Differential expression of presynaptic genes in a rat model of postnatal hypoxia: relevance to schizophrenia

Obstetric complications play a role in the pathophysiology of schizophrenia. However, the biological consequences during neurodevelopment until adulthood are unknown. Microarrays have been used for expression profiling in four brain regions of a rat model of neonatal hypoxia as a common factor of obstetric complications. Animals were repeatedly exposed to chronic hypoxia from postnatal (PD) day 4 through day 8 and killed at the age of 150 days. Additional groups of rats were treated with clozapine from PD 120-150. Self-spotted chips containing 340 cDNAs related to the glutamate system (""glutamate chips"") were used. The data show differential (up and down) regulations of numerous genes in frontal (FR), temporal (TE) and parietal cortex (PAR), and in caudate putamen (CPU), but evidently many more genes are upregulated in frontal and temporal cortex, whereas in parietal cortex the majority of genes are downregulated. Because of their primary presynaptic occurrence, five differentially expressed genes (CPX1, NPY, NRXN1, SNAP-25, and STX1A) have been selected for comparisons with clozapine-treated animals by qRT-PCR. Complexin 1 is upregulated in FR and TE cortex but unchanged in PAR by hypoxic treatment. Clozapine downregulates it in FR but upregulates it in PAR cortex. Similarly, syntaxin 1A was upregulated in FR, but downregulated in TE and unchanged in PAR cortex, whereas clozapine downregulated it in FR but upregulated it in PAR cortex. Hence, hypoxia alters gene expression regionally specific, which is in agreement with reports on differentially expressed presynaptic genes in schizophrenia. Chronic clozapine treatment may contribute to normalize synaptic connectivity.

Long-term survivor mixture model with random effects: application to a multi-centre clinical trial of carcinoma

A mixture model incorporating long-term survivors has been adopted in the field of biostatistics where some individuals may never experience the failure event under study. The surviving fractions may be considered as cured. In most applications, the survival times are assumed to be independent. However, when the survival data are obtained from a multi-centre clinical trial, it is conceived that the environ mental conditions and facilities shared within clinic affects the proportion cured as well as the failure risk for the uncured individuals. It necessitates a long-term survivor mixture model with random effects. In this paper, the long-term survivor mixture model is extended for the analysis of multivariate failure time data using the generalized linear mixed model (GLMM) approach. The proposed model is applied to analyse a numerical data set from a multi-centre clinical trial of carcinoma as an illustration. Some simulation experiments are performed to assess the applicability of the model based on the average biases of the estimates formed. Copyright (C) 2001 John Wiley & Sons, Ltd.

Evaluation of chronic omega-3 fatty acids supplementation on behavioral and neurochemical alterations in 6-hydroxydopamine-lesion model of Parkinson`s disease

Omega-3 polyunsaturated fatty acids (omega-3 PUFAs) have been widely associated to beneficial effects over different neuropathologies, but only a few studies associate them to Parkinson`s disease (PD). Rats were submitted to chronic supplementation (21-90 days of life) with fish oil, rich in omega-3 PUFAs, and were uni- or bilaterally lesioned with 4 mu g of the neurotoxin 6-hydroxydopamine (6-OHDA) in the medial forebrain bundle Although lipid incorporation was evidenced in neuronal membranes, it was not sufficient to compensate motor deficits induced by 6-OHDA. In contrast, omega-3 PUFAs were capable of reducing rotational behavior induced by apomorphine, suggesting neuroprotection over dyskinesia The beneficial effects of omega-3 PUFAs were also evident in the maintenance of thiobarbituric acid reactive substances index from animals lesioned with 6-OHDA similar to levels from SHAM and intact animals. Although omega-3 PUFAs did not modify the tyrosine hydroxylase immunoreactivity in the substantia nigra pars compacta and in the ventral tegmental area, nor the depletion of dopamine (DA) and its metabolites in the striatum, DA turnover was increased after omega-3 PUFAs chronic supplementation Therefore, it is proposed that omega-3 PUFAs action characterizes the adaptation of remaining neurons activity. altering striatal DA turnover without modifying the estimated neuronal population. (C) 2009 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved

The gambin model provides a superior fit to species abundance distributions with a single free parameter : evidence, implementation and interpretation

The species abundance distribution (SAD) has been a central focus of community ecology for over fifty years, and is currently the subject of widespread renewed interest. The gambin model has recently been proposed as a model that provides a superior fit to commonly preferred SAD models. It has also been argued that the model's single parameter (α) presents a potentially informative ecological diversity metric, because it summarises the shape of the SAD in a single number. Despite this potential, few empirical tests of the model have been undertaken, perhaps because the necessary methods and software for fitting the model have not existed. Here, we derive a maximum likelihood method to fit the model, and use it to undertake a comprehensive comparative analysis of the fit of the gambin model. The functions and computational code to fit the model are incorporated in a newly developed free-to-download R package (gambin). We test the gambin model using a variety of datasets and compare the fit of the gambin model to fits obtained using the Poisson lognormal, logseries and zero-sum multinomial distributions. We found that gambin almost universally provided a better fit to the data and that the fit was consistent for a variety of sample grain sizes. We demonstrate how α can be used to differentiate intelligibly between community structures of Azorean arthropods sampled in different land use types. We conclude that gambin presents a flexible model capable of fitting a wide variety of observed SAD data, while providing a useful index of SAD form in its single fitted parameter. As such, gambin has wide potential applicability in the study of SADs, and ecology more generally.

Hybrid adaptive control of a dragonfly model

Dragonflies show unique and superior flight performances than most of other insect species and birds. They are equipped with two pairs of independently controlled wings granting an unmatchable flying performance and robustness. In this paper, it is presented an adaptive scheme controlling a nonlinear model inspired in a dragonfly-like robot. It is proposed a hybrid adaptive (HA) law for adjusting the parameters analyzing the tracking error. At the current stage of the project it is considered essential the development of computational simulation models based in the dynamics to test whether strategies or algorithms of control, parts of the system (such as different wing configurations, tail) as well as the complete system. The performance analysis proves the superiority of the HA law over the direct adaptive (DA) method in terms of faster and improved tracking and parameter convergence.

Vision based context categorization for all-terrain robot

Dissertation presented at the Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa to obtain the Master degree in Electrical and Computer Engineering.

The CONCERTO methodology for model-based development of avionics SW

20th International Conference on Reliable Software Technologies - Ada-Europe 2015 (Ada-Europe 2015), 22 to 26, Jun, 2015, Madrid, Spain.

A system model and stack for the parallelization of time-critical applications on many-core architectures

3rd Workshop on High-performance and Real-time Embedded Systems (HIRES 2015). 21, Jan, 2015. Amsterdam, Netherlands.

An integrated model for simulation of construction phasing of arch concrete dams

Dissertação de mestrado integrado em Civil Engineering

Development of computational and experimental methods for biomass composition and evaluation of its impact in genome-scale models prediction

The use of genome-scale metabolic models has been rapidly increasing in fields such as metabolic engineering. An important part of a metabolic model is the biomass equation since this reaction will ultimately determine the predictive capacity of the model in terms of essentiality and flux distributions. Thus, in order to obtain a reliable metabolic model the biomass precursors and their coefficients must be as precise as possible. Ideally, determination of the biomass composition would be performed experimentally, but when no experimental data are available this is established by approximation to closely related organisms. Computational methods however, can extract some information from the genome such as amino acid and nucleotide compositions. The main objectives of this study were to compare the biomass composition of several organisms and to evaluate how biomass precursor coefficients affected the predictability of several genome-scale metabolic models by comparing predictions with experimental data in literature. For that, the biomass macromolecular composition was experimentally determined and the amino acid composition was both experimentally and computationally estimated for several organisms. Sensitivity analysis studies were also performed with the Escherichia coli iAF1260 metabolic model concerning specific growth rates and flux distributions. The results obtained suggest that the macromolecular composition is conserved among related organisms. Contrasting, experimental data for amino acid composition seem to have no similarities for related organisms. It was also observed that the impact of macromolecular composition on specific growth rates and flux distributions is larger than the impact of amino acid composition, even when data from closely related organisms are used.

Computational methods for model reduction of large-scale sparse structured descriptor systems

Magdeburg, Univ., Fak. für Mathematik, Diss., 2015

PFC : Analitzador de models UML

Aquest projecte descriu la construcció d'una aplicació encarregada de realitzar l'anàlisis d'un model UML. Està encabit dins el marc d'un aplicatiu de gestió de models en un repositori centralitzat de la àrea de Tècniques Avançades d'Enginyeria de Programari de la carrera d'Enginyeria Informàtica de la UOC.