Studies on the characterization of dental whitening process by using both hyperspectral imaging and colorimeter techniques

A beautiful smile is directly related with white teeth. Nowadays oral care has increased and developed processes for beautiful smiles. Dental bleaching is frequently used in odontology, not just for health care also for aesthetic treatment. With the possibility of teeth bleaching, now the importance is in, how white the tooth is? Because color is relate to an individual perception. In order to assets teeth correct color identification has been developed many color guides, models, spaces and analytical methods. Spite all of these useful tools the color interpretation depends on environmental factors, position of the sample in the data acquisition and most importantly the instrument sensitivity. The commons methods have proved to be useful. They are easy to handle, some are portable but they do not have a high sensitivity. The present work is based on the integration of a new analytical technique for color acquisition. High spectral Image (HSI) is able to performed image analysis with high quality and efficiency. HSI is used in many fields and we used it for color image analysis within the bleaching process. The main comparison was done with the HSI and the colorimeter through the processes of two different bleaching protocols. The results showed that HSI has higher sensitivity than the colorimeter. During the analysis the dental surface with the HSI we were able to notice surface changes. These changes were analyzed by roughness studies.

Identifying quantitative operation principles in metabolic pathways: a systematic method for searching feasible enzyme activity patterns leading to cellular adaptive responses

Background: Optimization methods allow designing changes in a system so that specific goals are attained. These techniques are fundamental for metabolic engineering. However, they are not directly applicable for investigating the evolution of metabolic adaptation to environmental changes. Although biological systems have evolved by natural selection and result in well-adapted systems, we can hardly expect that actual metabolic processes are at the theoretical optimum that could result from an optimization analysis. More likely, natural systems are to be found in a feasible region compatible with global physiological requirements. Results: We first present a new method for globally optimizing nonlinear models of metabolic pathways that are based on the Generalized Mass Action (GMA) representation. The optimization task is posed as a nonconvex nonlinear programming (NLP) problem that is solved by an outer- approximation algorithm. This method relies on solving iteratively reduced NLP slave subproblems and mixed-integer linear programming (MILP) master problems that provide valid upper and lower bounds, respectively, on the global solution to the original NLP. The capabilities of this method are illustrated through its application to the anaerobic fermentation pathway in Saccharomyces cerevisiae. We next introduce a method to identify the feasibility parametric regions that allow a system to meet a set of physiological constraints that can be represented in mathematical terms through algebraic equations. This technique is based on applying the outer-approximation based algorithm iteratively over a reduced search space in order to identify regions that contain feasible solutions to the problem and discard others in which no feasible solution exists. As an example, we characterize the feasible enzyme activity changes that are compatible with an appropriate adaptive response of yeast Saccharomyces cerevisiae to heat shock Conclusion: Our results show the utility of the suggested approach for investigating the evolution of adaptive responses to environmental changes. The proposed method can be used in other important applications such as the evaluation of parameter changes that are compatible with health and disease states.

In silico pathway reconstruction: Iron-sulfur cluster biogenesis in Saccharomyces cerevisiae

Background: Current advances in genomics, proteomics and other areas of molecular biology make the identification and reconstruction of novel pathways an emerging area of great interest. One such class of pathways is involved in the biogenesis of Iron-Sulfur Clusters (ISC). Results: Our goal is the development of a new approach based on the use and combination of mathematical, theoretical and computational methods to identify the topology of a target network. In this approach, mathematical models play a central role for the evaluation of the alternative network structures that arise from literature data-mining, phylogenetic profiling, structural methods, and human curation. As a test case, we reconstruct the topology of the reaction and regulatory network for the mitochondrial ISC biogenesis pathway in S. cerevisiae. Predictions regarding how proteins act in ISC biogenesis are validated by comparison with published experimental results. For example, the predicted role of Arh1 and Yah1 and some of the interactions we predict for Grx5 both matches experimental evidence. A putative role for frataxin in directly regulating mitochondrial iron import is discarded from our analysis, which agrees with also published experimental results. Additionally, we propose a number of experiments for testing other predictions and further improve the identification of the network structure. Conclusion: We propose and apply an iterative in silico procedure for predictive reconstruction of the network topology of metabolic pathways. The procedure combines structural bioinformatics tools and mathematical modeling techniques that allow the reconstruction of biochemical networks. Using the Iron Sulfur cluster biogenesis in S. cerevisiae as a test case we indicate how this procedure can be used to analyze and validate the network model against experimental results. Critical evaluation of the obtained results through this procedure allows devising new wet lab experiments to confirm its predictions or provide alternative explanations for further improving the models.

Coscheduling techniques and monitoring tools for non-dedicated cluster computing

Our efforts are directed towards the understanding of the coscheduling mechanism in a NOW system when a parallel job is executed jointly with local workloads, balancing parallel performance against the local interactive response. Explicit and implicit coscheduling techniques in a PVM-Linux NOW (or cluster) have been implemented. Furthermore, dynamic coscheduling remains an open question when parallel jobs are executed in a non-dedicated Cluster. A basis model for dynamic coscheduling in Cluster systems is presented in this paper. Also, one dynamic coscheduling algorithm for this model is proposed. The applicability of this algorithm has been proved and its performance analyzed by simulation. Finally, a new tool (named Monito) for monitoring the different queues of messages in such an environments is presented. The main aim of implementing this facility is to provide a mean of capturing the bottlenecks and overheads of the communication system in a PVM-Linux cluster.

Steady-state global optimization of metabolic non-linear dynamic models through recasting into power-law canonical models

Background: Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be analyzed and, with the development and application of appropriate optimization techniques, one could identify the modifications that need to be made to the organism in order to achieve the desired biotechnological goal. As appropriate models to perform such an analysis are necessarily non-linear and typically non-convex, finding their global optimum is a challenging task. Canonical modeling techniques, such as Generalized Mass Action (GMA) models based on the power-law formalism, offer a possible solution to this problem because they have a mathematical structure that enables the development of specific algorithms for global optimization. Results: Based on the GMA canonical representation, we have developed in previous works a highly efficient optimization algorithm and a set of related strategies for understanding the evolution of adaptive responses in cellular metabolism. Here, we explore the possibility of recasting kinetic non-linear models into an equivalent GMA model, so that global optimization on the recast GMA model can be performed. With this technique, optimization is greatly facilitated and the results are transposable to the original non-linear problem. This procedure is straightforward for a particular class of non-linear models known as Saturable and Cooperative (SC) models that extend the power-law formalism to deal with saturation and cooperativity. Conclusions: Our results show that recasting non-linear kinetic models into GMA models is indeed an appropriate strategy that helps overcoming some of the numerical difficulties that arise during the global optimization task.

Evolution of Genetic Techniques: Past, Present, and Beyond.

Genetics is the study of heredity, which means the study of genes and factors related to all aspects of genes. The scientific history of genetics began with the works of Gregor Mendel in the mid-19th century. Prior to Mendel, genetics was primarily theoretical whilst, after Mendel, the science of genetics was broadened to include experimental genetics. Developments in all fields of genetics and genetic technology in the first half of the 20th century provided a basis for the later developments. In the second half of the 20th century, the molecular background of genetics has become more understandable. Rapid technological advancements, followed by the completion of Human Genome Project, have contributed a great deal to the knowledge of genetic factors and their impact on human life and diseases. Currently, more than 1800 disease genes have been identified, more than 2000 genetic tests have become available, and in conjunction with this at least 350 biotechnology-based products have been released onto the market. Novel technologies, particularly next generation sequencing, have dramatically accelerated the pace of biological research, while at the same time increasing expectations. In this paper, a brief summary of genetic history with short explanations of most popular genetic techniques is given.

Applying precision feeding techniques in growing-finishing pig operations

The high cost of feed ingredients, the use of non-renewable sources of phosphate and the dramatic increase in the environmental load resulting from the excessive land application of manure are major challenges for the livestock industry. Precision feeding is proposed as an essential approach to improve the utilization of dietary nitrogen, phosphorus and other nutrients and thus reduce feeding costs and nutrient excretion. Precision feeding requires accurate knowledge of the nutritional value of feedstuffs and animal nutrient requirements, the formulation of diets in accordance with environmental constraints, and the gradual adjustment of the dietary nutrient supply to match the requirements of the animals. After the nutritional potential of feed ingredients has been precisely determined and has been improved by the addition of enzymes (e.g. phytases) or feed treatments, the addition of environmental objectives to the traditional feed formulation algorithms can promote the sustainability of the swine industry by reducing nutrient excretion in swine operations with small increases in feeding costs. Increasing the number of feeding phases can also contribute to significant reductions in nutrient excretion and feeding costs. However, the use of precision feeding techniques in which pigs are fed individually with daily tailored diets can further improve the efficiency with which pigs utilize dietary nutrients. Precision feeding involves the use of feeding techniques that allow the provision of the right amount of feed with the right composition at the right time to each pig in the herd. Using this approach, it has been estimated that feeding costs can be reduced by more than 4.6%, and nitrogen and phosphorus excretion can both be reduced by more than 38%. Moreover, the integration of precision feeding techniques into large-group production systems can provide real-time off-farm monitoring of feed and animals for optimal slaughter and production strategies, thus improving the environmental sustainability of pork production, animal well-being and meat-product quality.

Micronization of Pharmaceuticals and Food Ingredients using Supercritical Fluid Techniques

Micronization techniques based on supercritical fluids (SCFs) are promising for the production of particles with controlled size and distribution. The interest of the pharmaceutical field in the development of SCF techniques is increasing due to the need for clean processes, reduced consumption of energy, and to their several possible applications. The food field is still far from the application of SCF micronization techniques, but there is increasing interest mainly for the processing of products with high added value. The aim of this study is to use SCF micronization techniques for the production of particles of pharmaceuticals and food ingredients with controlled particle size and morphology, and to look at their production on semi-industrial scale. The results obtained are also used to understand the processes from the perspective of broader application within the pharmaceutical and food industries. Certain pharmaceuticals, a biopolymer and a food ingredient have been tested using supercritical antisolvent micronization (SAS) or supercritical assisted atomization (SAA) techniques. The reproducibility of the SAS technique has been studied using physically different apparatuses and on both laboratory and semi-industrial scale. Moreover, a comparison between semi-continuous and batch mode has been performed. The behaviour of the system during the SAS process has been observed using a windowed precipitation vessel. The micronized powders have been characterized by particle size and distribution, morphology and crystallinity. Several analyses have been performed to verify if the SCF process modified the structure of the compound or caused degradation or contamination of the product. The different powder morphologies obtained have been linked to the position of the process operating point with respect to the vapour-liquid equilibrium (VLE) of the systems studied, that is, mainly to the position of the mixture critical point (MCP) of the mixture. Spherical micro, submicro- and nanoparticles, expanded microparticles (balloons) and crystals were obtained by SAS. The obtained particles were amorphous or with different degrees of crystallinity and, in some cases, had different pseudo-polymorphic or polymorphic forms. A compound that could not be processed using SAS was micronized by SAA, and amorphous particles were obtained, stable in vials at room temperature. The SCF micronization techniques studied proved to be effective and versatile for the production of particles for several uses. Furthermore, the findings of this study and the acquired knowledge of the proposed processes can allow a more conscious application of SCF techniques to obtain products with the desired characteristics and enable the use of their principles for broader applications.

Selenium content of Finnish oats in 1997-1999 : effect of cultivars and cultivation techniques

Selostus: Suomalaisen kauran seleenipitoisuus vuosina 1997-1999