Abstract: The immune system is a fascinating complex system taking decisions on how to respond to a wide variety of stimuli, varying from lethal pathogens to harmless proteins in the food. This system relies on a large repertoire of randomly generated ‘detectors’ in the form of naïve lymphocytes. We are interested in the mechanisms behind the maintenance of these detectors during ageing. Nowadays, deep sequencing methods can be used to characterize the repertoires of naïve lymphocytes. To get a deeper understanding of how an important part of the complex immune system works, we developed a model regarding naïve lymphocyte dynamics which is similar to Hubbell’s Neutral Community Model used in ecology. The simulations and analytical solution of this model give a geometric clone-size distribution, whereas it has been argued that the repertoire is power-law distributed. In addition, we show that current diversity measures tend to overestimate the effect of ageing. Indeed, Next Generation Sequencing (NGS) data shows a geometric distribution, which is in line with our neutral model. Our simple model appears to be sufficient to describe the complex maintenance of naïve detectors in the immune system.

Abstract: The analysis of brain functional architecture is a paradigmatic example of complex system, since brain functionality emerges as a global property of local interactions. A complete description of multi-scale and multi-level segregation and integration of brain regions represents a challenging issue to address and unearths the complexity of its whole functional organization. Here we analysed functional magnetic resonance imaging data from forty human healthy subjects during resting condition. Network theory is able to visualize the skeleton of functional correlations (weights) between different regions (nodes) of the brain and to extract information, by selecting only the most important features out of the noise. On the resulting human functional brain network, we performed a modified version of the percolation analysis and compared the results with a null model: a not-trivial hierarchical organization in modules emerges. A zoom in the modular structure through a maximum spanning forest (MSF) approach unveiled a chain-like organization of the brain regions, never observed before. Intuitively, nodes tend to link with nodes in the same anatomical area, except for regions in the Temporal Lobe. Passing from the MSF to the maximum spanning tree, the network preserved the chain-like structure, confirming some outcomes and revealing the centrality of the Occipital Lobe and some regions from the Temporal Lobe and the Cerebellum. Furthermore, we explored the hierarchical organization of the brain function looking at network configurations when specific thresholds are introduced. Many connections within, rather than between, anatomical regions disclosed a high level of segregation of a specific area. Both the Occipital Lobe and the Cerebellum exhibit together this feature, even if an important difference emerged: while the former represents the core of the whole functional network with all the other modules connecting gradually to it, the latter is peripheral, joining the network only at the end.

Abstract: Influenza activity shows a complex spatio-temporal pattern with a strong seasonal dynamic whose complete understanding is still missing. Here we study 30 years of seasonal influenza circulation in France at the regional level from influenza-like-illness (ILI) cases time series. Our aim is to characterize common patterns of synchronization across seasons and assess how they change from the start of the outbreak to the time at which influenza activity reaches its peak. To each season we associate two vectors whose elements are the epidemic onset time or the epidemic peak time in a given region of France, normalized to remove seasonal trends. We cluster seasons according to their epidemic onset time (peak time) based on the distance between their corresponding vectors. We found that the distance computed on the peak time is generally smaller than the one computed on the onset time. A stronger clustering is therefore observed at the peak time, highlighting the larger synchronization that regions reach in the period of highest incidence with respect to the beginning of the epidemic. Seasons starting with rather different geographic distribution of epidemic onset become more similar in their peak time synchronization pattern. They are also characterized by larger epidemics and show no relevant correlation to weather time series, differently from the seasons not showing this recurrent pattern. Multi-scale transportation networks are found to play an important role in the emergence of such patterns. The study identifies the relevant factors in the shaping of the spatio-temporal diffusion of influenza in France, offering important information for the understanding of seasonal behavior and for the developments of realistic models of influenza spread.

Abstract: To better understand the complex relations between physical properties of foods and sensory perception, we have explored methods that are also used in the area of complex systems. We analysed temporal dominance of sensations (TDS) data [1] using methods from information theory[2]. We report that vastly different TDS curves can be mapped onto one master curve as a function of normalized time and an information theoretical measure. Furthermore the theory provides the basis for a recently proposed quantitative measure for complexity[3]. Interestingly, we find that this measure versus time maximizes at a point that is near to the moment of swallowing. This behaviour has a strong resemblance to that of a system near a phase transition[4]. Such an analogy has been put forward by Gershenson et al. for a random Boolean network[3]. New visualisation methods are investigated, like directed graphs, to research TDS profiles on an individual level for different food model systems. This showed that for most individuals the sequence of dominant sensations depended on system type, while for some it was independent of that. References [1] M. Devezeaux de Lavergne, M. van Delft, F. van de Velde, M. a. J. S. van Boekel, and M. Stieger, “Dynamic texture perception and oral processing of semi-solid food gels: Part 1: Comparison between QDA, progressive profiling and TDS,” Food Hydrocoll., vol. 43, pp. 207–217, 2015. [2] C. E. Shannon, “A Mathematical Theory of Communication,” Bell Syst. Tech. J., vol. 27, no. July, pp. 379–423, 1948. [3] C. Gershenson and N. Fernández, “Complexity and information: Measuring emergence, self-organization, and homeostasis at multiple scales,” Complexity, vol. 18, no. 2, pp. 29–44, Nov. 2012. [4] M. Prokopenko, J. T. Lizier, O. Obst, and X. R. Wang, “Relating Fisher information to order parameters,” Phys. Rev. E, vol. 84, no. 4, p. 041116, 2011.

Abstract: There is increasing evidence that aerosol transmission is a major contributor to the spread of influenza. Despite this, virtually all studies assessing the dynamics and control of influenza assume that it is transmitted solely through direct contact and large droplets that require close physical proximity. Here, we use wireless sensors to measure simultaneously both the location and close proximity contacts in the population of a US high school. This dataset, highly resolved in space and time, allows us to model both droplet and aerosol transmission either in isolation or in combination. In particular, it allows us to computationally assess the effectiveness of overlooked mitigation strategies such as improved ventilation that are available in the case of aerosol transmission. While the effects of the type of transmission on disease outbreak dynamics appear to be weak, we find that good ventilation could be as effective in mitigating outbreaks as vaccinating the majority of the population. In simulations using empirical transmission levels observed in Hong Kong and Bangkok households, we find that bringing ventilation to recommended levels has the same effect as vaccinating between 50% and 60% of the population, in the combined droplet-aerosol model. Our study therefore suggests that improvements of ventilation in public spaces could be an important strategy supplementing vaccination efforts for effective control of influenza spread.

Abstract: It is a long-standing question whether human sexual and reproductive cycles are affected predominantly by biology, hemisphere location, or culture. Here we show that interest in sex peaks sharply online during the major cultural and religious celebrations of countries with predominantly Christian or Muslim populations, regardless of hemisphere. These peaks in sex-related searches correspond to documented human birth cycles, even after adjusting sex-search data for numerous factors such as search language, season, amount of free time due to holidays, and changes in the overall volume of online searches. We further show that public mood sentiment measured independently from the Twitter content generated by the same country populations, contains distinct collective emotions associated with those cultural celebrations, even after removing all known greetings used during cultural and religious celebrations. Additionally, the observed collective moods correlate with sex search volume outside of these holidays. Our results provide converging evidence that the cyclic sexual and reproductive behavior of human populations is driven above all else by culture, and specifically that the seasonal sex-search and corresponding birth peaks derive from emotions that are maximized during major cultural and religious celebrations, but appear in other occasions when interest in sex also tends to increase.