Comparison Between Micro- and Macrosurgical Techniques for the Treatment of Localized Gingival Recessions Using Coronally Positioned Flaps and Enamel Matrix Derivative

Background: The aim of this study is to compare the macro- and microsurgery techniques for root coverage using a coronally positioned flap (CPF) associated with enamel matrix derivative (EMD). Methods: Thirty patients were selected for the treatment of localized gingival recessions (GRs) using CPF associated to EMD. Fifteen patients were randomly assigned to the test group (TG), and 15 patients were randomly assigned to the control group (CG). The microsurgical approach was performed in the TG, and the conventional macrosurgical technique was performed in the CG. The clinical parameters evaluated before surgery and after 6 months were GR, probing depth, relative clinical attachment level, width of keratinized tissue (WKT), and thickness of keratinized tissue (TKT). The discomfort evaluation was performed 1 week postoperative. Results: There were no statistically significant differences between groups for all parameters at baseline. At 6 months, there was no statistically significant difference between the techniques in achieving root coverage. The percentage of root coverage was 92% and 83% for TG and CG, respectively. After 6 months, there was a statistically significant increase of WKT and TKT in TG only. Both procedures were well tolerated by all patients. Conclusions: The macro- and microsurgery techniques provided a statistically significant reduction in GR height. After 6 months, there was no statistically significant difference between the techniques regarding root coverage, and the microsurgical technique demonstrated a statistically significant increase in WKT and TKT. J Periodontol 2010;81:1572-1579.

Subsurface drip irrigation: Conventional dripper and new prototype

Subsurface drip irrigation that uses an emitter protection system to avoid its clogging by roots and soil particles may be viable compared to a conventional system. The objective of this work was to evaluate the performance of a system with emitter protection, and to compare the results with a system that uses a conventional emitter for subsurface drip irrigation. In the system with protection an inexpensive materials polyethylene hose, microtube, connector, and a dripper to control the flow rate were used; and, in the conventional system a commercial emitter was used. After 12 months of evaluation, the system with protector showed good performance, with relative average flow rate of 0.97 and 0.98 in pots with and without crop, respectively, showing no clogging problems and lower cost. In conventional system relative flow rate of 0.51 and 0.98 were observed in pots with and without crop, respectively, also clogging degree by roots of 49.22%, and emitters with soil inside was observed. Thus, the use of emitter with protection presented feasibility for subsurface drip irrigation, under conditions used in this research.

Experimental Basis and New Insights for Cell Therapy in Chronic Obstructive Pulmonary Disease

Chronic Obstructive Pulmonary Disease (COPD) can be briefly described as air flow limitation and chronic dyspnea associated to an inflammatory response of the respiratory tract to noxious particles and gases. Its main feature is the obstruction of airflow and consequent chronic dyspnea. Despite recent advances, and the development of new therapeutic, medical and clinical approaches, a curative therapy is yet to be achieved. Therapies involving the use of tissue-specific or donor derived cells present a promising alternative in the treatment of degenerative diseases and injuries. Recent studies demonstrate that mesenchymal stem cells have the capacity to modulate immune responses in acute lung injury and pulmonary fibrosis in animal models, as well as in human patients. Due to these aspects, different groups raised the possibility that the stem cells from different sources, such as those found in bone marrow or adipose tissue, could act preventing the emphysematous lesion progression. In this paper, it is proposed a review of the current state of the art and future perspectives on the use of cell therapy in obstructive lung diseases.

Advances in primary immunodeficiency diseases in Latin America: epidemiology, research, and perspectives

Primary immunodeficiencies (PIDs) are genetic disorders of the immune system comprising many different phenotypes. Although previously considered rare, recent advances in their clinical, epidemiological, and molecular definitions are revealing how much we still need to learn about them. For example, geographical and ethnic variations as well as the impact of certain practices influence their frequency and presentation, making it necessary to consider their study in terms of regions. The Latin American Society for Immunodeficiencies was established as an organization dedicated to provide scientific support for basic and clinical research and to develop tools and educational resources to promote awareness in the medical community. Initiatives such as these are positively influencing the way PIDs are tackled in these countries, as shown by recent reports and publications. This paper provides a historical compilation and a current view of the many issues faced by scientists studying these diseases in these countries, highlighting the diverse scientific contributions and offering a promising perspective for the further developments in this field in Latin America.

Combining meta-learning and search techniques to select parameters for support vector machines

Support Vector Machines (SVMs) have achieved very good performance on different learning problems. However, the success of SVMs depends on the adequate choice of the values of a number of parameters (e.g., the kernel and regularization parameters). In the current work, we propose the combination of meta-learning and search algorithms to deal with the problem of SVM parameter selection. In this combination, given a new problem to be solved, meta-learning is employed to recommend SVM parameter values based on parameter configurations that have been successfully adopted in previous similar problems. The parameter values returned by meta-learning are then used as initial search points by a search technique, which will further explore the parameter space. In this proposal, we envisioned that the initial solutions provided by meta-learning are located in good regions of the search space (i.e. they are closer to optimum solutions). Hence, the search algorithm would need to evaluate a lower number of candidate solutions when looking for an adequate solution. In this work, we investigate the combination of meta-learning with two search algorithms: Particle Swarm Optimization and Tabu Search. The implemented hybrid algorithms were used to select the values of two SVM parameters in the regression domain. These combinations were compared with the use of the search algorithms without meta-learning. The experimental results on a set of 40 regression problems showed that, on average, the proposed hybrid methods obtained lower error rates when compared to their components applied in isolation.