Towards a global criteria based framework for the sustainability assessment of bioethanol supply chains: application to the Swiss dilemma : is local produced bioethanol more sustainable than bioethanol imported from Brazil?

Biofuels are considered as a promising substitute for fossil fuels when considering the possible reduction of greenhouse gases emissions. However limiting their impacts on potential benefits for reducing climate change is shortsighted. Global sustainability assessments are necessary to determine the sustainability of supply chains. We propose a new global criterion based framework enabling a comprehensive international comparison of bioethanol supply chains. The interest of this framework is that the selection of the sustainability indicators is qualified on three criterions: relevance, reliability and adaptability to the local context. Sustainability issues have been handled along environmental, social and economical issues. This new framework has been applied for a specific issue: from a Swiss perspective, is locally produced bioethanol in Switzerland more sustainable than imported from Brazil? Thanks to this framework integrating local context in its indicator definition, Brazilian production of bioethanol is shown as energy efficient and economically interesting for Brazil. From a strictly economic point of view, bioethanol production within Switzerland is not justified for Swiss consumption and questionable for the environmental issue. The social dimension is delicate to assess due to the lack of reliable data and is strongly linked to the agricultural policy in both countries. There is a need of establishing minimum sustainability criteria for imported bioethanol to avoid unwanted negative or leakage effects.

A framework to understand the variations of PSD-95 expression in brain aging and in Alzheimer's disease.

The postsynaptic density protein PSD-95 is a major element of synapses. PSD-95 is involved in aging, Alzheimer's disease (AD) and numerous psychiatric disorders. However, contradictory data about PSD-95 expression in aging and AD have been reported. Indeed in AD versus control brains PSD-95 varies according to regions, increasing in the frontal cortex, at least in a primary stage, and decreasing in the temporal cortex. In contrast, in transgenic mouse models of aging and AD PSD-95 expression is decreased, in behaviorally aged impaired versus unimpaired rodents it can decrease or increase and finally, it is increased in rodents grown in enriched environments. Different factors explain these contradictory results in both animals and humans, among others concomitant psychiatric endophenotypes, such as depression. The possible involvement of PSD-95 in reactive and/or compensatory mechanisms during AD progression is underscored, at least before the occurrence of important synaptic elimination. Thus, in AD but not in AD transgenic mice, enhanced expression might precede the diminution commonly observed in advanced aging. A two-compartments cell model, separating events taking place in cell bodies and synapses, is presented. Overall these data suggest that AD research will progress by untangling pathological from protective events, a prerequisite for effective therapeutic strategies.

A coherent neurobiological framework for functional neuroimaging provided by a model integrating compartmentalized energy metabolism.

Functional neuroimaging has undergone spectacular developments in recent years. Paradoxically, its neurobiological bases have remained elusive, resulting in an intense debate around the cellular mechanisms taking place upon activation that could contribute to the signals measured. Taking advantage of a modeling approach, we propose here a coherent neurobiological framework that not only explains several in vitro and in vivo observations but also provides a physiological basis to interpret imaging signals. First, based on a model of compartmentalized energy metabolism, we show that complex kinetics of NADH changes observed in vitro can be accounted for by distinct metabolic responses in two cell populations reminiscent of neurons and astrocytes. Second, extended application of the model to an in vivo situation allowed us to reproduce the evolution of intraparenchymal oxygen levels upon activation as measured experimentally without substantially altering the initial parameter values. Finally, applying the same model to functional neuroimaging in humans, we were able to determine that the early negative component of the blood oxygenation level-dependent response recorded with functional MRI, known as the initial dip, critically depends on the oxidative response of neurons, whereas the late aspects of the signal correspond to a combination of responses from cell types with two distinct metabolic profiles that could be neurons and astrocytes. In summary, our results, obtained with such a modeling approach, support the concept that both neuronal and glial metabolic responses form essential components of neuroimaging signals.

Conceptual framework for strengthening exercises to prevent hamstring strains

High-speed running accounts for the majority of hamstring strains in many sports. The terminal swing phase is believed to be the most hazardous as the hamstrings are undergoing an active lengthening contraction in a long muscle length position. Prevention-based strength training mainly focuses on eccentric exercises. However, it appears crucial to integrate other parameters than the contraction type. Therefore, the aim of this study is to present a conceptual framework based on six key parameters (contraction type, load, range of motion, angular velocity, uni-/bilateral exercises, kinetic chain) for the hamstring's strength exercise for strain prevention. Based on the biomechanical parameters of sprinting, it is proposed to use high-load eccentric contractions. The movement should be performed at a slow to moderate angular velocity and focused at the knee joint, while the hip is kept in a large flexion position in order to reach a greater elongation stress of the hamstrings than in the terminal swing phase. In this way, we believe that, during sprinting, athletes would be better trained to brake the knee extension effectively in the whole range of motion without overstretch of the hamstrings. Finally, based on its functional application, unilateral open kinetic chain should be preferred.

KCM, a general framework for codon-based model of evolution

With the advancement of high-throughput sequencing and dramatic increase of available genetic data, statistical modeling has become an essential part in the field of molecular evolution. Statistical modeling results in many interesting discoveries in the field, from detection of highly conserved or diverse regions in a genome to phylogenetic inference of species evolutionary history Among different types of genome sequences, protein coding regions are particularly interesting due to their impact on proteins. The building blocks of proteins, i.e. amino acids, are coded by triples of nucleotides, known as codons. Accordingly, studying the evolution of codons leads to fundamental understanding of how proteins function and evolve. The current codon models can be classified into three principal groups: mechanistic codon models, empirical codon models and hybrid ones. The mechanistic models grasp particular attention due to clarity of their underlying biological assumptions and parameters. However, they suffer from simplified assumptions that are required to overcome the burden of computational complexity. The main assumptions applied to the current mechanistic codon models are (a) double and triple substitutions of nucleotides within codons are negligible, (b) there is no mutation variation among nucleotides of a single codon and (c) assuming HKY nucleotide model is sufficient to capture essence of transition- transversion rates at nucleotide level. In this thesis, I develop a framework of mechanistic codon models, named KCM-based model family framework, based on holding or relaxing the mentioned assumptions. Accordingly, eight different models are proposed from eight combinations of holding or relaxing the assumptions from the simplest one that holds all the assumptions to the most general one that relaxes all of them. The models derived from the proposed framework allow me to investigate the biological plausibility of the three simplified assumptions on real data sets as well as finding the best model that is aligned with the underlying characteristics of the data sets. -- Avec l'avancement de séquençage à haut débit et l'augmentation dramatique des données géné¬tiques disponibles, la modélisation statistique est devenue un élément essentiel dans le domaine dé l'évolution moléculaire. Les résultats de la modélisation statistique dans de nombreuses découvertes intéressantes dans le domaine de la détection, de régions hautement conservées ou diverses dans un génome de l'inférence phylogénétique des espèces histoire évolutive. Parmi les différents types de séquences du génome, les régions codantes de protéines sont particulièrement intéressants en raison de leur impact sur les protéines. Les blocs de construction des protéines, à savoir les acides aminés, sont codés par des triplets de nucléotides, appelés codons. Par conséquent, l'étude de l'évolution des codons mène à la compréhension fondamentale de la façon dont les protéines fonctionnent et évoluent. Les modèles de codons actuels peuvent être classés en trois groupes principaux : les modèles de codons mécanistes, les modèles de codons empiriques et les hybrides. Les modèles mécanistes saisir une attention particulière en raison de la clarté de leurs hypothèses et les paramètres biologiques sous-jacents. Cependant, ils souffrent d'hypothèses simplificatrices qui permettent de surmonter le fardeau de la complexité des calculs. Les principales hypothèses retenues pour les modèles actuels de codons mécanistes sont : a) substitutions doubles et triples de nucleotides dans les codons sont négligeables, b) il n'y a pas de variation de la mutation chez les nucléotides d'un codon unique, et c) en supposant modèle nucléotidique HKY est suffisant pour capturer l'essence de taux de transition transversion au niveau nucléotidique. Dans cette thèse, je poursuis deux objectifs principaux. Le premier objectif est de développer un cadre de modèles de codons mécanistes, nommé cadre KCM-based model family, sur la base de la détention ou de l'assouplissement des hypothèses mentionnées. En conséquence, huit modèles différents sont proposés à partir de huit combinaisons de la détention ou l'assouplissement des hypothèses de la plus simple qui détient toutes les hypothèses à la plus générale qui détend tous. Les modèles dérivés du cadre proposé nous permettent d'enquêter sur la plausibilité biologique des trois hypothèses simplificatrices sur des données réelles ainsi que de trouver le meilleur modèle qui est aligné avec les caractéristiques sous-jacentes des jeux de données. Nos expériences montrent que, dans aucun des jeux de données réelles, tenant les trois hypothèses mentionnées est réaliste. Cela signifie en utilisant des modèles simples qui détiennent ces hypothèses peuvent être trompeuses et les résultats de l'estimation inexacte des paramètres. Le deuxième objectif est de développer un modèle mécaniste de codon généralisée qui détend les trois hypothèses simplificatrices, tandis que d'informatique efficace, en utilisant une opération de matrice appelée produit de Kronecker. Nos expériences montrent que sur un jeux de données choisis au hasard, le modèle proposé de codon mécaniste généralisée surpasse autre modèle de codon par rapport à AICc métrique dans environ la moitié des ensembles de données. En outre, je montre à travers plusieurs expériences que le modèle général proposé est biologiquement plausible.

Accurate and efficient simulation of multiphase flow in a heterogeneous reservoir by using error estimate and control in the multiscale finite-volume framework

The multiscale finite-volume (MSFV) method is designed to reduce the computational cost of elliptic and parabolic problems with highly heterogeneous anisotropic coefficients. The reduction is achieved by splitting the original global problem into a set of local problems (with approximate local boundary conditions) coupled by a coarse global problem. It has been shown recently that the numerical errors in MSFV results can be reduced systematically with an iterative procedure that provides a conservative velocity field after any iteration step. The iterative MSFV (i-MSFV) method can be obtained with an improved (smoothed) multiscale solution to enhance the localization conditions, with a Krylov subspace method [e.g., the generalized-minimal-residual (GMRES) algorithm] preconditioned by the MSFV system, or with a combination of both. In a multiphase-flow system, a balance between accuracy and computational efficiency should be achieved by finding a minimum number of i-MSFV iterations (on pressure), which is necessary to achieve the desired accuracy in the saturation solution. In this work, we extend the i-MSFV method to sequential implicit simulation of time-dependent problems. To control the error of the coupled saturation/pressure system, we analyze the transport error caused by an approximate velocity field. We then propose an error-control strategy on the basis of the residual of the pressure equation. At the beginning of simulation, the pressure solution is iterated until a specified accuracy is achieved. To minimize the number of iterations in a multiphase-flow problem, the solution at the previous timestep is used to improve the localization assumption at the current timestep. Additional iterations are used only when the residual becomes larger than a specified threshold value. Numerical results show that only a few iterations on average are necessary to improve the MSFV results significantly, even for very challenging problems. Therefore, the proposed adaptive strategy yields efficient and accurate simulation of multiphase flow in heterogeneous porous media.

CSF1R mutations link POLD and HDLS as a single disease entity.

OBJECTIVE: Pigmented orthochromatic leukodystrophy (POLD) and hereditary diffuse leukoencephalopathy with axonal spheroids (HDLS) are rare neurodegenerative disorders characterized by cerebral white matter abnormalities, myelin loss, and axonal swellings. The striking overlap of clinical and pathologic features of these disorders suggested a common pathogenesis; however, no genetic or mechanistic link between POLD and HDLS has been established. Recently, we reported that mutations in the colony-stimulating factor 1 receptor (CSF1R) gene cause HDLS. In this study, we determined whether CSF1R mutations are also a cause of POLD. METHODS: We performed sequencing of CSF1R in 2 pathologically confirmed POLD families. For the largest family (FTD368), a detailed case report was provided and brain samples from 2 affected family members previously diagnosed with POLD were re-evaluated to determine whether they had HDLS features. In vitro functional characterization of wild-type and mutant CSF1R was also performed. RESULTS: We identified CSF1R mutations in both POLD families: in family 5901, we found c.2297T>C (p.M766T), previously reported by us in HDLS family CA1, and in family FTD368, we identified c.2345G>A (p.R782H), recently reported in a biopsy-proven HDLS case. Immunohistochemical examination in family FTD368 showed the typical neuronal and glial findings of HDLS. Functional analyses of CSF1R mutant p.R782H (identified in this study) and p.M875T (previously observed in HDLS), showed a similar loss of CSF1R autophosphorylation of selected tyrosine residues in the kinase domain for both mutations when compared with wild-type CSF1R. CONCLUSIONS: We provide the first genetic and mechanistic evidence that POLD and HDLS are a single clinicopathologic entity.

A Three-Dimensional Framework to Analyse the Governance of Population Registers

In June 2006, the Swiss Parliament made two important decisions with regards to public registers' governance and individuals' identification. It adopted a new law on the harmonisation of population registers in order to simplify statistical data collection and data exchange from around 4'000 decentralized registers, and it also approved the introduction of a Unique Person Identifier (UPI). The law is rather vague about the implementation of this harmonisation and even though many projects are currently being undertaken in this domain, most of them are quite technical. We believe there is a need for analysis tools and therefore we propose a conceptual framework based on three pillars (Privacy, Identity and Governance) to analyse the requirements in terms of data management for population registers.

Schizotypy as an organizing framework for social and affective sciences

Schizotypy, defined in terms of commonly occurring personality traits related to the schizophrenia spectrum, has been an important construct for understanding the neurodevelopment and stress-diathesis of schizophrenia. However, as schizotypy nears its sixth decade of application, it is important to acknowledge its impressively rich literature accumulating outside of schizophrenia research. In this article, we make the case that schizotypy has considerable potential as a conceptual framework for understanding individual differences in affective and social functions beyond those directly involved in schizophrenia spectrum pathology. This case is predicated on (a) a burgeoning literature noting anomalies in a wide range of social functioning, affiliative, positive and negative emotional, expressive, and social cognitive systems, (b) practical and methodological features associated with schizotypy research that help facilitate empirical investigation, and (c) close ties to theoretical constructs of central importance to affective and social science (eg, stress diathesis, neural compensation). We highlight recent schizotypy research, ie providing insight into the nature of affective and social systems more generally. This includes current efforts to clarify the neurodevelopmental, neurobiological, and psychological underpinnings of affiliative drives, hedonic capacity, social cognition, and stress responsivity systems. Additionally, we discuss neural compensatory and resilience factors that may mitigate the expression of stress-diathesis and functional outcome, and highlight schizotypy's potential role for understanding cultural determinants of social and affective functions.

The connectome viewer toolkit: an open source framework to manage, analyze, and visualize connectomes.

Advanced neuroinformatics tools are required for methods of connectome mapping, analysis, and visualization. The inherent multi-modality of connectome datasets poses new challenges for data organization, integration, and sharing. We have designed and implemented the Connectome Viewer Toolkit - a set of free and extensible open source neuroimaging tools written in Python. The key components of the toolkit are as follows: (1) The Connectome File Format is an XML-based container format to standardize multi-modal data integration and structured metadata annotation. (2) The Connectome File Format Library enables management and sharing of connectome files. (3) The Connectome Viewer is an integrated research and development environment for visualization and analysis of multi-modal connectome data. The Connectome Viewer's plugin architecture supports extensions with network analysis packages and an interactive scripting shell, to enable easy development and community contributions. Integration with tools from the scientific Python community allows the leveraging of numerous existing libraries for powerful connectome data mining, exploration, and comparison. We demonstrate the applicability of the Connectome Viewer Toolkit using Diffusion MRI datasets processed by the Connectome Mapper. The Connectome Viewer Toolkit is available from http://www.cmtk.org/