Copula functions: A semi-parametric approach to the pricing of basket credit derivatives

Master'sMASTER OF SCIENC

In vivo importance of homologous recombination DNA repair for mouse neural stem and progenitor cells

We characterized the in vivo importance of the homologous recombination factor RAD54 for the developing mouse brain cortex in normal conditions or after ionizing radiation exposure. Contrary to numerous homologous recombination genes, Rad54 disruption did not impact the cortical development without exogenous stress, but it dramatically

The MNI data-sharing and processing ecosystem

AbstractNeuroimaging has been facing a data deluge characterized by the exponential growth of both raw and processed data. As a result, mining the massive quantities of digital data collected in these studies offers unprecedented opportunities and has become paramount for today's research. As the neuroimaging community enters the world of “Big Data”, there has been a concerted push for enhanced sharing initiatives, whether within a multisite study, across studies, or federated and shared publicly. This article will focus on the database and processing ecosystem developed at the Montreal Neurological Institute (MNI) to support multicenter data acquisition both nationally and internationally, create database repositories, facilitate data-sharing initiatives, and leverage existing software toolkits for large-scale data processing

Mega-Analysis of Gray Matter Volume in Substance Dependence: General and Substance-Specific Regional Effects

Objective: Although lower brain volume has been routinely observed in individuals with substance dependence compared with nondependent control subjects, the brain regions exhibiting lower volume have not been consistent across studies. In addition, it is not clear whether a common set of regions are involved in substance dependence regardless of the substance used or whether some brain volume effects are substance specific. Resolution of these issues may contribute to the identification of clinically relevant imaging biomarkers. Using pooled data from 14 countries, the authors sought to identify general and substance-specific associations between dependence and regional brain volumes. Method: Brain structure was examined in a mega-analysis of previously published data pooled from 23 laboratories, including 3,240 individuals, 2,140 of whom had substance dependence on one of five substances: alcohol, nicotine, cocaine, methamphetamine, or cannabis. Subcortical volume and cortical thickness in regions defined by FreeSurfer were compared with nondependent control subjects when all sampled substance categories were combined, as well as separately, while controlling for age, sex, imaging site, and total intracranial volume. Because of extensive associations with alcohol dependence, a secondary contrast was also performed for dependence on all substances except alcohol. An optimized split-half strategy was used to assess the reliability of the findings. Results: Lower volume or thickness was observed in many brain regions in individuals with substance dependence. The greatest effects were associated with alcohol use disorder. A set of affected regions related to dependence in general, regardless of the substance, included the insula and the medial orbitofrontal cortex. Furthermore, a support vector machine multivariate classification of regional brain volumes successfully classified individuals with substance dependence on alcohol or nicotine relative to nondependent control subjects. Conclusions: The results indicate that dependence on a range of different substances shares a common neural substrate and that differential patterns of regional volume could serve as useful biomarkers of dependence on alcohol and nicotine

Analysis of SAW Sensor Coated by a Biocompatible Parylen Polymer

International audiencePiezoelectric sensors are moving rapidly toward commercialization. The issue of robustness and mechanical characterization has become an important consideration in device design and manufacturing. This paper explores experiments and an in-depth analysis of surface acoustic waves (SAW) manufactured on AT-cut quartz substrate with gold transducers and with biocompatible and hydrophobic parylene C (poly(2-chloro-p-xylylene)) coating layer. We discuss different experimental techniques that use electrical and interferometric measurements to analyze the performance of SAW sensors. The present study highlights several approved SAW device characterization techniques and methods, the ways in which they can be optimized, and the ways in which they can be used to enhance SAW device performances

C11orf83, a Mitochondrial Cardiolipin-Binding Protein Involved in bc₁ Complex Assembly and Supercomplex Stabilization

Mammalian mitochondria may contain up to 1,500 different proteins, and many of them have neither been confidently identified nor characterized. In this study, we demonstrated that C11orf83, which was lacking experimental characterization, is a mitochondrial inner membrane protein facing the intermembrane space. This protein is specifically associated with the bc1 complex of the electron transport chain and involved in the early stages of its assembly by stabilizing the bc1 core complex. C11orf83 displays some overlapping functions with Cbp4p, a yeast bc1 complex assembly factor. Therefore, we suggest that C11orf83, now called UQCC3, is the functional human equivalent of Cbp4p. In addition, C11orf83 depletion in HeLa cells caused abnormal crista morphology, higher sensitivity to apoptosis, a decreased ATP level due to impaired respiration and subtle, but significant, changes in cardiolipin composition. We showed that C11orf83 binds to cardiolipin by its α-helices 2 and 3 and is involved in the stabilization of bc1 complex-containing supercomplexes, especially the III2/IV supercomplex. We also demonstrated that the OMA1 metalloprotease cleaves C11orf83 in response to mitochondrial depolarization, suggesting a role in the selection of cells with damaged mitochondria for their subsequent elimination by apoptosis, as previously described for OPA1

Predicting sensorial attribute scores of ornamental plants assessed in 3D through rotation on video by image analysis: A study on the morphology of virtual rose bushes

International audienceThe visual appearance of a plant is tightly linked to its 3D architecture, and can be characterized by means of sensorial experiments. Providing a method to manage image features to predict objective visual traits of real or in silico ornamental plants seen and assessed in rotation, could be a valuable tool to take into account the 3D of the plants in order to reach faster, more faithful and more reproducible hedonic-free characterizations. The present study aims to present a simple approach to manage image data from rotating plant videos in order to predict some visual characteristics as beforehand determined through a non-hedonic sensory evaluation. It is proposed to implement plant morphometrical descriptors using common descriptive statistics computed from 2D features measured along the plant rotation with the aim to integrate the plant 3D. As a preliminary study to evaluate the potential of the proposed approach, the present experiment used virtual plants. First, a sensory profile on 20 virtual rose bushes videos for which 12 plant morphology-related sensory attributes were developed is presented. In parallel, 2D features from the video frames have been extracted considering an 8°-rotation interval and their discriminant power have been checked. Results showed that each sensory attributes presented at least one strong and significant linear relationship with a specific morphometrical descriptor (Pearson’s correlation coefficient ⩾0.8, p-values < 0.001). A stepwise predictor selection procedure to design ordinary least squares (OLS) regression models allowed quite good modeling of the sensory attributes with no more than four morphometrical descriptors (adjusted R2 ⩾ 0.9). Regression on components and penalized models presented also good to acceptable fit, but model cross-validation (CV) and model complexity confirmed the relevance of the OLS models and their selected morphometrical descriptors (R2-CV ⩾ 0.9 and root mean square error of prediction <0.7) and strengthened the pertinence of transposing this image data management for experiments with real plants considering also their color characteristics thus achieving a proof of the concept

Electrical and Optical Characterization of SAW Sensors Coated with Parylene C and Their Analysis Using the Coupling-of-Modes (COM) Theory

International audienceIn this paper, we present how complementary characterization techniques, such as electrical measurements with a vector network analyzer (VNA), optical measurements with a laser Doppler vibrometer (LDV), and numerical simulations with the finite element method, coupled with spectral domain analysis (FEMSDA), allow us to independently access different properties of a SAW device and fully characterize its operation using the coupling-of-modes theory (COM). A set of chemical SAW sensors coated with parylene C layers of different thicknesses (1, 1.5, and 2 µm) and an uncoated sensor were used as test samples. The sensors represent dual-channel electroacoustic delay lines operating in the vicinity of 77 MHz. The IDTs consist of split aluminum electrodes deposited on a AT-cut quartz substrate. The thickness-dependent influence of the parylene C layer was observed on the operating frequency (SAW velocity), static capacitance, attenuation, crosstalk, and reflection coefficient. COM parameters were reported for the four cases considered; measured and simulated data show good agreement. The presented approach is suitable for the design, characterization, and validation of polymer film-coated SAW sensors