Hybrid Forecasting with Estimated Temporally Aggregated Linear Processes

We introduce a new strategy for the prediction of linear temporal aggregates; we call it ‘hybrid’ and study its performance using asymptotic theory. This scheme consists of carrying out model parameter estimation with data sampled at the highest available frequency and the subsequent prediction with data and models aggregated according to the forecasting horizon of interest. We develop explicit expressions that approximately quantify the mean square forecasting errors associated with the different prediction schemes and that take into account the estimation error component. These approximate estimates indicate that the hybrid forecasting scheme tends to outperform the so‐called ‘all‐aggregated’ approach and, in some instances, the ‘all‐disaggregated’ strategy that is known to be optimal when model selection and estimation errors are neglected. Unlike other related approximate formulas existing in the literature, those proposed in this paper are totally explicit and require neither assumptions on the second‐order stationarity of the sample nor Monte Carlo simulations for their evaluation. Copyright © 2014 John Wiley & Sons, Ltd.     

Sequential inactivation of Rho GTPases and Lim kinase by Pseudomonas aeruginosa toxins ExoS and ExoT leads to endothelial monolayer breakdown

Pseudomonas aeruginosa is a major human opportunistic pathogen and one of the most important causal agents of bacteremia. For non-blood-borne infection, bacterial dissemination requires the crossing of the vascular endothelium, the main barrier between blood and the surrounding tissues. Here, we investigated the effects of P. aeruginosa type 3 secretion effectors, namely ExoS, ExoT, and ExoY, on regulators of actin cytoskeleton dynamics in primary endothelial cells. ExoS and ExoT similarly affected the Lim kinase-cofilin pathway, thereby promoting actin filament severing. Cofilin activation was also observed in a mouse model of P. aeruginosa-induced acute pneumonia. Rho, Rac, and Cdc42 GTPases were sequentially inactivated, leading to inhibition of membrane ruffling, filopodia, and stress fiber collapse, and focal adhesion disruption. At the end of the process, ExoS and ExoT produced a dramatic retraction in all primary endothelial cell types tested and thus a rupture of the endothelial monolayer. ExoY alone had no effect in this context. Cell retraction could be counteracted by overexpression of actin cytoskeleton regulators. In addition, our data suggest that moesin is neither a direct exotoxin target nor an important player in this process. We conclude that any action leading to inhibition of actin filament breakdown will improve the barrier function of the endothelium during P. aeruginosa infection.     

Myostatin and the skeletal muscle atrophy and hypertrophy signaling pathways

Myostatin, a member of the transforming growth factor-β superfamily, is a potent negative regulator of skeletal muscle growth and is conserved in many species, from rodents to humans. Myostatin inactivation can induce skeletal muscle hypertrophy, while its overexpression or systemic administration causes muscle atrophy. As it represents a potential target for stimulating muscle growth and/or preventing muscle wasting, myostatin regulation and functions in the control of muscle mass have been extensively studied. A wealth of data strongly suggests that alterations in skeletal muscle mass are associated with dysregulation in myostatin expression. Moreover, myostatin plays a central role in integrating/mediating anabolic and catabolic responses. Myostatin negatively regulates the activity of the Akt pathway, which promotes protein synthesis, and increases the activity of the ubiquitin–proteasome system to induce atrophy. Several new studies have brought new information on how myostatin may affect both ribosomal biogenesis and translation efficiency of specific mRNA subclasses. In addition, although myostatin has been identified as a modulator of the major catabolic pathways, including the ubiquitin–proteasome and the autophagy–lysosome systems, the underlying mechanisms are only partially understood. The goal of this review is to highlight outstanding questions about myostatin-mediated regulation of the anabolic and catabolic signaling pathways in skeletal muscle. Particular emphasis has been placed on (1) the cross-regulation between myostatin, the growth-promoting pathways and the proteolytic systems; (2) how myostatin inhibition leads to muscle hypertrophy; and (3) the regulation of translation by myostatin.     

A bibliographical study of the introduction of Lavoisier's Traité élémentaire de chimie into Great Britain and America

As the most famous woman scientist of the twentieth century, there has been no shortage of books and articles on the life and career of Marie Curie (1867–1934). Her role as a director of a laboratory-based research school in the new scientific field of radioactivity, a field which embraced both chemistry and physics, however, has never been examined. In recent years, there has been a growing interest in the question of research schools, and Morrell, Ravetz, Geison, and Klosterman, amongst others, have written on this subject. Using, in part, the methodology of Morrell, this paper investigates the role of Marie Curie as a school director in the Paris Faculty in the years 1907–14, examining the work and characteristics of her school and assessing her effectiveness as a director.     

Testing Interval Forecasts: A GMM‐Based Approach

This paper proposes a new evaluation framework for interval forecasts. Our model‐free test can be used to evaluate interval forecasts and high‐density regions, potentially discontinuous and/or asymmetric. Using a simple J‐statistic, based on the moments defined by the orthonormal polynomials associated with the binomial distribution, this new approach presents many advantages. First, its implementation is extremely easy. Second, it allows for a separate test for unconditional coverage, independence and conditional coverage hypotheses. Third, Monte Carlo simulations show that for realistic sample sizes our GMM test has good small‐sample properties. These results are corroborated by an empirical application on SP500 and Nikkei stock market indexes. It confirms that using this GMM test leads to major consequences for the ex post evaluation of interval forecasts produced by linear versus nonlinear models. Copyright © 2011 John Wiley & Sons, Ltd.     

Hormonal control of Sertoli cell metabolism regulates spermatogenesis

Hormonal regulation is essential to spermatogenesis. Sertoli cells (SCs) have functions that reach far beyond the physical support of germ cells, as they are responsible for creating the adequate ionic and metabolic environment for germ cell development. Thus, much attention has been given to the metabolic functioning of SCs. During spermatogenesis, germ cells are provided with suitable metabolic substrates, in a set of events mediated by SCs. Multiple signaling cascades regulate SC function and several of these signaling pathways are hormone-dependent and cell-specific. Within the seminiferous tubules, only SCs possess receptors for some hormones rendering them major targets for the hormonal signaling that regulates spermatogenesis. Although the mechanisms by which SCs fulfill their own and germ cells metabolic needs are mostly studied in vitro, SC metabolism is unquestionably a regulation point for germ cell development and the hormonal control of these processes is required for a normal spermatogenesis.     

Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes

Genome-wide association (GWA) studies have identified multiple loci at which common variants modestly but reproducibly influence risk of type 2 diabetes (T2D). Established associations to common and rare variants explain only a small proportion of the heritability of T2D. As previously published analyses had limited power to identify variants with modest effects, we carried out meta-analysis of three T2D GWA scans comprising 10,128 individuals of European descent and approximately 2.2 million SNPs (directly genotyped and imputed), followed by replication testing in an independent sample with an effective sample size of up to 53,975. We detected at least six previously unknown loci with robust evidence for association, including the JAZF1 (P = 5.0 x 10(-14)), CDC123-CAMK1D (P = 1.2 x 10(-10)), TSPAN8-LGR5 (P = 1.1 x 10(-9)), THADA (P = 1.1 x 10(-9)), ADAMTS9 (P = 1.2 x 10(-8)) and NOTCH2 (P = 4.1 x 10(-8)) gene regions. Our results illustrate the value of large discovery and follow-up samples for gaining further insights into the inherited basis of T2D.     

Improving moving average trading rules with boosting and statistical learning methods

We present a system for combining the different types of predictions given by a wide category of mechanical trading rules through statistical learning methods (boosting, and several model averaging methods like Bayesian or simple averaging methods). Statistical learning methods supply better out‐of‐sample results than most of the single moving average rules in the NYSE Composite Index from January 1993 to December 2002. Moreover, using a filter to reduce trading frequency, the filtered boosting model produces a technical strategy which, although it is not able to overcome the returns of the buy‐and‐hold (B&H) strategy during rising periods, it does overcome the B&H during falling periods and is able to absorb a considerable part of falls in the market. Copyright © 2008 John Wiley & Sons, Ltd.     

Forecasting for the LCD monitor market

The TFT‐LCD (thin‐film transistor–liquid crystal display) industry is one of the key global industries with products that have high clock speed. In this research, the LCD monitor market is considered for an empirical study on hierarchical forecasting (HF). The proposed HF methodology consists of five steps. First, the three hierarchical levels of the LCD monitor market are identified. Second, several exogenously driven factors that significantly affect the demand for LCD monitors are identified at each level of product hierarchy. Third, the three forecasting techniques—regression analysis, transfer function, and simultaneous equations model—are combined to forecast future demand at each hierarchical level. Fourth, various forecasting approaches and disaggregating proportion methods are adopted to obtain consistent demand forecasts at each hierarchical level. Finally, the forecast errors with different forecasting approaches are assessed in order to determine the best forecasting level and the best forecasting approach. The findings show that the best forecast results can be obtained by using the middle‐out forecasting approach. These results could guide LCD manufacturers and brand owners on ways to forecast future market demands. Copyright 2008 John Wiley & Sons, Ltd.