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Search Results: 1 - 10 of 26253 matches for " Martin Maechler "
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Nested Archimedean Copulas Meet R: The nacopula Package
Marius Hofert,Martin Maechler
Journal of Statistical Software , 2011,
Abstract: The package nacopula provides procedures for constructing nested Archimedean copulas in any dimensions and with any kind of nesting structure, generating vectors of random variates from the constructed objects, computing function values and probabilities of falling into hypercubes, as well as evaluation of characteristics such as Kendall's tau and the tail-dependence coefficients. As by-products, algorithms for various distributions, including exponentially tilted stable and Sibuya distributions, are implemented. Detailed examples are given.
Estimators for Archimedean copulas in high dimensions
Marius Hofert,Martin Maechler,Alexander J. McNeil
Statistics , 2012,
Abstract: The performance of known and new parametric estimators for Archimedean copulas is investigated, with special focus on large dimensions and numerical difficulties. In particular, method-of-moments-like estimators based on pairwise Kendall's tau, a multivariate extension of Blomqvist's beta, minimum distance estimators, the maximum-likelihood estimator, a simulated maximum-likelihood estimator, and a maximum-likelihood estimator based on the copula diagonal are studied. Their performance is compared in a large-scale simulation study both under known and unknown margins (pseudo-observations), in small and high dimensions, under small and large dependencies, various different Archimedean families and sample sizes. High dimensions up to one hundred are considered for the first time and computational problems arising from such large dimensions are addressed in detail. All methods are implemented in the open source \R{} package \pkg{copula} and can thus be easily accessed and studied.
Mitochondrial Hormesis in Pancreatic β Cells: Does Uncoupling Protein 2 Play a Role?
Ning Li,Suzana Stojanovski,Pierre Maechler
Oxidative Medicine and Cellular Longevity , 2012, DOI: 10.1155/2012/740849
Abstract: In pancreatic β cells, mitochondrial metabolism translates glucose sensing into signals regulating insulin secretion. Chronic exposure of β cells to excessive nutrients, namely, glucolipotoxicity, impairs β-cell function. This is associated with elevated ROS production from overstimulated mitochondria. Mitochondria are not only the major source of cellular ROS, they are also the primary target of ROS attacks. The mitochondrial uncoupling protein UCP2, even though its uncoupling properties are debated, has been associated with protective functions against ROS toxicity. Hormesis, an adaptive response to cellular stresses, might contribute to the protection against β-cell death, possibly limiting the development of type 2 diabetes. Mitochondrial hormesis, or mitohormesis, is a defense mechanism observed in ROS-induced stress-responses by mitochondria. In β cells, mitochondrial damages induced by sublethal exogenous H2O2 can induce secondary repair and defense mechanisms. In this context, UCP2 is a marker of mitohormesis, being upregulated following stress conditions. When overexpressed in nonstressed naïve cells, UCP2 confers resistance to oxidative stress. Whether treatment with mitohormetic inducers is sufficient to restore or ameliorate secretory function of β cells remains to be determined.
Bioconductor: open software development for computational biology and bioinformatics
Robert C Gentleman, Vincent J Carey, Douglas M Bates, Ben Bolstad, Marcel Dettling, Sandrine Dudoit, Byron Ellis, Laurent Gautier, Yongchao Ge, Jeff Gentry, Kurt Hornik, Torsten Hothorn, Wolfgang Huber, Stefano Iacus, Rafael Irizarry, Friedrich Leisch, Cheng Li, Martin Maechler, Anthony J Rossini, Gunther Sawitzki, Colin Smith, Gordon Smyth, Luke Tierney, Jean YH Yang, Jianhua Zhang
Genome Biology , 2004, DOI: 10.1186/gb-2004-5-10-r80
Abstract: The Bioconductor project [1] is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics (CBB). Biology, molecular biology in particular, is undergoing two related transformations. First, there is a growing awareness of the computational nature of many biological processes and that computational and statistical models can be used to great benefit. Second, developments in high-throughput data acquisition produce requirements for computational and statistical sophistication at each stage of the biological research pipeline. The main goal of the Bioconductor project is creation of a durable and flexible software development and deployment environment that meets these new conceptual, computational and inferential challenges. We strive to reduce barriers to entry to research in CBB. A key aim is simplification of the processes by which statistical researchers can explore and interact fruitfully with data resources and algorithms of CBB, and by which working biologists obtain access to and use of state-of-the-art statistical methods for accurate inference in CBB.Among the many challenges that arise for both statisticians and biologists are tasks of data acquisition, data management, data transformation, data modeling, combining different data sources, making use of evolving machine learning methods, and developing new modeling strategies suitable to CBB. We have emphasized transparency, reproducibility, and efficiency of development in our response to these challenges. Fundamental to all these tasks is the need for software; ideas alone cannot solve the substantial problems that arise.The primary motivations for an open-source computing environment for statistical genomics are transparency, pursuit of reproducibility and efficiency of development.High-throughput methodologies in CBB are extremely complex, and many steps are involved in the conversion of information from low-level information structures (for example,
Changes in Mitochondrial Carriers Exhibit Stress-Specific Signatures in INS-1Eβ-Cells Exposed to Glucose Versus Fatty Acids
Thierry Brun, Pasquale Scarcia, Ning Li, Pascale Gaudet, Dominique Duhamel, Ferdinando Palmieri, Pierre Maechler
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0082364
Abstract: Chronic exposure of β-cells to metabolic stresses impairs their function and potentially induces apoptosis. Mitochondria play a central role in coupling glucose metabolism to insulin secretion. However, little is known on mitochondrial responses to specific stresses; i.e. low versus high glucose, saturated versus unsaturated fatty acids, or oxidative stress. INS-1E cells were exposed for 3 days to 5.6 mM glucose, 25 mM glucose, 0.4 mM palmitate, and 0.4 mM oleate. Culture at standard 11.1 mM glucose served as no-stress control and transient oxidative stress (200 μM H2O2 for 10 min at day 0) served as positive stressful condition. Mito-array analyzed transcripts of 60 mitochondrion-associated genes with special focus on members of the Slc25 family. Transcripts of interest were evaluated at the protein level by immunoblotting. Bioinformatics analyzed the expression profiles to delineate comprehensive networks. Chronic exposure to the different metabolic stresses impaired glucose-stimulated insulin secretion; revealing glucotoxicity and lipo-dysfunction. Both saturated and unsaturated fatty acids increased expression of the carnitine/acylcarnitine carrier CAC, whereas the citrate carrier CIC and energy sensor SIRT1 were specifically upregulated by palmitate and oleate, respectively. High glucose upregulated CIC, the dicarboxylate carrier DIC and glutamate carrier GC1. Conversely, it reduced expression of energy sensors (AMPK, SIRT1, SIRT4), metabolic genes, transcription factor PDX1, and anti-apoptotic Bcl2. This was associated with caspase-3 cleavage and cell death. Expression levels of GC1 and SIRT4 exhibited positive and negative glucose dose-response, respectively. Expression profiles of energy sensors and mitochondrial carriers were selectively modified by the different conditions, exhibiting stress-specific signatures.
A role for pancreatic beta-cell secretory hyperresponsiveness in catch-up growth hyperinsulinemia: Relevance to thrifty catch-up fat phenotype and risks for type 2 diabetes
Marina Casimir, Paula B de Andrade, Asllan Gjinovci, Jean-Pierre Montani, Pierre Maechler, Abdul G Dulloo
Nutrition & Metabolism , 2011, DOI: 10.1186/1743-7075-8-2
Abstract: A large body of evidence indicate that subjects who had low birth weight or who showed reduced growth rate during childhood, but who subsequently showed catch-up growth, have higher susceptibility for type 2 diabetes or cardiovascular diseases later in life [1-5]. While the nature of this association between catch-up growth and later disease risks remains obscure [6], it is intricately linked to the state of hyperinsulinemia and accelerated recovery of body fat (catch-up fat) that characterizes catch-up growth [5-7]. There is a well-described rat model of semistarvation-refeeding in which catch-up fat and hyperinsulinemia occur in absence of hyperphagia and could be linked to an elevated metabolic efficiency due to suppressed thermogenesis [8]. Using this model, we previously showed that insulin-mediated glucose utilization is diminished in skeletal muscle but enhanced in white adipose tissue [9], thereby suggesting that catch-up fat is characterized by glucose redistribution from skeletal muscle to adipose tissue. The suppressed thermogenesis is thus associated with establishment of a thrifty metabolism which spares glucose for catch-up fat via coordinated induction of insulin resistance in skeletal muscle, insulin hyperresponsiveness in adipose tissue and a state of hyperinsulinemia. In this context, putative implication of insulin-secreting cells remains unknown. Here, we tested the hypothesis that the hyperinsulinemic state of catch-up fat might also be contributed by pancreatic beta-cell hyperresponsiveness to glucose. To this end, we investigated the semistarvation-refeeding rat model for pancreatic endocrine function and morphology. In particular, the secretory responses of perfused pancreases and isolated islets were analyzed.Male Sprague Dawley rats (Elevage Janvier, France), caged singly in a temperature-controlled room (22 ± 1°C) with 12-h light/dark cycle, were maintained on chow diet (Kliba, Cossonay, Switzerland) consisting, by energy, of 24% protein,
Preventing Mitochondrial Fission Impairs Mitochondrial Function and Leads to Loss of Mitochondrial DNA
Philippe A. Parone, Sandrine Da Cruz, Daniel Tondera, Yves Mattenberger, Dominic I. James, Pierre Maechler, Fran?ois Barja, Jean-Claude Martinou
PLOS ONE , 2008, DOI: 10.1371/journal.pone.0003257
Abstract: Mitochondria form a highly dynamic tubular network, the morphology of which is regulated by frequent fission and fusion events. However, the role of mitochondrial fission in homeostasis of the organelle is still unknown. Here we report that preventing mitochondrial fission, by down-regulating expression of Drp1 in mammalian cells leads to a loss of mitochondrial DNA and a decrease of mitochondrial respiration coupled to an increase in the levels of cellular reactive oxygen species (ROS). At the cellular level, mitochondrial dysfunction resulting from the lack of fission leads to a drop in the levels of cellular ATP, an inhibition of cell proliferation and an increase in autophagy. In conclusion, we propose that mitochondrial fission is required for preservation of mitochondrial function and thereby for maintenance of cellular homeostasis.
Adenovector GAD65 gene delivery into the rat trigeminal ganglion produces orofacial analgesia
Jean-Philippe Vit, Peter T Ohara, Christopher Sundberg, Blanca Rubi, Pierre Maechler, Chunyan Liu, Mariana Puntel, Pedro Lowenstein, Maria Castro, Luc Jasmin
Molecular Pain , 2009, DOI: 10.1186/1744-8069-5-42
Abstract: Injection of adenoviral vectors (AdGAD65) directly into the trigeminal ganglion leads to sustained expression of the GAD65 isoform over the 4 weeks observation period. Immunohistochemical analysis showed that adenovirus-mediated GAD65 expression and GABA synthesis were mainly in SGCs. GABAA and GABAB receptors were both seen in sensory neurons, yet only GABAA receptors decorated the neuronal surface. GABA receptors were not found on SGCs. Six days after injection of AdGAD65 into the trigeminal ganglion, there was a statistically significant decrease of pain behavior in the orofacial formalin test, a model of inflammatory pain. Rats injected with control virus (AdGFP or AdLacZ) had no reduction in their pain behavior. AdGAD65-dependent analgesia was blocked by bicuculline, a selective GABAA receptor antagonist, but not by CGP46381, a selective GABAB receptor antagonist.Transfection of glial cells in the trigeminal ganglion with the GAD gene blocks pain behavior by acting on GABAA receptors on neuronal perikarya.Pain sensation most commonly results from the activation of peripheral branches of primary sensory neurons, the perikarya of which are located in either dorsal root ganglia (DRG) for body sensation or the trigeminal ganglia for sensation from the face. The central branches of sensory neurons in DRG terminate in the dorsal horn of the spinal cord and those of the trigeminal ganglion in the brainstem trigeminal nucleus. Injury to tissue or peripheral nerve induces central nervous system sensitization, facilitating pain processing responsible for allodynia and hyperalgesia [1,2]. A number of studies have shown that reducing the activity of primary afferents is often sufficient to alleviate peripherally generated pain conditions.One approach to reducing neuronal activity is through the use of the inhibitory transmitter gamma-aminobutyric acid (GABA). Although there is an abundant literature showing the antinociceptive efficacy of GABA-acting drugs, most reports ha
A Yield Mapping Procedure Based on Robust Fitting Paraboloid Cones on Moving Elliptical Neighborhoods and the Determination of Their Size Using a Robust Variogram  [PDF]
Martin Bachmaier
Positioning (POS) , 2010, DOI: 10.4236/pos.2010.11004
Abstract: The yield map is generated by fitting the yield surface shape of yield monitor data mainly using paraboloid cones on floating neighborhoods. Each yield map value is determined by the fit of such a cone on an elliptical neighborhood that is wider across the harvest tracks than it is along them. The coefficients of regression for modeling the paraboloid cones and the scale parameter are estimated using robust weighted M-estimators where the weights decrease quadratically from 1 in the middle to zero at the border of the selected neighborhood. The robust way of estimating the model parameters supersedes a procedure for detecting outliers. For a given neighborhood shape, this yield mapping method is implemented by the Fortran program paraboloidmapping.exe, which can be downloaded from the web. The size of the selected neighborhood is considered appropriate if the variance of the yield map values equals the variance of the true yields, which is the difference between the variance of the raw yield data and the error variance of the yield monitor. It is estimated using a robust variogram on data that have not had the trend removed.
Sources of inaccuracy when estimating economically optimum N fertilizer rates  [PDF]
Martin Bachmaier
Agricultural Sciences (AS) , 2012, DOI: 10.4236/as.2012.33037
Abstract: Nitrogen rate trials are often performed to determine the economically optimum N application rate. For this purpose, the yield is modeled as a function of the N application. The regression analysis provides an estimate of the modeled function and thus also an estimate of the economic optimum, Nopt. Obtaining the accuracy of such estimates by confidence intervals for Nopt is subject to the model assumptions. The dependence of these assumptions is a further source of inaccuracy. The Nopt estimate also strongly depends on the N level design, i.e., the area on which the model is fitted. A small area around the supposed Nopt diminishes the dependence of the model assumptions, but prolongs the confidence interval. The investigations of the impact of the mentioned sources on the inaccuracy of the Nopt estimate rely on N rate trials on the experimental field Sieblerfeld (Bavaria). The models applied are the quadratic and the linear-plus-plateau yield regression model.
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