Search

This paper highlights the potential of Sargassum algae, recovered from raw beach seaweed wastes, as a valid source of valuable sodium alginate. Alginate is a biodegradable, highly attractive polysaccharide widely used in food, pharmaceuticals, and biomedicine applications. The aim of this work is to employ a new eco-sustainable and cost-effective extractive method to obtain alginate as a raw material from pollutant organic Sargassum seaweeds. Algae were exposed to microwave pre-treatment under static and dynamic conditions, and three different extractive protocols were followed: (a) conventional, (b) hot water and (c) alkaline method. All samples were characterized by GPC, SEM, FTIR/ATR and TGA. It was found that alginate's best performances were obtained by the microwave dynamic pre-treatment method followed by alkaline extractive protocol. Nevertheless, the microwave pre-treatment of algae allowed the easiest breaking of their cell walls and the following fast releasing of sodium alginate. The authors demonstrated that microwave-enhanced extraction is an effective way to obtain sodium alginate from Sargassum-stranded seaweed waste materials in a cost-effective and eco-sustainable approach. They also assessed their applications as mulching films for agricultural applications. [ABSTRACT FROM AUTHOR]

Drying of bio-substrates such as food can be enhanced when exploiting a variety of simultaneous transport phenomena mechanisms, such as jet impingement and exposure to microwaves. To this end, a laboratory prototype has been exercised to infer on substrate quality departure. Among the various available operating conditions, there are some that address the preservation of color attributes. As an example, emphasis to pulsed exposure to microwaves would result in less spoiled substrates, while colder air would not necessarily lead to optimal processing, and higher flow rates would increase oxidation and color degradation. [ABSTRACT FROM AUTHOR]

Simulation of tumor evolution at the macroscopic, tissue scale can be applied to cancer treatment optimization. This paper aims to gain deeper insight into the dynamics of tumor growth at this scale and to develop predictive, quantitative mathematical models which can be used as a decision tool supporting oncologists and surgeons. This preliminary model describes tumor progression as mass transfer governed by partial differential equations, incorporating a multi-species logistic growth/decay law to account for the production of necrosis and the interaction with therapy. The set of governing equations is integrated by a commercial platform of Finite Element Method. After a validation study with literature data on a hepatocellular carcinoma, a sensitivity analysis was conducted by including the driving source terms (growth rates, drug efficiency and its delivery/availability). Results suggest that, in the first two months of therapy, tumor volume progress is related nonlinearly so that a mere 10% of stronger/weaker cancer malignancy lead to doubling/halving the tumor volume, the increment of drug efficiency by 25% lead to a 60% decrease of the volume, while a smaller efficiency by 25% lead to a sudden run-away of the disease. Finally, the optimal administration pattern for chemoembolization was found with a 4-points therapy delivery on the same side with respect to the Region of Interest. [ABSTRACT FROM AUTHOR]