Toxicity induced by a metal mixture (Cd, Pb and Zn) in the yeast Pichia kudriavzevii: The role of oxidative stress

The present work aims to contribute for the elucidation of the role of oxidative stress in the toxicity associated with the exposure of Pichia kudriavzevii to multi-metals (Cd, Pb and Zn). Cells of the non-conventional yeast P. kudriavzevii exposed for 6 h to the action of multi-metals accumulated intracellular reactive oxygen species (ROS), evaluated through the oxidation of the probe 2,7-dichlorodihydrofluorescein diacetate. A progressive loss of membrane integrity (monitored using propidium iodide) was observed in multi-metal-treated cells. The triggering of intracellular ROS accumulation preceded the loss of membrane integrity. These results suggest that the disruption of membrane integrity can be attributed to the oxidative stress. The exposure of yeast cells to single metal showed that, under the concentrations tested, Pb was the metal responsible for the induction of the oxidative stress. Yeast cells coexposed to an antioxidant (ascorbic acid) and multi-metals did not accumulate intracellular ROS, but loss proliferation capacity. Together, the data obtained indicated that intracellular ROS accumulation contributed to metal toxicity, namely for the disruption of membrane integrity of the yeast P. kudriavzevii. It was proposed that Pb toxicity (the metal responsible for the toxic symptoms under the conditions tested) result from the combination of an ionic mechanism and the intracellular ROS accumulation.

O gosto como fator motivacional nos primeiros anos de estudo de violino

Relatório de estágio de mestrado em Ensino de Música

As potencialidades pedagógicas da WebQuest no ensino e aprendizagem da Geologia: um estudo com alunos do 11.º ano no tema "Principais etapas de formação das rochas sedimentares"

Relatório de estágio de mestrado em Ensino de Biologia e Geologia no 3.º Ciclo do Ensino Básico e no Ensino Secundário

Aprendizagem baseada na resolução de problemas: uma experiência pedagógica com alunos de um Curso de Especialização Tecnológica

Relatório de estágio de mestrado em Ensino de Informática

Desenvolvendo aprendizagens integradas

Relatório de estágio de mestrado em Educação Pré-Escolar

À descoberta do mundo pelo jogo dos sentidos

Relatório de estágio de mestrado em Educação Pré-Escolar

A deslocalização produtiva em Portugal: o caso de uma empresa do setor das cutelarias

Projeto de estágio de mestrado em Economia Industrial e da Empresa

Saber cooperar para saber aprender: contributos da aprendizagem cooperativa na promoção de competências sociais e no sucesso educativo através do desenvolvimento de um projeto curricular integrado

Relatório de estágio de mestrado em Educação Pré-Escolar e Ensino do 1.º Ciclo do Ensino Básico

Os contributos do texto literário para o ensino-aprendizagem de PLE: elaboração de uma proposta de didatização de um conto de Sophia de Mello Breyner Andresen

Dissertação de mestrado em Português Língua Não Materna (PLNM) – Português Língua Estrangeira (PLE) e Língua Segunda (PL2)

Ciências e experiências em contexto de educação pré-escolar

Relatório de estágio de mestrado em Educação Pré-Escolar e Ensino do 1ºCiclo do Ensino Básico

A Hora do Conto: descobrir os livros e o prazer da leitura de histórias

Relatório de estágio de mestrado em Educação Pré-Escolar e Ensino do 1ºCiclo do Ensino Básico

Hair coloration by gene regulation: fact or fiction?

The unravelling of hair pigmentation genetics and robust delivery systems to the hair follicle (HF) will allow the development of a new class of colouring products. The challenge will be changing hair colour from inside out by safely regulating the activity of target genes through the specific delivery of synthetic/natural compounds, proteins, genes, or small RNAs.

In silico constraint-based strain optimization methods: the quest for optimal cell factories

Shifting from chemical to biotechnological processes is one of the cornerstones of 21st century industry. The production of a great range of chemicals via biotechnological means is a key challenge on the way toward a bio-based economy. However, this shift is occurring at a pace slower than initially expected. The development of efficient cell factories that allow for competitive production yields is of paramount importance for this leap to happen. Constraint-based models of metabolism, together with in silico strain design algorithms, promise to reveal insights into the best genetic design strategies, a step further toward achieving that goal. In this work, a thorough analysis of the main in silico constraint-based strain design strategies and algorithms is presented, their application in real-world case studies is analyzed, and a path for the future is discussed.

UV-visible scanning spectrophotometry and chemometric analysis as tools for carotenoids analysis in cassava genotypes (Manihot esculenta Crantz)

In this study, the metabolomics characterization focusing on the carotenoid composition of ten cassava (Manihot esculenta) genotypes cultivated in southern Brazil by UV-visible scanning spectrophotometry and reverse phase-high performance liquid chromatography was performed. Cassava roots rich in -carotene are an important staple food for populations with risk of vitamin A deficiency. Cassava genotypes with high pro-vitamin A activity have been identified as a strategy to reduce the prevalence of deficiency of this vitamin. The data set was used for the construction of a descriptive model by chemometric analysis. The genotypes of yellow-fleshed roots were clustered by the higher concentrations of cis--carotene and lutein. Inversely, cream-fleshed roots genotypes were grouped precisely due to their lower concentrations of these pigments, as samples rich in lycopene (redfleshed) differed among the studied genotypes. The analytical approach (UV-Vis, HPLC, and chemometrics) used showed to be efficient for understanding the chemodiversity of cassava genotypes, allowing to classify them according to important features for human health and nutrition.

Integrating data from heterogeneous DNA microarray platforms

DNA microarrays are one of the most used technologies for gene expression measurement. However, there are several distinct microarray platforms, from different manufacturers, each with its own measurement protocol, resulting in data that can hardly be compared or directly integrated. Data integration from multiple sources aims to improve the assertiveness of statistical tests, reducing the data dimensionality problem. The integration of heterogeneous DNA microarray platforms comprehends a set of tasks that range from the re-annotation of the features used on gene expression, to data normalization and batch effect elimination. In this work, a complete methodology for gene expression data integration and application is proposed, which comprehends a transcript-based re-annotation process and several methods for batch effect attenuation. The integrated data will be used to select the best feature set and learning algorithm for a brain tumor classification case study. The integration will consider data from heterogeneous Agilent and Affymetrix platforms, collected from public gene expression databases, such as The Cancer Genome Atlas and Gene Expression Omnibus.