of the other two groups. In Chapter 5 we summarise the results and provide suggestions for further work. Our main contribution is the use of simulation and experimental methodologies to explain the collective behaviour generated by customers' and managers' decisions in queueing systems as well as the analysis of the individual behaviour of these agents. In this way, we differ from the typical literature related to queueing systems which focuses on optimising performance measures and the analysis of equilibrium solutions. Our work can be seen as a first step towards understanding the interaction between customer behaviour and the capacity adjustment process in queueing systems. This framework is still in its early stages and accordingly there is a large potential for further work that spans several research topics. Interesting extensions to this work include incorporating other characteristics of queueing systems which affect the customers' experience (e.g. balking, reneging and jockeying); providing customers and managers with additional information to take their decisions (e.g. service price, quality, customers' profile); analysing different decision rules and studying other characteristics which determine the profile of customers and managers.

Trapping of naive lymphocytes triggers rapid growth and remodeling of the fibroblast network in reactive murine lymph nodes.

Adaptive immunity is initiated in T-cell zones of secondary lymphoid organs. These zones are organized in a rigid 3D network of fibroblastic reticular cells (FRCs) that are a rich cytokine source. In response to lymph-borne antigens, draining lymph nodes (LNs) expand several folds in size, but the fate and role of the FRC network during immune response is not fully understood. Here we show that T-cell responses are accompanied by the rapid activation and growth of FRCs, leading to an expanded but similarly organized network of T-zone FRCs that maintains its vital function for lymphocyte trafficking and survival. In addition, new FRC-rich environments were observed in the expanded medullary cords. FRCs are activated within hours after the onset of inflammation in the periphery. Surprisingly, FRC expansion depends mainly on trapping of naïve lymphocytes that is induced by both migratory and resident dendritic cells. Inflammatory signals are not required as homeostatic T-cell proliferation was sufficient to trigger FRC expansion. Activated lymphocytes are also dispensable for this process, but can enhance the later growth phase. Thus, this study documents the surprising plasticity as well as the complex regulation of FRC networks allowing the rapid LN hyperplasia that is critical for mounting efficient adaptive immunity.

Combined clonotyping and gene signatures of individual tumor-reactive CD8 T-cells define their functional relevance following peptide vaccination in melanoma patients

Novel cancer vaccines are capableto efficiently induce and boost humantumor antigen specific T-cells. However,the properties of these CD8T-cells are only partially characterized.For in depth investigation ofT-cells following Melan-A/MART-1peptide vaccination in melanoma patients,we conducted a detailed prospectivestudy at the single cell level.We first sorted individual human naiveand effector CD8 T-cells from peripheralblood by flow cytometry, andtested a modified RT-PCR protocolincluding a global amplification ofexpressed mRNAs to obtain sufficientcDNAfromsingle cells.We successfullydetected the expression ofseveral specific genes of interest evendown to 106-fold dilution (equivalentto 10-5 cell). We then analyzed tumor-specific effector memory (EM)CD8T-cell subpopulations ex vivo, assingle cells from vaccinated melanomapatients. To elucidate the hallmarksof effective immunity the genesignatures were defined by a panel ofgenes related to effector functions(e.g. IFN-, granzyme B, perforin),and individual clonotypes were identifiedaccording to the expression ofdistinct T-cell receptors (TCR). Usingthis novel single cell analysis approach,we observed that T-cell differentiationis clonotype dependent,with a progressive restriction in TCRBV clonotype diversity from EMCD28pos to EMCD28neg subsets. However,the effector function gene imprintingis clonotype-independent,but dependent on differentiation,since it correlates with the subset oforigin (EMCD28pos or EMCD28neg). We also conducted a detailedcomparative analysis after vaccinationwith natural vs. analog Melan-Apeptide. We found that the peptideused for vaccination determines thefunctional outcome of individualT-cell clonotypes, with native peptideinducing more potent effector functions.Yet, selective clonotypic expansionwith differentiation was preservedregardless of the peptide usedfor vaccination. In summary, the exvivo single cell RT-PCR approach ishighly sensitive and efficient, andrepresents a reliable and powerfultool to refine our current view of molecularprocesses taking place duringT-cell differentiation.

Immuno-reactive proteins from Mycobacterium immunogenum useful for serodiagnosis of metalworking fluid hypersensitivity pneumonitis.

Metalworking fluid-associated hypersensitivity pneumonitis (MWF-HP) is a pulmonary disease caused by inhaling microorganisms present in the metalworking fluids used in the industrial sector. Mycobacterium immunogenum is the main etiological agent. Among the clinical, radiological and biological tools used for diagnosis, serological tests are important. The aim of this study was to identify immunogenic proteins in M. immunogenum and to use recombinant antigens for serological diagnosis of MWF-HP. Immunogenic proteins were detected by two-dimensional Western blot and candidate proteins were identified by mass spectrometry. Recombinant antigens were expressed in Escherichia coli and tested by enzyme-linked immunosorbent assay (ELISA) with the sera of 14 subjects with MWF-HP and 12 asymptomatic controls exposed to M. immunogenum. From the 350 spots visualized by two-dimensional gel electrophoresis with M. immunogenum extract, 6 immunogenic proteins were selected to be expressed as recombinant antigens. Acyl-CoA dehydrogenase antigen allowed for the best discrimination of MWF-HP cases against controls with an area under the receiver operating characteristics (ROC) curve of 0.930 (95% CI=0.820-1), a sensitivity of 100% and a specificity of 83% for the optimum threshold. Other recombinant antigens correspond to acyl-CoA dehydrogenase FadE, cytosol aminopeptidase, dihydrolipoyl dehydrogenase, serine hydroxymethyltransferase and superoxide dismutase. This is the first time that recombinant antigens have been used for the serodiagnosis of hypersensitivity pneumonitis. The availability of recombinant antigens makes it possible to develop standardized serological tests which in turn could simplify diagnosis, thus making it less invasive.

Sex difference and the role of leptin in the association between high-sensitivity C-reactive protein and adiposity in two different populations.

Elevated high-sensitivity C-reactive protein (hs-CRP) concentration is associated with an increased risk of cardiovascular disease but this association seems to be largely mediated via conventional cardiovascular risk factors. In particular, the association between hs-CRP and obesity has been extensively demonstrated and correlations are stronger in women than men. We used fractional polynomials-a method that allows flexible modeling of non linear relations-to investigate the dose/response mathematical relationship between hs-CRP and several indicators of adiposity in Caucasians (Switzerland) and Africans (Seychelles) surveyed in two population-based studies. This relationship was non-linear exhibiting a steeper slope for low levels of hs-CRP and a higher level in women. The observed sex difference in the relationship between hs-CRP and adiposity almost disappeared upon adjustment for leptin, suggesting that these sex differences might be partially mediated, by leptin. All these relationship were similar in Caucasians and Africans. This is the first report on a non-linear relation, stratified by gender, between hs-CRP and adiposity.

Fecal calprotectin more accurately reflects endoscopic activity of ulcerative colitis than the Lichtiger Index, C-reactive protein, platelets, hemoglobin, and blood leukocytes.

BACKGROUND: The correlation between noninvasive markers with endoscopic activity according to the modified Baron Index in patients with ulcerative colitis (UC) is unknown. We aimed to evaluate the correlation between endoscopic activity and fecal calprotectin (FC), C-reactive protein (CRP), hemoglobin, platelets, blood leukocytes, and the Lichtiger Index (clinical score). METHODS: UC patients undergoing complete colonoscopy were prospectively enrolled and scored clinically and endoscopically. Samples from feces and blood were analyzed in UC patients and controls. RESULTS: We enrolled 228 UC patients and 52 healthy controls. Endoscopic disease activity correlated best with FC (Spearman's rank correlation coefficient r = 0.821), followed by the Lichtiger Index (r = 0.682), CRP (r = 0.556), platelets (r = 0.488), blood leukocytes (r = 0.401), and hemoglobin (r = -0.388). FC was the only marker that could discriminate between different grades of endoscopic activity (grade 0, 16 [10-30] μg/g; grade 1, 35 [25-48] μg/g; grade 2, 102 [44-159] μg/g; grade 3, 235 [176-319] μg/g; grade 4, 611 [406-868] μg/g; P < 0.001 for discriminating the different grades). FC with a cutoff of 57 μg/g had a sensitivity of 91% and a specificity of 90% to detect endoscopically active disease (modified Baron Index ≥ 2). CONCLUSIONS: FC correlated better with endoscopic disease activity than clinical activity, CRP, platelets, hemoglobin, and blood leukocytes. The strong correlation with endoscopic disease activity suggests that FC represents a useful biomarker for noninvasive monitoring of disease activity in UC patients.

Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science

Continuing developments in science and technology mean that the amounts of information forensic scientists are able to provide for criminal investigations is ever increasing. The commensurate increase in complexity creates difficulties for scientists and lawyers with regard to evaluation and interpretation, notably with respect to issues of inference and decision. Probability theory, implemented through graphical methods, and specifically Bayesian networks, provides powerful methods to deal with this complexity. Extensions of these methods to elements of decision theory provide further support and assistance to the judicial system. Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science provides a unique and comprehensive introduction to the use of Bayesian decision networks for the evaluation and interpretation of scientific findings in forensic science, and for the support of decision-makers in their scientific and legal tasks. Includes self-contained introductions to probability and decision theory. Develops the characteristics of Bayesian networks, object-oriented Bayesian networks and their extension to decision models. Features implementation of the methodology with reference to commercial and academically available software. Presents standard networks and their extensions that can be easily implemented and that can assist in the reader's own analysis of real cases. Provides a technique for structuring problems and organizing data based on methods and principles of scientific reasoning. Contains a method for the construction of coherent and defensible arguments for the analysis and evaluation of scientific findings and for decisions based on them. Is written in a lucid style, suitable for forensic scientists and lawyers with minimal mathematical background. Includes a foreword by Ian Evett. The clear and accessible style of this second edition makes this book ideal for all forensic scientists, applied statisticians and graduate students wishing to evaluate forensic findings from the perspective of probability and decision analysis. It will also appeal to lawyers and other scientists and professionals interested in the evaluation and interpretation of forensic findings, including decision making based on scientific information.

Characterization of Melan-A reactive memory CD8+ T cells in a healthy donor.

Melan-A specific CD8+ T cells are thought to play an important role against the development of melanoma. Their in vivo expansion is often observed with advanced disease. In recent years, low levels of Melan-A reactive CD8+ T cells have also been found in HLA-A2 healthy donors, but these cells harbor naive characteristics and are thought to be mostly cross-reactive for the Melan-A antigen. Here, we report on a large population of CD8+ T cells reactive for the Melan-A antigen, identified in one donor with no evidence of melanoma. Interestingly, this population is oligoclonal and displays a clear memory phenotype. However, a detailed study of these cells indicated that they are unlikely to be directly specific for melanoma, so that their in vivo expansion may have been driven by an exogenous antigen. Screening of a Melan-A cross-reactive peptide library suggested that these cells may be specific for an epitope derived from a Mycobacterium protein, which would provide a further example of CD8+ T cell cross-reactivity between a pathogen antigen and a tumor antigen. Finally, we discuss potential perspectives regarding the role of such cells in heterologous immunity, by influencing the balance between protective immunity and pathology, e.g. in the case of melanoma development.

Reactive electrophile species.

The interest in reactive electrophile species (RES) stems largely from the fact that they can have powerful biological activities. RES stimulate the expression of cell survival genes as well many other genes commonly upregulated in environmental stress and pathogenesis. RES levels must be carefully controlled in healthy cells but their formation and destruction during stress is of great interest. Unlike many 'classical' signals and hormones, RES can potentially affect gene expression at all levels by chemically reacting with nucleic acids, proteins and small molecules as well as by indirectly lowering pools of cellular reductants. Recent works involving genetic approaches have begun to provide compelling evidence that, although excess RES production can lead to cell damage, lower levels of RES may modulate the expression of cell survival genes and may actually contribute to survival during severe stress.

DNA evidence, probabilistic evaluation and collaborative tests.

Forensic scientists working in 12 state or private laboratories participated in collaborative tests to improve the reliability of the presentation of DNA data at trial. These tests were motivated in response to the growing criticism of the power of DNA evidence. The experts' conclusions in the tests are presented and discussed in the context of the Bayesian approach to interpretation. The use of a Bayesian approach and subjective probabilities in trace evaluation permits, in an easy and intuitive manner, the integration into the decision procedure of any revision of the measure of uncertainty in the light of new information. Such an integration is especially useful with forensic evidence. Furthermore, we believe that this probabilistic model is a useful tool (a) to assist scientists in the assessment of the value of scientific evidence, (b) to help jurists in the interpretation of judicial facts and (c) to clarify the respective roles of scientists and of members of the court. Respondents to the survey were reluctant to apply this methodology in the assessment of DNA evidence.

Induction of circulating tumor-reactive CD8+ T cells after vaccination of melanoma patients with the gp100 209-2M peptide.

Patients with stage I-III melanoma were vaccinated with the modified HLA-A2-binding gp100(209-2M)-peptide after complete surgical resection of their primary lesion and sentinel node biopsy. Cytoplasmic interferon-gamma production by freshly thawed peripheral blood mononuclear cells (direct ex vivo analysis) or by peripheral blood mononuclear cells subjected to 1 cycle of in vitro sensitization with peptide, interleukin-2, and interleukin-15 was measured following restimulation with the modified and native gp100 peptides, and also A2gp100 melanoma cell lines. Peptide-reactive and tumor-reactive T cells were detected in 79% and 66% of selected patients, respectively. Patients could be classified into 3 groups according to their vaccine-elicited T-cell responses. One group of patients responded only to the modified peptide used for immunization, whereas another group of patients reacted to both the modified and native gp100 peptides, but not to naturally processed gp100 antigen on melanoma cells. In the third group of patients, circulating CD8 T cells recognized A2gp100 melanoma cell lines and also both the modified and native peptides. T cells with a low functional avidity, which were capable of lysing tumor cells only if tumor cells were first pulsed by the exogenous administration of native gp100(209-217) peptide were identified in most patients. These results indicate that vaccination with a modified gp100 peptide induced a heterogeneous group of gp100-specific T cells with a spectrum of functional avidities; however, high avidity, tumor-reactive T cells were detected in the majority of patients.

LACK-reactive CD4+ T cells require autocrine IL-2 to mediate susceptibility to Leishmania major.

Mice from most inbred strains are resistant to infection with Leishmania major whereas mice from BALB strains are highly susceptible. Resistance and susceptibility result from the development of Th1 or Th2 cells, respectively. In this report, we document an IL-2 mRNA burst, preceding the reported early IL-4 response, in draining lymph nodes of susceptible mice infected with L. major. Neutralization of IL-2 during the first days of infection redirected Th1 cell maturation and resistance to L. major, through interference with the rapid IL-4 transcription in Leishmania homolog of mammalian RACK1 (LACK)-reactive CD4(+) cells. A burst of IL-2 transcripts also occurred in infected C57BL/6 mice that do not mount an early IL-4 response. However, although the LACK protein induced IL-2 transcripts in susceptible mice, it failed to trigger this response in resistant C57BL/6 mice. Reconstitution experiments using C.B.-17 SCID mice and LACK-reactive CD4(+) T cells from IL-2(-/-) BALB/c mice showed that triggering of the early IL-4 response required autocrine IL-2. Thus, in C57BL/6 mice, the inability of LACK-reactive CD4(+) T cells to express early IL-4 mRNA transcription, important for disease progression, appears due to an incapacity of these cells to produce IL-2.