Impact of taxes on competition: the legal status quo in the European Union

Dissertação de mestrado em Direito dos Negócios, Europeu e Transnacional

Exploring chemical conversions in metabolic networks by tracing atoms transitions

Dissertação de mestrado em Bioinformática

Nutritional status and food intake at workplace as health indicators for industrial workers

This study aimed to verify the correlation among the nutritional composition of the food consumed in the work environment, the energy expenditure and the nutritional status of workers from different sectors (administration and production) in different industries. The anthropometric data, in addition to the energy expenditure and food intake at lunch were evaluated for 292 workers, all of them included in the Brazilian Worker Food Program (also called PAT). The food consumption was assessed from the direct observation of the meal, for five consecutive days. The obtained data were analyzed by Pearson correlation test and by a Principal Components Analysis. Prevalence of overweight was detected in the studied population, according to the Body Mass Index (BMI). A statistically significant difference was found in terms of the energy expenditure of physical activity and daily energy expenditure in relation to gender and the working sector. The obtained results indicate that there is significant positive correlation (p < 0.01) between the following variables: body weight and BMI (r = 0.84), weight and daily energy expenditure (DEE) (r = 0.52), BMI and DEE (r = 0.27), DEE and energy (r = 0.38), and energy and lipid intake (r = 0.50). These findings seems to indicate the importance of ensuring an adequate balance of nutrients at meals, due to the heterogeneity of workers, in particular in the case of those workers who perform tasks or functions requiring less energy expenditure.

Modeling microbes: New methods for integrated metabolic and regulatory network reconstruction

PhD Thesis in Bioengineering

Análise do desempenho motor e sua relação com status social em crianças de uma escola

Relatório de estágio de mestrado em Ensino de Educação Física nos Ensinos Básico e Secundário

Effect of short chain fructooligosaccharides (scFOS) on immunological status and gut microbiota of gilthead sea bream (Sparus aurata) reared at two temperatures

The effects of dietary short chain fructooligosaccharides (scFOS) incorporation on hematology, fish immune status, gut microbiota composition, digestive enzymes activities, and gut morphology, was evaluated in gilthead sea bream (Sparus aurata) juveniles reared at 18 °C and 25 °C. For that purpose, fish with 32 g were fed diets including 0, 0.1, 0.25 and 0.5% scFOS during 8 weeks. Overall, scFOS had only minor effects on gilthead sea bream immune status. Lymphocytes decreased in fish fed the 0.1% scFOS diet. Fish fed the 0.5% scFOS diet presented increased nitric oxide (NO) production, while total immunoglobulins (Ig) dropped in those fish, but only in the ones reared at 25 °C. Red blood cells, hemoglobin, bactericidal activity and NO were higher at 25 °C, whereas total white blood cells, circulating thrombocytes, monocytes and neutrophils were higher at 18 °C. In fish fed scFOS, lymphocytes were higher at 18 °C. Total Ig were also higher at 18 °C but only in fish fed 0.1% and 0.5% scFOS diets. No differences in gut bacterial profiles were detected by PCR-DGGE (polymerase chain reaction denaturing gradient gel electrophoresis) between dietary treatments. However, group's similarity was higher at 25 °C. Digestive enzymes activities were higher at 25 °C but were unaffected by prebiotics incorporation. Gut morphology was also unaffected by dietary prebiotic incorporation. Overall, gut microbiota composition, digestive enzymes activities and immunity parameters were affected by rearing temperature whereas dietary scFOS incorporation had only minor effects on these parameters. In conclusion, at the tested levels scFOS does not seem worthy of including it in gilthead sea bream juveniles diets.

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

The influence of kaolin application on key metabolic pathways associated with grape berry quality: a molecular and biochemical analysis

Dissertação de mestrado em Biologia Molecular, Biotecnologia e Bioempreendedorismo em Plantas

A glycolytic phenotype is associated with prostate cancer progression and aggressiveness: a role for Monocarboxylate Transporters as metabolic targets for therapy.

Metabolic adaptation is considered an emerging hallmark of cancer, whereby cancer cells exhibit high rates of glucose consumption with consequent lactate production. To ensure rapid efflux of lactate, most cancer cells express high levels of monocarboxylate transporters (MCTs), which therefore may constitute suitable therapeutic targets. The impact of MCT inhibition, along with the clinical impact of altered cellular metabolism during prostate cancer (PCa) initiation and progression, has not been described. Using a large cohort of human prostate tissues of different grades, in silico data, in vitro and ex vivo studies, we demonstrate the metabolic heterogeneity of PCa and its clinical relevance. We show an increased glycolytic phenotype in advanced stages of PCa and its correlation with poor prognosis. Finally, we present evidence supporting MCTs as suitable targets in PCa, affecting not only cancer cell proliferation and survival but also the expression of a number of hypoxia-inducible factor target genes associated with poor prognosis. Herein, we suggest that patients with highly glycolytic tumours have poorer outcome, supporting the notion of targeting glycolytic tumour cells in prostate cancer through the use of MCT inhibitors.

HPV DNA testing with cytology triage in cervical cancer screening: Influence of revealing HPV infection status

BACKGROUND: Knowledge of cervical human papillomavirus (HPV) status might influence a cytotechnician's assessment of cellular abnormalities. The authors compared original cytotechnicians' Papanicolaou (Pap) readings for which HPV status was concealed with Pap rereads for which HPV status was revealed separately for 3 screening populations. METHODS: Previously collected cervical Pap smears and clinical data were obtained from the Canadian Cervical Cancer Screening Trial (study A), the Democratic Republic of Congo Community-Based Screening Study (study B), and the Brazilian Investigation into Nutrition and Cervical Cancer Prevention (study C). Smears were reread with knowledge of HPV status for all HPV-positive women as well as a sample of HPV-negative women. Diagnostic performance of Pap cytology was compared between original readings and rereads. RESULTS: A total of 1767 Pap tests were reread. Among 915 rereads for HPV-positive women, the contrast between "revealed" and "concealed" Pap readings demonstrated revisions from negative to positive results for 109 women (cutoff was atypical squamous cells of undetermined significance or worse) and 124 women (cutoff was low-grade squamous intraepithelial lesions [LSIL] or worse). For a disease threshold of cervical intraepithelial neoplasia of grade 2 or worse, specificity significantly declined at the atypical squamous cells of undetermined significance cutoff for studies A (86.6% to 75.3%) and C (42.5% to 15.5%), and at the LSIL cutoff for study C (61.9% to 37.6%). Sensitivity remained nearly unchanged between readings, except in study C, in which reread performance was superior (91.3% vs 71.9% for the LSIL cutoff). CONCLUSIONS: A reduction in the diagnostic accuracy of Pap cytology was observed when revealing patients' cervical HPV status, possibly due to a heightened awareness of potential abnormalities, which led to more false-positive results. Cancer (Cancer Cytopathol) 2015. (c) 2015 American Cancer Society.

Metabolic engineering with multi-objective optimization of kinetic models

Kinetic models have a great potential for metabolic engineering applications. They can be used for testing which genetic and regulatory modifications can increase the production of metabolites of interest, while simultaneously monitoring other key functions of the host organism. This work presents a methodology for increasing productivity in biotechnological processes exploiting dynamic models. It uses multi-objective dynamic optimization to identify the combination of targets (enzymatic modifications) and the degree of up- or down-regulation that must be performed in order to optimize a set of pre-defined performance metrics subject to process constraints. The capabilities of the approach are demonstrated on a realistic and computationally challenging application: a large-scale metabolic model of Chinese Hamster Ovary cells (CHO), which are used for antibody production in a fed-batch process. The proposed methodology manages to provide a sustained and robust growth in CHO cells, increasing productivity while simultaneously increasing biomass production, product titer, and keeping the concentrations of lactate and ammonia at low values. The approach presented here can be used for optimizing metabolic models by finding the best combination of targets and their optimal level of up/down-regulation. Furthermore, it can accommodate additional trade-offs and constraints with great flexibility.

Algorithms and computational tools for metabolic flux analysis

PhD thesis in Biomedical Engineering

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.

Candida tropicalis biofilms: biomass, metabolic activity and secreted aspartyl proteinase production

According to epidemiological data, Candida tropicalis has been related to urinary tract infections and haematological malignancy. Several virulence factors seem to be responsible for C. tropicalis infections, for example: their ability to adhere and to form biofilms onto different indwelling medical devices; their capacity to adhere, invade and damage host human tissues due to enzymes production such as proteinases. The main aim of this work was to study the behaviour of C. tropicalis biofilms of different ages (24120 h) formed in artificial urine (AU) and their ability to express aspartyl proteinase (SAPT) genes. The reference strain C. tropicalis ATCC 750 and two C. tropicalis isolates from urine were used. Biofilms were evaluated in terms of culturable cells by colony-forming units enumeration; total biofilm biomass was evaluated using the crystal violet staining method; metabolic activity was evaluated by XTT assay; and SAPT gene expression was determined by real-time PCR. All strains of C. tropicalis were able to form biofilms in AU, although with differences between strains. Candida tropicalis biofilms showed a decrease in terms of the number of culturable cells from 48 to 72 h. Generally, SAPT3 was highly expressed. C. tropicalis strains assayed were able to form biofilms in the presence of AU although in a strain- and time-dependent way, and SAPT genes are expressed during C. tropicalis biofilm formation.