Laboratory assessment of the hypertensive individual. Value of the main guidelines for high blood pressure

OBJECTIVE: To determine if abnormal laboratory findings are more common in individuals with hypertension and in those with other risk factors, such as obesity, smoking and alcohol ingestion. METHODS: A study was carried out in the general outpatient clinics of a university hospital (145 individuals without previous diagnosis of hypertension) and the following variables were assessed: high blood pressure (as defined by the VI Joint National Committee on Prevention, Detection and Treatment of High Blood Pressure - VI JNC), obesity [calculated using body mass index (BMI)], tobacco use, and alcoholic ingestion. The laboratory examinations consisted of the following tests: hemogram, glycemia, uric acid, potassium, total/HDL-fraction cholesterol, triglycerides, calcium and creatinine. RESULTS: High blood pressure was not associated with a higher number of abnormal laboratory tests. Hypertensive individuals with a BMI > or = 25kg/m² or normotensive obese individuals, however, had a higher frequency of diabetes (12X), hypertriglyceridemia (3X), and hypercholesterolemia (2X), as compared with hypertensive individuals with BMI <25kg/m² and preobese/normal weight normotensive individuals. CONCLUSION: High blood pressure is not associated with a higher frequency of abnormal laboratory tests. The association of high blood pressure and obesity, however, increases the detection of diabetes and dyslipidemias.

Tapping the wealth of microbial data in high-throughput metabolic model reconstruction

Genome-scale metabolic models are valuable tools in the metabolic engineering process, based on the ability of these models to integrate diverse sources of data to produce global predictions of organism behavior. At the most basic level, these models require only a genome sequence to construct, and once built, they may be used to predict essential genes, culture conditions, pathway utilization, and the modifications required to enhance a desired organism behavior. In this chapter, we address two key challenges associated with the reconstruction of metabolic models: (a) leveraging existing knowledge of microbiology, biochemistry, and available omics data to produce the best possible model; and (b) applying available tools and data to automate the reconstruction process. We consider these challenges as we progress through the model reconstruction process, beginning with genome assembly, and culminating in the integration of constraints to capture the impact of transcriptional regulation. We divide the reconstruction process into ten distinct steps: (1) genome assembly from sequenced reads; (2) automated structural and functional annotation; (3) phylogenetic tree-based curation of genome annotations; (4) assembly and standardization of biochemistry database; (5) genome-scale metabolic reconstruction; (6) generation of core metabolic model; (7) generation of biomass composition reaction; (8) completion of draft metabolic model; (9) curation of metabolic model; and (10) integration of regulatory constraints. Each of these ten steps is documented in detail.

Particle transport in fouling caused by kaolin-water suspensions on copper tubes

Particulate fouling tests were carried out using kaolin-water suspensions flowing through an annular heat exchanger with a copper inner tube. The flow rate was changed from test to test, but the fluid temperature and pH, as well as the particle concentration, were maintained constant. In the lower range of fluid velocities (<0.5 m/s), the deposition process seemed to be controlled by mass transfer. The corresponding experimental transport fluxes were compared to the predictions obtained with several models, showing that diffusion governed particle transport. The absolute values of the mass transfer fluxes and their dependences on the Reynolds number were satisfactorily predicted by some of the models.

Exploitation of Ashbya gossypii for the production of high-value products from glycerol feedstocks

Dissertação de mestrado em Bioengenharia