Trend analysis in two standard growth models

This paper analyzes the trend processes characterized by two standard growth models using simple econometrics. The first model is the basic neoclassical growth model that postulates a deterministic trend for output. The second model is the Uzawa-Lucas model that postulates a stochastic trend for output. The aim is to understand how the different trend processes for output assumed by these two standard growth models determine the ability of each model to explain the observed trend processes of other macroeconomic variables such as consumption and investment. The results show that the two models reproduce the output trend process. Moreover, the results show that the basic growth model captures properly the consumption trend process, but fails in characterizing the investment trend process. The reverse is true for the Uzawa-Lucas model.

Intranasal Delivery of Plasma and Platelet Growth Factors Using PRGF-Endoret System Enhances Neurogenesis in a Mouse Model of Alzheimer’s Disease

[EN] Neurodegeneration together with a reduction in neurogenesis are cardinal features of Alzheimer’s disease (AD) induced by a combination of toxic amyloid-β peptide (Aβ) and a loss of trophic factor support. Amelioration of these was assessed with diverse neurotrophins in experimental therapeutic approaches. The aim of this study was to investigate whether intranasal delivery of plasma rich in growth factors (PRGF-Endoret), an autologous pool of morphogens and proteins, could enhance hippocampal neurogenesis and reduce neurodegeneration in an amyloid precursor protein/presenilin-1 (APP/PS1) mouse model. Neurotrophic and neuroprotective actions were firstly evident in primary neuronal cultures, where cell proliferation and survival were augmented by Endoret treatment. Translation of these effects in vivo was assessed in wild type and APP/PS1 mice, where neurogenesis was evaluated using 5-bromodeoxyuridine (BdrU), doublecortin (DCX), and NeuN immunostaining 5 weeks after Endoret administration. The number of BrdU, DCX, and NeuN positive cell was increased after chronic treatment. The number of degenerating neurons, detected with fluoro Jade-B staining was reduced in Endoret-treated APP/PS1 mice at 5 week after intranasal administration. In conclusion, Endoret was able to activate neuronal progenitor cells, enhancing hippocampal neurogenesis, and to reduce Aβ-induced neurodegeneration in a mouse model of AD.

An R package for permutations, Mallows and Generalized Mallows models

[EN]Probability models on permutations associate a probability value to each of the permutations on n items. This paper considers two popular probability models, the Mallows model and the Generalized Mallows model. We describe methods for making inference, sampling and learning such distributions, some of which are novel in the literature. This paper also describes operations for permutations, with special attention in those related with the Kendall and Cayley distances and the random generation of permutations. These operations are of key importance for the efficient computation of the operations on distributions. These algorithms are implemented in the associated R package. Moreover, the internal code is written in C++.

Life Expectancy, Schooling Time and Endogenous Growth

Published as an article in: Economic Inquiry, 2004, vol. 42, issue 4, pp. 602–617.

Pravastatin inhibits cell proliferation and increased MAT1A expression in hepatocarcinoma cells and in vivo models

Background: Statins may have therapeutic effects on hepatocarcinoma (HCC). This type of disorder is the most common malignant primary tumour in the liver. Our objective was to determine whether pravastatin had a therapeutic effect in vitro and in vivo models. Method: We design in vitro and in vivo model. In vitro we used PLC and determine cell proliferation. In vivo, we used and animal model to determined, PCNA and MAT1A expression and transaminases levels. Results: We found that pravastatin decreases cell proliferation in vitro (cell proliferation in pravastatin group was 82%, in sorafenib group 51% and in combined group 40%) and in vivo (in pravastatin group 80%, in sorafenib group 76.4% and in combined group 72.72%). The MAT1A levels, was significantly higher in Pravastatin group (D 62%, P 94%, S 71%, P + S 91%). The transaminases levels, decreased significantly in Pravastatin group (GOT and GPT levels D 619.5 U/L; 271 U/L) (P 117.5 U/L; 43.5 U/L) (S 147 U/L; 59 U/L) (P + S 142 U/L; 59 U/L). Conclusion: The combination of pravastatin + sorafenib were more effective than Sorafenib alone.

Sampling and learning the Mallows and Generalized Mallows models under the Cayley distance

[EN]The Mallows and Generalized Mallows models are compact yet powerful and natural ways of representing a probability distribution over the space of permutations. In this paper we deal with the problems of sampling and learning (estimating) such distributions when the metric on permutations is the Cayley distance. We propose new methods for both operations, whose performance is shown through several experiments. We also introduce novel procedures to count and randomly generate permutations at a given Cayley distance both with and without certain structural restrictions. An application in the field of biology is given to motivate the interest of this model.

Sampling and learning the Mallows and Weighted Mallows models under the Hamming distance

[EN]In this paper we deal with distributions over permutation spaces. The Mallows model is the mode l in use. The associated distance for permutations is the Hamming distance.