Bayesian Networks and the Value of the Evidence for the Forensic Two-Trace Transfer Problem

Forensic scientists face increasingly complex inference problems for evaluating likelihood ratios (LRs) for an appropriate pair of propositions. Up to now, scientists and statisticians have derived LR formulae using an algebraic approach. However, this approach reaches its limits when addressing cases with an increasing number of variables and dependence relationships between these variables. In this study, we suggest using a graphical approach, based on the construction of Bayesian networks (BNs). We first construct a BN that captures the problem, and then deduce the expression for calculating the LR from this model to compare it with existing LR formulae. We illustrate this idea by applying it to the evaluation of an activity level LR in the context of the two-trace transfer problem. Our approach allows us to relax assumptions made in previous LR developments, produce a new LR formula for the two-trace transfer problem and generalize this scenario to n traces.

On the convergence of EM-like algorithms for image segmentation using Markov random fields.

Inference of Markov random field images segmentation models is usually performed using iterative methods which adapt the well-known expectation-maximization (EM) algorithm for independent mixture models. However, some of these adaptations are ad hoc and may turn out numerically unstable. In this paper, we review three EM-like variants for Markov random field segmentation and compare their convergence properties both at the theoretical and practical levels. We specifically advocate a numerical scheme involving asynchronous voxel updating, for which general convergence results can be established. Our experiments on brain tissue classification in magnetic resonance images provide evidence that this algorithm may achieve significantly faster convergence than its competitors while yielding at least as good segmentation results.

Probabilistic age classification with Bayesian networks: a study on the ossification status of the medial clavicular epiphysis

In the past few decades, the rise of criminal, civil and asylum cases involving young people lacking valid identification documents has generated an increase in the demand of age estimation. The chronological age or the probability that an individual is older or younger than a given age threshold are generally estimated by means of some statistical methods based on observations performed on specific physical attributes. Among these statistical methods, those developed in the Bayesian framework allow users to provide coherent and transparent assignments which fulfill forensic and medico-legal purposes. The application of the Bayesian approach is facilitated by using probabilistic graphical tools, such as Bayesian networks. The aim of this work is to test the performances of the Bayesian network for age estimation recently presented in scientific literature in classifying individuals as older or younger than 18 years of age. For these exploratory analyses, a sample related to the ossification status of the medial clavicular epiphysis available in scientific literature was used. Results obtained in the classification are promising: in the criminal context, the Bayesian network achieved, on the average, a rate of correct classifications of approximatively 97%, whilst in the civil context, the rate is, on the average, close to the 88%. These results encourage the continuation of the development and the testing of the method in order to support its practical application in casework.

Trapping of naive lymphocytes triggers rapid growth and remodeling of the fibroblast network in reactive murine lymph nodes.

Adaptive immunity is initiated in T-cell zones of secondary lymphoid organs. These zones are organized in a rigid 3D network of fibroblastic reticular cells (FRCs) that are a rich cytokine source. In response to lymph-borne antigens, draining lymph nodes (LNs) expand several folds in size, but the fate and role of the FRC network during immune response is not fully understood. Here we show that T-cell responses are accompanied by the rapid activation and growth of FRCs, leading to an expanded but similarly organized network of T-zone FRCs that maintains its vital function for lymphocyte trafficking and survival. In addition, new FRC-rich environments were observed in the expanded medullary cords. FRCs are activated within hours after the onset of inflammation in the periphery. Surprisingly, FRC expansion depends mainly on trapping of naïve lymphocytes that is induced by both migratory and resident dendritic cells. Inflammatory signals are not required as homeostatic T-cell proliferation was sufficient to trigger FRC expansion. Activated lymphocytes are also dispensable for this process, but can enhance the later growth phase. Thus, this study documents the surprising plasticity as well as the complex regulation of FRC networks allowing the rapid LN hyperplasia that is critical for mounting efficient adaptive immunity.

A concentric analysis of the impact of urbanization on the threatened European tree frog in an agricultural landscape

Pond-breeding amphibians are affected by site-specific factors and regional and landscape-scale patterns of land use. Recent anthropogenic landscape modifications (drainage, agriculture intensification, larger road networks, and increased traffic) affect species by reducing the suitable habitat area and fragmenting remaining populations. Using a robust concentric approach based on permutation tests, we evaluated the impact of recent landscape changes on the presence of the endangered European tree frog (Hyla arborea.) in wetlands. We analyzed the frequency of 1 traffic and 14 land-use indices at 20 circular ranges (from 100-m up to 2-km radii) around 76 ponds identified in western Switzerland. Urban areas and road surfaces had a strong adverse effect on tree frog presence even at relatively great distances (from 100 m up to 1 km). When traffic measurements were considered instead of road surfaces, the effect increased, suggesting a negative impact due to a vehicle-induced effect. Altogether, our results indicate that urbanization and traffic must be taken into account when pond creation is an option in conservation management plans, as is the case for the European tree frog in western Switzerland. We conclude that our easy-to-use and robust concentric method of analysis can successfully assist managers in identifying potential sites for pond creation, where probability of the presence of tree frogs is maximized.

Complementary function and integrated wiring of the evolutionarily distinct Drosophila olfactory subsystems.

To sense myriad environmental odors, animals have evolved multiple, large families of divergent olfactory receptors. How and why distinct receptor repertoires and their associated circuits are functionally and anatomically integrated is essentially unknown. We have addressed these questions through comprehensive comparative analysis of the Drosophila olfactory subsystems that express the ionotropic receptors (IRs) and odorant receptors (ORs). We identify ligands for most IR neuron classes, revealing their specificity for select amines and acids, which complements the broader tuning of ORs for esters and alcohols. IR and OR sensory neurons exhibit glomerular convergence in segregated, although interconnected, zones of the primary olfactory center, but these circuits are extensively interdigitated in higher brain regions. Consistently, behavioral responses to odors arise from an interplay between IR- and OR-dependent pathways. We integrate knowledge on the different phylogenetic and developmental properties of these receptors and circuits to propose models for the functional contributions and evolution of these distinct olfactory subsystems.

Analysis of a finite volume element method for the Stokes problem

In this paper we propose a stabilized conforming finite volume element method for the Stokes equations. On stating the convergence of the method, optimal a priori error estimates in different norms are obtained by establishing the adequate connection between the finite volume and stabilized finite element formulations. A superconvergence result is also derived by using a postprocessing projection method. In particular, the stabilization of the continuous lowest equal order pair finite volume element discretization is achieved by enriching the velocity space with local functions that do not necessarily vanish on the element boundaries. Finally, some numerical experiments that confirm the predicted behavior of the method are provided.

Neonatal dexamethasone induces premature microvascular maturation of the alveolar capillary network.

Postnatal glucocorticoid treatment of preterm infants was mimicked by treating newborn rats with dexamethasone (0.1-0.01 microg/g, days 1-4). This regimen has been shown to cause delayed alveolarization. Knowing that microvascular maturation (transformation of double- to single-layered capillary networks in alveolar septa) and septal thinning prevent further alveolarization, we measured septal maturation on electron photomicrographs in treated and control animals. In treated rats and before day 10, we observed a premature nonreversing microvascular maturation and a transient septal thinning, which both appeared focally. In vascular casts of both groups, we observed contacts between the two capillary layers of immature alveolar septa, which were predictive for capillary fusions. Studying serial electron microscopic sections of human lungs, we were able to confirm the postulated fusion process for the first time. We conclude that alveolar microvascular maturation indeed occurs by capillary fusion and that the dexamethasone-induced impairment of alveolarization is associated with focal premature capillary fusion.

The AP-1 transcription factor c-Jun prevents stress-imposed maladaptive remodeling of the heart.

Systemic hypertension increases cardiac workload and subsequently induces signaling networks in heart that underlie myocyte growth (hypertrophic response) through expansion of sarcomeres with the aim to increase contractility. However, conditions of increased workload can induce both adaptive and maladaptive growth of heart muscle. Previous studies implicate two members of the AP-1 transcription factor family, junD and fra-1, in regulation of heart growth during hypertrophic response. In this study, we investigate the function of the AP-1 transcription factors, c-jun and c-fos, in heart growth. Using pressure overload-induced cardiac hypertrophy in mice and targeted deletion of Jun or Fos in cardiomyocytes, we show that c-jun is required for adaptive cardiac hypertrophy, while c-fos is dispensable in this context. c-jun promotes expression of sarcomere proteins and suppresses expression of extracellular matrix proteins. Capacity of cardiac muscle to contract depends on organization of principal thick and thin filaments, myosin and actin, within the sarcomere. In line with decreased expression of sarcomere-associated proteins, Jun-deficient cardiomyocytes present disarrangement of filaments in sarcomeres and actin cytoskeleton disorganization. Moreover, Jun-deficient hearts subjected to pressure overload display pronounced fibrosis and increased myocyte apoptosis finally resulting in dilated cardiomyopathy. In conclusion, c-jun but not c-fos is required to induce a transcriptional program aimed at adapting heart growth upon increased workload.

Dynamic simulation of regulatory networks using SQUAD.

BACKGROUND: The ambition of most molecular biologists is the understanding of the intricate network of molecular interactions that control biological systems. As scientists uncover the components and the connectivity of these networks, it becomes possible to study their dynamical behavior as a whole and discover what is the specific role of each of their components. Since the behavior of a network is by no means intuitive, it becomes necessary to use computational models to understand its behavior and to be able to make predictions about it. Unfortunately, most current computational models describe small networks due to the scarcity of kinetic data available. To overcome this problem, we previously published a methodology to convert a signaling network into a dynamical system, even in the total absence of kinetic information. In this paper we present a software implementation of such methodology. RESULTS: We developed SQUAD, a software for the dynamic simulation of signaling networks using the standardized qualitative dynamical systems approach. SQUAD converts the network into a discrete dynamical system, and it uses a binary decision diagram algorithm to identify all the steady states of the system. Then, the software creates a continuous dynamical system and localizes its steady states which are located near the steady states of the discrete system. The software permits to make simulations on the continuous system, allowing for the modification of several parameters. Importantly, SQUAD includes a framework for perturbing networks in a manner similar to what is performed in experimental laboratory protocols, for example by activating receptors or knocking out molecular components. Using this software we have been able to successfully reproduce the behavior of the regulatory network implicated in T-helper cell differentiation. CONCLUSION: The simulation of regulatory networks aims at predicting the behavior of a whole system when subject to stimuli, such as drugs, or determine the role of specific components within the network. The predictions can then be used to interpret and/or drive laboratory experiments. SQUAD provides a user-friendly graphical interface, accessible to both computational and experimental biologists for the fast qualitative simulation of large regulatory networks for which kinetic data is not necessarily available.

The Complete Chromosomal Organization of the Reference Strain of the Leishmania Genome Project, L. major ;Friedlin'.

In recent years, analysis of the genomes of many organisms has received increasing international attention. The bulk of the effort to date has centred on the Human Genome Project and analysis of model organisms such as yeast, Drosophila and Caenorhabditis elegans. More recently, the revolution in genome sequencing and gene identification has begun to impact on infectious disease organisms. Initially, much of the effort was concentrated on prokaryotes, but small eukaryotic genomes, including the protozoan parasites Plasmodium, Toxoplasma and trypanosomatids (Leishmania, Trypanosoma brucei and T. cruzi), as well as some multicellular organisms, such as Brugia and Schistosoma, are benefiting from the technological advances of the genome era. These advances promise a radical new approach to the development of novel diagnostic tools, chemotherapeutic targets and vaccines for infectious disease organisms, as well as to the more detailed analysis of cell biology and function.Several networks or consortia linking laboratories around the world have been established to support these parasite genome projects[1] (for more information, see http://www.ebi.ac.uk/ parasites/paratable.html). Five of these networks were supported by an initiative launched in 1994 by the Specific Programme for Research and Tropical Diseases (TDR) of the WHO[2, 3, 4, 5, 6]. The Leishmania Genome Network (LGN) is one of these[3]. Its activities are reported at http://www.ebi.ac.uk/parasites/leish.html, and its current aim is to map and sequence the genome of Leishmania by the year 2002. All the mapping, hybridization and sequence data are also publicly available from LeishDB, an AceDB-based genome database (http://www.ebi.ac.uk/parasites/LGN/leissssoft.html).

A survey on the enlistment of pharmacists in a hospital battalion of the Swiss Armed Forces

Background: Pharmacists, mainly militiamen, are incorporated in the Swiss Armed Forces, for instance in hospital battalions to supply drugs and medical devices, as well as to coordinate hygiene service. Presently, their duties are only very globally defined. Aims: The objective of this survey was to investigate the tasks that were actually assumed by the military pharmacy of the 2nd Hospital Battalion. Methods: Two types of commitments, offering military and civilian interest's convergence, were considered between 2005 and 2011: (1) army camps for the disabled and (2) operations and supports provided to two nursing homes. While relieving the civil caregiver usually involved with disabled or elderly people, such missions offer indeed the possibility to the army medical service to train its care and logistical processes with real patients, even in the absence of any sanitary crisis or war in the country. Results: Two basis activities have been assumed: (1) centralized supply of drugs and medical devices and (2) coordination of hygiene monitoring and disinfection operations. New tasks were also performed: (3) support to the management of ward-based pharmacies, (4) pillboxes preparation, (5) medication review and (6) selective participation in clinical rounds. The last two were integrated in an interdisciplinary education process. Conclusions: Results shows that, apart from traditional duties, new clinical-oriented activities have been evenly developed and assumed by militia pharmacists. They call thus for a possible renewed definition of the tasks of military hospital pharmacists and of their related military education. A wider study in all hospital battalions is yet mandatory.

Map of ecological networks for landscape planning

This paper presents a method based on a geographical information system (GIS) to model ecological networks in a fragmented landscape. The ecological networks are generated with the help of a landscape model (which integrate human activities) and with a wildlife dispersal model. The main results are maps which permit the analysis and the understanding of the impact of human activities on wildlife dispersal. Three applications in a study area are presented: ecological networks at the landscape scale, conflicting areas at the farmstead scale and ecological distance between biotopes. These applications show the flexibility of the model and its potential to give information on ecological networks at different planning scales.

Update of the FANTOM web resource: from mammalian transcriptional landscape to its dynamic regulation.

The international Functional Annotation Of the Mammalian Genomes 4 (FANTOM4) research collaboration set out to better understand the transcriptional network that regulates macrophage differentiation and to uncover novel components of the transcriptome employing a series of high-throughput experiments. The primary and unique technique is cap analysis of gene expression (CAGE), sequencing mRNA 5'-ends with a second-generation sequencer to quantify promoter activities even in the absence of gene annotation. Additional genome-wide experiments complement the setup including short RNA sequencing, microarray gene expression profiling on large-scale perturbation experiments and ChIP-chip for epigenetic marks and transcription factors. All the experiments are performed in a differentiation time course of the THP-1 human leukemic cell line. Furthermore, we performed a large-scale mammalian two-hybrid (M2H) assay between transcription factors and monitored their expression profile across human and mouse tissues with qRT-PCR to address combinatorial effects of regulation by transcription factors. These interdependent data have been analyzed individually and in combination with each other and are published in related but distinct papers. We provide all data together with systematic annotation in an integrated view as resource for the scientific community (http://fantom.gsc.riken.jp/4/). Additionally, we assembled a rich set of derived analysis results including published predicted and validated regulatory interactions. Here we introduce the resource and its update after the initial release.

Decision fusion for the classification of hyperspectral data: Outcome of the 2008 GRS-S data fusion contest

The 2008 Data Fusion Contest organized by the IEEE Geoscience and Remote Sensing Data Fusion Technical Committee deals with the classification of high-resolution hyperspectral data from an urban area. Unlike in the previous issues of the contest, the goal was not only to identify the best algorithm but also to provide a collaborative effort: The decision fusion of the best individual algorithms was aiming at further improving the classification performances, and the best algorithms were ranked according to their relative contribution to the decision fusion. This paper presents the five awarded algorithms and the conclusions of the contest, stressing the importance of decision fusion, dimension reduction, and supervised classification methods, such as neural networks and support vector machines.