Mesoscale modeling and simulation of microstructure evolution during dynamic recrystallization of a Ni-based superalloy

Microstructural evolution and plastic flow characteristics of a Ni-based superalloy were investigated using a simulative model that couples the basic metallurgical principle of dynamic recrystallization (DRX) with the twodimensional (2D) cellular automaton (CA). Variation of dislocation density with local strain of deformation is considered for accurate determination of the microstructural evolution during DRX. The grain topography, the grain size and the recrystallized fraction can be well predicted by using the developed CA model, which enables to the establishment of the relationship between the flow stress, dislocation density, recrystallized fraction volume, recrystallized grain size and the thermomechanical parameters

EZH2 protein: A promising immunomarker for the detection of hepatocellular carcinomas in liver needle biopsies

Background and aims: A previous study of ours indicated that enhancer of zeste homologue 2 (EZH2) plays an important role in hepatocellular carcinoma (HCC) tumorigenesis. The aim of the present study was to investigate the potential diagnostic utility of EZH2 in HCC. Methods: Immunohistochemistry was performed to examine the expression dynamics of EZH2 in two independent surgical cohorts of HCC and non-malignant liver tissues to develop a diagnostic yield of EZH2, HSP70 and GPC3 for HCC detection. The diagnostic performances of EZH2 and a three-marker panel in HCC were re-evaluated by using an additional biopsy cohort. Results: Immunohistochemistry analysis demonstrated that the sensitivity and specificity of EZH2 for HCC detection was 95.8% and 97.8% in the testing cohort. Similar results were confirmed in the validation cohort. For diagnosis of well-differentiated HCCs, the sensitivity and specificity were 68.9% and 91.5% for EZH2, 62.5% and 98.5% for HSP70, 50.0% and 92.1% for GPC3, and 75.0% and 100% for a three-marker panel. In biopsies, positive cases for at least one marker increased from large regenerative nodule and hepatocellular adenoma (0/12) to focal nodular hyperplasia (2/20), dysplastic nodule (7/25), well-differentiated HCC (16/18) and moderately and poorly differentiated HCC (54/54). When at least two positive markers were considered, regardless of their identity, the positive cases were detected in 0/12 large regenerative nodules and hepatocellular adenomas, 0/20 focal nodular hyperplasias, 0/25 dysplastic nodules, 11/18 well-differentiated HCCs, 32/37 moderately differentiated HCCs and 15/17 poorly differentiated HCCs. Conclusion: Our findings suggest that EZH2 protein, as examined by immunohistochemistry, may serve as a promising diagnostic biomarker of HCCs, and the use of a three-marker panel (EZH2, HSP70 and GPC3) can improve the rate of detection of HCCs in liver biopsy tissues.published_or_final_versio

Rupture by damage accumulation in rocks

The deformation of rocks is associated with microcracks nucleation and propagation, i.e. damage. The accumulation of damage and its spatial localization lead to the creation of a macroscale discontinuity, so-called "fault" in geological terms, and to the failure of the material, i.e. a dramatic decrease of the mechanical properties as strength and modulus. The damage process can be studied both statically by direct observation of thin sections and dynamically by recording acoustic waves emitted by crack propagation (acoustic emission). Here we first review such observations concerning geological objects over scales ranging from the laboratory sample scale (dm) to seismically active faults (km), including cliffs and rock masses (Dm, hm). These observations reveal complex patterns in both space (fractal properties of damage structures as roughness and gouge), time (clustering, particular trends when the failure approaches) and energy domains (power-law distributions of energy release bursts). We use a numerical model based on progressive damage within an elastic interaction framework which allows us to simulate these observations. This study shows that the failure in rocks can be the result of damage accumulation

Academic Performance and Behavioral Patterns

Identifying the factors that influence academic performance is an essential part of educational research. Previous studies have documented the importance of personality traits, class attendance, and social network structure. Because most of these analyses were based on a single behavioral aspect and/or small sample sizes, there is currently no quantification of the interplay of these factors. Here, we study the academic performance among a cohort of 538 undergraduate students forming a single, densely connected social network. Our work is based on data collected using smartphones, which the students used as their primary phones for two years. The availability of multi-channel data from a single population allows us to directly compare the explanatory power of individual and social characteristics. We find that the most informative indicators of performance are based on social ties and that network indicators result in better model performance than individual characteristics (including both personality and class attendance). We confirm earlier findings that class attendance is the most important predictor among individual characteristics. Finally, our results suggest the presence of strong homophily and/or peer effects among university students

The MRN complex is transcriptionally regulated by MYCN during neural cell proliferation to control replication stress

The MRE11/RAD50/NBS1 (MRN) complex is a major sensor of DNA double strand breaks, whose role in controlling faithful DNA replication and preventing replication stress is also emerging. Inactivation of the MRN complex invariably leads to developmental and/or degenerative neuronal defects, the pathogenesis of which still remains poorly understood. In particular, NBS1 gene mutations are associated with microcephaly and strongly impaired cerebellar development, both in humans and in the mouse model. These phenotypes strikingly overlap those induced by inactivation of MYCN, an essential promoter of the expansion of neuronal stem and progenitor cells, suggesting that MYCN and the MRN complex might be connected on a unique pathway essential for the safe expansion of neuronal cells. Here, we show that MYCN transcriptionally controls the expression of each component of the MRN complex. By genetic and pharmacological inhibition of the MRN complex in a MYCN overexpression model and in the more physiological context of the Hedgehog-dependent expansion of primary cerebellar granule progenitor cells, we also show that the MRN complex is required for MYCN-dependent proliferation. Indeed, its inhibition resulted in DNA damage, activation of a DNA damage response, and cell death in a MYCN- and replication-dependent manner. Our data indicate the MRN complex is essential to restrain MYCN-induced replication stress during neural cell proliferation and support the hypothesis that replication-born DNA damage is responsible for the neuronal defects associated with MRN dysfunctions.Cell Death and Differentiation advance online publication, 12 June 2015; doi:10.1038/cdd.2015.81

Variational Methods for Biomolecular Modeling

Structure, function and dynamics of many biomolecular systems can be characterized by the energetic variational principle and the corresponding systems of partial differential equations (PDEs). This principle allows us to focus on the identification of essential energetic components, the optimal parametrization of energies, and the efficient computational implementation of energy variation or minimization. Given the fact that complex biomolecular systems are structurally non-uniform and their interactions occur through contact interfaces, their free energies are associated with various interfaces as well, such as solute-solvent interface, molecular binding interface, lipid domain interface, and membrane surfaces. This fact motivates the inclusion of interface geometry, particular its curvatures, to the parametrization of free energies. Applications of such interface geometry based energetic variational principles are illustrated through three concrete topics: the multiscale modeling of biomolecular electrostatics and solvation that includes the curvature energy of the molecular surface, the formation of microdomains on lipid membrane due to the geometric and molecular mechanics at the lipid interface, and the mean curvature driven protein localization on membrane surfaces. By further implicitly representing the interface using a phase field function over the entire domain, one can simulate the dynamics of the interface and the corresponding energy variation by evolving the phase field function, achieving significant reduction of the number of degrees of freedom and computational complexity. Strategies for improving the efficiency of computational implementations and for extending applications to coarse-graining or multiscale molecular simulations are outlined.Comment: 36 page

The Hubbard model within the equations of motion approach

The Hubbard model has a special role in Condensed Matter Theory as it is considered as the simplest Hamiltonian model one can write in order to describe anomalous physical properties of some class of real materials. Unfortunately, this model is not exactly solved except for some limits and therefore one should resort to analytical methods, like the Equations of Motion Approach, or to numerical techniques in order to attain a description of its relevant features in the whole range of physical parameters (interaction, filling and temperature). In this manuscript, the Composite Operator Method, which exploits the above mentioned analytical technique, is presented and systematically applied in order to get information about the behavior of all relevant properties of the model (local, thermodynamic, single- and two- particle ones) in comparison with many other analytical techniques, the above cited known limits and numerical simulations. Within this approach, the Hubbard model is shown to be also capable to describe some anomalous behaviors of the cuprate superconductors.Comment: 232 pages, more than 300 figures, more than 500 reference

Image informatics strategies for deciphering neuronal network connectivity

Brain function relies on an intricate network of highly dynamic neuronal connections that rewires dramatically under the impulse of various external cues and pathological conditions. Among the neuronal structures that show morphologi- cal plasticity are neurites, synapses, dendritic spines and even nuclei. This structural remodelling is directly connected with functional changes such as intercellular com- munication and the associated calcium-bursting behaviour. In vitro cultured neu- ronal networks are valuable models for studying these morpho-functional changes. Owing to the automation and standardisation of both image acquisition and image analysis, it has become possible to extract statistically relevant readout from such networks. Here, we focus on the current state-of-the-art in image informatics that enables quantitative microscopic interrogation of neuronal networks. We describe the major correlates of neuronal connectivity and present workflows for analysing them. Finally, we provide an outlook on the challenges that remain to be addressed, and discuss how imaging algorithms can be extended beyond in vitro imaging studies

Structure of hadron resonances with a nearby zero of the amplitude

We discuss the relation between the analytic structure of the scattering amplitude and the origin of an eigenstate represented by a pole of the amplitude.If the eigenstate is not dynamically generated by the interaction in the channel of interest, the residue of the pole vanishes in the zero coupling limit. Based on the topological nature of the phase of the scattering amplitude, we show that the pole must encounter with the Castillejo-Dalitz-Dyson (CDD) zero in this limit. It is concluded that the dynamical component of the eigenstate is small if a CDD zero exists near the eigenstate pole. We show that the line shape of the resonance is distorted from the Breit-Wigner form as an observable consequence of the nearby CDD zero. Finally, studying the positions of poles and CDD zeros of the KbarN-piSigma amplitude, we discuss the origin of the eigenstates in the Lambda(1405) region.Comment: 7 pages, 3 figures, v2: published versio

Measurement of CP-violation asymmetries in D0 to Ks pi+ pi-

We report a measurement of time-integrated CP-violation asymmetries in the resonant substructure of the three-body decay D0 to Ks pi+ pi- using CDF II data corresponding to 6.0 invfb of integrated luminosity from Tevatron ppbar collisions at sqrt(s) = 1.96 TeV. The charm mesons used in this analysis come from D*+(2010) to D0 pi+ and D*-(2010) to D0bar pi-, where the production flavor of the charm meson is determined by the charge of the accompanying pion. We apply a Dalitz-amplitude analysis for the description of the dynamic decay structure and use two complementary approaches, namely a full Dalitz-plot fit employing the isobar model for the contributing resonances and a model-independent bin-by-bin comparison of the D0 and D0bar Dalitz plots. We find no CP-violation effects and measure an asymmetry of ACP = (-0.05 +- 0.57 (stat) +- 0.54 (syst))% for the overall integrated CP-violation asymmetry, consistent with the standard model prediction.Comment: 15 page