How does the body-scale model affect back-calculated growth: the example of arctic charr Salvelinus alpinus (L.) of Lake Geneva (Switzerland)

When back-calculating fish length from scale measurements, the choice of the body-scale relationship is a fundamental step. Using data from the arctic charrSalvelinus alpinus (L.) of Lake Geneva (Switzerland) we show the need for a curvilinear model, on both statistical and biological grounds. From several 2-parameters models, the log-linear relationship appears to provide the best fit. A 3-parameters, Bertalanffy model did not improve the fit. We show moreover that using the proportional model would lead to important misinterpretations of the data.

Work-related stress according to the demand-control model and minor psychic disorders in nursing workers

This was a cross-sectional study that aimed to assess the association between work-related stress according to the Demand-Control Model, and the occurrence of Minor Psychic Disorder (MPD) in nursing workers. The participants were 335 professionals, out of which 245 were nursing technicians, aged predominantly between 20 and 40 years. Data were collected using the Job Stress Scale and the Self-Reporting Questionnaire-20. The analysis was performed using descriptive and analytical statistics. The prevalence of suspected MPD was 20.6%. Workers classified in the quadrants active job and high strain of the Demand-Control Model presented higher potential for developing MPD compared with those classified in the quadrant low strain. In conclusion, stress affects the mental health of workers and the aspects related to high psychological demands and high control still require further insight in order to understand their influence on the disease processes of nursing workers.

Selective tumor localization of radiolabeled anti-human melanoma monoclonal antibody fragment demonstrated in the nude mouse model.

Monoclonal antibodies (Mab) directed against distinct epitopes of the human 240 kD melanoma-associated antigen have been evaluated for their capacity to localize in human melanoma grafted into nude mice. A favorable tumor to normal tissue ratio of 13 was obtained with intact 131I-labeled MAb Me1-14. This ratio was further increased to 43 and 23 by the use of F(ab')2 and Fab fragments, respectively. The specificity of tumor localization was demonstrated by the simultaneous injection of F(ab')2 fragments from MAb Me1-14 and anti-CEA MAb 35, each labeled with a different iodine isotope, into nude mice grafted with a melanoma and colon carcinoma. The fragments from both MAb localized with perfect selectivity in their relevant tumor as shown by differential whole body scanning and by direct measurement of the two isotopes in tumors and normal tissues. These in vivo experimental results suggest that the F(ab')2 fragment from MAb Me1-14 is suitable for melanoma detection by immunoscintigraphy in patients.

Temporal changes in mRNA expression of the brain nutrient transporters in the lithium-pilocarpine model of epilepsy in the immature and adult rat.

The lithium-pilocarpine model mimics most features of human temporal lobe epilepsy. Following our prior studies of cerebral metabolic changes, here we explored the expression of transporters for glucose (GLUT1 and GLUT3) and monocarboxylates (MCT1 and MCT2) during and after status epilepticus (SE) induced by lithium-pilocarpine in PN10, PN21, and adult rats. In situ hybridization was used to study the expression of transporter mRNAs during the acute phase (1, 4, 12 and 24h of SE), the latent phase, and the early and late chronic phases. During SE, GLUT1 expression was increased throughout the brain between 1 and 12h of SE, more strongly in adult rats; GLUT3 increased only transiently, at 1 and 4h of SE and mainly in PN10 rats; MCT1 was increased at all ages but 5-10-fold more in adult than in immature rats; MCT2 expression increased mainly in adult rats. At all ages, MCT1 and MCT2 up-regulation was limited to the circuit of seizures while GLUT1 and GLUT3 changes were more widespread. During the latent and chronic phases, the expression of nutrient transporters was normal in PN10 rats. In PN21 rats, GLUT1 was up-regulated in all brain regions. In contrast, in adult rats GLUT1 expression was down-regulated in the piriform cortex, hilus and CA1 as a result of extensive neuronal death. The changes in nutrient transporter expression reported here further support previous findings in other experimental models demonstrating rapid transcriptional responses to marked changes in cerebral energetic/glucose demand.

Real wage rigidities and the new Keynesian model

Most central banks perceive a trade-off between stabilizing inflation and stabilizing the gap between output and desired output. However, the standard new Keynesian framework implies no such trade-off. In that framework, stabilizing inflation is equivalent to stabilizing the welfare-relevant output gap. In this paper, we argue that this property of the new Keynesian framework, which we call the divine coincidence, is due to a special feature of the model: the absence of non trivial real imperfections.We focus on one such real imperfection, namely, real wage rigidities. When the baseline new Keynesian model is extended to allow for real wage rigidities, the divine coincidence disappears, and central banks indeed face a trade-off between stabilizing inflation and stabilizing the welfare-relevant output gap. We show that not only does the extended model have more realistic normative implications, but it also has appealing positive properties. In particular, it provides a natural interpretation for the dynamic inflation-unemployment relation found in the data.

Concepts of metastasis in flux: the stromal progression model.

The ability of tumor cells to leave a primary tumor, to disseminate through the body, and to ultimately seed new secondary tumors is universally agreed to be the basis for metastasis formation. An accurate description of the cellular and molecular mechanisms that underlie this multistep process would greatly facilitate the rational development of therapies that effectively allow metastatic disease to be controlled and treated. A number of disparate and sometimes conflicting hypotheses and models have been suggested to explain various aspects of the process, and no single concept explains the mechanism of metastasis in its entirety or encompasses all observations and experimental findings. The exciting progress made in metastasis research in recent years has refined existing ideas, as well as giving rise to new ones. In this review we survey some of the main theories that currently exist in the field, and show that significant convergence is emerging, allowing a synthesis of several models to give a more comprehensive overview of the process of metastasis. As a result we postulate a stromal progression model of metastasis. In this model, progressive modification of the tumor microenvironment is equally as important as genetic and epigenetic changes in tumor cells during primary tumor progression. Mutual regulatory interactions between stroma and tumor cells modify the stemness of the cells that drive tumor growth, in a manner that involves epithelial-mesenchymal and mesenchymal-epithelial-like transitions. Similar interactions need to be recapitulated at secondary sites for metastases to grow. Early disseminating tumor cells can progress at the secondary site in parallel to the primary tumor, both in terms of genetic changes, as well as progressive development of a metastatic stroma. Although this model brings together many ideas in the field, there remain nevertheless a number of major open questions, underscoring the need for further research to fully understand metastasis, and thereby identify new and effective ways of treating metastatic disease.

General preferences for consumption goods in the random matching model of commodity money

This paper generalizes the original random matching model of money byKiyotaki and Wright (1989) (KW) in two aspects: first, the economy ischaracterized by an arbitrary distribution of agents who specialize in producing aparticular consumption good; and second, these agents have preferences suchthat they want to consume any good with some probability. The resultsdepend crucially on the size of the fraction of producers of each goodand the probability with which different agents want to consume eachgood. KW and other related models are shown to be parameterizations ofthis more general one.

Local volatility changes in the black-scholes model

In this paper we address a problem arising in risk management; namely the study of price variations of different contingent claims in the Black-Scholes model due to anticipating future events. The method we propose to use is an extension of the classical Vega index, i.e. the price derivative with respect to the constant volatility, in thesense that we perturb the volatility in different directions. Thisdirectional derivative, which we denote the local Vega index, will serve as the main object in the paper and one of the purposes is to relate it to the classical Vega index. We show that for all contingent claims studied in this paper the local Vega index can be expressed as a weighted average of the perturbation in volatility. In the particular case where the interest rate and the volatility are constant and the perturbation is deterministic, the local Vega index is an average of this perturbation multiplied by the classical Vega index. We also study the well-known goal problem of maximizing the probability of a perfect hedge and show that the speed of convergence is in fact dependent of the local Vega index.

Surviving in a competitive spatial market: The threshold capture model

Most facility location decision models ignore the fact that for a facility to survive it needs a minimum demand level to cover costs. In this paper we present a decision model for a firm thatwishes to enter a spatial market where there are several competitors already located. This market is such that for each outlet there is a demand threshold level that has to be achievedin order to survive. The firm wishes to know where to locate itsoutlets so as to maximize its market share taking into account the threshold level. It may happen that due to this new entrance, some competitors will not be able to meet the threshold and therefore will disappear. A formulation is presented together with a heuristic solution method and computational experience.

The optimal dividend barrier in the Gamma-Omega model

In the traditional actuarial risk model, if the surplus is negative, the company is ruined and has to go out of business. In this paper we distinguish between ruin (negative surplus) and bankruptcy (going out of business), where the probability of bankruptcy is a function of the level of negative surplus. The idea for this notion of bankruptcy comes from the observation that in some industries, companies can continue doing business even though they are technically ruined. Assuming that dividends can only be paid with a certain probability at each point of time, we derive closed-form formulas for the expected discounted dividends until bankruptcy under a barrier strategy. Subsequently, the optimal barrier is determined, and several explicit identities for the optimal value are found. The surplus process of the company is modeled by a Wiener process (Brownian motion).

Use of the FACTS solvation model for protein-ligand docking calculations. Application to EADock.

Protein-ligand docking has made important progress during the last decade and has become a powerful tool for drug development, opening the way to virtual high throughput screening and in silico structure-based ligand design. Despite the flattering picture that has been drawn, recent publications have shown that the docking problem is far from being solved, and that more developments are still needed to achieve high successful prediction rates and accuracy. Introducing an accurate description of the solvation effect upon binding is thought to be essential to achieve this goal. In particular, EADock uses the Generalized Born Molecular Volume 2 (GBMV2) solvent model, which has been shown to reproduce accurately the desolvation energies calculated by solving the Poisson equation. Here, the implementation of the Fast Analytical Continuum Treatment of Solvation (FACTS) as an implicit solvation model in small molecules docking calculations has been assessed using the EADock docking program. Our results strongly support the use of FACTS for docking. The success rates of EADock/FACTS and EADock/GBMV2 are similar, i.e. around 75% for local docking and 65% for blind docking. However, these results come at a much lower computational cost: FACTS is 10 times faster than GBMV2 in calculating the total electrostatic energy, and allows a speed up of EADock by a factor of 4. This study also supports the EADock development strategy relying on the CHARMM package for energy calculations, which enables straightforward implementation and testing of the latest developments in the field of Molecular Modeling.

The mean-variance model from the inverse of the variance-covariance matrix

En este artículo, a partir de la inversa de la matriz de varianzas y covarianzas se obtiene el modelo Esperanza-Varianza de Markowitz siguiendo un camino más corto y matemáticamente riguroso. También se obtiene la ecuación de equilibrio del CAPM de Sharpe.