How the gut links innate and adaptive immunity.

Mucosal surfaces represent the main sites in which environmental microorganisms and antigens interact with the host. Sentinel cells, including epithelial cells, lumenal macrophages, and intraepithelial dendritic cells, continuously sense the environment and coordinate defenses for the protection of mucosal tissues. The mucosal epithelial cells are crucial actors in coordinating defenses. They sense the outside world and respond to environmental signals by releasing chemokines and cytokines that recruit inflammatory and immune cells to control potential infectious agents and to attract cells able to trigger immune responses. Among immune cells, dendritic cells (DC) play a key role in controlling adaptive immune responses, due to their capacity to internalize foreign materials and to present antigens to naive T and B lymphocytes, locally or in draining organized lymphoid tissues. Immune cells recruited in epithelial tissues can, in turn, act upon the epithelial cells and change their phenotype in a process referred to as epithelial metaplasia.

Notes on Agents’ Behavioral Rules Under Adaptive Learning and Studies of Monetary Policy

These notes try to clarify some discussions on the formulation of individual intertemporal behavior under adaptive learning in representative agent models. First, we discuss two suggested approaches and related issues in the context of a simple consumption-saving model. Second, we show that the analysis of learning in the NewKeynesian monetary policy model based on “Euler equations” provides a consistent and valid approach.

Adaptive Continuous time Markov Chain Approximation Model to General Jump-Diusions

We propose a non-equidistant Q rate matrix formula and an adaptive numerical algorithm for a continuous time Markov chain to approximate jump-diffusions with affine or non-affine functional specifications. Our approach also accommodates state-dependent jump intensity and jump distribution, a flexibility that is very hard to achieve with other numerical methods. The Kolmogorov-Smirnov test shows that the proposed Markov chain transition density converges to the one given by the likelihood expansion formula as in Ait-Sahalia (2008). We provide numerical examples for European stock option pricing in Black and Scholes (1973), Merton (1976) and Kou (2002).

Automatic front-crawl temporal phase detection using adaptive filtering of inertial signals

This study introduces a novel approach for automatic temporal phase detection and inter-arm coordination estimation in front-crawl swimming using inertial measurement units (IMUs). We examined the validity of our method by comparison against a video-based system. Three waterproofed IMUs (composed of 3D accelerometer, 3D gyroscope) were placed on both forearms and the sacrum of the swimmer. We used two underwater video cameras in side and frontal views as our reference system. Two independent operators performed the video analysis. To test our methodology, seven well-trained swimmers performed three 300 m trials in a 50 m indoor pool. Each trial was in a different coordination mode quantified by the index of coordination. We detected different phases of the arm stroke by employing orientation estimation techniques and a new adaptive change detection algorithm on inertial signals. The difference of 0.2 +/- 3.9% between our estimation and video-based system in assessment of the index of coordination was comparable to experienced operators' difference (1.1 +/- 3.6%). The 95% limits of agreement of the difference between the two systems in estimation of the temporal phases were always less than 7.9% of the cycle duration. The inertial system offers an automatic easy-to-use system with timely feedback for the study of swimming.

Control of the adaptive response of the heart to stress via the Notch1 receptor pathway.

In the damaged heart, cardiac adaptation relies primarily on cardiomyocyte hypertrophy. The recent discovery of cardiac stem cells in the postnatal heart, however, suggests that these cells could participate in the response to stress via their capacity to regenerate cardiac tissues. Using models of cardiac hypertrophy and failure, we demonstrate that components of the Notch pathway are up-regulated in the hypertrophic heart. The Notch pathway is an evolutionarily conserved cell-to-cell communication system, which is crucial in many developmental processes. Notch also plays key roles in the regenerative capacity of self-renewing organs. In the heart, Notch1 signaling takes place in cardiomyocytes and in mesenchymal cardiac precursors and is activated secondary to stimulated Jagged1 expression on the surface of cardiomyocytes. Using mice lacking Notch1 expression specifically in the heart, we show that the Notch1 pathway controls pathophysiological cardiac remodeling. In the absence of Notch1, cardiac hypertrophy is exacerbated, fibrosis develops, function is altered, and the mortality rate increases. Therefore, in cardiomyocytes, Notch controls maturation, limits the extent of the hypertrophic response, and may thereby contribute to cell survival. In cardiac precursors, Notch prevents cardiogenic differentiation, favors proliferation, and may facilitate the expansion of a transient amplifying cell compartment.

Innate receptors for adaptive immunity.

Pattern recognition receptors (PRRs) are commonly known as sensor proteins crucial for the early detection of microbial or host-derived stress signals by innate immune cells. Interestingly, some PRRs are also expressed and functional in cells of the adaptive immune system. These receptors provide lymphocytes with innate sensing abilities; for example, B cells express Toll-like receptors, which are important for the humoral response. Strikingly, certain other NOD-like receptors are not only highly expressed in adaptive immune cells, but also exert functions related specifically to adaptive immune system pathways, such as regulating antigen presentation. In this review, we will focus particularly on the current understanding of PRR functions intrinsic to B and T lymphocytes; a developing aspect of PRR biology.

Regulation of adaptive behaviour during fasting by hypothalamic Foxa2.

The lateral hypothalamic area is considered the classic 'feeding centre', regulating food intake, arousal and motivated behaviour through the actions of orexin and melanin-concentrating hormone (MCH). These neuropeptides are inhibited in response to feeding-related signals and are released during fasting. However, the molecular mechanisms that regulate and integrate these signals remain poorly understood. Here we show that the forkhead box transcription factor Foxa2, a downstream target of insulin signalling, regulates the expression of orexin and MCH. During fasting, Foxa2 binds to MCH and orexin promoters and stimulates their expression. In fed and in hyperinsulinemic obese mice, insulin signalling leads to nuclear exclusion of Foxa2 and reduced expression of MCH and orexin. Constitutive activation of Foxa2 in the brain (Nes-Cre/+;Foxa2T156A(flox/flox) genotype) results in increased neuronal MCH and orexin expression and increased food consumption, metabolism and insulin sensitivity. Spontaneous physical activity of these animals in the fed state is significantly increased and is similar to that in fasted mice. Conditional activation of Foxa2 through the T156A mutation expression in the brain of obese mice also resulted in improved glucose homeostasis, decreased fat and increased lean body mass. Our results demonstrate that Foxa2 can act as a metabolic sensor in neurons of the lateral hypothalamic area to integrate metabolic signals, adaptive behaviour and physiological responses.

The role of chemokines in cancer immune surveillance by the adaptive immune system.

Chemokines are key molecules involved in the migration and homeostasis of immune cells. However, also tumor cells use chemokine signals for different processes such as tumor progression and metastasis. It is thus unclear whether chemokines, through their immunostimulatory roles, contribute to the repression of tumor cells by tumor immunosurveillance or whether chemokines act primarily as growth factors and chemoattractants for primary and metastatizing tumors, respectively. Research of recent years, using gene knockout mice, recombinant chemokines, and agents able to block chemokine actions, has provided further insight into the diverse functions of chemokines. Here, we review the current knowledge on the complex actions of chemokines at the interface of the immune system and the tumor.

Local-global splitting for spatiotemporal-adaptive multiscale methods

We present a novel spatiotemporal-adaptive Multiscale Finite Volume (MsFV) method, which is based on the natural idea that the global coarse-scale problem has longer characteristic time than the local fine-scale problems. As a consequence, the global problem can be solved with larger time steps than the local problems. In contrast to the pressure-transport splitting usually employed in the standard MsFV approach, we propose to start directly with a local-global splitting that allows to locally retain the original degree of coupling. This is crucial for highly non-linear systems or in the presence of physical instabilities. To obtain an accurate and efficient algorithm, we devise new adaptive criteria for global update that are based on changes of coarse-scale quantities rather than on fine-scale quantities, as it is routinely done before in the adaptive MsFV method. By means of a complexity analysis we show that the adaptive approach gives a noticeable speed-up with respect to the standard MsFV algorithm. In particular, it is efficient in case of large upscaling factors, which is important for multiphysics problems. Based on the observation that local time stepping acts as a smoother, we devise a self-correcting algorithm which incorporates the information from previous times to improve the quality of the multiscale approximation. We present results of multiphase flow simulations both for Darcy-scale and multiphysics (hybrid) problems, in which a local pore-scale description is combined with a global Darcy-like description. The novel spatiotemporal-adaptive multiscale method based on the local-global splitting is not limited to porous media flow problems, but it can be extended to any system described by a set of conservation equations.

Hybridisation and diversification in the adaptive radiation of clownfishes.

BackgroundThe importance of hybridisation during species diversification has long been debated among evolutionary biologists. It is increasingly recognised that hybridisation events occurred during the evolutionary history of numerous species, especially during the early stages of adaptive radiation. We study the effect of hybridisation on diversification in the clownfishes, a clade of coral reef fish that diversified through an adaptive radiation process. While two species of clownfish are likely to have been described from hybrid specimens, the occurrence and effect of hybridisation on the clade diversification is yet unknown.ResultsWe generate sequences of three mitochondrial genes to complete an existing dataset of nuclear sequences and document cytonuclear discordance at a node, which shows a drastic increase of diversification rate. Then, using a tree-based jack-knife method, we identify clownfish species likely stemming from hybridisation events. Finally, we use molecular cloning and identify the putative parental species of four clownfish specimens that display the morphological characteristics of hybrids.ConclusionsOur results show that consistently with the syngameon hypothesis, hybridisation events are linked with a burst of diversification in the clownfishes. Moreover, several recently diverged clownfish lineages likely originated through hybridisation, which indicates that diversification, catalysed by hybridisation events, may still be happening.

Adaptive filtering methods for identifying cross-frequency couplings in human EEG.

Oscillations have been increasingly recognized as a core property of neural responses that contribute to spontaneous, induced, and evoked activities within and between individual neurons and neural ensembles. They are considered as a prominent mechanism for information processing within and communication between brain areas. More recently, it has been proposed that interactions between periodic components at different frequencies, known as cross-frequency couplings, may support the integration of neuronal oscillations at different temporal and spatial scales. The present study details methods based on an adaptive frequency tracking approach that improve the quantification and statistical analysis of oscillatory components and cross-frequency couplings. This approach allows for time-varying instantaneous frequency, which is particularly important when measuring phase interactions between components. We compared this adaptive approach to traditional band-pass filters in their measurement of phase-amplitude and phase-phase cross-frequency couplings. Evaluations were performed with synthetic signals and EEG data recorded from healthy humans performing an illusory contour discrimination task. First, the synthetic signals in conjunction with Monte Carlo simulations highlighted two desirable features of the proposed algorithm vs. classical filter-bank approaches: resilience to broad-band noise and oscillatory interference. Second, the analyses with real EEG signals revealed statistically more robust effects (i.e. improved sensitivity) when using an adaptive frequency tracking framework, particularly when identifying phase-amplitude couplings. This was further confirmed after generating surrogate signals from the real EEG data. Adaptive frequency tracking appears to improve the measurements of cross-frequency couplings through precise extraction of neuronal oscillations.

Adaptive Privacy Management System Design For Context-Aware Mobile Devices

While mobile technologies can provide great personalized services for mobile users, they also threaten their privacy. Such personalization-privacy paradox are particularly salient for context aware technology based mobile applications where user's behaviors, movement and habits can be associated with a consumer's personal identity. In this thesis, I studied the privacy issues in the mobile context, particularly focus on an adaptive privacy management system design for context-aware mobile devices, and explore the role of personalization and control over user's personal data. This allowed me to make multiple contributions, both theoretical and practical. In the theoretical world, I propose and prototype an adaptive Single-Sign On solution that use user's context information to protect user's private information for smartphone. To validate this solution, I first proved that user's context is a unique user identifier and context awareness technology can increase user's perceived ease of use of the system and service provider's authentication security. I then followed a design science research paradigm and implemented this solution into a mobile application called "Privacy Manager". I evaluated the utility by several focus group interviews, and overall the proposed solution fulfilled the expected function and users expressed their intentions to use this application. To better understand the personalization-privacy paradox, I built on the theoretical foundations of privacy calculus and technology acceptance model to conceptualize the theory of users' mobile privacy management. I also examined the role of personalization and control ability on my model and how these two elements interact with privacy calculus and mobile technology model. In the practical realm, this thesis contributes to the understanding of the tradeoff between the benefit of personalized services and user's privacy concerns it may cause. By pointing out new opportunities to rethink how user's context information can protect private data, it also suggests new elements for privacy related business models.