Planarians as a model to assess in vivo the role of matrix metalloproteinase genes during homeostasis and regeneration

Matrix metalloproteinases (MMPs) are major executors of extracellular matrix remodeling and, consequently, play key roles in the response of cells to their microenvironment. The experimentally accessible stem cell population and the robust regenerative capabilities of planarians offer an ideal model to study how modulation of the proteolytic system in the extracellular environment affects cell behavior in vivo. Genome-wide identification of Schmidtea mediterranea MMPs reveals that planarians possess four mmp-like genes. Two of them (mmp1 and mmp2) are strongly expressed in a subset of secretory cells and encode putative matrilysins. The other genes (mt-mmpA and mt-mmpB) are widely expressed in postmitotic cells and appear structurally related to membrane-type MMPs. These genes are conserved in the planarian Dugesia japonica. Here we explore the role of the planarian mmp genes by RNA interference (RNAi) during tissue homeostasis and regeneration. Our analyses identify essential functions for two of them. Following inhibition of mmp1 planarians display dramatic disruption of tissues architecture and significant decrease in cell death. These results suggest that mmp1 controls tissue turnover, modulating survival of postmitotic cells. Unexpectedly, the ability to regenerate is unaffected by mmp1(RNAi). Silencing of mt-mmpA alters tissue integrity and delays blastema growth, without affecting proliferation of stem cells. Our data support the possibility that the activity of this protease modulates cell migration and regulates anoikis, with a consequent pivotal role in tissue homeostasis and regeneration. Our data provide evidence of the involvement of specific MMPs in tissue homeostasis and regeneration and demonstrate that the behavior of planarian stem cells is critically dependent on the microenvironment surrounding these cells. Studying MMPs function in the planarian model provides evidence on how individual proteases work in vivo in adult tissues. These results have high potential to generate significant information for development of regenerative and anti cancer therapies.

Continuum bound states as surface states of a finite periodic system

We discuss the relation between continuum bound states (CBSs) localized on a defect, and surface states of a finite periodic system. We model an experiment of Capasso et al. [F. Capasso, C. Sirtori, J. Faist, D. L. Sivco, S-N. G. Chu, and A. Y. Cho, Nature (London) 358, 565 (1992)] using the transfer-matrix method. We compute the rate for intrasubband transitions from the ground state to the CBS and derive a sum rule. Finally we show how to improve the confinement of a CBS while keeping the energy fixed.

Select-divide-and-conquer method for large-scale configuration interaction

A select-divide-and-conquer variational method to approximate configuration interaction (CI) is presented. Given an orthonormal set made up of occupied orbitals (Hartree-Fock or similar) and suitable correlation orbitals (natural or localized orbitals), a large N-electron target space S is split into subspaces S0,S1,S2,...,SR. S0, of dimension d0, contains all configurations K with attributes (energy contributions, etc.) above thresholds T0={T0egy, T0etc.}; the CI coefficients in S0 remain always free to vary. S1 accommodates KS with attributes above T1≤T0. An eigenproblem of dimension d0+d1 for S0+S 1 is solved first, after which the last d1 rows and columns are contracted into a single row and column, thus freezing the last d1 CI coefficients hereinafter. The process is repeated with successive Sj(j≥2) chosen so that corresponding CI matrices fit random access memory (RAM). Davidson's eigensolver is used R times. The final energy eigenvalue (lowest or excited one) is always above the corresponding exact eigenvalue in S. Threshold values {Tj;j=0, 1, 2,...,R} regulate accuracy; for large-dimensional S, high accuracy requires S 0+S1 to be solved outside RAM. From there on, however, usually a few Davidson iterations in RAM are needed for each step, so that Hamiltonian matrix-element evaluation becomes rate determining. One μhartree accuracy is achieved for an eigenproblem of order 24 × 106, involving 1.2 × 1012 nonzero matrix elements, and 8.4×109 Slater determinants

Assessing the assignation of public subsidies: Do the experts choose the most efficient R&D projects?

The implementation of public programs to support business R&D projects requires the establishment of a selection process. This selection process faces various difficulties, which include the measurement of the impact of the R&D projects as well as selection process optimization among projects with multiple, and sometimes incomparable, performance indicators. To this end, public agencies generally use the peer review method, which, while presenting some advantages, also demonstrates significant drawbacks. Private firms, on the other hand, tend toward more quantitative methods, such as Data Envelopment Analysis (DEA), in their pursuit of R&D investment optimization. In this paper, the performance of a public agency peer review method of project selection is compared with an alternative DEA method.

Doppler ultrasound in the measurement of pulse wave velocity: agreement with the Complior method

Aortic stiffness is an independent predictor factor for cardiovascular risk. Different methods for determining pulse wave velocity (PWV) are used, among which the most common are mechanical methods such as SphygmoCor or Complior, which require specific devices and are limited by technical difficulty in obtaining measurements. Doppler guided by 2D ultrasound is a good alternative to these methods. We studied 40 patients (29 male, aged 21 to 82 years) comparing the Complior method with Doppler. Agreement of both devices was high (R = 0.91, 0.84-0.95, 95% CI). The reproducibility analysis revealed no intra-nor interobserver differences. Based on these results, we conclude that Doppler ultrasound is a reliable and reproducible alternative to other established methods for themeasurement of aortic PWV

Protein phosphatase inhibition assays for okadaic acid detection in shellfish: matrix effects, applicability and comparison with LC-MS/MS analysis

The applicability of the protein phosphatase inhibition assay (PPIA) to the determination of okadaic acid (OA) and its acyl derivatives in shellfish samples has been investigated, using a recombinant PP2A and a commercial one. Mediterranean mussel, wedge clam, Pacific oyster and flat oyster have been chosen as model species. Shellfish matrix loading limits for the PPIA have been established, according to the shellfish species and the enzyme source. A synergistic inhibitory effect has been observed in the presence of OA and shellfish matrix, which has been overcome by the application of a correction factor (0.48). Finally, Mediterranean mussel samples obtained from Rı´a de Arousa during a DSP closure associated to Dinophysis acuminata, determined as positive by the mouse bioassay, have been analysed with the PPIAs. The OA equivalent contents provided by the PPIAs correlate satisfactorily with those obtained by liquid chromatography–tandem mass spectrometry (LC–MS/MS).

Three-dimensional morphological analysis of intracranial aneurysms: a fully automated method for aneurysm sac isolation and quantification

Morphological descriptors are practical and essential biomarkers for diagnosis andtreatment selection for intracranial aneurysm management according to the current guidelinesin use. Nevertheless, relatively little work has been dedicated to improve the three-dimensionalquanti cation of aneurysmal morphology, automate the analysis, and hence reduce the inherentintra- and inter-observer variability of manual analysis. In this paper we propose a methodologyfor the automated isolation and morphological quanti cation of saccular intracranial aneurysmsbased on a 3D representation of the vascular anatomy.

Improved estimation of the covariance matrix of stock returns with an application to portofolio selection

This paper proposes to estimate the covariance matrix of stock returnsby an optimally weighted average of two existing estimators: the samplecovariance matrix and single-index covariance matrix. This method isgenerally known as shrinkage, and it is standard in decision theory andin empirical Bayesian statistics. Our shrinkage estimator can be seenas a way to account for extra-market covariance without having to specifyan arbitrary multi-factor structure. For NYSE and AMEX stock returns from1972 to 1995, it can be used to select portfolios with significantly lowerout-of-sample variance than a set of existing estimators, includingmulti-factor models.

Computation of multiple correspondence analysis, with code in R

The generalization of simple correspondence analysis, for two categorical variables, to multiple correspondence analysis where they may be three or more variables, is not straighforward, both from a mathematical and computational point of view. In this paper we detail the exact computational steps involved in performing a multiple correspondence analysis, including the special aspects of adjusting the principal inertias to correct the percentages of inertia, supplementary points and subset analysis. Furthermore, we give the algorithm for joint correspondence analysis where the cross-tabulations of all unique pairs of variables are analysed jointly. The code in the R language for every step of the computations is given, as well as the results of each computation.

Rate of convergence of a particle method to the solution of the Mc Kean-Vlasov's equation

This paper studies the rate of convergence of an appropriatediscretization scheme of the solution of the Mc Kean-Vlasovequation introduced by Bossy and Talay. More specifically,we consider approximations of the distribution and of thedensity of the solution of the stochastic differentialequation associated to the Mc Kean - Vlasov equation. Thescheme adopted here is a mixed one: Euler/weakly interactingparticle system. If $n$ is the number of weakly interactingparticles and $h$ is the uniform step in the timediscretization, we prove that the rate of convergence of thedistribution functions of the approximating sequence in the $L^1(\Omega\times \Bbb R)$ norm and in the sup norm is of theorder of $\frac 1{\sqrt n} + h $, while for the densities is ofthe order $ h +\frac 1 {\sqrt {nh}}$. This result is obtainedby carefully employing techniques of Malliavin Calculus.

Assessing the assignation of public subsidies: Do the experts choose the most efficient R and D projects?

[spa] La implementación de un programa de subvenciones públicas a proyectos empresariales de I+D comporta establecer un sistema de selección de proyectos. Esta selección se enfrenta a problemas relevantes, como son la medición del posible rendimiento de los proyectos de I+D y la optimización del proceso de selección entre proyectos con múltiples y a veces incomparables medidas de resultados. Las agencias públicas utilizan mayoritariamente el método peer review que, aunque presenta ventajas, no está exento de críticas. En cambio, las empresas privadas con el objetivo de optimizar su inversión en I+D utilizan métodos más cuantitativos, como el Data Envelopment Análisis (DEA). En este trabajo se compara la actuación de los evaluadores de una agencia pública (peer review) con una metodología alternativa de selección de proyectos como es el DEA.

Assessing the assignation of public subsidies: Do the experts choose the most efficient R and D projects?

[spa] La implementación de un programa de subvenciones públicas a proyectos empresariales de I+D comporta establecer un sistema de selección de proyectos. Esta selección se enfrenta a problemas relevantes, como son la medición del posible rendimiento de los proyectos de I+D y la optimización del proceso de selección entre proyectos con múltiples y a veces incomparables medidas de resultados. Las agencias públicas utilizan mayoritariamente el método peer review que, aunque presenta ventajas, no está exento de críticas. En cambio, las empresas privadas con el objetivo de optimizar su inversión en I+D utilizan métodos más cuantitativos, como el Data Envelopment Análisis (DEA). En este trabajo se compara la actuación de los evaluadores de una agencia pública (peer review) con una metodología alternativa de selección de proyectos como es el DEA.

Assessing the assignation of public subsidies: Do the experts choose the most efficient R and D projects?

[spa] La implementación de un programa de subvenciones públicas a proyectos empresariales de I+D comporta establecer un sistema de selección de proyectos. Esta selección se enfrenta a problemas relevantes, como son la medición del posible rendimiento de los proyectos de I+D y la optimización del proceso de selección entre proyectos con múltiples y a veces incomparables medidas de resultados. Las agencias públicas utilizan mayoritariamente el método peer review que, aunque presenta ventajas, no está exento de críticas. En cambio, las empresas privadas con el objetivo de optimizar su inversión en I+D utilizan métodos más cuantitativos, como el Data Envelopment Análisis (DEA). En este trabajo se compara la actuación de los evaluadores de una agencia pública (peer review) con una metodología alternativa de selección de proyectos como es el DEA.

R commands secondary production

R commands to calculate the secondary production estimates using the size-frequency method after Hynes and Coleman (1968), Benke (1979) and Huryn (1996).

Impact of incorrect assumptions on the covariance structure of random effects and/or residuals in nonlinear mixed models for repeated measures data

In this paper we analyse, using Monte Carlo simulation, the possible consequences of incorrect assumptions on the true structure of the random effects covariance matrix and the true correlation pattern of residuals, over the performance of an estimation method for nonlinear mixed models. The procedure under study is the well known linearization method due to Lindstrom and Bates (1990), implemented in the nlme library of S-Plus and R. Its performance is studied in terms of bias, mean square error (MSE), and true coverage of the associated asymptotic confidence intervals. Ignoring other criteria like the convenience of avoiding over parameterised models, it seems worst to erroneously assume some structure than do not assume any structure when this would be adequate.