In vivo imaging of glycol chitosan-based nanogel biodistribution

The preclinical development of nanomedicines raises several challenges and requires a comprehensive characterization. Among them is the evaluation of the biodistribution following systemic administration. In previous work, the biocompatibility and in vitro targeting ability of a glycol chitosan (GC) based nanogel have been validated. In the present study, its biodistribution in the mice is assessed, using near-infrared (NIR) fluorescence imaging as a tool to track the nanogel over time, after intravenous administration. Rapid whole body biodistribution of both Cy5.5 labeled GC nanogel and free polymer is found at early times. It remains widespreadly distributed in the body at least up to 6 h postinjection and its concentration then decreases drastically after 24 h. Nanogel blood circulation half-life lies around 2 h with the free linear GC polymer presenting lower blood clearance rate. After 24 h, the blood NIR fluorescence intensity associated with both samples decreases to insignificant values. NIR imaging of the organs shows that the nanogel had a body clearance time of 48 h, because at this time point a weak signal of NIR fluorescence is observed only in the kidneys. Hereupon it can be concluded that the engineered GC nanogel has a fairly long blood circulation time, suitable for biomedical applications, namely, drug delivery, simultaneously allowing efficient and quick body clearance.

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.

Activity of carvacrol against Coagulase-negative Staphylococci biofilm related infections

Dissertação de mestrado em Bioengenharia

Influence of oxygen conditions on bacterial interactions within biofilms related with cystic fibrosis

Dissertação de mestrado em Bioengineering

Development of nanohydrogels as a vehicle for the release of bioactive compounds in food matrices

PhD in Chemical and Biological Engineering

Characterization of microbial populations in a wastewater treatment plant focusing on Staphylococcus aureus and Pseudomonas aeruginosa

Dissertação de mestrado em Bioengenharia