First trimester maternal level of PAPP-A, βhCG and ethnicity as predictive of Intrauterine Growth Restriction

Intrauterine growth restriction (IUGR) is one of the leading causes of perinatal mortality and morbidity. Nowadays, this condition is detected in the 3rt and last trimester of gestation when the pathology is already established and success of therapeutic strategies are limited. As the physiopathology of the disease suggests that the problem stems from poor placental implantation, it would be quite advantageous to identify women at increased risk in the first or second trimester of gestation because it then might be possible to offer treatment interventions or at least to establish increased surveillance for high risk pregnancies. Maternal levels of pregnancy-associated plasma protein-A (PAPP-A) and free β human chorionic gonadotropin (free βhCG) has been shown to be effective in first trimester screening for chromosomal abnormalities, primarily trisomies 21, 13 and 18. Previous studies evaluating PAPP-A and free βhCG measured in the first trimester in relation with IUGR have provided conflicting results. Moreover, it has been suggested that black ethnicity is another important predictive factor for fetal growth restriction.Objective: To analyse the association between first trimester serum analytes (PAPP-A and free βhCG) and ethnicity with Intrauterine Growth Restriction.Methods: The study consists in a retrospective cohort, including all singleton pregnancies with complete outcome data that had undergone first trimester screening (PAPP-A and free βhCG) at 11-13+6weeks of gestation between 1/1/2010 - 31/12/2012 in Hospital Universitari Dr Josep Trueta. Biochemical markers are converted to multiples of the median (MoMs) and percentiles 5 and 10 are calculated. The association between free βhCG and PAPP-A with the incidence of IUGR is evaluated in combination with maternal ethnicity. Bivariate and logistic regression analyses are performed to adjust this association for co variables

First trimester maternal level of PAPP-A, βhCG and ethnicity as predictive of Intrauterine Growth Restriction

Intrauterine growth restriction (IUGR) is one of the leading causes of perinatal mortality and morbidity. Nowadays, this condition is detected in the 3rt and last trimester of gestation when the pathology is already established and success of therapeutic strategies are limited. As the physiopathology of the disease suggests that the problem stems from poor placental implantation, it would be quite advantageous to identify women at increased risk in the first or second trimester of gestation because it then might be possible to offer treatment interventions or at least to establish increased surveillance for high risk pregnancies. Maternal levels of pregnancy-associated plasma protein-A (PAPP-A) and free β human chorionic gonadotropin (free βhCG) has been shown to be effective in first trimester screening for chromosomal abnormalities, primarily trisomies 21, 13 and 18. Previous studies evaluating PAPP-A and free βhCG measured in the first trimester in relation with IUGR have provided conflicting results. Moreover, it has been suggested that black ethnicity is another important predictive factor for fetal growth restriction.Objective: To analyse the association between first trimester serum analytes (PAPP-A and free βhCG) and ethnicity with Intrauterine Growth Restriction.Methods: The study consists in a retrospective cohort, including all singleton pregnancies with complete outcome data that had undergone first trimester screening (PAPP-A and free βhCG) at 11-13+6weeks of gestation between 1/1/2010 - 31/12/2012 in Hospital Universitari Dr Josep Trueta. Biochemical markers are converted to multiples of the median (MoMs) and percentiles 5 and 10 are calculated. The association between free βhCG and PAPP-A with the incidence of IUGR is evaluated in combination with maternal ethnicity. Bivariate and logistic regression analyses are performed to adjust this association for co variables

First trimester maternal level of PAPP-A, βhCG and ethnicity as predictive of Intrauterine Growth Restriction

Intrauterine growth restriction (IUGR) is one of the leading causes of perinatal mortality and morbidity. Nowadays, this condition is detected in the 3rt and last trimester of gestation when the pathology is already established and success of therapeutic strategies are limited. As the physiopathology of the disease suggests that the problem stems from poor placental implantation, it would be quite advantageous to identify women at increased risk in the first or second trimester of gestation because it then might be possible to offer treatment interventions or at least to establish increased surveillance for high risk pregnancies. Maternal levels of pregnancy-associated plasma protein-A (PAPP-A) and free β human chorionic gonadotropin (free βhCG) has been shown to be effective in first trimester screening for chromosomal abnormalities, primarily trisomies 21, 13 and 18. Previous studies evaluating PAPP-A and free βhCG measured in the first trimester in relation with IUGR have provided conflicting results. Moreover, it has been suggested that black ethnicity is another important predictive factor for fetal growth restriction.Objective: To analyse the association between first trimester serum analytes (PAPP-A and free βhCG) and ethnicity with Intrauterine Growth Restriction.Methods: The study consists in a retrospective cohort, including all singleton pregnancies with complete outcome data that had undergone first trimester screening (PAPP-A and free βhCG) at 11-13+6weeks of gestation between 1/1/2010 - 31/12/2012 in Hospital Universitari Dr Josep Trueta. Biochemical markers are converted to multiples of the median (MoMs) and percentiles 5 and 10 are calculated. The association between free βhCG and PAPP-A with the incidence of IUGR is evaluated in combination with maternal ethnicity. Bivariate and logistic regression analyses are performed to adjust this association for co variables

Combining multivariate density forecasts using predictive criteria

This paper combines multivariate density forecasts of output growth, inflationand interest rates from a suite of models. An out-of-sample weighting scheme based onthe predictive likelihood as proposed by Eklund and Karlsson (2005) and Andersson andKarlsson (2007) is used to combine the models. Three classes of models are considered: aBayesian vector autoregression (BVAR), a factor-augmented vector autoregression (FAVAR)and a medium-scale dynamic stochastic general equilibrium (DSGE) model. Using Australiandata, we find that, at short forecast horizons, the Bayesian VAR model is assignedthe most weight, while at intermediate and longer horizons the factor model is preferred.The DSGE model is assigned little weight at all horizons, a result that can be attributedto the DSGE model producing density forecasts that are very wide when compared withthe actual distribution of observations. While a density forecast evaluation exercise revealslittle formal evidence that the optimally combined densities are superior to those from thebest-performing individual model, or a simple equal-weighting scheme, this may be a resultof the short sample available.

CBS: an open platform that integrates predictive methods and epigenetics information to characterize conserved regulatory features in multiple Drosophila genomes.

Background: Information about the composition of regulatory regions is of great value for designing experiments to functionally characterize gene expression. The multiplicity of available applications to predict transcription factor binding sites in a particular locus contrasts with the substantial computational expertise that is demanded to manipulate them, which may constitute a potential barrier for the experimental community. Results: CBS (Conserved regulatory Binding Sites, http://compfly.bio.ub.es/CBS) is a public platform of evolutionarily conserved binding sites and enhancers predicted in multiple Drosophila genomes that is furnished with published chromatin signatures associated to transcriptionally active regions and other experimental sources of information. The rapid access to this novel body of knowledge through a user-friendly web interface enables non-expert users to identify the binding sequences available for any particular gene, transcription factor, or genome region. Conclusions: The CBS platform is a powerful resource that provides tools for data mining individual sequences and groups of co-expressed genes with epigenomics information to conduct regulatory screenings in Drosophila.

Human capital as a factor of growth and employment at the regional level. The case of Spain

We use statistical techniques to quantify the effects of school attainment on individual wages, participation rates and employment probabilities in Spain, and to measure the contribution of education to labour productivity at the regional level. These estimates are then combined with data on private and public expenditure on education and with information on taxes and social benefits to construct measures of the private and social returns to schooling, to explore the effects of public policies on private incentives to invest in human capital, and to analyse the long-term effects of schooling on public finances. The results are used, together with estimates of the returns to alternative assets, to draw some tentative conclusions regarding the adequacy of the aggregate investment patterns observed in the regions of Spain, and to identify changes in the design of national and EU cohesion and growth policies that may help enhance their effectiveness.

Are one factor logarithmic volatility models useful to fit the features of financial data? An application to microsoft data.

This paper provides empirical evidence that continuous time models with one factor of volatility, in some conditions, are able to fit the main characteristics of financial data. It also reports the importance of the feedback factor in capturing the strong volatility clustering of data, caused by a possible change in the pattern of volatility in the last part of the sample. We use the Efficient Method of Moments (EMM) by Gallant and Tauchen (1996) to estimate logarithmic models with one and two stochastic volatility factors (with and without feedback) and to select among them.

Inflation and factor shares

We use results from the literature on the determinants of price-cost margins to derive an equation relating labor's share of national income to the inflation rate (as well as to the output gap, the unemployment rate and the capital stock per worker). The equation is tested with a panel of 15 OECD countries. We obtain a robust positive relationship between inflation and the labor share. Our results suggest that disinflation is not distributively neutral, provide empirical support for the distinct concern about price stability shown by trade unions and employers' organizations, and help explaining the negative impact of inflation on growth.

Factor decomposition of spatial income inequality: a revision

Duro and Esteban (1998) proposed an additive decomposition of Theil populationweighted index by four income multiplicative factors (in spatial contexts). This note makes some additional methodological points: first, it argues that interaction effects are taken into account in the factoral indexes although only in a fairly restrictive way. As a consequence, we suggest to rewrite the decomposition formula as a sum of strict Theil indexes plus the interactive terms; second, it might be instructive to aggregate some of the initial factors; third, this decomposition can be immediately extended to the between- and within-group components.

An analysis of strategic paths through the decomposition of total factor productivity: the case of Spanish savings banks

The Spanish savings banks attracted quite a considerable amount of interest within the scientific arena, especially subsequent to the disappearance of the regulatory constraints during the second decade of the 1980s. Nonetheless, a lack of research identified with respect to mainstream paths given by strategic groups, and the analysis of the total factor productivity. Therefore, on the basis of the resource-based view of the firm and cluster analysis, we make use of changes in structure and performance ratios in order to identify the strategic groups extant in the sector. We attain a threeways division, which we link with different input-output specifications defining strategic paths. Consequently, on the basis of these three dissimilar approaches we compute and decompose a Hicks-Moorsteen total factor productivity index. Obtained results put forward an interesting interpretation under a multi-strategic approach, together with the setbacks of employing cluster analysis within a complex strategic environment. Moreover, we also propose an ex-post method of analysing the outcomes of the decomposed total factor productivity index that could be merged with non-traditional techniques of forming strategic groups, such as cognitive approaches.

Generalized factor models: a bayesian approach

There is recent interest in the generalization of classical factor models in which the idiosyncratic factors are assumed to be orthogonal and there are identification restrictions on cross-sectional and time dimensions. In this study, we describe and implement a Bayesian approach to generalized factor models. A flexible framework is developed to determine the variations attributed to common and idiosyncratic factors. We also propose a unique methodology to select the (generalized) factor model that best fits a given set of data. Applying the proposed methodology to the simulated data and the foreign exchange rate data, we provide a comparative analysis between the classical and generalized factor models. We find that when there is a shift from classical to generalized, there are significant changes in the estimates of the structures of the covariance and correlation matrices while there are less dramatic changes in the estimates of the factor loadings and the variation attributed to common factors.

Regulació del factor de transcripció NFAT5 per les quinases WNK1, SPAK i OSR1 i cerca de quinases activadores de la pròpia WNK1 en resposta a estrés osmòtic

Estudi elaborat a partir d’una estada a la School of Life Sciences de la University of Dundee, Gran Bretanya, entre gener i març del 2007.L'estrès osmòtic causa rà pidament l'activació de la quinasa WNK1, que fosforila i activa a continuació les quinases SPAK i OSR1, que alhora regulen canals i transportadors d’ions preexistents a la membrana cel•lular. El factor de transcripció NFAT5 és el principal regulador de la resposta cel•lular transcripcional secundà ria a hipertonicitat i s’ha descrit que les quinases p38, Fyn, PKA, ERK/MEK i ATM estan involucrades en la seva regulació post-traduccional. No obstant, com que la funció d’aquestes quinases no explica totalment els mecanismes d'activació de NFAT5, s’ha estudiat si l’activitat transcripcional de NFAT5 pot estar regulada per WNK1, SPAK o OSR1. Així doncs, es va observar que l’activitat d’un reporter dependent de NFAT5 no es veu afectada per la presència de cap de les quinases anteriors, en la seva forma wild-type o dominant negatiu. D’altra banda, es va estudiar quin domini de WNK1 és necessari per a que pugui respondre a hipertonicitat i quines quinases poden estar involucrades en la fosforilació de la serina 382 de WNK1. En conclusió, les dades obtingudes apunten que l’activació de WNK1 en resposta a estrès osmòtic requereix la seva fosforilació en la serina 382 per quinases upstream com PAK2 o RSK i que també és necessari un dels seus dominis coiled-coil, almenys els aminoà cids 558 i 561. Aquests processos, però, semblen ser independents de l’activació de NFAT5 en resposta a hipertonicitat.   

Decomposing differences in total factor productivity across firm size

This paper investigates the extent to which the gap in total factor productivity between small and large firms is due to differences in the endowment of factors determining productivity and to the returns associated with these factors. We place particular emphasis on the contribution of differences in the propensity to innovate and in the use of skilled labor across firms of different size. Empirical evidence from a representative sample of Spanish manufacturing firms corroborates that both differences in endowments and returns to innovation and skilled labor significantly contribute to the productivity gap between small and large firms. In addition, it is observed that the contribution of innovation to this gap is caused only by differences in quantity, while differences in returns have no effect; in the case of human capital, however, most of the effect can be attributed to increasing differences in returns between small and large firms.