Differential activation of the default mode network in jet lagged individuals

Long-term exposure to transmeridian flights has been shown to impact cognitive functioning. Nevertheless, the immediate effects of jet lag in the activation of specific brain networks have not been investigated. We analyzed the impact of short-term jet lag on the activation of the default mode network (DMN). A group of individuals who were on a transmeridian flight and a control group went through a functional magnetic resonance imaging acquisition. Statistical analysis was performed to test for differences in the DMN activation between groups. Participants from the jet lag group presented decreased activation in the anterior nodes of the DMN, specifically in bilateral medial prefrontal and anterior cingulate cortex. No areas of increased activation were observed for the jet lag group. These results may be suggestive of a negative impact of jet lag on important cognitive functions such as introspection, emotional regulation and decision making in a few days after individuals arrive at their destination.

A network approach to brain aging through multimodal neuroimaging

Tese de Doutoramento em Ciências da Saúde.

Algorithms and computational tools for metabolic flux analysis

PhD thesis in Biomedical Engineering

A modular traffic sampling architecture for flexible network measurements

Dissertação de Mestrado (Programa Doutoral em Informática)

System analysis of a Peer-to-Peer Video-on-Demand architecture: Kangaroo

Architectural design and deployment of Peer-to-Peer Video-on-Demand (P2PVoD) systems which support VCR functionalities is attracting the interest of an increasing number of research groups within the scientific community; especially due to the intrinsic characteristics of such systems and the benefits that peers could provide at reducing the server load. This work focuses on the performance analysis of a P2P-VoD system considering user behaviors obtained from real traces together with other synthetic user patterns. The experiments performed show that it is feasible to achieve a performance close to the best possible. Future work will consider monitoring the physical characteristics of the network in order to improve the design of different aspects of a VoD system.

Objective analysis of gait coordination for total knee arthroplasty outcome

Introduction: Coordination is a strategy chosen by the central nervous system to control the movements and maintain stability during gait. Coordinated multi-joint movements require a complex interaction between nervous outputs, biomechanical constraints, and pro-prioception. Quantitatively understanding and modeling gait coordination still remain a challenge. Surgeons lack a way to model and appreciate the coordination of patients before and after surgery of the lower limbs. Patients alter their gait patterns and their kinematic synergies when they walk faster or slower than normal speed to maintain their stability and minimize the energy cost of locomotion. The goal of this study was to provide a dynamical system approach to quantitatively describe human gait coordination and apply it to patients before and after total knee arthroplasty. Methods: A new method of quantitative analysis of interjoint coordination during gait was designed, providing a general model to capture the whole dynamics and showing the kinematic synergies at various walking speeds. The proposed model imposed a relationship among lower limb joint angles (hips and knees) to parameterize the dynamics of locomotion of each individual. An integration of different analysis tools such as Harmonic analysis, Principal Component Analysis, and Artificial Neural Network helped overcome high-dimensionality, temporal dependence, and non-linear relationships of the gait patterns. Ten patients were studied using an ambulatory gait device (Physilog®). Each participant was asked to perform two walking trials of 30m long at 3 different speeds and to complete an EQ-5D questionnaire, a WOMAC and Knee Society Score. Lower limbs rotations were measured by four miniature angular rate sensors mounted respectively, on each shank and thigh. The outcomes of the eight patients undergoing total knee arthroplasty, recorded pre-operatively and post-operatively at 6 weeks, 3 months, 6 months and 1 year were compared to 2 age-matched healthy subjects. Results: The new method provided coordination scores at various walking speeds, ranged between 0 and 10. It determined the overall coordination of the lower limbs as well as the contribution of each joint to the total coordination. The difference between the pre-operative and post-operative coordination values were correlated with the improvements of the subjective outcome scores. Although the study group was small, the results showed a new way to objectively quantify gait coordination of patients undergoing total knee arthroplasty, using only portable body-fixed sensors. Conclusion: A new method for objective gait coordination analysis has been developed with very encouraging results regarding the objective outcome of lower limb surgery.

Chemical genetic analysis of cdc2p : new insights into the regulation of cytokinesis in "Schizosaccharomyces pombe"

RÉSUMÉ La protéine kinase cyciine-cdc2p (Cdk) joue un rôle fondamental dans la progression du cycle cellulaire dans la levure de fission Schizosaccharomyces pombe. Nous avons étudié le rôle de cdc2p dans la régulation de la cascade de septation ou SIN (septation initiation network) en mitose et en méiose. Le SIN contrôle l'initiation de la cytokinèse à la fin de la mitose, et est supposé être négativement régulé par cdc2p. Nous avons mutagénéisé le site actif de cdc2p afin qu'il puisse lier un analogue de l'ATP (PP1) qui agit comme inhibiteur. Cet analogue ne peut pas lier la kinase de type sauvage. Cette approche dite «chemical genetics» permet une meilleure résolution temporelle comparée à l'approche classique utilisant les mutants sensibles à une température élevée. Nous avons montré que ce mutant cdc2-as (analogue sensitive) est fonctionnel et que, in vitro, l'activité kinase est inhibée en présence de l'analogue. Les cellules portant cette mutation, contrairement aux cellules de type sauvage s'arrêtent de manière irréversible soit en G2 soit en G1 et G2, suivant la concentration de l'inhibiteur. L'inactivation de cdc2p-as dans des cellules arrêtées en métaphase conduit au recrutement asymétrique des protéines du SIN sur le pôle du fuseau mitotique et au recrutement des composants du SIN, ainsi que de la ß-(1,3)glucan synthase à l'anneau contractile. De plus, nos résultats montrent que l'orthologue de la phosphatase cdc14p dans S. pombe, fip1p/clp1p, joue un rôle dans la régulation de la localisation des protéines du SIN suite à l'inactivation de cdc2p. Finalement, l'activité de cdc2p est requise pour maintenir la polo-like kinase plo1p sur les pôles du fuseau mitotique dans les premiers stages de la mitose. C'est pourquoi nous concluons que l'inactivation de cdc2p est suffisante pour activer le SIN et promouvoir la cytokinèse. Dans une étude séparée, nous avons caractérisé des potentiellement nouveaux composants ou régulateurs du SIN qui ont été isolés dans deux criblages génétiques visant à isoler des mutants atténuants la signalisation du SIN. Summary : The cyclin dependent protein kinase (Cdk) cdc2p plays a central role in the cell cycle progression of fission yeast Schizosaccharomyces pombe. We have studied the role of cdc2p in regulating the septation initiation network (SIN) in mitosis and meiosis. The SIN regulates the initiation of cytokinesis at the end of mitosis and is thought to be inhibited by cdc2p. We have mutated the active site of cdc2p to permit binding of an inhibitory ATP analogue (PP1), which is unable to bind unmodified kinases. This "chemical genetic" approach provides a much higher temporal resolution than it can be achieved with classical temperature-sensitive mutants. We demonstrate that cdc2-as (analogue sensitive) is functional and that addition of PP1 inhibits cdc2p kinase activity in vitro. Cells carrying the cdc2-as allele, but not cdc2+, undergo reversible cell cycle arrest following addition of PP1 either in G2, or at both major commitment points in the cell cycle (G1 and G2), depending upon the concentration of PP1. Inactivation of cdc2p-as in cells arrested in early mitosis promotes both the asymmetric recruitment of SIN proteins to the spindle pole bodies (SPBs), and the recruitment of the most downstream SIN components and ß-(1,3)-glucan synthase to the contractile ring. Furthermore, our results indicate that the S. pombe orthologue of Cdc14p, flp1p/clp1p, plays a role in regulating the relocalisation of SIN proteins following inactivation of cdc2p, and that cdc2p activity is required to retain the polo like kinase plot p on the SPBs in early mitosis. Thus, we conclude that inactivation of cdc2p is sufficient to activate the SIN and to promote cytokinesis. In a separate study, we have initially characterised potential novel components or regulators of the SIN pathway identified by two genetic screens for mutants attenuating SIN signaling.

Ultrastructural and stereological analysis of trypanosomatidis of the genus Endotrypanum

Culture forms of four strains of Endotrypanum (E. schaudinni and E. monterogeii) were processed for transmission electron microscopy and analyzed at the ultrastructural level. Quantitative data about some cytoplasmic organelles were obeined by stereology. All culture forms were promastigotes. In their cytoplasm four different organelles could be found: lipid inclusions (0,2-0,4 µm in diameter), mebrane-bounded vacuoles (0.10-0,28 µm in diameter), glycosomes (0,2-0,3 µm in diameter), and the mitochondrion. The kenetoplast appears as a thin band, except for the strain IM201, which possesses a broader structure, and possibly is not a member of this genus. Clusters of virus-like particles were seen in the cytoplasm of the strain LV88. The data obtained show that all strains have the typical morphological feature of the trypanosomatids. Only strain IM201 could be differentiated from the others, due to its larger kenetoplast-DNA network and its large mitochondrial and glycosomal relative volume. The morphometrical data did not allow the differentiation between E. schaudinni (strains IM217 and M6226) and E. monterogeii (strain LV88).

Primary pineal tumors: outcome and prognostic factors-a study from the Rare Cancer Network (RCN).

PURPOSE: To better define outcome and prognostic factors in primary pineal tumors. MATERIALS AND METHODS: Thirty-five consecutive patients from seven academic centers of the Rare Cancer Network diagnosed between 1988 and 2006 were included. Median age was 36 years. Surgical resection consisted of biopsy in 12 cases and resection in 21 (2 cases with unknown resection). All patients underwent radiotherapy and 12 patients received also chemotherapy. RESULTS: Histological subtypes were pineoblastoma (PNB) in 21 patients, pineocytoma (PC) in 8 patients and pineocytoma with intermediate differentiation in 6 patients. Six patients with PNB had evidence of spinal seeding. Fifteen patients relapsed (14 PNB and 1 PC) with PNB cases at higher risk (p = 0.031). Median survival time was not reached. Median disease-free survival was 82 months (CI 50 % 28-275). In univariate analysis, age younger than 36 years was an unfavorable prognostic factor (p = 0.003). Patients with metastases at diagnosis had poorer survival (p = 0.048). Late side effects related to radiotherapy were dementia, leukoencephalopathy or memory loss in seven cases, occipital ischemia in one, and grade 3 seizures in two cases. Side effects related to chemotherapy were grade 3-4 leucopenia in five cases, grade 4 thrombocytopenia in three cases, grade 2 anemia in two cases, grade 4 pancytopenia in one case, grade 4 vomiting in one case and renal failure in one case. CONCLUSIONS: Age and dissemination at diagnosis influenced survival in our series. The prevalence of chronic toxicity suggests that new adjuvant strategies are advisable.

Multilayer perceptron with local constraint as an emerging method in spatial data analysis

The use of Geographic Information Systems has revolutionalized the handling and the visualization of geo-referenced data and has underlined the critic role of spatial analysis. The usual tools for such a purpose are geostatistics which are widely used in Earth science. Geostatistics are based upon several hypothesis which are not always verified in practice. On the other hand, Artificial Neural Network (ANN) a priori can be used without special assumptions and are known to be flexible. This paper proposes to discuss the application of ANN in the case of the interpolation of a geo-referenced variable.

The multipoint Morisita index for the analysis of spatial patterns

In many fields, the spatial clustering of sampled data points has many consequences. Therefore, several indices have been proposed to assess the level of clustering affecting datasets (e.g. the Morisita index, Ripley's Kfunction and Rényi's generalized entropy). The classical Morisita index measures how many times it is more likely to select two measurement points from the same quadrats (the data set is covered by a regular grid of changing size) than it would be in the case of a random distribution generated from a Poisson process. The multipoint version (k-Morisita) takes into account k points with k >= 2. The present research deals with a new development of the k-Morisita index for (1) monitoring network characterization and for (2) detection of patterns in monitored phenomena. From a theoretical perspective, a connection between the k-Morisita index and multifractality has also been found and highlighted on a mathematical multifractal set.

SYSGENET: a meeting report from a new European network for systems genetics.

The first scientific meeting of the newly established European SYSGENET network took place at the Helmholtz Centre for Infection Research (HZI) in Braunschweig, April 7-9, 2010. About 50 researchers working in the field of systems genetics using mouse genetic reference populations (GRP) participated in the meeting and exchanged their results, phenotyping approaches, and data analysis tools for studying systems genetics. In addition, the future of GRP resources and phenotyping in Europe was discussed.

Dynamical modeling and analysis of large cellular regulatory networks.

The dynamical analysis of large biological regulatory networks requires the development of scalable methods for mathematical modeling. Following the approach initially introduced by Thomas, we formalize the interactions between the components of a network in terms of discrete variables, functions, and parameters. Model simulations result in directed graphs, called state transition graphs. We are particularly interested in reachability properties and asymptotic behaviors, which correspond to terminal strongly connected components (or "attractors") in the state transition graph. A well-known problem is the exponential increase of the size of state transition graphs with the number of network components, in particular when using the biologically realistic asynchronous updating assumption. To address this problem, we have developed several complementary methods enabling the analysis of the behavior of large and complex logical models: (i) the definition of transition priority classes to simplify the dynamics; (ii) a model reduction method preserving essential dynamical properties, (iii) a novel algorithm to compact state transition graphs and directly generate compressed representations, emphasizing relevant transient and asymptotic dynamical properties. The power of an approach combining these different methods is demonstrated by applying them to a recent multilevel logical model for the network controlling CD4+ T helper cell response to antigen presentation and to a dozen cytokines. This model accounts for the differentiation of canonical Th1 and Th2 lymphocytes, as well as of inflammatory Th17 and regulatory T cells, along with many hybrid subtypes. All these methods have been implemented into the software GINsim, which enables the definition, the analysis, and the simulation of logical regulatory graphs.

Analysis of nonlinear noisy integrate & fire neuron models: blow-up and steady states

Nonlinear Noisy Leaky Integrate and Fire (NNLIF) models for neurons networks can be written as Fokker-Planck-Kolmogorov equations on the probability density of neurons, the main parameters in the model being the connectivity of the network and the noise. We analyse several aspects of the NNLIF model: the number of steady states, a priori estimates, blow-up issues and convergence toward equilibrium in the linear case. In particular, for excitatory networks, blow-up always occurs for initial data concentrated close to the firing potential. These results show how critical is the balance between noise and excitatory/inhibitory interactions to the connectivity parameter.