Tuning the average path length of complex networks and its influence to the emergent dynamics of the majority-rule model

We show how appropriate rewiring with the aid of Metropolis Monte Carlo computational experiments can be exploited to create network topologies possessing prescribed values of the average path length (APL) while keeping the same connectivity degree and clustering coefficient distributions. Using the proposed rewiring rules we illustrate how the emergent dynamics of the celebrated majority-rule model are shaped by the distinct impact of the APL attesting the need for developing efficient algorithms for tuning such network characteristics.Comment: 10 figure

On the effect of the path length and transitivity of small-world networks on epidemic dynamics

We show how one can trace in a systematic way the coarse-grained solutions of individual-based stochastic epidemic models evolving on heterogeneous complex networks with respect to their topological characteristics. In particular, we have developed algorithms that allow the tuning of the transitivity (clustering coefficient) and the average mean-path length allowing the investigation of the "pure" impacts of the two characteristics on the emergent behavior of detailed epidemic models. The framework could be used to shed more light into the influence of weak and strong social ties on epidemic spread within small-world network structures, and ultimately to provide novel systematic computational modeling and exploration of better contagion control strategies

A Motion Illusion Reveals Mechanisms of Perceptual Stabilization

Visual illusions are valuable tools for the scientific examination of the mechanisms underlying perception. In the peripheral drift illusion special drift patterns appear to move although they are static. During fixation small involuntary eye movements generate retinal image slips which need to be suppressed for stable perception. Here we show that the peripheral drift illusion reveals the mechanisms of perceptual stabilization associated with these micromovements. In a series of experiments we found that illusory motion was only observed in the peripheral visual field. The strength of illusory motion varied with the degree of micromovements. However, drift patterns presented in the central (but not the peripheral) visual field modulated the strength of illusory peripheral motion. Moreover, although central drift patterns were not perceived as moving, they elicited illusory motion of neutral peripheral patterns. Central drift patterns modulated illusory peripheral motion even when micromovements remained constant. Interestingly, perceptual stabilization was only affected by static drift patterns, but not by real motion signals. Our findings suggest that perceptual instabilities caused by fixational eye movements are corrected by a mechanism that relies on visual rather than extraretinal (proprioceptive or motor) signals, and that drift patterns systematically bias this compensatory mechanism. These mechanisms may be revealed by utilizing static visual patterns that give rise to the peripheral drift illusion, but remain undetected with other patterns. Accordingly, the peripheral drift illusion is of unique value for examining processes of perceptual stabilization

Coarse-grained computational analysis of the dynamics of epidemic diseases: from the individual-based/microscopic model to the macroscopic behavior

127 σ.Η ραγδαία θεωρητική και τεχνολογική ανάπτυξη των τελευταίων ετών μας επιτρέπει να γνωρίζουμε με μεγάλη λεπτομέρεια ακόμα και τη μοριακή δομή διαφόρων ιών. Παρά όμως τη σημαντική πρόοδο, σε επίπεδο κατανόησης τόσο της δομής των ιών σε μοριακό επίπεδο όσο και της διαδικασίας μετάδοσης ενός ιού μεταξύ των ανθρώπων, δεν υπάρχει πλήρης κατανόηση των μηχανισμών που οφείλονται για τη δυναμική της εξάπλωσης επιδημικών καταστάσεων, όπως π.χ. είναι ο χρόνος μεταξύ της προσβολής και της εμφάνισης της ασθένειας στα άτομα ή της ισχύος και διάρκειας μίας επιδημίας στο επίπεδο του πληθυσμού. Η απάντηση σε τέτοιου είδους ερωτήματα βρίσκεται στην ανάπτυξη κατάλληλων μαθηματικών/υπολογιστικών εργαλείων που θα επιτρέψουν την καλύτερη κατανόηση της δυναμικής της εξάπλωσης μίας ασθένειας. Οι χωρικές και χρονικές κλίμακες συμπεριφοράς και εξέλιξης των φαινομένων εκτείνονται από τη προσβολή του ανοσοποιητικού συστήματος από τον ιό, την επώαση του ιού και την εκδήλωση της νόσου στο άτομο, τη μετάδοση του ιού σε άλλα άτομα και την εξάπλωση του στο επίπεδο του πληθυσμού. Λόγω της πολυπλοκότητας των φαινομένων και της ύπαρξης διαφορετικών χωρο-χρονικών κλιμάκων, καθώς και της πολυπλοκότητας της δομής των υποκείμενων κοινωνικών δικτύων μετάδοσης της επιδημίας, η σύγχρονη τάση στη μαθηματική περιγραφή και την υπολογιστική προσομοίωση της δυναμικής μεταδοτικών νόσων είναι η ανάπτυξη λεπτομερών μικροσκοπικών-ατομικιστικών (individual-based) δικτυακών μοντέλων. Βασικός σκοπός της διδακτορικής διατριβής ήταν η ανάπτυξη συστηματικών υπολογιστικών μεθόδων για τη γεφύρωση του χάσματος, στον χώρο και στο χρόνο, μεταξύ του επιπέδου που μπορεί να είναι διαθέσιμη η περιγραφή (μικροσκοπικό-ατομικιστικό (microscopic/individual-based)) μετάδοσης της νόσου και του επιπέδου που είναι επιθυμητή η ανάλυση της δυναμικής και ο σχεδιασμός κατάλληλων μεθόδων ελέγχου (μακροσκοπικό-πληθυσμιακό επίπεδο) συναρτήσει τοπολογικών χαρακτηριστικών των υποκείμενων κοινωνικών δικτύων επαφής. Στα πλαίσια της Διατριβής αναπτύχθηκε για αυτό το λόγο το κατάλληλο υπολογιστικό πλαίσιο που επιτρέπει σε λεπτομερείς μικροσκοπικούς-ατομικιστικούς προσομοιωτές μεταδοτικών νόσων σε δίκτυα να εκτελούν άμεσα ανάλυση στο μακροσκοπικό επίπεδο του πληθυσμού, χωρίς να είναι απαραίτητη η ανάπτυξη μακροσκοπικών εξισώσεων σε κλειστή μορφή (με τη μορφή διαφορικών ή διαφορικών-ολοκληρωτικών εξισώσεων). Αναπτύχθηκε επίσης μία νέα μεθοδολογία με σκοπό τη συστηματική διερεύνηση του «καθαρού» ρόλου του μέσου μήκους, μιας ιδιαίτερα σημαντικής στατιστικής ιδιότητας της τοπολογίας δικτύων «μικρού κόσμου». Είναι η πρώτη φορά που παρουσιάζεται ένα ολοκληρωμένο υπολογιστικό πλαίσιο για την συστηματική μελέτη της εμφανιζόμενης δυναμικής λεπτομερών ατομικιστικών επιδημιολογικών προσομοιωτών σε πολύπλοκα δίκτυα με βάση τα τοπολογικά χαρακτηριστικά δικτύων.Over the last years rapid theoretical and technological progress has enhanced our knowledge in fighting epidemics and we are getting constantly better at it. The global surveillance network is growing fast; our knowledge at the molecular level for many viruses is growing fast. A large and intensive research effort is evolving for the design of better drugs and vaccines and our knowledge has progressed deeper in details such as the molecular structure of a variety of viruses. However, despite these major progresses in a comprehension level both of the viruses’ molecular structure and of a virus’ transmission process among people, there is no utter/complete grasp of the mechanisms held responsible for the proliferation/expansion dynamics of epidemics. The complex multi-scale interplay between a host of factors ranging from the micro host-pathogen and individual-scale host-host interactions to macro-scale ecological, social, economic and demographical conditions complicated by technical issues such as the time lag between vaccine prototype development and commercial production and distribution imposes a real impediment to our control strategy potential. Hence, the quest for the efficient, analysis, long-term prediction and control of epidemic spread is one of the most significant and tough research pursuits of our time. The key answer to such questions lies in the development of efficient mathematical/computational tools allowing a better understanding of the spreading of a disease as this evolves on heterogeneous social networks. Towards this aim the multi-agent models, and dynamic network agent-based models are touted as key approaches for reasoning about and analyzing “complex epidemic systems”. Public-health epidemiologists, researchers and policy makers are turning to these detailed models for reasons of ethics, cost, timeliness and appropriateness. To date the only thing that is done with such micro-scaled detailed agent-based epidemiological models is to do simple simulation: set up many initial conditions, for each initial condition create a large enough number of ensemble realizations, probably change some of the rules and then run the detailed dynamics for a long time to investigate how things such as different vaccination policies, malignancy of the virus -as this may be expressed in terms of the reproduction number-, and resource availability may influence the spread of an outbreak. However, this simulation “lives” on extremely fine space and time scales, and simple simulation is inadequate for systematic investigations. The major target(s) of this Doctoral Thesis was the development of a-beyond the current state-of-the-art-computational framework to enhance the investigation of the dynamics of emerging epidemics evolving on heterogeneous contact networks. The framework allows the extraction of “large scale, system level” information and design of intervention policies for emerging epidemics “easier, faster, better” than what is currently done. The framework enables individual-based epidemic simulators to perform system-level analysis at the macroscopic level of the population, bypassing the need of analytical derivation of closures for the macroscopic-level equations (in the form of differential or differential-integral equations) taking into account key topological characteristics of the underlying contact networks. Moreover, in order to investigate the pure effect of an important statistic describing the topology of small-world networks, namely the mean path length which pertain to the transmission mechanism of many infectious diseases, a methodology was developed to systematically explore its role.Ανδρέας Ι. Ρέππα

Multidimensional Analysis Integrating Human T-Cell Signatures in Lymphatic Tissues with Sex of Humanized Mice for Prediction of Responses after Dendritic Cell Immunization

Mice transplanted with human cord blood-derived hematopoietic stem cells (HSCs) became a powerful experimental tool for studying the heterogeneity of human immune reconstitution and immune responses in vivo. Yet, analyses of human T cell maturation in humanized models have been hampered by an overall low immune reactivity and lack of methods to define predictive markers of responsiveness. Long-lived human lentiviral induced dendritic cells expressing the cytomegalovirus pp65 protein (iDCpp65) promoted the development of pp65-specific human CD8+ T cell responses in NOD.Cg-Rag1tm1Mom-Il2rγtm1Wj humanized mice through the presentation of immune-dominant antigenic epitopes (signal 1), expression of co-stimulatory molecules (signal 2), and inflammatory cytokines (signal 3). We exploited this validated system to evaluate the effects of mouse sex in the dynamics of T cell homing and maturation status in thymus, blood, bone marrow, spleen, and lymph nodes. Statistical analyses of cell relative frequencies and absolute numbers demonstrated higher CD8+ memory T cell reactivity in spleen and lymph nodes of immunized female mice. In order to understand to which extent the multidimensional relation between organ-specific markers predicted the immunization status, the immunophenotypic profiles of individual mice were used to train an artificial neural network designed to discriminate immunized and non-immunized mice. The highest accuracy of immune reactivity prediction could be obtained from lymph node markers of female mice (77.3%). Principal component analyses further identified clusters of markers best suited to describe the heterogeneity of immunization responses in vivo. A correlation analysis of these markers reflected a tissue-specific impact of immunization. This allowed for an organ-resolved characterization of the immunization status of individual mice based on the identified set of markers. This new modality of multidimensional analyses can be used as a framework for defining minimal but predictive signatures of human immune responses in mice and suggests critical markers to characterize responses to immunization after HSC transplantation

Dissolution testing of modified release products with biorelevant media: An OrBiTo ring study using the USP apparatus III and IV

During the OrBiTo project, our knowledge on the gastrointestinal environment has improved substantially and biorelevant media composition have been refined. The aim of this study was to propose optimized biorelevant testing conditions for modified release products, to evaluate the reproducibility of the optimized compendial apparatus III (USP apparatus III) and compendial apparatus IV (USP apparatus IV, open-loop mode) dissolution methods and to evaluate the usefulness of these methods to forecast the direction of food effects, if any, based on the results of two «ring» studies and by using two model modified release (MR) products, Ciproxin / Cipro XR and COREG CR. Six OrBiTo partners participated in each of the ring studies. All laboratories were provided with standard protocols, pure drug substance, and dose units. For the USP apparatus III, the dissolution methods applied to Ciproxin / Cipro XR, a monolithic MR product of an active pharmaceutical ingredient (API) with moderate aqueous solubility, were robust with low intra- and inter-laboratory data variability. Data from all partners were in line on a qualitative basis with food effect data in humans. For the USP apparatus IV, the dissolution methods applied to COREG CR, a multiparticulate, pH dependent, MR product of an API with low and pH dependent solubility led to high intra- and inter- laboratory data variability. Data from all partners were in line, on a qualitative basis, with the previously observed food effects in humans. © 2020 Elsevier B.V