FIB-SEM tomography in biology.

Three-dimensional information is much easier to understand than a set of two-dimensional images. Therefore a layman is thrilled by the pseudo-3D image taken in a scanning electron microscope (SEM) while, when seeing a transmission electron micrograph, his imagination is challenged. First approaches to gain insight in the third dimension were to make serial microtome sections of a region of interest (ROI) and then building a model of the object. Serial microtome sectioning is a tedious and skill-demanding work and therefore seldom done. In the last two decades with the increase of computer power, sophisticated display options, and the development of new instruments, an SEM with a built-in microtome as well as a focused ion beam scanning electron microscope (FIB-SEM), serial sectioning, and 3D analysis has become far easier and faster.Due to the relief like topology of the microtome trimmed block face of resin-embedded tissue, the ROI can be searched in the secondary electron mode, and at the selected spot, the ROI is prepared with the ion beam for 3D analysis. For FIB-SEM tomography, a thin slice is removed with the ion beam and the newly exposed face is imaged with the electron beam, usually by recording the backscattered electrons. The process, also called "slice and view," is repeated until the desired volume is imaged.As FIB-SEM allows 3D imaging of biological fine structure at high resolution of only small volumes, it is crucial to perform slice and view at carefully selected spots. Finding the region of interest is therefore a prerequisite for meaningful imaging. Thin layer plastification of biofilms offers direct access to the original sample surface and allows the selection of an ROI for site-specific FIB-SEM tomography just by its pronounced topographic features.

S-system parameter estimation for noisy metabolic profiles using newton-flow analysis.

Biochemical systems are commonly modelled by systems of ordinary differential equations (ODEs). A particular class of such models called S-systems have recently gained popularity in biochemical system modelling. The parameters of an S-system are usually estimated from time-course profiles. However, finding these estimates is a difficult computational problem. Moreover, although several methods have been recently proposed to solve this problem for ideal profiles, relatively little progress has been reported for noisy profiles. We describe a special feature of a Newton-flow optimisation problem associated with S-system parameter estimation. This enables us to significantly reduce the search space, and also lends itself to parameter estimation for noisy data. We illustrate the applicability of our method by applying it to noisy time-course data synthetically produced from previously published 4- and 30-dimensional S-systems. In addition, we propose an extension of our method that allows the detection of network topologies for small S-systems. We introduce a new method for estimating S-system parameters from time-course profiles. We show that the performance of this method compares favorably with competing methods for ideal profiles, and that it also allows the determination of parameters for noisy profiles.

Cellular and molecular mechanisms underlying the effects of sleep loss on hippocampal synaptic plasticity

SUMMARY : The function of sleep for the organism is one of the most persistent and perplexing questions in biology. Current findings lead to the conclusion that sleep is primarily for the brain. In particular, a role for sleep in cognitive aspects of brain function is supported by behavioral evidence both in humans and animals. However, in spite of remarkable advancement in the understanding of the mechanisms underlying sleep generation and regulation, it has been proven difficult to determine the neurobiological mechanisms underlying the beneficial effect of sleep, and the detrimental impact of sleep loss, on learning and memory processes. In my thesis, I present results that lead to several critical steps forward in the link between sleep and cognitive function. My major result is the molecular identification and physiological analysis of a protein, the NR2A subunit of NMDA receptor (NMDAR), that confers sensitivity to sleep loss to the hippocampus, a brain structure classically involved in mnemonic processes. Specifically, I used a novel behavioral approach to achieve sleep deprivation in adult C57BL6/J mice, yet minimizing the impact of secondary factors associated with the procedure,.such as stress. By using in vitro electrophysiological analysis, I show, for the first time, that sleep loss dramatically affects bidirectional plasticity at CA3 to CA1 synapses in the hippocampus, a well established cellular model of learning and memory. 4-6 hours of sleep loss elevate the modification threshold for bidirectional synaptic plasticity (MT), thereby promoting long-term depression of CA3 to CA 1 synaptic strength after stimulation in the theta frequency range (5 Hz), and rendering long-term potentiation induction.more difficult. Remarkably, 3 hours of recovery sleep, after the deprivation, reset the MT at control values, thus re-establishing the normal proneness of synapses to undergo long-term plastic changes. At the molecular level, these functional changes are paralleled by a change in the NMDAR subunit composition. In particular, the expression of the NR2A subunit protein of NMDAR at CA3 to CA1 synapses is selectively and rapidly increased by sleep deprivation, whereas recovery sleep reset NR2A synaptic content to control levels. By using an array of genetic, pharmacological and computational approaches, I demonstrate here an obligatory role for NR2A-containing NMDARs in conveying the effect of sleep loss on CA3 to CAl MT. Moreover, I show that a genetic deletion of the NR2A subunit fully preserves hippocampal plasticity from the impact of sleep loss, whereas it does not alter sleepwake behavior and homeostatic response to sleep deprivation. As to the mechanism underlying the effects of the NR2A subunit on hippocampal synaptic plasticity, I show that the increased NR2A expression after sleep loss distinctly affects the contribution of synaptic and more slowly recruited NMDAR pools activated during plasticity-induction protocols. This study represents a major step forward in understanding the mechanistic basis underlying sleep's role for the brain. By showing that sleep and sleep loss affect neuronal plasticity by regulating the expression and function of a synaptic neurotransmitter receptor, I propose that an important aspect of sleep function could consist in maintaining and regulating protein redistribution and ion channel trafficking at central synapses. These findings provide a novel starting point for investigations into the connections between sleep and learning, and they may open novel ways for pharmacological control over hippocampal .function during periods of sleep restriction. RÉSUMÉ DU PROJET La fonction du sommeil pour l'organisme est une des questions les plus persistantes et difficiles dans la biologie. Les découvertes actuelles mènent à la conclusion que le sommeil est essentiel pour le cerveau. En particulier, le rôle du sommeil dans les aspects cognitifs est soutenu par des études comportementales tant chez les humains que chez les animaux. Cependant, malgré l'avancement remarquable dans la compréhension des mécanismes sous-tendant la génération et la régulation du sommeil, les mécanismes neurobiologiques qui pourraient expliquer l'effet favorable du sommeil sur l'apprentissage et la mémoire ne sont pas encore clairs. Dans ma thèse, je présente des résultats qui aident à clarifier le lien entre le sommeil et la fonction cognitive. Mon résultat le plus significatif est l'identification moléculaire et l'analyse physiologique d'une protéine, la sous-unité NR2A du récepteur NMDA, qui rend l'hippocampe sensible à la perte de sommeil. Dans cette étude, nous avons utilisé une nouvelle approche expérimentale qui nous a permis d'induire une privation de sommeil chez les souris C57BL6/J adultes, en minimisant l'impact de facteurs confondants comme, par exemple, le stress. En utilisant les techniques de l'électrophysiologie in vitro, j'ai démontré, pour la première fois, que la perte de sommeil est responsable d'affecter radicalement la plasticité bidirectionnelle au niveau des synapses CA3-CA1 de l'hippocampe. Cela correspond à un mécanisme cellulaire de l'apprentissage et de la mémoire bien établi. En particulier, 4-6 heures de privation de sommeil élèvent le seuil de modification pour la plasticité synaptique bidirectionnelle (SM). Comme conséquence, la dépression à long terme de la transmission synaptique est induite par la stimulation des fibres afférentes dans la bande de fréquences thêta (5 Hz), alors que la potentialisation à long terme devient plus difficile. D'autre part, 3 heures de sommeil de récupération sont suffisant pour rétablir le SM aux valeurs contrôles. Au niveau moléculaire, les changements de la plasticité synaptiques sont associés à une altération de la composition du récepteur NMDA. En particulier, l'expression synaptique de la protéine NR2A du récepteur NMDA est rapidement augmentée de manière sélective par la privation de sommeil, alors que le sommeil de récupération rétablit l'expression de la protéine au niveau contrôle. En utilisant des approches génétiques, pharmacologiques et computationnelles, j'ai démontré que les récepteurs NMDA qui expriment la sous-unité NR2A sont responsables de l'effet de la privation de sommeil sur le SM. De plus, nous avons prouvé qu'une délétion génétique de la sous-unité NR2A préserve complètement la plasticité synaptique hippocampale de l'impact de la perte de sommeil, alors que cette manipulation ne change pas les mécanismes de régulation homéostatique du sommeil. En ce qui concerne les mécanismes, j'ai .découvert que l'augmentation de l'expression de la sous-unité NR2A au niveau synaptique modifie les propriétés de la réponse du récepteur NMDA aux protocoles de stimulations utilisés pour induire la plasticité. Cette étude représente un pas en avant important dans la compréhension de la base mécaniste sous-tendant le rôle du sommeil pour le cerveau. En montrant que le sommeil et la perte de sommeil affectent la plasticité neuronale en régulant l'expression et la fonction d'un récepteur de la neurotransmission, je propose qu'un aspect important de la fonction du sommeil puisse être finalisé au règlement de la redistribution des protéines et du tracking des récepteurs aux synapses centraux. Ces découvertes fournissent un point de départ pour mieux comprendre les liens entre le sommeil et l'apprentissage, et d'ailleurs, ils peuvent ouvrir des voies pour des traitements pharmacologiques dans le .but de préserver la fonction hippocampale pendant les périodes de restriction de sommeil.

Knowledge management for systems biology a general and visually driven framework applied to translational medicine

Background: To enhance our understanding of complex biological systems like diseases we need to put all of the available data into context and use this to detect relations, pattern and rules which allow predictive hypotheses to be defined. Life science has become a data rich science with information about the behaviour of millions of entities like genes, chemical compounds, diseases, cell types and organs, which are organised in many different databases and/or spread throughout the literature. Existing knowledge such as genotype - phenotype relations or signal transduction pathways must be semantically integrated and dynamically organised into structured networks that are connected with clinical and experimental data. Different approaches to this challenge exist but so far none has proven entirely satisfactory. Results: To address this challenge we previously developed a generic knowledge management framework, BioXM™, which allows the dynamic, graphic generation of domain specific knowledge representation models based on specific objects and their relations supporting annotations and ontologies. Here we demonstrate the utility of BioXM for knowledge management in systems biology as part of the EU FP6 BioBridge project on translational approaches to chronic diseases. From clinical and experimental data, text-mining results and public databases we generate a chronic obstructive pulmonary disease (COPD) knowledge base and demonstrate its use by mining specific molecular networks together with integrated clinical and experimental data. Conclusions: We generate the first semantically integrated COPD specific public knowledge base and find that for the integration of clinical and experimental data with pre-existing knowledge the configuration based set-up enabled by BioXM reduced implementation time and effort for the knowledge base compared to similar systems implemented as classical software development projects. The knowledgebase enables the retrieval of sub-networks including protein-protein interaction, pathway, gene - disease and gene - compound data which are used for subsequent data analysis, modelling and simulation. Pre-structured queries and reports enhance usability; establishing their use in everyday clinical settings requires further simplification with a browser based interface which is currently under development.

Tandem chimeric transcription as a means to increase protein diversity in the human genome

The “one-gene, one-protein” rule, coined by Beadle and Tatum, has been fundamental to molecular biology. The rule implies that the genetic complexity of an organism depends essentially on its gene number. The discovery, however, that alternative gene splicing and transcription are widespread phenomena dramatically altered our understanding of the genetic complexity of higher eukaryotic organisms; in these, a limited number of genes may potentially encode a much larger number of proteins. Here we investigate yet another phenomenon that may contribute to generate additional protein diversity. Indeed, by relying on both computational and experimental analysis, we estimate that at least 4%–5% of the tandem gene pairs in the human genome can be eventually transcribed into a single RNA sequence encoding a putative chimeric protein. While the functional significance of most of these chimeric transcripts remains to be determined, we provide strong evidence that this phenomenon does not correspond to mere technical artifacts and that it is a common mechanism with the potential of generating hundreds of additional proteins in the human genome.

A general definition and nomenclature for alternative splicing events

Understanding the molecular mechanisms responsible for the regulation of the transcriptome present in eukaryotic cells isone of the most challenging tasks in the postgenomic era. In this regard, alternative splicing (AS) is a key phenomenoncontributing to the production of different mature transcripts from the same primary RNA sequence. As a plethora ofdifferent transcript forms is available in databases, a first step to uncover the biology that drives AS is to identify thedifferent types of reflected splicing variation. In this work, we present a general definition of the AS event along with anotation system that involves the relative positions of the splice sites. This nomenclature univocally and dynamically assignsa specific ‘‘AS code’’ to every possible pattern of splicing variation. On the basis of this definition and the correspondingcodes, we have developed a computational tool (AStalavista) that automatically characterizes the complete landscape of ASevents in a given transcript annotation of a genome, thus providing a platform to investigate the transcriptome diversityacross genes, chromosomes, and species. Our analysis reveals that a substantial part—in human more than a quarter—ofthe observed splicing variations are ignored in common classification pipelines. We have used AStalavista to investigate andto compare the AS landscape of different reference annotation sets in human and in other metazoan species and found thatproportions of AS events change substantially depending on the annotation protocol, species-specific attributes, andcoding constraints acting on the transcripts. The AStalavista system therefore provides a general framework to conductspecific studies investigating the occurrence, impact, and regulation of AS.

Identifying protein-coding genes in genomic sequences

The vast majority of the biology of a newly sequenced genome is inferred from the set of encoded proteins. Predicting this set is therefore invariably the first step after the completion of the genome DNA sequence. Here we review the main computational pipelines used to generate the human reference protein-coding gene sets.

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.

Computational Representation of Collaborative Learning Flow Patterns Using IMS Learning Design

The identification and integration of reusable and customizable CSCL (Computer Supported Collaborative Learning) may benefit from the capture of best practices in collaborative learning structuring. The authors have proposed CLFPs (Collaborative Learning Flow Patterns) as a way of collecting these best practices. To facilitate the process of CLFPs by software systems, the paper proposes to specify these patterns using IMS Learning Design (IMS-LD). Thus, teachers without technical knowledge can particularize and integrate CSCL tools. Nevertheless, the support of IMS-LD for describing collaborative learning activities has some deficiencies: the collaborative tools that can be defined in these activities are limited. Thus, this paper proposes and discusses an extension to IMS-LD that enables to specify several characteristics of the use of tools that mediate collaboration. In order to obtain a Unit of Learning based on a CLFP, a three stage process is also proposed. A CLFP-based Unit of Learning example is used to illustrate the process and the need of the proposed extension.

Patient-specific computational hemodynamics of intracranial aneurysms from 3D rotational angiography and CT angiography: an in vivo reproducibility study

Patient-specific simulations of the hemodynamics in intracranial aneurysms can be constructed by using image-based vascular models and CFD techniques. This work evaluates the impact of the choice of imaging technique on these simulations

Estimation of the viscoelastic properties of vessel walls using a computational model and Doppler ultrasound

Human arteries affected by atherosclerosis are characterized by altered wall viscoelastic properties. The possibility of noninvasively assessing arterial viscoelasticity in vivo would significantly contribute to the early diagnosis and prevention of this disease. This paper presents a noniterative technique to estimate the viscoelastic parameters of a vascular wall Zener model. The approach requires the simultaneous measurement of flow variations and wall displacements, which can be provided by suitable ultrasound Doppler instruments. Viscoelastic parameters are estimated by fitting the theoretical constitutive equations to the experimental measurements using an ARMA parameter approach. The accuracy and sensitivity of the proposed method are tested using reference data generated by numerical simulations of arterial pulsation in which the physiological conditions and the viscoelastic parameters of the model can be suitably varied. The estimated values quantitatively agree with the reference values, showing that the only parameter affected by changing the physiological conditions is viscosity, whose relative error was about 27% even when a poor signal-to-noise ratio is simulated. Finally, the feasibility of the method is illustrated through three measurements made at different flow regimes on a cylindrical vessel phantom, yielding a parameter mean estimation error of 25%.

Deployment of self-expandable stents in aneurysmatic cerebral vessels: comparison of different computational approaches for interventional planning

In the last few years, there has been a growing focus on faster computational methods to support clinicians in planning stenting procedures. This study investigates the possibility of introducing computational approximations in modelling stent deployment in aneurysmatic cerebral vessels to achieve simulations compatible with the constraints of real clinical workflows. The release of a self-expandable stent in a simplified aneurysmatic vessel was modelled in four different initial positions. Six progressively simplified modelling approaches (based on Finite Element method and Fast Virtual Stenting – FVS) have been used. Comparing accuracy of the results, the final configuration of the stent is more affected by neglecting mechanical properties of materials (FVS) than by adopting 1D instead of 3D stent models. Nevertheless, the differencesshowed are acceptable compared to those achieved by considering different stent initial positions. Regarding computationalcosts, simulations involving 1D stent features are the only ones feasible in clinical context.

On the computational security of a distributed key distribution scheme

In a distributed key distribution scheme, a set of servers helps a set of users in a group to securely obtain a common key. Security means that an adversary who corrupts some servers and some users has no information about the key of a noncorrupted group. In this work, we formalize the security analysis of one such scheme which was not considered in the original proposal. We prove the scheme is secure in the random oracle model, assuming that the Decisional Diffie-Hellman (DDH) problem is hard to solve. We also detail a possible modification of that scheme and the one in which allows us to prove the security of the schemes without assuming that a specific hash function behaves as a random oracle. As usual, this improvement in the security of the schemes is at the cost of an efficiency loss.

Opportunities for a cultural specific approach in the computational description of music

The current research in Music Information Retrieval (MIR) is showing the potential that the Information Technologies can have in music related applications. Amajor research challenge in that direction is how to automaticallydescribe/annotate audio recordings and how to use the resulting descriptions to discover and appreciate music in new ways. But music is a complex phenomenonand the description of an audio recording has to deal with this complexity. For example, each musicculture has specificities and emphasizes different musicaland communication aspects, thus the musical recordings of each culture should be described differently. At the same time these cultural specificities give us the opportunity to pay attention to musical concepts andfacets that, despite being present in most world musics, are not easily noticed by listeners. In this paper we present some of the work done in the CompMusic project, including ideas and specific examples on how to take advantage of the cultural specificities of differentmusical repertoires. We will use examples from the art music traditions of India, Turkey and China.

HER2 shedding and serum HER2 extracellular domain: Biology and clinical utility in breast cancer.

The transmembrane protein HER2 is over-expressed in approximately 15% of invasive breast cancers as a result of HER2 gene amplification. HER2 proteolytic cleavage (HER2 shedding) generates soluble truncated HER2 molecules that include only the extracellular domain and the concentration of which can be measured in the serum fraction of blood. HER2 shedding also generates a constitutively active truncated intracellular receptor of 95kDa (p95(HER2)). Another soluble truncated HER2 protein (Herstatin), which can also be found in serum, is the product of an alternatively spliced HER2 transcript. Recent preclinical findings may provide crucial insights into the biological and clinical relevance of increased sHER2 concentrations for the outcome of HER2-positive breast cancer and sensitivity to trastuzumab and lapatinib treatment. We present here the most recent findings about the role and biology of sHER2 based on data obtained using a standardized test, which has been cleared by FDA in 2000, for measuring sHER2. This test includes quality control assessments and has been already widely used to evaluate the clinical utility of sHER2 as a biomarker in breast cancer. We will describe in detail data concerning the assessment of sHER2 as a surrogate maker to optimize the evaluation of the HER2 status of a primary tumor and as a prognosis and predictive marker of response to therapies, both in early and metastatic breast cancer.