Do patients with osteogenesis imperfecta need individualized nutritional support?

Objective: Information regarding nutrition and body composition in patients diagnosed with osteogenesis imperfecta (OI) is scarce. In the present study, nutritional status, bone mineral density, and biochemical parameters of subjects with Of were evaluated. Methods: Patients with type I OI (n = 13) and type III OI (n = 13) and healthy controls (n = 8) were selected. Nutritional status and bone mineral density were assessed by a 3-d food diary and dual-energy X-ray absorptiometry at the lumbar spine, respectively. Body mass index, serum albumin, calcium, creatinine, cross-linked C-telopeptide, parathyroid hormone, and 25-hydroxivitamin D-3 were also evaluated. Results: Patients with OI had lower bone mineral density (P < 0.05 versus controls). Patients with type III OI had the highest body mass index (P < 0.05 versus patients with type I OI and controls) and the lowest lean body mass (P < 0.05 versus patients with type I OI and controls). In patients with OI, the number of fractures was positively correlated with body mass index (r = 0.581, P = 0.002) and the percentage of body fat (r = 0.451, P = 0.027) and negatively correlated to lean body mass (r = -0.523, P = 0.009). Even when taking dietary supplements, 58% and 12% of subjects with OI did not achieve the calcium and vitamin D recommendations, respectively. Conclusions: Body composition is a risk factor for bone fractures in subjects with OI. Individualized nutritional support is recommended not only to improve body composition but also to potentiate pharmacologic and physical therapies. (C) 2012 Elsevier Inc. All rights reserved.

Effect of treatment delay on disease severity and need for resuscitation in porcine fecal peritonitis

Objective: Early treatment in sepsis may improve outcome. The aim of this study was to evaluate how the delay in starting resuscitation influences the severity of sepsis and the treatment needed to achieve hemodynamic stability. Design: Prospective, randomized, controlled experimental study. Setting: Experimental laboratory in a university hospital. Subjects: Thirty-two anesthetized and mechanically ventilated pigs. Interventions: Pigs were randomly assigned (n = 8 per group) to a nonseptic control group or one of three groups in which fecal peritonitis (peritoneal instillation of 2 g/kg autologous feces) was induced, and a 48-hr period of protocolized resuscitation started 6 (Delta T-6 hrs), 12 (Delta T-12 hrs), or 24 (Delta T-24 hrs) hrs later. The aim of this study was to evaluate the impact of delays in resuscitation on disease severity, need for resuscitation, and the development of sepsis-associated organ and mitochondrial dysfunction. Measurements and Main Results: Any delay in starting resuscitation was associated with progressive signs of hypovolemia and increased plasma levels of interleukin-6 and tumor necrosis factor-alpha prior to resuscitation. Delaying resuscitation increased cumulative net fluid balances (2.1 +/- 0.5 mL/kg/hr, 2.8 +/- 0.7 mL/kg/hr, and 3.2 +/- 1.5 mL/kg/hr, respectively, for groups.T-6 hrs, Delta T-12 hrs, and.T-24 hrs; p < .01) and norepinephrine requirements during the 48-hr resuscitation protocol (0.02 +/- 0.04 mu g/kg/min, 0.06 +/- 0.09 mu g/kg/min, and 0.13 +/- 0.15 mu g/kg/min; p = .059), decreased maximal brain mitochondrial complex II respiration (p = .048), and tended to increase mortality (p = .08). Muscle tissue adenosine triphosphate decreased in all groups (p < .01), with lowest values at the end in groups Delta T-12 hrs and.T-24 hrs. Conclusions: Increasing the delay between sepsis initiation and resuscitation increases disease severity, need for resuscitation, and sepsis-associated brain mitochondrial dysfunction. Our results support the concept of a critical window of opportunity in sepsis resuscitation. (Crit Care Med 2012; 40:2841-2849)

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.

The need of a weight management control program in judo: a proposal based on the successful case of wrestling

Judo competitions are divided into weight classes. However, most athletes reduce their body weight in a few days before competition in order to obtain a competitive advantage over lighter opponents. To achieve fast weight reduction, athletes use a number of aggressive nutritional strategies so many of them place themselves at a high health-injury risk. In collegiate wrestling, a similar problem has been observed and three wrestlers died in 1997 due to rapid weight loss regimes. After these deaths, the National Collegiate Athletic Association had implemented a successful weight management program which was proven to improve weight management behavior. No similar program has ever been discussed by judo federations even though judo competitors present a comparable inappropriate pattern of weight control. In view of this, the basis for a weight control program is provided in this manuscript, as follows: competition should begin within 1 hour after weigh-in, at the latest; each athlete is allowed to be weighed-in only once; rapid weight loss as well as artificial rehydration (i.e., saline infusion) methods are prohibited during the entire competition day; athletes should pass the hydration test to get their weigh-in validated; an individual minimum competitive weight (male athletes competing at no less than 7% and females at no less than 12% of body fat) should be determined at the beginning of each season; athletes are not allowed to compete in any weight class that requires weight reductions greater than 1.5% of body weight per week. In parallel, educational programs should aim at increasing the athletes', coaches' and parents' awareness about the risks of aggressive nutritional strategies as well as healthier ways to properly manage body weight.

Computational framework to support integration of biomolecular and clinical data within a translational approach

Background The use of the knowledge produced by sciences to promote human health is the main goal of translational medicine. To make it feasible we need computational methods to handle the large amount of information that arises from bench to bedside and to deal with its heterogeneity. A computational challenge that must be faced is to promote the integration of clinical, socio-demographic and biological data. In this effort, ontologies play an essential role as a powerful artifact for knowledge representation. Chado is a modular ontology-oriented database model that gained popularity due to its robustness and flexibility as a generic platform to store biological data; however it lacks supporting representation of clinical and socio-demographic information. Results We have implemented an extension of Chado – the Clinical Module - to allow the representation of this kind of information. Our approach consists of a framework for data integration through the use of a common reference ontology. The design of this framework has four levels: data level, to store the data; semantic level, to integrate and standardize the data by the use of ontologies; application level, to manage clinical databases, ontologies and data integration process; and web interface level, to allow interaction between the user and the system. The clinical module was built based on the Entity-Attribute-Value (EAV) model. We also proposed a methodology to migrate data from legacy clinical databases to the integrative framework. A Chado instance was initialized using a relational database management system. The Clinical Module was implemented and the framework was loaded using data from a factual clinical research database. Clinical and demographic data as well as biomaterial data were obtained from patients with tumors of head and neck. We implemented the IPTrans tool that is a complete environment for data migration, which comprises: the construction of a model to describe the legacy clinical data, based on an ontology; the Extraction, Transformation and Load (ETL) process to extract the data from the source clinical database and load it in the Clinical Module of Chado; the development of a web tool and a Bridge Layer to adapt the web tool to Chado, as well as other applications. Conclusions Open-source computational solutions currently available for translational science does not have a model to represent biomolecular information and also are not integrated with the existing bioinformatics tools. On the other hand, existing genomic data models do not represent clinical patient data. A framework was developed to support translational research by integrating biomolecular information coming from different “omics” technologies with patient’s clinical and socio-demographic data. This framework should present some features: flexibility, compression and robustness. The experiments accomplished from a use case demonstrated that the proposed system meets requirements of flexibility and robustness, leading to the desired integration. The Clinical Module can be accessed in http://dcm.ffclrp.usp.br/caib/pg=iptrans webcite.