Measurement of differential J/psi production cross sections and forward-backward ratios in p plus Pb collisions with the ATLAS detector

Measurements of differential cross sections for J/ψ production in p+Pb collisions at sNN−−−−√=5.02 TeV at the CERN Large Hadron Collider with the ATLAS detector are presented. The data set used corresponds to an integrated luminosity of 28.1 nb−1. The J/ψ mesons are reconstructed in the dimuon decay channel over the transverse momentum range 8modifications of charmonium and b-quark production in p+Pb collisions.

Otimização da remoção de condensados num mural de frio

Dissertação de mestrado integrado em Engenharia Mecânica

Geração de aplicações a partir de especificações UML como fator de sucesso para o desenvolvimento de sistemas de informação

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

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.

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.

Bacterial cellulose surface modification

The unique properties of bacterial nanocellulose (BNC) provide the basis for a wide range of applications in human and veterinary medicine, odontology, pharmaceuticals, acoustic and filter membranes, biotechnological devices, and in the food and paper industry. In this chapter, an overview of surface modifications of bacterial cellulose is presented. Depending on the envisaged applications, chemical modifications, incorporation of bioactive molecules, modification of the porosity, crystallinity, and biodegradability may be obtained, further enlarging the potential of BNC.

Zeolite-based nanomaterials for the control of opportunistic pathogenic microorganisms

Dissertação de mestrado em Applied Biochemistry (área de especialização em Biomedicine)