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Simone Carradori Melissa D’Ascenzio Paola Chimenti Daniela Secci Adriana Bolasco 《Molecular diversity》2014,18(1):219-243
Monoamine oxidases (MAOs) are mitochondrial bound enzymes, which catalyze the oxidative deamination of monoamine neurotransmitters. Inside the brain, MAOs are present in two isoforms: MAO-A and MAO-B. The activity of MAO-B is generally higher in patients affected by neurodegenerative diseases like Alzheimer’s and Parkinson’s. Therefore, the search for potent and selective MAO-B inhibitors is still a challenge for medicinal chemists. Nature has always been a source of inspiration for the discovery of new lead compounds. Moreover, natural medicine is a major component in all traditional medicine systems. In this review, we present the latest discoveries in the search for selective MAO-B inhibitors from natural sources. For clarity, compounds have been classified on the basis of structural analogy or source: flavonoids, xanthones, tannins, proanthocyanidins, iridoid glucosides, curcumin, alkaloids, cannabinoids, and natural sources extracts. MAO inhibition values reported in the text are not always consistent due to the high variability of MAO sources (bovine, pig, rat brain or liver, and human) and to the heterogeneity of the experimental protocols used. 相似文献
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Valentin Guillon Daniela Bauer Marc Fleury Marie-Christine Néel 《Transport in Porous Media》2014,101(2):251-267
We present a pore network model combined with a random walk algorithm allowing the simulation of molecular displacement distributions in porous media as measured by NMR. A particular feature of this technique is the ability to probe the time evolution of these distributions. The objective is to predict the displacement behaviour for time intervals larger than the experimental observation time and explore the asymptotic dispersion regime at long times. Starting from 3D micro-CT images, we computed the variance of displacement distributions of water molecules in a Fontainebleau sand and found very good agreement of the time evolution of the variance with experimental data, without fitting parameter. The model confirms a weak superdispersion in the asymptotic regime. In addition, we conclude that, since pore network models do not take into account small scale features of the porous medium (e.g., surface roughness and grain shape), the origin of the observed superdispersion is mainly due to the topology and geometry of the porous medium. 相似文献
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