sensitivity analysis

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Hybrid endoscopic thymectomy : combined transesophageal and transthoracic approach in a survival porcine model with cadaver assessment

BACKGROUND: Video-assisted thoracoscopic surgery thymectomy has been used in the treatment of Myastenia Gravis and thymomas (coexisting or not). In natural orifice transluminal endoscopic surgery, new approaches to the thorax are emerging as alternatives to the classic transthoracic endoscopic surgery. The aim of this study was to assess the feasibility and reliability of hybrid endoscopic thymectomy (HET) using a combined transthoracic and transesophageal approach. METHODS: Twelve consecutive in vivo experiments were undertaken in the porcine model (4 acute and 8 survival). The same procedure was assessed in a human cadaver afterward. For HET, an 11-mm trocar was inserted in the 2nd intercostal space in the left anterior axillary line. A 0° 10-mm thoracoscope with a 5-mm working channel was introduced. Transesophageal access was created through a submucosal tunnel using a flexible gastroscope with a single working channel introduced through the mouth. Using both flexible (gastroscope) and rigid (thoracoscope) instruments, the mediastinum was opened; the thymus was dissected, and the vessels were ligated using electrocautery alone. RESULTS: Submucosal tunnel creation and esophagotomy were performed safely without incidents in all animals. Complete thymectomy was achieved in all experiments. All animals in the survival group lived for 14 days. Thoracoscopic and postmortem examination revealed pleural adhesions on site of the surgical procedure with no signs of infection. Histological analysis of the proximal third of the esophagus revealed complete cicatrization of both mucosal defect and myotomy site. In the human cadaver, we were able to replicate all the procedure even though we were not able to identify the thymus. CONCLUSIONS: Hybrid endoscopic thymectomy is feasible and reliable. HET could be regarded as a possible alternative to classic thoracoscopic approach for patients requiring thymectomy.This project was funded by the FCT Grants project PTDC/SAU-OSM/105578/2008

Human predisposition to cognitive impairment and its relation with environmental exposure to potentially toxic elements

New lines of evidence suggest that less than 10% of neurodegenerative diseases have a strict genetic aetiology and other factors may be prevalent. Environmental exposures to potentially toxic elements appear to be a risk factor for Parkinson’s, Alzheimer’s and sclerosis diseases. This study proposes a multidisciplinary approach combining neurosciences, psychology and environmental sciences while integrating socio-economic, neuropsychological, environmental and health data. We present the preliminary results of a neuropsychological assessment carried out in elderly residents of the industrial city of Estarreja. A battery of cognitive tests and a personal questionnaire were administered to the participants. Multivariate analysis and multiple linear regression analysis were used to identify potential relationships between the cognitive status of the participants and environmental exposure to potentially toxic elements. The results suggest a relationship between urinary PTEs levels and the incidence of cognitive disorders. They also point towards water consumption habits and profession as relevant factors of exposure. Linear regression models show that aluminium (R2 = 38%), cadmium (R2 = 11%) and zinc (R2 = 6%) are good predictors of the scores of the Mini-Mental State Examination cognitive test. Median contents (µg/l) in groundwater are above admissible levels for drinking water for aluminium (371), iron (860), manganese (250), and zinc (305). While the World Health Organization does not provide health-based reference values for aluminium, results obtained from this study suggest that it may have an important role in the cognitive status of the elderly. Urine proved to be a suitable biomarker of exposure both to elements with low and high excretion rates

Natural computation meta-heuristics for the in silico optimization of microbial strains

<p>Abstract</p> <p>Background</p> <p>One of the greatest challenges in Metabolic Engineering is to develop quantitative models and algorithms to identify a set of genetic manipulations that will result in a microbial strain with a desirable metabolic phenotype which typically means having a high yield/productivity. This challenge is not only due to the inherent complexity of the metabolic and regulatory networks, but also to the lack of appropriate modelling and optimization tools. To this end, Evolutionary Algorithms (EAs) have been proposed for <it>in silico </it>metabolic engineering, for example, to identify sets of gene deletions towards maximization of a desired physiological objective function. In this approach, each mutant strain is evaluated by resorting to the simulation of its phenotype using the Flux-Balance Analysis (FBA) approach, together with the premise that microorganisms have maximized their growth along natural evolution.</p> <p>Results</p> <p>This work reports on improved EAs, as well as novel Simulated Annealing (SA) algorithms to address the task of <it>in silico </it>metabolic engineering. Both approaches use a variable size set-based representation, thereby allowing the automatic finding of the best number of gene deletions necessary for achieving a given productivity goal. The work presents extensive computational experiments, involving four case studies that consider the production of succinic and lactic acid as the targets, by using <it>S. cerevisiae </it>and <it>E. coli </it>as model organisms. The proposed algorithms are able to reach optimal/near-optimal solutions regarding the production of the desired compounds and presenting low variability among the several runs.</p> <p>Conclusion</p> <p>The results show that the proposed SA and EA both perform well in the optimization task. A comparison between them is favourable to the SA in terms of consistency in obtaining optimal solutions and faster convergence. In both cases, the use of variable size representations allows the automatic discovery of the approximate number of gene deletions, without compromising the optimality of the solutions.</p

Asthma App Use and Interest Among Patients With Asthma: A Multicenter Study

info:eu-repo/semantics/publishedVersio

OptFlux: an open-source software platform for in silico metabolic engineering

<p>Abstract</p> <p>Background</p> <p>Over the last few years a number of methods have been proposed for the phenotype simulation of microorganisms under different environmental and genetic conditions. These have been used as the basis to support the discovery of successful genetic modifications of the microbial metabolism to address industrial goals. However, the use of these methods has been restricted to bioinformaticians or other expert researchers. The main aim of this work is, therefore, to provide a user-friendly computational tool for Metabolic Engineering applications.</p> <p>Results</p> <p><it>OptFlux </it>is an open-source and modular software aimed at being the reference computational application in the field. It is the first tool to incorporate strain optimization tasks, i.e., the identification of Metabolic Engineering targets, using Evolutionary Algorithms/Simulated Annealing metaheuristics or the previously proposed OptKnock algorithm. It also allows the use of stoichiometric metabolic models for (i) phenotype simulation of both wild-type and mutant organisms, using the methods of Flux Balance Analysis, Minimization of Metabolic Adjustment or Regulatory on/off Minimization of Metabolic flux changes, (ii) Metabolic Flux Analysis, computing the admissible flux space given a set of measured fluxes, and (iii) pathway analysis through the calculation of Elementary Flux Modes.</p> <p><it>OptFlux </it>also contemplates several methods for model simplification and other pre-processing operations aimed at reducing the search space for optimization algorithms.</p> <p>The software supports importing/exporting to several flat file formats and it is compatible with the SBML standard. <it>OptFlux </it>has a visualization module that allows the analysis of the model structure that is compatible with the layout information of <it>Cell Designer</it>, allowing the superimposition of simulation results with the model graph.</p> <p>Conclusions</p> <p>The <it>OptFlux </it>software is freely available, together with documentation and other resources, thus bridging the gap from research in strain optimization algorithms and the final users. It is a valuable platform for researchers in the field that have available a number of useful tools. Its open-source nature invites contributions by all those interested in making their methods available for the community.</p> <p>Given its plug-in based architecture it can be extended with new functionalities. Currently, several plug-ins are being developed, including network topology analysis tools and the integration with Boolean network based regulatory models.</p