Adaptation

Related publications (100)

Vascular remodeling is defined as any enduring change in the size and composition of an adult blood vessel, allowing adaptation or repair. The vascular remodeling response has been shown to depend on a variety of endogenous and environmental factors. Physiological remodeling is a tightly regulated process that mainly occurs in response to long-term changes in hemodynamic conditions. The adaptation to these hemodynamic changes implies the production of mediators that influence structure as well as function. A loss of regulation in the adaptive response underlies the pathogenesis of major cardiovascular diseases, including hypertension, atherosclerosis, restenosis and arterial aneurismal dilatation. Specialized enzymes called matrix metalloproteinases (MMPs) have been shown to have a predominant participation in the reorganization of the vessel structure, through the degradation of the extracellular matrix scaffold. The aim of this thesis is to gain insight in the biological and mechanical processes taking place in the vascular wall as an adaptive response to different biomechanical stimuli such as blood pressure and blood flow. This work proposes a new model for the study of vascular remodeling where physical factors acting on the arterial wall can be dissociated and analyzed, individually, in relation to the biological response. The results are presented in form of an introduction, three scientific papers and a conclusion section. The investigation has been designed around three different approaches: adaptation of a non-uniform artery to an in vitro environment, vascular adaptation to steady and pulsatile pressure and vascular adaptation to unidirectional and oscillatory flow. The adaptive response to each one of the variables chosen has been analyzed through biological and biomechanical remodeling indicators of the arterial wall. The introduction is an overview of the biological and biomechanical characteristics of arterial wall in relation to the remodeling process. The contribution of vascular smooth muscle cells and extracellular matrix to physiological and pathological arterial remodeling is discussed. Paper I assesses the relative remodeling of a non-axisymmetric artery in relation to its environment. The study considers the native circumferential asymmetry of the porcine right common carotid, which results from the non-homogenous mechanical and hemodynamic native environment. The adaptive response of the artery to an in vitro perfusion environment is analyzed. The study shows that in vitro perfusion leads, through remodeling, to a circumferentially uniform scleroprotein distribution and to a change in arterial compliance. This study emphasizes the link between structural changes, the biomechanical response and the enzymatic implication in the adaptive response. In paper II we investigate the role of continuous and cyclic stretch, produced by steady or pulsatile pressure acting on the arterial wall, on the remodeling response. The study shows that exposure to continuous and cyclic stretch differentially affects the relative scleroprotein content and leads to a change in arterial wall stiffness. The adaptive outcome is studied through an integrative approach taking into consideration the geometrical and structural adaptation, the biomechanical behavior and the enzymatic agents implicated in extracellular matrix turnover. Paper III analyzes the influence of different flow patterns on the arterial adaptive response. We investigate the differential effects of oscillatory flow, mimicking a plaque-prone hemodynamic environment, and unidirectional flow, to mimicking a physiologically protective (plaquefree) environment. The effect of these hemodynamic forces on the remodeling response are characterized through the study of endothelial and smooth muscle cell function as well as through assessment of agents influencing extracellular matrix turnover. The conclusions section presents a synthesis of the results and contribution of this thesis and proposes perspectives for future studies.

EPFL2004

L’adaptation de l’homme à l’implant cochléaire

Julien Gassino

2010

Tracking genes of ecological relevance using a genome scan in two independent regional population samples of Arabis alpina

Doris Herrmann, Pierre Taberlet

Understanding the genetic basis of adaptation in response to environmental variation is fundamental as adaptation plays a key role in the extension of ecological niches to marginal habitats and in ecological speciation. Based on the assumption that some genomic markers are correlated to environmental variables, we aimed to detect loci of ecological relevance in the alpine plant Arabis alpina L. sampled in two regions, the French (99 locations) and the Swiss (109 locations) Alps. We used an unusually large genome scan [825 amplified fragment length polymorphism loci (AFLPs)] and four environmental variables related to temperature, precipitation and topography. We detected linkage disequilibrium among only 3.5% of the considered AFLP loci. A population structure analysis identified no admixture in the study regions, and the French and Swiss Alps were differentiated and therefore could be considered as two independent regions. We applied generalized estimating equations (GEE) to detect ecologically relevant loci separately in the French and Swiss Alps. We identified 78 loci of ecological relevance (9%), which were mainly related to mean annual minimum temperature. Only four of these loci were common across the French and Swiss Alps. Finally, we discuss that the genomic characterization of these ecologically relevant loci, as identified in this study, opens up new perspectives for studying functional ecology in A. alpina, its relatives and other alpine plant species.

2010

Cultural Adaptation, Validation, and Psychometric Description of the Pictorial Empathy Test (PET) in the Spanish Population

Maria del Carmen Sandi Perez

Research in psychology and social neuroscience distinguishes between dispositional and situational empathy for the cognitive and affective aspects of empathy. Yet, the Pictorial Empathy Test (PET) is one of the few brief tests focusing on situational affective empathy. This paper describes the adaptation of PET in a two-stage process, consisting of instrument translation and exploratory analysis of the construct in a university student sample, followed by confirmatory factor analysis and psychometric validation in a general population sample (Study 1, N = 79 and Study 2, N = 580). Our results indicate that the Spanish PET version constitutes a single factor structure with high internal consistency as well as high construct stability across genders and across in-person and online test administration setups. We report satisfactory convergent, discriminant, and nomological validity of the Spanish PET, as reported for the original version, in addition to when explored across new dimensions, like the Interpersonal Reactivity Index or in relation to age and prosocial tendencies. Based on the above, we discuss delineation of the distinct components of emotional empathy as measured by the instrument. The work presented supports the use of the Spanish PET version as a brief screening toot for state affective (emotional) empathy.

HOGREFE PUBLISHING CORP2022

On the Role of Constraints in Optimization under Uncertainty

Saurabh Anand Deshpande

This thesis addresses the problem of industrial real-time process optimization that suffers from the presence of uncertainty. Since a process model is typically used to compute the optimal operating conditions, both plant-model mismatch and process disturbances can result in suboptimal or, worse, infeasible operation. Hence, for practical applications, methodologies that help avoid re-optimization during process operation, at the cost of an acceptable optimality loss, become important. The design and analysis of such approximate solution strategies in real-time optimization (RTO) demand a careful analysis of the components of the necessary conditions of optimality. This thesis analyzes the role of constraints in process optimality in the presence of uncertainty. This analysis is made in two steps. Firstly, a general analysis is developed to quantify the effect of input adaptation on process performance for static RTO problems. In the second part, the general features of input adaptation for dynamic RTO problems are analyzed with focus on the constraints. Accordingly, the thesis is organized in two parts: For static RTO, a joint analysis of the model optimal inputs, the plant optimal inputs and a class of adapted inputs, and For dynamic RTO, an analytical study of the effect of local adaptation of the model optimal inputs. The first part (Chapters 2 and 3) addresses the problem of adapting the inputs to optimize the plant. The investigation takes a constructive viewpoint, but it is limited to static RTO problems modeled as parametric nonlinear programming (pNLP) problems. In this approach, the inputs are not limited to being local adaptation of the model optimal inputs but, instead, they can change significantly to optimize the plant. Hence, one needs to consider the fact that the set of active constraints for the model and the plant can be different. It is proven that, for a wide class of systems, the detection of a change in the active set contributes only negligibly to optimality, as long as the adapted solution remains feasible. More precisely, if η denotes the magnitude of the parametric variations and if the linear independence constraint qualification (LICQ) and strong second-order sufficient condition (SSOSC) hold for the underlying pNLP, the optimality loss due to any feasible input that conserves only the strict nominal active set is of magnitude O(η2), irrespective of whether or not there is a change in the set of active constraints. The implication of this result for a static RTO algorithm is to prioritize the satisfaction of only a core set of constraints, as long as it is possible to meet the feasibility requirements. The second part (Chapters 4 and 5) of the thesis deals with a way of adapting the model optimal inputs in dynamic RTO problems. This adaptation is made along two sets of directions such that one type of adaptation does not affect the nominally active constraints, while the other does. These directions are termed the sensitivity-seeking (SS) and the constraint-seeking (CS) directions, respectively. The SS and CS directions are defined as elements of a fairly general function space of input variations. A mathematical criterion is derived to define SS directions for a general class of optimal control problems involving both path and terminal constraints. According to this criterion, the SS directions turn out to be solutions of linear integral equations that are completely defined by the model optimal solution. The CS directions are then chosen orthogonal to the subspace of SS directions, where orthogonality is defined with respect to a chosen inner product on the space of input variations. It follows that the corresponding subspaces are infinite-dimensional subspaces of the function space of input variations. It is proven that, when uncertainty is modeled in terms of small parametric variations, the aforementioned classification of input adaptation leads to clearly distinguishable cost variations. More precisely, if η denotes the magnitude of the parametric variations, adaptation of the model optimal inputs along SS directions causes a cost variation of magnitude O(η2). On the other hand, the cost variation due to input adaptation along CS directions is of magnitude O(η). Furthermore, a numerical procedure is proposed for computing the SS and CS components of a given input variation. These components are projections of the input variation on the infinite-dimensional subspaces of SS and CS directions. The numerical procedure consists of the following three steps: approximation of the optimal control problem by a pNLP problem, projection of the given direction on the finite-dimensional SS and CS subspaces of the pNLP and, finally, reconstruction of the SS and CS components of the original problem from those of the pNLP.

EPFL2012

Exploring barriers to climate change adaptation in the Swiss tourism sector

Cecilia Matasci, Philippe Thalmann

Increasingly, various sectors are affected by climate change and need to find ways to adapt with much public guidance and support. This paper examines the adaptation process of a sector that started it some time ago - Swiss Alpine tourism. It identifies barriers that may be relevant for all sectors, all along the successive phases of the adaptation process. It additionally identifies the barriers which are most important and how these can be overcome. In order to do this we use an online survey directed to Swiss tourism stakeholders. Our results indicate that both economic and social feasibility barriers are important impediments to the adjustment process, whereas the acceptability among inhabitants and the willingness to act of stakeholders appear less critical. These barriers can be overcome and adaptation facilitated with more and especially better information about the regional consequences of climate change and feasible adaptation measures, by some top-down leadership and coordination, and by providing financial support.

Springer Verlag2014

Coral cover surveys corroborate predictions on reef adaptive potential to thermal stress

Véronique Berteaux-Lecellier, Stéphane Joost, Oliver Michele Selmoni

As anomalous heat waves are causing the widespread decline of coral reefs worldwide, there is an urgent need to identify coral populations tolerant to thermal stress. Heat stress adaptive potential is the degree of tolerance expected from evolutionary processes and, for a given reef, depends on the arrival of propagules from reefs exposed to recurrent thermal stress. For this reason, assessing spatial patterns of thermal adaptation and reef connectivity is of paramount importance to inform conservation strategies. In this work, we applied a seascape genomics framework to characterize the spatial patterns of thermal adaptation and connectivity for coral reefs of New Caledonia (Southern Pacific). In this approach, remote sensing of seascape conditions was combined with genomic data from three coral species. For every reef of the region, we computed a probability of heat stress adaptation, and two indices forecasting inbound and outbound connectivity. We then compared our indicators to field survey data, and observed that decrease of coral cover after heat stress was lower at reefs predicted with high probability of adaptation and inbound connectivity. Last, we discussed how these indicators can be used to inform local conservation strategies and preserve the adaptive potential of New Caledonian reefs.

2020

A Framework for Coupled Simulations of Robots and Spiking Neuronal Networks

Nino Cauli, Oliver Denninger, Egidio Falotico, Marc-Oliver Gewaltig, Henning Groenda, Georg Hinkel, Stefan Ulbrich, Lorenzo Vannucci

Bio-inspired robots still rely on classic robot control although advances in neurophysiology allow adaptation to control as well. However, the connection of a robot to spiking neuronal networks needs adjustments for each purpose and requires frequent adaptation during an iterative development. Existing approaches cannot bridge the gap between robotics and neuroscience or do not account for frequent adaptations. The contribution of this paper is an architecture and domain-specific language (DSL) for connecting robots to spiking neuronal networks for iterative testing in simulations, allowing neuroscientists to abstract from implementation details. The framework is implemented in a web-based platform. We validate the applicability of our approach with a case study based on image processing for controlling a four-wheeled robot in an experiment setting inspired by Braitenberg vehicles.

Springer Verlag2017

Gene expression analysis of metastases and IL-1R1 characterization in a NALP3 mouse model

Heidi Fournier

Tumor microenvironment contributes strongly to tumor evolution toward metastasis, a final stage in cancer progression. It provides essential clues to promote migration of cancer cells in metastatic sites. Moreover, inflammatory cells and immunomodulatory mediators present in the microenvironment are able to polarize the host immune response, thereby potentiating primary tumor development. The reciprocal and dynamic interactions between microenvironment and tumor cells orchestrate critical steps of evolution toward metastasis. To address the role of inflammation in tumor progression, a mouse model of downregulated inflammation was used: the NALP3 gene in these mice is knocked-out, causing a impaired processing of the two inflammatory cytokines Interleukin-1[beta] and IL-18 which are essential for the recruitment and activation of immune cells. In this case, a decrease in tumor growth and metastasis was observed in previous studies, leading us to investigate the molecular and cellular interactions of tumor and immune cells in inflammatory and non-inflammatory contexts. Gene expression analysis was performed on two steps of mouse tumor cells: the B16-F10 melanoma cells seem to be more dependent on the immune cells recruitment to metastasize in vivo, while the Lewis Lung Carcinomas cells showed a quite equivalent growth in both wild-type or NALP3 knock-out mice. Different techniques were used to do so, such as standard in vitro assays and mRNA expression analyses, and in vivo tests with extraction of tumoral mRNA by Laser Capture Microdissection. Gene expression analyses of tumor cells were performed to address the influence of the inflammatory background. Comparison of these two gene expression profiles may reveal genes related to the specific reactive inflammatory response surrounding the given metastases. Another point that was investigated was the importance of the IL-1R1, receptor of interleukin-1. Since it represents the counterpart of IL-1[beta] signaling, its expression by immune and tumor cells may correlate with degree of tumor growth and invasion. In vitro and in vivo assays allowed better understanding the importance of this receptor. While a downregulation of this receptor impairs proliferation of in vitro cell cultures, at the in vivo level, the number of metastases is decreased too. These results provide potential clues indicating the important role played by the inflammatory cells, and how they can support and promote tumor progression, in particular through the expression of NALP3. The adaptation mechanisms of tumor cells to their microenvironment were also assessed, opening different insights for targeting the tumor itself as well as the inflammatory microenvironment.

2011

Dynamic mesh adaptation on unstructured grids, by localised refinement and derefinement, is a very efficient tool for enhancing solution accuracy and optimise computational time. One of the major drawbacks however resides in the projection of the new nodes created, during the refinement process, onto the boundary surfaces. This can be addressed by the introduction of a library capable of handling geometric properties given by a CAD (Computer Aided Design) description. This is of particular interest also to enhance the adaptation module when the mesh is being smoothed, and hence moved, to then re-project it onto the surface of the exact geometry. However, the above procedure is not always possibly due to either faulty or too complex designs, which require a higher level of complexity in the CAD library. It is therefore paramount to have a built-in algorithm able to place the new nodes, belonging to the boundary, closer to the geometric definition of it. Such a procedure is proposed in this work, based on the idea of interpolating subdivision. In order to efficiently and effectively adapt a mesh to a solution field, the criteria used for the adaptation process needs to be as accurate as possible. Due to the nature of the solution, which is obtained by discretisation of a continuum model, numerical error is intrinsic in the calculation. A posteriori error estimation allows us to somewhat assess the accuracy by using the computed solution itself. In particular, an a posteriori error estimator based on the Zienkievicz Zhu model is introduced. This can be used in the adaptation procedure to refine the mesh in those areas where the local error exceeds a set tolerance, hence further increasing the accuracy of the solution in those regions during the next computational step. Variants of this error estimator have also been studied and implemented. One of the important aspects of this project is the fact that the algorithmic concepts are developed thinking parallel, i.e. the algorithms take into account the possibility of multiprocessor implementation. Indeed these concepts require complex programming if one tries to parallelise them, once they have been devised serially. Another important and innovative aspect of this work is the consistency of the algorithms with parallel processor execution.

EPFL2008