Evolution of the Pelagonian carbonate platform complex and the adjacent oceanic realm in response to plate tectonic forcing (Late Triassic and Jurassic), Evvoia, Greece

The Late Triassic and Jurassic platform and the oceanic complexes in Evvoia, Greece, share a complementary plate-tectonic evolution. Shallow marine carbonate deposition responded to changing rates of subsidence and uplift, whilst the adjacent ocean underwent spreading, and then convergence, collision and finally obduction over the platform complex. Late Triassic ocean spreading correlated with platform subsidence and the formation of a long-persisting peritidal passive-margin platform. Incipient drowning occurred from the Sinemurian to the late Middle Jurassic. This subsidence correlated with intra-oceanic subduction and plate convergence that led to supra-subduction calc-alkaline magmatism and the formation of a primitive volcanic arc. During the Middle Jurassic, plate collision caused arc uplift above the carbonate compensation depth (CCD) in the oceanic realm, and related thrust-faulting, on the platform, led to sub-aerial exposures. Patch-reefs developed there during the Late Oxfordian to Kimmeridgian. Advanced oceanic nappe-loading caused platform drowning below the CCD during the Tithonian, which is documented by intercalations of reefal turbidites with non-carbonate radiolarites. Radiolarites and bypass-turbidites, consisting of siliciclastic greywacke, terminate the platform succession beneath the emplaced oceanic nappe during late Tithonian to Valanginian time.

Analysis and spatial modeling of the indoor radon Swiss data

The present research deals with an important public health threat, which is the pollution created by radon gas accumulation inside dwellings. The spatial modeling of indoor radon in Switzerland is particularly complex and challenging because of many influencing factors that should be taken into account. Indoor radon data analysis must be addressed from both a statistical and a spatial point of view. As a multivariate process, it was important at first to define the influence of each factor. In particular, it was important to define the influence of geology as being closely associated to indoor radon. This association was indeed observed for the Swiss data but not probed to be the sole determinant for the spatial modeling. The statistical analysis of data, both at univariate and multivariate level, was followed by an exploratory spatial analysis. Many tools proposed in the literature were tested and adapted, including fractality, declustering and moving windows methods. The use of Quan-tité Morisita Index (QMI) as a procedure to evaluate data clustering in function of the radon level was proposed. The existing methods of declustering were revised and applied in an attempt to approach the global histogram parameters. The exploratory phase comes along with the definition of multiple scales of interest for indoor radon mapping in Switzerland. The analysis was done with a top-to-down resolution approach, from regional to local lev¬els in order to find the appropriate scales for modeling. In this sense, data partition was optimized in order to cope with stationary conditions of geostatistical models. Common methods of spatial modeling such as Κ Nearest Neighbors (KNN), variography and General Regression Neural Networks (GRNN) were proposed as exploratory tools. In the following section, different spatial interpolation methods were applied for a par-ticular dataset. A bottom to top method complexity approach was adopted and the results were analyzed together in order to find common definitions of continuity and neighborhood parameters. Additionally, a data filter based on cross-validation was tested with the purpose of reducing noise at local scale (the CVMF). At the end of the chapter, a series of test for data consistency and methods robustness were performed. This lead to conclude about the importance of data splitting and the limitation of generalization methods for reproducing statistical distributions. The last section was dedicated to modeling methods with probabilistic interpretations. Data transformation and simulations thus allowed the use of multigaussian models and helped take the indoor radon pollution data uncertainty into consideration. The catego-rization transform was presented as a solution for extreme values modeling through clas-sification. Simulation scenarios were proposed, including an alternative proposal for the reproduction of the global histogram based on the sampling domain. The sequential Gaussian simulation (SGS) was presented as the method giving the most complete information, while classification performed in a more robust way. An error measure was defined in relation to the decision function for data classification hardening. Within the classification methods, probabilistic neural networks (PNN) show to be better adapted for modeling of high threshold categorization and for automation. Support vector machines (SVM) on the contrary performed well under balanced category conditions. In general, it was concluded that a particular prediction or estimation method is not better under all conditions of scale and neighborhood definitions. Simulations should be the basis, while other methods can provide complementary information to accomplish an efficient indoor radon decision making.

Regional deterministic characterization of fracture networks and its application to GIS-based rock fall risk assessment

The study investigates the possibility to incorporate fracture intensity and block geometry as spatially continuous parameters in GIS-based systems. For this purpose, a deterministic method has been implemented to estimate block size (Bloc3D) and joint frequency (COLTOP). In addition to measuring the block size, the Bloc3D Method provides a 3D representation of the shape of individual blocks. These two methods were applied using field measurements (joint set orientation and spacing) performed over a large field area, in the Swiss Alps. This area is characterized by a complex geology, a number of different rock masses and varying degrees of metamorphism. The spatial variability of the parameters was evaluated with regard to lithology and major faults. A model incorporating these measurements and observations into a GIS system to assess the risk associated with rock falls is proposed. The analysis concludes with a discussion on the feasibility of such an application in regularly and irregularly jointed rock masses, with persistent and impersistent discontinuities.

Systems Genetics of Metabolism: The Use of the BXD Murine Reference Panel for Multiscalar Integration of Traits.

Metabolic homeostasis is achieved by complex molecular and cellular networks that differ significantly among individuals and are difficult to model with genetically engineered lines of mice optimized to study single gene function. Here, we systematically acquired metabolic phenotypes by using the EUMODIC EMPReSS protocols across a large panel of isogenic but diverse strains of mice (BXD type) to study the genetic control of metabolism. We generated and analyzed 140 classical phenotypes and deposited these in an open-access web service for systems genetics (www.genenetwork.org). Heritability, influence of sex, and genetic modifiers of traits were examined singly and jointly by using quantitative-trait locus (QTL) and expression QTL-mapping methods. Traits and networks were linked to loci encompassing both known variants and novel candidate genes, including alkaline phosphatase (ALPL), here linked to hypophosphatasia. The assembled and curated phenotypes provide key resources and exemplars that can be used to dissect complex metabolic traits and disorders.

Graphical probabilistic analysis of the combination of items of evidence

Unlike the evaluation of single items of scientific evidence, the formal study and analysis of the jointevaluation of several distinct items of forensic evidence has to date received some punctual, ratherthan systematic, attention. Questions about the (i) relationships among a set of (usually unobservable)propositions and a set of (observable) items of scientific evidence, (ii) the joint probative valueof a collection of distinct items of evidence as well as (iii) the contribution of each individual itemwithin a given group of pieces of evidence still represent fundamental areas of research. To somedegree, this is remarkable since both, forensic science theory and practice, yet many daily inferencetasks, require the consideration of multiple items if not masses of evidence. A recurrent and particularcomplication that arises in such settings is that the application of probability theory, i.e. the referencemethod for reasoning under uncertainty, becomes increasingly demanding. The present paper takesthis as a starting point and discusses graphical probability models, i.e. Bayesian networks, as frameworkwithin which the joint evaluation of scientific evidence can be approached in some viable way.Based on a review of existing main contributions in this area, the article here aims at presentinginstances of real case studies from the author's institution in order to point out the usefulness andcapacities of Bayesian networks for the probabilistic assessment of the probative value of multipleand interrelated items of evidence. A main emphasis is placed on underlying general patterns of inference,their representation as well as their graphical probabilistic analysis. Attention is also drawnto inferential interactions, such as redundancy, synergy and directional change. These distinguish thejoint evaluation of evidence from assessments of isolated items of evidence. Together, these topicspresent aspects of interest to both, domain experts and recipients of expert information, because theyhave bearing on how multiple items of evidence are meaningfully and appropriately set into context.

Fertility preservation in cancer patients. Review of the French speaking part of Switzerland and recommendations for different situations.

Due to constant progress in oncology, survival rates of patients (children and adults) with cancer are increasing. Consequently, the reproductive future of young cancer patients needs to be addressed carefully. Fertility preservation techniques are available and issues such as the time available for fertility treatments, patients' age, presence of a partner and patients' personal wishes have to be considered. In Switzerland, a first therapeutic network (Réseau Romand de Cancer et Fertilité), was created in the French speaking part of Switzerland in 2006. Since 2010, a global Swiss network (FertiSave) has been created. The goal of these networks is to maximise the safety and efficacy of fertility preservation options offered to cancer patients without compromising their oncological prognosis. Patients' needs have to be identified, the therapeutic options evaluated rapidly and the optimal treatment promptly implemented in these urgent situations. This article reviews the fertility preservation options currently available and makes recommendations for different specific cancer situations, consistent with the latest scientific evidence and in general agreement with international recommendations.

Contribution of neural networks to Alzheimer disease's progression.

The neuropathology of Alzheimer disease is characterized by senile plaques, neurofibrillary tangles and cell death. These hallmarks develop according to the differential vulnerability of brain networks, senile plaques accumulating preferentially in the associative cortical areas and neurofibrillary tangles in the entorhinal cortex and the hippocampus. We suggest that the main aetiological hypotheses such as the beta-amyloid cascade hypothesis or its variant, the synaptic beta-amyloid hypothesis, will have to consider neural networks not just as targets of degenerative processes but also as contributors of the disease's progression and of its phenotype. Three domains of research are highlighted in this review. First, the cerebral reserve and the redundancy of the network's elements are related to brain vulnerability. Indeed, an enriched environment appears to increase the cerebral reserve as well as the threshold of disease's onset. Second, disease's progression and memory performance cannot be explained by synaptic or neuronal loss only, but also by the presence of compensatory mechanisms, such as synaptic scaling, at the microcircuit level. Third, some phenotypes of Alzheimer disease, such as hallucinations, appear to be related to progressive dysfunction of neural networks as a result, for instance, of a decreased signal to noise ratio, involving a diminished activity of the cholinergic system. Overall, converging results from studies of biological as well as artificial neural networks lead to the conclusion that changes in neural networks contribute strongly to Alzheimer disease's progression.

A high-resolution anatomical atlas of the transcriptome in the mouse embryo.

Ascertaining when and where genes are expressed is of crucial importance to understanding or predicting the physiological role of genes and proteins and how they interact to form the complex networks that underlie organ development and function. It is, therefore, crucial to determine on a genome-wide level, the spatio-temporal gene expression profiles at cellular resolution. This information is provided by colorimetric RNA in situ hybridization that can elucidate expression of genes in their native context and does so at cellular resolution. We generated what is to our knowledge the first genome-wide transcriptome atlas by RNA in situ hybridization of an entire mammalian organism, the developing mouse at embryonic day 14.5. This digital transcriptome atlas, the Eurexpress atlas (http://www.eurexpress.org), consists of a searchable database of annotated images that can be interactively viewed. We generated anatomy-based expression profiles for over 18,000 coding genes and over 400 microRNAs. We identified 1,002 tissue-specific genes that are a source of novel tissue-specific markers for 37 different anatomical structures. The quality and the resolution of the data revealed novel molecular domains for several developing structures, such as the telencephalon, a novel organization for the hypothalamus, and insight on the Wnt network involved in renal epithelial differentiation during kidney development. The digital transcriptome atlas is a powerful resource to determine co-expression of genes, to identify cell populations and lineages, and to identify functional associations between genes relevant to development and disease.

Functions of the human papillomavirus type 16 E4 protein

1. Abstract Cervical cancer is thought to be the consequence of infection by human papillomaviruses (HPV). In the majority of cases, DNA from HPV type 16 (HPV16) is found in malignant cervical lesions. The initial steps leading to transformation of an infected cell are not clearly understood but in most cases, disruption and integration of the episomal viral DNA must take place. As a consequence, the E2 and E4 genes are usually not expressed whereas the E6 and E7 oncogenes are highly expressed. However, in a normal infection in which the viral DNA is maintained as an episome, all viral genes are expressed. The pattern according to which the viral proteins are made, and therefore the life cycle of the virus, is tightly linked to the differentiation process of the host keratinocyte. The study of the viral oncogenes E6 and E7 has revealed crucial functions in the process of malignant transformation such as degradation of the p53 tumor suppressor protein, deregulation of the Retinoblastoma protein pathway and activation of the telomerase ribonucleoprotein. All these steps are necessary for cancerous lesions to develop. However, the loss of the E2 gene product seems to be necessary for sufficient expression of E6 and E7 in order to achieve such effects. In normal infections, the E4 protein is made abundantly in the later stages of the viral life cycle. Though extensive amounts of work have been carried out to define the function of E4, it still remains unclear. In this study, several approaches have been used to try and determine the functions of E4. First, a cell-penetrating fusion protein was designed and produced in order to circumvent the chronic difficulties of expressing E4 in mammalian cells. Unfortunately, this approach was not successful due to precipitation of the purified fusion protein. Second, the observation that E4 accumulates in cells having modified their adhesion properties led to the hypothesis that E4 might be involved in the differentiation process of keratinocytes. Preliminary results suggest that E4 triggers differentiation. Last, as E4 has been reported to collapse the cytokeratin network of keratinocytes, a direct approach using atomic force microscopy has allowed us to test the potential modification of mechanical properties of cells harboring reorganized cytokeratin networks. If so, a potential role for E4 in viral particle release could be hypothesized. 2. Résumé Il a été établi que le cancer du col de l'utérus se développe essentiellement à la suite d'une infection par le virus du papillome humain (HPV). Dans la majorité des cas analysés, de l'ADN du HPV de type 16 (HPV16) est détecté. Les étapes initiales de la transformation d'une cellule infectée sont mal connues mais il semble qu'une rupture du génome viral, normalement épisomal, suivi d'une intégration dans le génome de la cellule hôte soient des étapes nécessaires dans la plupart des cas. Or il semble qu'il y ait une sélection pour les cas où l'expression des oncogènes viraux E6 et E7 soit favorisée alors que l'expression des gènes E2 et E4 est en général impossible. Par contre, dans une infection dite normale où le génome viral n'est pas rompu, il n'y pas développement de cancer et tous les gènes viraux sont exprimés. L'ordre dans lequel les protéines virales sont produites, et donc le cycle de réplication du virus, est intimement lié au processus de différentiation de la cellule hôte. L'étude des protéines oncogènes E6 et E7 a révélé des fonctions clés dans le processus de transformation des cellules infectées telles que la dégradation du suppresseur de tumeur p53, la dérégulation de la voie de signalisation Rb ainsi que l'activation de la télomérase. Toutes ces activités sont nécessaires au développement de lésions cancéreuses. Toutefois, il semble que l'expression du gène E2 doit être empêchée afin que suffisamment des protéines E6 et E7 soient produites. Lorsque le gène E2 est exprimé, et donc lorsque le génome viral n'est pas rompu, les protéines E6 et E7 n'entraînent pas de telles conséquences. Le gène E4, qui se trouve dans la séquence codante de E2, a aussi besoin d'un génome viral intact pour être exprimé. Dans une infection normale, le gène E4 est exprimé abondamment dans les dernières étapes de la réplication du virus. Bien que de nombreuses études aient été menées afin de déterminer la fonction virale à E4, aucun résultat n'apparaît évident. Dans ce travail, plusieurs approches ont été utilisées afin d'adresser cette question. Premièrement, une protéine de fusion TAT-E4 a été produite et purifiée. Cette protéine, pouvant entrer dans les cellules vivantes par diffusion au travers de la membrane plasmique, aurait permis d'éviter ainsi les problèmes chroniques rencontrés lors de l'expression de E4 dans les cellules mammifères. Malheureusement, cette stratégie n'a pas pu être utilisée à cause de la précipitation de la protéine purifiée. Ensuite, l'observation que E4 s'accumule dans les cellules ayant modifié leurs propriétés d'adhésion a suggéré que E4 pourrait être impliqué dans le procédé de différentiation des kératinocytes. Des résultats préliminaires supportent cette possibilité. Enfin, il a été montré que E4 pouvait induire une réorganisation du réseau des cytokératines. Une approche directe utilisant le microscope à force atomique nous a ainsi permis de tester une potentielle modification des propriétés mécaniques de cellules ayant modifié leur réseau de cytokératines en présence de E4. Si tel est le cas, un rôle dans la libération de particules virales peut être proposé pour E4.

Genome-wide profiling of the cardiac transcriptome after myocardial infarction identifies novel heart-specific long non-coding RNAs.

AIM: Heart disease is recognized as a consequence of dysregulation of cardiac gene regulatory networks. Previously, unappreciated components of such networks are the long non-coding RNAs (lncRNAs). Their roles in the heart remain to be elucidated. Thus, this study aimed to systematically characterize the cardiac long non-coding transcriptome post-myocardial infarction and to elucidate their potential roles in cardiac homoeostasis. METHODS AND RESULTS: We annotated the mouse transcriptome after myocardial infarction via RNA sequencing and ab initio transcript reconstruction, and integrated genome-wide approaches to associate specific lncRNAs with developmental processes and physiological parameters. Expression of specific lncRNAs strongly correlated with defined parameters of cardiac dimensions and function. Using chromatin maps to infer lncRNA function, we identified many with potential roles in cardiogenesis and pathological remodelling. The vast majority was associated with active cardiac-specific enhancers. Importantly, oligonucleotide-mediated knockdown implicated novel lncRNAs in controlling expression of key regulatory proteins involved in cardiogenesis. Finally, we identified hundreds of human orthologues and demonstrate that particular candidates were differentially modulated in human heart disease. CONCLUSION: These findings reveal hundreds of novel heart-specific lncRNAs with unique regulatory and functional characteristics relevant to maladaptive remodelling, cardiac function and possibly cardiac regeneration. This new class of molecules represents potential therapeutic targets for cardiac disease. Furthermore, their exquisite correlation with cardiac physiology renders them attractive candidate biomarkers to be used in the clinic.

Using Pareto optimality to explore the topology and dynamics of the human connectome.

Graph theory has provided a key mathematical framework to analyse the architecture of human brain networks. This architecture embodies an inherently complex relationship between connection topology, the spatial arrangement of network elements, and the resulting network cost and functional performance. An exploration of these interacting factors and driving forces may reveal salient network features that are critically important for shaping and constraining the brain's topological organization and its evolvability. Several studies have pointed to an economic balance between network cost and network efficiency with networks organized in an 'economical' small-world favouring high communication efficiency at a low wiring cost. In this study, we define and explore a network morphospace in order to characterize different aspects of communication efficiency in human brain networks. Using a multi-objective evolutionary approach that approximates a Pareto-optimal set within the morphospace, we investigate the capacity of anatomical brain networks to evolve towards topologies that exhibit optimal information processing features while preserving network cost. This approach allows us to investigate network topologies that emerge under specific selection pressures, thus providing some insight into the selectional forces that may have shaped the network architecture of existing human brains.

A systems view of risk factors for knee osteoarthritis reveals insights into the pathogenesis of the disease.

Early detection of osteoarthritis (OA) remains a critical yet unsolved multifaceted problem. To address the multifaceted nature of OA a systems model was developed to consolidate a number of observations on the biological, mechanical and structural components of OA and identify features common to the primary risk factors for OA (aging, obesity and joint trauma) that are present prior to the development of clinical OA. This analysis supports a unified view of the pathogenesis of OA such that the risk for developing OA emerges when one of the components of the disease (e.g., mechanical) becomes abnormal, and it is the interaction with the other components (e.g., biological and/or structural) that influences the ultimate convergence to cartilage breakdown and progression to clinical OA. The model, applied in a stimulus-response format, demonstrated that a mechanical stimulus at baseline can enhance the sensitivity of a biomarker to predict cartilage thinning in a 5 year follow-up in patients with knee OA. The systems approach provides new insight into the pathogenesis of the disease and offers the basis for developing multidisciplinary studies to address early detection and treatment at a stage in the disease where disease modification has the greatest potential for a successful outcome.

An 8-Item Short Form of the Inventory of Dimensions of Emerging Adulthood (IDEA) Among Young Swiss Men.

Emerging adulthood is a period of life transition, in which youths are no longer adolescents but have not yet reached full adulthood. Measuring emerging adulthood is crucial because of its association with psychopathology and risky behaviors such as substance use. Unfortunately, the only validated scale for such measurement has a long format (Inventory of Dimensions of Emerging Adulthood [IDEA]-31 items). This study aimed to test whether a shorter form yields satisfactory results without substantial loss of information among a sample of young Swiss men. Data from the longitudinal Cohort Study on Substance Use Risk Factors were used (N = 5,049). IDEA, adulthood markers (e.g., parenthood or financial independence), and risk factors (i.e., substance use and mental health issues) were assessed. The results showed that an 8-item, short-form scale (IDEA-8) with four factors (experimentation, negativity, identity exploration, and feeling in between) returned satisfactory results, including good psychometric properties, high convergence with the initial scale, and strong empirical validity. This study was a step toward downsizing a measure of emerging adulthood. Indeed, this 8-item short form is a good alternative to the 31-item long form and could be more convenient for surveys with constraints on questionnaire length. Moreover, it should help health care practitioners in identifying at-risk populations to prevent and treat risky behaviors.

Proximity of excitatory synapses and astroglial gap junctions in layer IV of the mouse barrel cortex.

Neurons and astrocytes, the two major cell populations in the adult brain, are characterized by their own mode of intercellular communication--the synapses and the gap junctions (GJ), respectively. In addition, there is increasing evidence for dynamic and metabolic neuroglial interactions resulting in the modulation of synaptic transmission at the so-called "tripartite synapse". Based on this, we have investigated at the ultrastructural level how excitatory synapses (ES) and astroglial GJ are spatially distributed in layer IV of the barrel cortex of the adult mouse. We used specific antibodies for connexin (Cx) 30 and 43 to identify astroglial GJ, these two proteins are known to be present in the majority of astroglial GJ in the cerebral cortex. In electron-microscopic images, we measured the distance between two ES, between two GJ and between a GJ and its nearest ES. We found a ratio of two GJ per three ES in the hollow and septal areas. Taking into account the size of an astrocyte domain, the high density of GJ suggests the occurrence of reflexive type, i.e. GJ between processes of the same astrocyte. Interestingly, the distance between an ES and an astroglial GJ was found to be significantly lower than that between either two synapses or between two GJ. These observations indicate that the two modes of cell-to-cell communication are not randomly distributed in layer IV of the barrel cortex. Consequently, this feature may provide the morphological support for the recently reported functional interactions between neuronal circuits and astroglial networks.