Functional dynamics of PDZ binding domains: a normal-mode analysis.

Postsynaptic density-95/disks large/zonula occludens-1 (PDZ) domains are relatively small (80-120 residues) protein binding modules central in the organization of receptor clusters and in the association of cellular proteins. Their main function is to bind C-terminals of selected proteins that are recognized through specific amino acids in their carboxyl end. Binding is associated with a deformation of the PDZ native structure and is responsible for dynamical changes in regions not in direct contact with the target. We investigate how this deformation is related to the harmonic dynamics of the PDZ structure and show that one low-frequency collective normal mode, characterized by the concerted movements of different secondary structures, is involved in the binding process. Our results suggest that even minimal structural changes are responsible for communication between distant regions of the protein, in agreement with recent NMR experiments. Thus, PDZ domains are a very clear example of how collective normal modes are able to characterize the relation between function and dynamics of proteins, and to provide indications on the precursors of binding/unbinding events.

Telomere length dynamics in human lymphocyte subpopulations measured by flow cytometry.

To measure the average length of telomere repeats at chromosome ends in individual cells we developed a flow cytometry method using fluorescence in situ hybridization (flow FISH) with labeled peptide nucleic acid (PNA) probes. Results of flow FISH measurements correlated with results of conventional telomere length measurements by Southern blot analysis (R = 0.9). Consistent differences in telomere length in CD8+ T-cell subsets were identified. Naive and memory CD4+ T lymphocytes in normal adults differed by around 2.5 kb in telomere length, in agreement with known replicative shortening of telomeres in lymphocytes in vivo. T-cell clones grown in vitro showed stabilization of telomere length after an initial decline and rare clones capable of growing beyond 100 population doublings showed variable telomere length. These results show that flow FISH can be used to measure specific nucleotide repeat sequences in single cells and indicate that the very large replicative potential of lymphocytes is only indirectly related to telomere length.

Cannabinoid addiction: behavioral models and neural correlates

The use of cannabis sativa preparations as recreational drugs can be traced back to the earliest civilizations. However, animal models of cannabinoid addiction allowing the exploration of neural correlates of cannabinoid abuse have been developed only recently. We review these models and the role of the CB1 cannabinoid receptor, the main target of natural cannabinoids, and its interaction with opioid and dopamine transmission in reward circuits. Extensive reviews on the molecular basis of cannabinoid action are available elsewhere (Piomelli et al., 2000;Schlicker and Kathmann, 2001).

The role of computational fluid dynamics in the management of unruptured intracranial aneurysms: a clinicians' view

Objective: The importance of hemodynamics in the etiopathogenesis of intracranial aneurysms (IAs) is widely accepted.Computational fluid dynamics (CFD) is being used increasingly for hemodynamic predictions. However, alogn with thecontinuing development and validation of these tools, it is imperative to collect the opinion of the clinicians. Methods: A workshopon CFD was conducted during the European Society of Minimally Invasive Neurological Therapy (ESMINT) Teaching Course,Lisbon, Portugal. 36 delegates, mostly clinicians, performed supervised CFD analysis for an IA, using the @neuFuse softwaredeveloped within the European project @neurIST. Feedback on the workshop was collected and analyzed. The performancewas assessed on a scale of 1 to 4 and, compared with experts’ performance. Results: Current dilemmas in the management ofunruptured IAs remained the most important motivating factor to attend the workshop and majority of participants showedinterest in participating in a multicentric trial. The participants achieved an average score of 2.52 (range 0–4) which was 63% (range 0–100%) of an expert user. Conclusions: Although participants showed a manifest interest in CFD, there was a clear lack ofawareness concerning the role of hemodynamics in the etiopathogenesis of IAs and the use of CFD in this context. More effortstherefore are required to enhance understanding of the clinicians in the subject.

Leveraging explicitly disclosed location information to understand tourist dynamics: a case study

In recent years, the large deployment of mobile devices has led to a massiveincrease in the volume of records of where people have been and when they were there.The analysis of these spatio-temporal data can supply high-level human behaviorinformation valuable to urban planners, local authorities, and designer of location-basedservices. In this paper, we describe our approach to collect and analyze the history ofphysical presence of tourists from the digital footprints they publicly disclose on the web.Our work takes place in the Province of Florence in Italy, where the insights on thevisitors’ flows and on the nationalities of the tourists who do not sleep in town has beenlimited to information from survey-based hotel and museums frequentation. In fact, mostlocal authorities in the world must face this dearth of data on tourist dynamics. In thiscase study, we used a corpus of geographically referenced photos taken in the provinceby 4280 photographers over a period of 2 years. Based on the disclosure of the locationof the photos, we design geovisualizations to reveal the tourist concentration and spatiotemporalflows. Our initial results provide insights on the density of tourists, the points ofinterests they visit as well as the most common trajectories they follow.

What can spike train distances tell us about the neural code?

Time scale parametric spike train distances like the Victor and the van Rossum distancesare often applied to study the neural code based on neural stimuli discrimination.Different neural coding hypotheses, such as rate or coincidence coding,can be assessed by combining a time scale parametric spike train distance with aclassifier in order to obtain the optimal discrimination performance. The time scalefor which the responses to different stimuli are distinguished best is assumed to bethe discriminative precision of the neural code. The relevance of temporal codingis evaluated by comparing the optimal discrimination performance with the oneachieved when assuming a rate code.We here characterize the measures quantifying the discrimination performance,the discriminative precision, and the relevance of temporal coding. Furthermore,we evaluate the information these quantities provide about the neural code. Weshow that the discriminative precision is too unspecific to be interpreted in termsof the time scales relevant for encoding. Accordingly, the time scale parametricnature of the distances is mainly an advantage because it allows maximizing thediscrimination performance across a whole set of measures with different sensitivitiesdetermined by the time scale parameter, but not due to the possibility toexamine the temporal properties of the neural code.

Bilinear models for spatio-temporal point distribution analysis: application to extrapolation of left ventricular, biventricular and whole heart cardiac dynamics

In this work we describe the usage of bilinear statistical models as a means of factoring the shape variability into two components attributed to inter-subject variation and to the intrinsic dynamics of the human heart. We show that it is feasible to reconstruct the shape of the heart at discrete points in the cardiac cycle. Provided we are given a small number of shape instances representing the same heart atdifferent points in the same cycle, we can use the bilinearmodel to establish this. Using a temporal and a spatial alignment step in the preprocessing of the shapes, around half of the reconstruction errors were on the order of the axial image resolution of 2 mm, and over 90% was within 3.5 mm. From this, weconclude that the dynamics were indeed separated from theinter-subject variability in our dataset.

Dynamics of diversity within the Mossos d’Esquadra

This chapter offers a case-study of diversity and diversity policies withinthe Mossos d’Esquadra, the police force of the Catalan autonomous communityin Spain. The case is described in a comprehensive way (includingpolicies in all relevant policy areas: recruitment, retention, and promotion)and at the same time analyzed with a new analytical framework (includingthe definition of diversity, the motivation for diversity within the organisation,and the facilitation of diversity within the organisation with policies).The goal of the chapter is twofold. First, offer a deeper understanding ofthe dynamics of diversity within this police force. Second, demonstrate theacademic potential of this new analytical framework.

The history and role of long duration stimulation in fMRI.

During the past 20 years, BOLD fMRI has developed towards a central and fundamental tool in neuroscience. It has been shown that the BOLD response provides an indicator of neuronal activity in the brain. Consequently, for an accurate interpretation of findings in BOLD MRI experiments and to draw meaningful conclusions about the temporal evolution of neural events, a deep understanding of the nature of the BOLD contrast has become of essential importance. Since the dynamics of the major direct determinants of the BOLD signal (CBF, CBV and CMRO(2)) range between seconds and minutes, long duration stimulation was an early key strategy needed to study and understand the BOLD characteristics. This paper summarizes and discusses the thoughts and rationales of the long duration stimulation studies.

The dynamics of the Swiss electricity market : three essays

Executive Summary Electricity is crucial for modern societies, thus it is important to understand the behaviour of electricity markets in order to be prepared to face the consequences of policy changes. The Swiss electricity market is now in a transition stage from a public monopoly to a liberalised market and it is undergoing an "emergent" liberalisation - i.e. liberalisation taking place without proper regulation. The withdrawal of nuclear capacity is also being debated. These two possible changes directly affect the mechanisms for capacity expansion. Thus, in this thesis we concentrate on understanding the dynamics of capacity expansion in the Swiss electricity market. A conceptual model to help understand the dynamics of capacity expansion in the Swiss electricity market is developed an explained in the first essay. We identify a potential risk of imports dependence. In the second essay a System Dynamics model, based on the conceptual model, is developed to evaluate the consequences of three scenarios: a nuclear phase-out, the implementation of a policy for avoiding imports dependence, and the combination of both. We conclude that the Swiss market is not well prepared to face unexpected changes of supply and demand, and we identify a risk of imports dependence, mainly in the case of a nuclear phase-out. The third essay focus on the opportunity cost of hydro-storage power generation, one of the main generation sources in Switzerland. We use and extended version of our model to test different policies for assigning an opportunity cost to hydro-storage power generation. We conclude that the preferred policies are different for different market participants and depend on market structure.

Wavelet analysis residual kriging vs. neural network residual kriging

This paper deals with the problem of spatial data mapping. A new method based on wavelet interpolation and geostatistical prediction (kriging) is proposed. The method - wavelet analysis residual kriging (WARK) - is developed in order to assess the problems rising for highly variable data in presence of spatial trends. In these cases stationary prediction models have very limited application. Wavelet analysis is used to model large-scale structures and kriging of the remaining residuals focuses on small-scale peculiarities. WARK is able to model spatial pattern which features multiscale structure. In the present work WARK is applied to the rainfall data and the results of validation are compared with the ones obtained from neural network residual kriging (NNRK). NNRK is also a residual-based method, which uses artificial neural network to model large-scale non-linear trends. The comparison of the results demonstrates the high quality performance of WARK in predicting hot spots, reproducing global statistical characteristics of the distribution and spatial correlation structure.

Dual functions of DP1 promote biphasic Wnt-on and Wnt-off states during anteroposterior neural patterning.

DP1, a dimerization partner protein of the transcription factor E2F, is known to inhibit Wnt/β-catenin signalling along with E2F, although the function of DP1 itself was not well characterized. Here, we present a novel dual regulatory mechanism of Wnt/β-catenin signalling by DP1 independent from E2F. DP1 negatively regulates Wnt/β-catenin signalling by inhibiting Dvl-Axin interaction and by enhancing poly-ubiquitination of β-catenin. In contrast, DP1 positively modulates the signalling upon Wnt stimulation, via increasing cytosolic β-catenin and antagonizing the kinase activity of NLK. In Xenopus embryos, DP1 exerts both positive and negative roles in Wnt/β-catenin signalling during anteroposterior neural patterning. From subcellular localization analyses, we suggest that the dual roles of DP1 in Wnt/β-catenin signalling are endowed by differential nucleocytoplasmic localizations. We propose that these dual functions of DP1 can promote and stabilize biphasic Wnt-on and Wnt-off states in response to a gradual gradient of Wnt/β-catenin signalling to determine differential cell fates.

Financing Constraints, Irreversibility, and Investment Dynamics

We develop a model of an industry with many heterogeneous firms that face both financing constraints and irreversibility constraints. The financing constraint implies that firms cannot borrow unless the debt is secured by collateral; the irreversibility constraint that they can only sell their fixed capital by selling their business. We use this model to examine the cyclical behavior of aggregate fixed investment, variable capital investment, and output in the presence of persistent idiosyncratic and aggregate shocks. Our model yields three main results. First, the effect of the irreversibility constraint on fixed capital investment is reinforced by the financing constraint. Second, the effect of the financing constraint on variable capital investment is reinforced by the irreversibility constraint. Finally, the interaction between the two constraints is key for explaining why input inventories and material deliveries of US manufacturing firms are so volatile and procyclical, and also why they are highly asymmetrical over the business cycle.