Chemical features of Ganoderma polysaccharides with antioxidant, antitumor and antimicrobial activities

Review aricle

Production and extraction of polysaccharides and oligosaccharides and their use as new food additives

Polysaccharides and oligosaccharides can improve quality and enhance nutritional value of final food products due to their technological and nutritional features ranging from their capacity to improve texture to their effect as dietary fibers. For this reason, they are among the most studied ingredients in the food industry. The use of natural polysaccharides and oligosaccharides as food additives has been a reality since the food industry understood their potential technological and nutritional applications. Currently, the replacement of traditional ingredients and/or the synergy between traditional ingredients and polysaccharides and oligosaccharides are perceived as promising approaches by the food industry. Traditionally, polysaccharides have been used as thickening, emulsifying, and stabilizing agents, however, at this moment polysaccharides and oligosaccharides claim health and nutritional advantages, thus opening a new market of nutritional and functional foods. Indeed, their use as nutritional food ingredients enabled the food industry to develop a countless number of applications, e.g., fat replacers, prebiotics, dietary fiber, and antiulcer agents. Based on this, among the scientific community and food industry, in the last years many research studies and commercial products showed the possibility of using either new or already used sources (though with changed properties) of polysaccharides for the production of food additives with new and enhanced properties. The increasing interest in such products is clearly illustrated by the market figures and consumption trends. As an example, the sole market of hydrocolloids is estimated to reach $7 billion in 2018. Moreover, oligosaccharides can be found in more than 500 food products resulting in a significant daily consumption. A recent study from the Transparency Market Research on Prebiotic Ingredients Market reported that prebiotics' demand was worth $2.3 billion in 2012 and it is estimated to reach $4.5 billion in 2018, growing at a compound annual growth rate of 11.4% between 2012 and 2018. The entrance of this new generation of food additives in the market, often claiming health and nutritional benefits, imposes an impartial analysis by the legal authorities regarding the accomplishment of requirements that have been established for introducing novel ingredients/food, including new poly- and oligosaccharides. This chapter deals with the potential use of polysaccharides and oligosaccharides as food additives, as well as alternative sources of these compounds and their possible applications in food products. Moreover, the regulation process to introduce novel polysaccharides and oligosaccharides in the market as food additives and to assign them health claims is discussed.

Hand gesture recognition for human computer interaction : a comparative study of different image features

Hand gesture recognition for human computer interaction, being a natural way of human computer interaction, is an area of active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them to convey information or for device control. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. In this study we try to identify hand features that, isolated, respond better in various situations in human-computer interaction. The extracted features are used to train a set of classifiers with the help of RapidMiner in order to find the best learner. A dataset with our own gesture vocabulary consisted of 10 gestures, recorded from 20 users was created for later processing. Experimental results show that the radial signature and the centroid distance are the features that when used separately obtain better results, with an accuracy of 91% and 90,1% respectively obtained with a Neural Network classifier. These to methods have also the advantage of being simple in terms of computational complexity, which make them good candidates for real-time hand gesture recognition.

Step towards multiplatform framework for supporting pediatric and neonatology care unit decision process

Children are an especially vulnerable population, particularly in respect to drug administration. It is estimated that neonatal and pediatric patients are at least three times more vulnerable to damage due to adverse events and medication errors than adults are. With the development of this framework, it is intended the provision of a Clinical Decision Support System based on a prototype already tested in a real environment. The framework will include features such as preparation of Total Parenteral Nutrition prescriptions, table pediatric and neonatal emergency drugs, medical scales of morbidity and mortality, anthropometry percentiles (weight, length/height, head circumference and BMI), utilities for supporting medical decision on the treatment of neonatal jaundice and anemia and support for technical procedures and other calculators and widespread use tools. The solution in development means an extension of INTCare project. The main goal is to provide an approach to get the functionality at all times of clinical practice and outside the hospital environment for dissemination, education and simulation of hypothetical situations. The aim is also to develop an area for the study and analysis of information and extraction of knowledge from the data collected by the use of the system. This paper presents the architecture, their requirements and functionalities and a SWOT analysis of the solution proposed.

Segmentação do tecido tumoral cerebral em imagens de ressonância magnética

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Eletrónica Médica)

Automatic eye blink detection using consumer web cameras

This research aims to advance blinking detection in the context of work activity. Rather than patients having to attend a clinic, blinking videos can be acquired in a work environment, and further automatically analyzed. Therefore, this paper presents a methodology to perform the automatic detection of eye blink using consumer videos acquired with low-cost web cameras. This methodology includes the detection of the face and eyes of the recorded person, and then it analyzes the low-level features of the eye region to create a quantitative vector. Finally, this vector is classified into one of the two categories considered —open and closed eyes— by using machine learning algorithms. The effectiveness of the proposed methodology was demonstrated since it provides unbiased results with classification errors under 5%

Extraction and characterization of polysaccharides from non-traditional Brazilian Amazon sources

[Excerpt] Cupuassu (Theobroma grandiflorum), tucumã (Astrocaryum aculeatum), peach palm (Bactris gasipaes) and abricó (American Mammea L.) are exotic fruits found in the Brazilian Amazon rainforest. All of them are well known by the native populations, and for centuries the pulps have been used in the production of juices, deserts, jams, syrups, and alcoholic beverages, among others. Additionally, the fruit seeds have been used as animal feed, fertilizers or to plant new seedlings, but a great part of these seeds are usually discarded. (...)

Biological extraction of bromelain from pineapple byproducts

[Excerpt] Isolation and purification of valuable compounds are very important processes to valorize agro-food byproducts. Currently, protein extraction and development of environmentally friendly technologies are industrially relevant topics [1]. Among the extracted proteins from byproducts proteases are a relevant group for industrial applications. These enzymes are a class of hydrolytic enzymes capable of cleaving the peptide bonds of proteins chains and are essential in physiological processes [2]. (...)

Bioethanol production by Saccharomyces cerevisiae, Pichia stipitis and Zymomonas mobilis from delignified coconut fibre mature and lignin extraction according to biorefinery concept

In search to increase the offer of liquid, clean, renewable and sustainable energy in the world energy matrix, the use of lignocellulosic materials (LCMs) for bioethanol production arises as a valuable alternative. The objective of this work was to analyze and compare the performance of Saccharomyces cerevisiae, Pichia stipitis and Zymomonas mobilis in the production of bioethanol from coconut fibre mature (CFM) using different strategies: simultaneous saccharification and fermentation (SSF) and semi-simultaneous saccharification and fermentation (SSSF). The CFM was pretreated by hydrothermal pretreatment catalyzed with sodium hydroxide (HPCSH). The pretreated CFM was characterized by X-ray diffractometry and SEM, and the lignin recovered in the liquid phase by FTIR and TGA. After the HPCSH pretreatment (2.5% (v/v) sodium hydroxide at 180 °C for 30 min), the cellulose content was 56.44%, while the hemicellulose and lignin were reduced 69.04% and 89.13%, respectively. Following pretreatment, the obtained cellulosic fraction was submitted to SSF and SSSF. Pichia stipitis allowed for the highest ethanol yield 90.18% in SSSF, 91.17% and 91.03% were obtained with Saccharomyces cerevisiae and Zymomonas mobilis, respectively. It may be concluded that the selection of the most efficient microorganism for the obtention of high bioethanol production yields from cellulose pretreated by HPCSH depends on the operational strategy used and this pretreatment is an interesting alternative for add value of coconut fibre mature compounds (lignin, phenolics) being in accordance with the biorefinery concept.