3 resultados para Food-Drug Interactions

em Universidade do Minho


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[Excerpt] The incidence of fungal infections has greatly increased in patients under sustained immunosuppression with considerable risk associated. Difficulties regarding prompt diagnosis and the limited therapeutic options dictate high mortality rates. Available antifungals display substantial toxicity, a predictable consequence of the cellular structure of the organisms involved, reduced spectrum of activity, and drug interactions. Our group had previously identified three (Z)-5-amino-N'-aryl-1-methyl-1H-imidazole-4-carbohydrazonamides 1 [aryl= phenyl (1a), 4-fluorophenyl (1b), 3fluorophenyl (1c)] as potent antifungal agents.1 (...)

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The potential of salicylic acid (SA) encapsulated in porous materials as drug delivery carriers for cancer treatment was studied. Different porous structures, the microporous zeolite NaY, and the mesoporous SBA-15 and MCM-41 were used as hosts for the anti-inflammatory drug. Characterization with different techniques (FTIR, UV/vis, TGA, 1H NMR, and 13C CPMAS NMR) demonstrated the successful loading of SA into the porous hosts. The mesoporous structures showed to be very efficient to encapsulate the SA molecule. The obtained drug delivery systems (DDS) accommodated 0.74 mmol (341 mg/gZEO) in NaY and 1.07 mmol (493 mg/gZEO) to 1.23 mmol (566 mg/gZEO) for SBA-15 and MCM-41, respectively. Interactions between SA molecules and pore structures were identified. A fast and unrestricted liberation of SA at 10 min of the dissolution assay was achieved with 29.3, 46.6, and 50.1 µg/mL of SA from NaY, SBA-15, and MCM-41, respectively, in the in vitro drug release studies (PBS buffer pH 7.4, 37 °C). Kinetic modeling was used to determine the release patterns of the DDS. The porous structures and DDS were evaluated on Hs578T and MDA-MB-468 breast cancer cell lines viability. The porous structures are nontoxic to cancer cells. Cell viability reduction was only observed after the release of SA from MCM- 41 followed by SBA-15 in both breast cancer cell lines.

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Under the framework of constraint based modeling, genome-scale metabolic models (GSMMs) have been used for several tasks, such as metabolic engineering and phenotype prediction. More recently, their application in health related research has spanned drug discovery, biomarker identification and host-pathogen interactions, targeting diseases such as cancer, Alzheimer, obesity or diabetes. In the last years, the development of novel techniques for genome sequencing and other high-throughput methods, together with advances in Bioinformatics, allowed the reconstruction of GSMMs for human cells. Considering the diversity of cell types and tissues present in the human body, it is imperative to develop tissue-specific metabolic models. Methods to automatically generate these models, based on generic human metabolic models and a plethora of omics data, have been proposed. However, their results have not yet been adequately and critically evaluated and compared. This work presents a survey of the most important tissue or cell type specific metabolic model reconstruction methods, which use literature, transcriptomics, proteomics and metabolomics data, together with a global template model. As a case study, we analyzed the consistency between several omics data sources and reconstructed distinct metabolic models of hepatocytes using different methods and data sources as inputs. The results show that omics data sources have a poor overlapping and, in some cases, are even contradictory. Additionally, the hepatocyte metabolic models generated are in many cases not able to perform metabolic functions known to be present in the liver tissue. We conclude that reliable methods for a priori omics data integration are required to support the reconstruction of complex models of human cells.