Forensic intelligence framework. Part II: study of the main generic building blocks and challenges through the examples of illicit drugs and false identity documents monitoring

The development of forensic intelligence relies on the expression of suitable models that better represent the contribution of forensic intelligence in relation to the criminal justice system, policing and security. Such models assist in comparing and evaluating methods and new technologies, provide transparency and foster the development of new applications. Interestingly, strong similarities between two separate projects focusing on specific forensic science areas were recently observed. These observations have led to the induction of a general model (Part I) that could guide the use of any forensic science case data in an intelligence perspective. The present article builds upon this general approach by focusing on decisional and organisational issues. The article investigates the comparison process and evaluation system that lay at the heart of the forensic intelligence framework, advocating scientific decision criteria and a structured but flexible and dynamic architecture. These building blocks are crucial and clearly lay within the expertise of forensic scientists. However, it is only part of the problem. Forensic intelligence includes other blocks with their respective interactions, decision points and tensions (e.g. regarding how to guide detection and how to integrate forensic information with other information). Formalising these blocks identifies many questions and potential answers. Addressing these questions is essential for the progress of the discipline. Such a process requires clarifying the role and place of the forensic scientist within the whole process and their relationship to other stakeholders.

SwissSidechain: a molecular and structural database of non-natural sidechains.

Amino acids form the building blocks of all proteins. Naturally occurring amino acids are restricted to a few tens of sidechains, even when considering post-translational modifications and rare amino acids such as selenocysteine and pyrrolysine. However, the potential chemical diversity of amino acid sidechains is nearly infinite. Exploiting this diversity by using non-natural sidechains to expand the building blocks of proteins and peptides has recently found widespread applications in biochemistry, protein engineering and drug design. Despite these applications, there is currently no unified online bioinformatics resource for non-natural sidechains. With the SwissSidechain database (http://www.swisssidechain.ch), we offer a central and curated platform about non-natural sidechains for researchers in biochemistry, medicinal chemistry, protein engineering and molecular modeling. SwissSidechain provides biophysical, structural and molecular data for hundreds of commercially available non-natural amino acid sidechains, both in l- and d-configurations. The database can be easily browsed by sidechain names, families or physico-chemical properties. We also provide plugins to seamlessly insert non-natural sidechains into peptides and proteins using molecular visualization software, as well as topologies and parameters compatible with molecular mechanics software.

Gondwana-derived microcontinents - The constituents of the Variscan and Alpine collisional orogens

The European Variscan and Alpine mountain chains are collisional orogens, and are built up of pre-Variscan ``building blocks'' which, in most. cases, originated at the Gondwana margin. Such pre-Variscan elements were part of a pre-Ordovician archipelago-like continental ribbon in the former eastern prolongation of Avalonia, and their present-day distribution resulted from juxtaposition through Variscan and/or Alpine tectonic evolution. The well-known nomenclatures applied to these mountain chains are the mirror of Variscan resp. Alpine organization. It is the aim of this paper to present a terminology taking into account their pre-Variscan evolution at the Gondwana margin. They may contain relics of volcanic islands with pieces of Cadomian crust, relics of volcanic arc settings, and accretionary wedges, which were separated from Gondwana by initial stages of Rheic ocean. opening. After a short-lived Ordovician orogenic event and amalgamation of these elements at the Gondwanan margin, the still continuing Gondwana-directed subduction triggered the formation of Ordovician Al-rich granitoids and; the latest Ordovician opening of Palaeo-Tethys. An example from the Alps (External Massifs) illustrates the gradual reworking of Gondwana-derived, pre-Variscan. elements during the Variscan and Alpine/ Tertiary orogenic cycles. (C) 2003 Elsevier Science B.V. All rights reserved.

Synthesis and Biological Evaluation of S-Neofucopeptides as E- and P-Selectin Inhibitors.

The synthesis of /-L-fucosylated cysteamine, 3-thiopropionic acid, and 3-thioacetic acid derivatives as building blocks for the preparation of S-neofucopeptides is shown. These compounds were used in the synthesis of new thiofucosides derivatives (8, 9, 9, 10, 22, 22, 24, 26) that show affinity towards E- and P-selectins. They constitute a new series of hydrolytically stable and low-molecular-weight mimetics of the natural SLex tetrasaccharide.

Modular support for developing mobile ad hoc applications

Abstract This PhD thesis addresses the issue of alleviating the burden of developing ad hoc applications. Such applications have the particularity of running on mobile devices, communicating in a peer-to-peer manner and implement some proximity-based semantics. A typical example of such application can be a radar application where users see their avatar as well as the avatars of their friends on a map on their mobile phone. Such application become increasingly popular with the advent of the latest generation of mobile smart phones with their impressive computational power, their peer-to-peer communication capabilities and their location detection technology. Unfortunately, the existing programming support for such applications is limited, hence the need to address this issue in order to alleviate their development burden. This thesis specifically tackles this problem by providing several tools for application development support. First, it provides the location-based publish/subscribe service (LPSS), a communication abstraction, which elegantly captures recurrent communication issues and thus allows to dramatically reduce the code complexity. LPSS is implemented in a modular manner in order to be able to target two different network architectures. One pragmatic implementation is aimed at mainstream infrastructure-based mobile networks, where mobile devices can communicate through fixed antennas. The other fully decentralized implementation targets emerging mobile ad hoc networks (MANETs), where no fixed infrastructure is available and communication can only occur in a peer-to-peer fashion. For each of these architectures, various implementation strategies tailored for different application scenarios that can be parametrized at deployment time. Second, this thesis provides two location-based message diffusion protocols, namely 6Shot broadcast and 6Shot multicast, specifically aimed at MANETs and fine tuned to be used as building blocks for LPSS. Finally this thesis proposes Phomo, a phone motion testing tool that allows to test proximity semantics of ad hoc applications without having to move around with mobile devices. These different developing support tools have been packaged in a coherent middleware framework called Pervaho.

State-of-the-art of 3D cultures (organs-on-a-chip) in safety testing and pathophysiology.

Integrated approaches using different in vitro methods in combination with bioinformatics can (i) increase the success rate and speed of drug development; (ii) improve the accuracy of toxicological risk assessment; and (iii) increase our understanding of disease. Three-dimensional (3D) cell culture models are important building blocks of this strategy which has emerged during the last years. The majority of these models are organotypic, i.e., they aim to reproduce major functions of an organ or organ system. This implies in many cases that more than one cell type forms the 3D structure, and often matrix elements play an important role. This review summarizes the state of the art concerning commonalities of the different models. For instance, the theory of mass transport/metabolite exchange in 3D systems and the special analytical requirements for test endpoints in organotypic cultures are discussed in detail. In the next part, 3D model systems for selected organs--liver, lung, skin, brain--are presented and characterized in dedicated chapters. Also, 3D approaches to the modeling of tumors are presented and discussed. All chapters give a historical background, illustrate the large variety of approaches, and highlight up- and downsides as well as specific requirements. Moreover, they refer to the application in disease modeling, drug discovery and safety assessment. Finally, consensus recommendations indicate a roadmap for the successful implementation of 3D models in routine screening. It is expected that the use of such models will accelerate progress by reducing error rates and wrong predictions from compound testing.

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.

Stochastic models and numerical algorithms for a class of regulatory gene networks.

Regulatory gene networks contain generic modules, like those involving feedback loops, which are essential for the regulation of many biological functions (Guido et al. in Nature 439:856-860, 2006). We consider a class of self-regulated genes which are the building blocks of many regulatory gene networks, and study the steady-state distribution of the associated Gillespie algorithm by providing efficient numerical algorithms. We also study a regulatory gene network of interest in gene therapy, using mean-field models with time delays. Convergence of the related time-nonhomogeneous Markov chain is established for a class of linear catalytic networks with feedback loops.

Structural motifs of biomolecules.

Biomolecular structures are assemblies of emergent anisotropic building modules such as uniaxial helices or biaxial strands. We provide an approach to understanding a marginally compact phase of matter that is occupied by proteins and DNA. This phase, which is in some respects analogous to the liquid crystal phase for chain molecules, stabilizes a range of shapes that can be obtained by sequence-independent interactions occurring intra- and intermolecularly between polymeric molecules. We present a singularity-free self-interaction for a tube in the continuum limit and show that this results in the tube being positioned in the marginally compact phase. Our work provides a unified framework for understanding the building blocks of biomolecules.

Imaging the time-integrated cerebral metabolic activity with subcellular resolution through nanometer-scale detection of biosynthetic products deriving from (13)C-glucose.

Glucose is the primary source of energy for the brain but also an important source of building blocks for proteins, lipids, and nucleic acids. Little is known about the use of glucose for biosynthesis in tissues at the cellular level. We demonstrate that local cerebral metabolic activity can be mapped in mouse brain tissue by quantitatively imaging the biosynthetic products deriving from [U-(13)C]glucose metabolism using a combination of in situ electron microscopy and secondary ion mass-spectroscopy (NanoSIMS). Images of the (13)C-label incorporated into cerebral ultrastructure with ca. 100nm resolution allowed us to determine the timescale on which the metabolic products of glucose are incorporated into different cells, their sub-compartments and organelles. These were mapped in astrocytes and neurons in the different layers of the motor cortex. We see evidence for high metabolic activity in neurons via the nucleus (13)C enrichment. We observe that in all the major cell compartments, such as e.g. nucleus and Golgi apparatus, neurons incorporate substantially higher concentrations of (13)C-label than astrocytes.

Versatile gene-specific sequence tags for Arabidopsis functional genomics: transcript profiling and reverse genetics applications.

Microarray transcript profiling and RNA interference are two new technologies crucial for large-scale gene function studies in multicellular eukaryotes. Both rely on sequence-specific hybridization between complementary nucleic acid strands, inciting us to create a collection of gene-specific sequence tags (GSTs) representing at least 21,500 Arabidopsis genes and which are compatible with both approaches. The GSTs were carefully selected to ensure that each of them shared no significant similarity with any other region in the Arabidopsis genome. They were synthesized by PCR amplification from genomic DNA. Spotted microarrays fabricated from the GSTs show good dynamic range, specificity, and sensitivity in transcript profiling experiments. The GSTs have also been transferred to bacterial plasmid vectors via recombinational cloning protocols. These cloned GSTs constitute the ideal starting point for a variety of functional approaches, including reverse genetics. We have subcloned GSTs on a large scale into vectors designed for gene silencing in plant cells. We show that in planta expression of GST hairpin RNA results in the expected phenotypes in silenced Arabidopsis lines. These versatile GST resources provide novel and powerful tools for functional genomics.

Association of hemolytic activity of Pseudomonas entomophila, a versatile soil bacterium, with cyclic lipopeptide production.

Pseudomonas entomophila is an entomopathogenic bacterium that is able to infect and kill Drosophila melanogaster upon ingestion. Its genome sequence suggests that it is a versatile soil bacterium closely related to Pseudomonas putida. The GacS/GacA two-component system plays a key role in P. entomophila pathogenicity, controlling many putative virulence factors and AprA, a secreted protease important to escape the fly immune response. P. entomophila secretes a strong diffusible hemolytic activity. Here, we showed that this activity is linked to the production of a new cyclic lipopeptide containing 14 amino acids and a 3-C(10)OH fatty acid that we called entolysin. Three nonribosomal peptide synthetases (EtlA, EtlB, EtlC) were identified as responsible for entolysin biosynthesis. Two additional components (EtlR, MacAB) are necessary for its production and secretion. The P. entomophila GacS/GacA two-component system regulates entolysin production, and we demonstrated that its functioning requires two small RNAs and two RsmA-like proteins. Finally, entolysin is required for swarming motility, as described for other lipopeptides, but it does not participate in the virulence of P. entomophila for Drosophila. While investigating the physiological role of entolysin, we also uncovered new phenotypes associated with P. entomophila, including strong biocontrol abilities.

Lufaxin, a novel factor Xa inhibitor from the salivary gland of the sand fly Lutzomyia longipalpis blocks protease-activated receptor 2 activation and inhibits inflammation and thrombosis in vivo.

OBJECTIVE: Blood-sucking arthropods' salivary glands contain a remarkable diversity of antihemostatics. The aim of the present study was to identify the unique salivary anticoagulant of the sand fly Lutzomyia longipalpis, which remained elusive for decades. METHODS AND RESULTS: Several L. longipalpis salivary proteins were expressed in human embryonic kidney 293 cells and screened for inhibition of blood coagulation. A novel 32.4-kDa molecule, named Lufaxin, was identified as a slow, tight, noncompetitive, and reversible inhibitor of factor Xa (FXa). Notably, Lufaxin's primary sequence does not share similarity to any physiological or salivary inhibitors of coagulation reported to date. Lufaxin is specific for FXa and does not interact with FX, Dansyl-Glu-Gly-Arg-FXa, or 15 other enzymes. In addition, Lufaxin blocks prothrombinase and increases both prothrombin time and activated partial thromboplastin time. Surface plasmon resonance experiments revealed that FXa binds Lufaxin with an equilibrium constant ≈3 nM, and isothermal titration calorimetry determined a stoichiometry of 1:1. Lufaxin also prevents protease-activated receptor 2 activation by FXa in the MDA-MB-231 cell line and abrogates edema formation triggered by injection of FXa in the paw of mice. Moreover, Lufaxin prevents FeCl(3)-induced carotid artery thrombus formation and prolongs activated partial thromboplastin time ex vivo, implying that it works as an anticoagulant in vivo. Finally, salivary gland of sand flies was found to inhibit FXa and to interact with the enzyme. CONCLUSIONS: Lufaxin belongs to a novel family of slow-tight FXa inhibitors, which display antithrombotic and anti-inflammatory activities. It is a useful tool to understand FXa structural features and its role in prohemostatic and proinflammatory events.