In Vivo Effects of Bothrops jararaca Venom on Metabolic Profile and on Muscle Protein Metabolism in Rats

This study investigated the in vivo effects of the Bothrops Jararaca venom (BjV) on general metabolic profile and, specifically. oil muscle protein metabolism in rats. The crude venom (0.4 mg/kg body weight, IV) was infused in awake rats, and plasma activity of enzymes and metabolites levels were determined after 1, 2, 3, and 4 hours. BjV increased urea, lactate, and activities of creatine kinase. lactate dehydrogenase. and aspartate aminotransferase after 4 hours. The content of liver glycogen was reduced by BjV. Protein metabolism was evaluated by means of microdialysis technique and in isolated muscles. BjV induced increase in the muscle interstitial-arterial tyrosine concentration difference. indicating a high protein catabolism. The myotoxicity induced by this venom is associated with reduction of protein synthesis and increase in rates of overall proteolysis, which was accompanied by activation of lysosomal and ubiquitin-proteasome systems without changes in protein levels of cathepsins and ubiquitin-protein conjugates.

Neural networks and statistical analysis for classification of corneal videokeratography maps based on Zernike coefficients: a quantitative comparison

PURPOSE: The main goal of this study was to develop and compare two different techniques for classification of specific types of corneal shapes when Zernike coefficients are used as inputs. A feed-forward artificial Neural Network (NN) and discriminant analysis (DA) techniques were used. METHODS: The inputs both for the NN and DA were the first 15 standard Zernike coefficients for 80 previously classified corneal elevation data files from an Eyesys System 2000 Videokeratograph (VK), installed at the Departamento de Oftalmologia of the Escola Paulista de Medicina, São Paulo. The NN had 5 output neurons which were associated with 5 typical corneal shapes: keratoconus, with-the-rule astigmatism, against-the-rule astigmatism, "regular" or "normal" shape and post-PRK. RESULTS: The NN and DA responses were statistically analyzed in terms of precision ([true positive+true negative]/total number of cases). Mean overall results for all cases for the NN and DA techniques were, respectively, 94% and 84.8%. CONCLUSION: Although we used a relatively small database, results obtained in the present study indicate that Zernike polynomials as descriptors of corneal shape may be a reliable parameter as input data for diagnostic automation of VK maps, using either NN or DA.

Metabolic syndrome and dietary components are associated with coronary artery disease risk score in free-living adults: a cross-sectional study

Background: Coronary artery disease (CAD) is among the main causes of death in developed countries, and diet and lifestyle can influence CAD incidence. Objective: To evaluate the association of coronary artery disease risk score with dietary, anthropometric and biochemical components in adults clinically selected for a lifestyle modification program. Methods: 362 adults (96 men, 266 women, 53.9 +/- 9.4 years) fulfilled the inclusion criteria by presenting all the required data. The Framingham score was calculated and the IV Brazilian Guideline on Dyslipidemia and Prevention of Atherosclerosis was adopted for classification of the CAD risks. Anthropometric assessments included waist circumference (WC), body fat and calculated BMI (kg/m(2)) and muscle-mass index (MMI kg/m(2)). Dietary intake was estimated through 24 h dietary recall. Fasting blood was used for biochemical analysis. Metabolic Syndrome (MS) was diagnosed using NCEP-ATPIII (2001) criteria. Logistic regression was used to determine the odds of CAD risks according to the altered components of MS, dietary, anthropometric, and biochemical components. Results: For a sample with a BMI 28.5 +/- 5.0 kg/m(2) the association with lower risk (<10% CAD) were lower age (<60 years old), and plasma values of uric acid. The presence of MS within low, intermediary, and high CAD risk categories was 30.8%, 55.5%, and 69.8%, respectively. The independent risk factors associated with CAD risk score was MS and uric acid, and the protective factors were recommended intake of saturated fat and fiber and muscle mass index. Conclusion: Recommended intake of saturated fat and dietary fiber, together with proper muscle mass, are inversely associated with CAD risk score. On the other hand, the presence of MS and high plasma uric acid are associated with CAD risk score.

Biomarkers of metabolic syndrome and its relationship with the zinc nutritional status in obese women

Introduction: Obesity is a chronic disease that induces risk factors for metabolic syndrome and, is associated with disturbances in the metabolism of the zinc. Therefore, the aim of this study was to investigate the existence of relationship between the biomarkers of metabolic syndrome and the zinc nutricional status in obese women. Method: Seventy-three premenopausal women, aged between 20 and 50 years, were divided into two groups: case group, composed of obese (n = 37) and control group, composed of no obese (n = 36). The assessment of the body mass index and waist circumference were carried out using anthropometric measurements. The plasmatic and erythrocytary zinc were analyzed by method atomic absorption spectrophotometry (lambda=213.9 nm). Results: In the study, body mass index and waist circumference were higher in obese women than control group (p < 0.05). The mean plasmatic zinc was 72.2 +/- 9.0 mu g/dl in obese women and 73.4 +/- 8.5 mu g/dl in control group (p > 0.05). The mean erythrocytary zinc was 36.4 +/- 15.0 mu g/gHb and 45.4 +/- 14.3 mu g/gHb in the obese and controls, respectively (p < 0.05). Regression analysis showed that the body mass index (t=-2.85) and waist circumference (t=-2.37) have a negative relationship only with the erythrocytary zinc (R(2)=0.32, p < 0.05). Conclusions: The study shows that there are alterations in biochemical parameters of zinc in obese women, with low zinc concentrations in erythrocytes. Regression analysis demonstrates that the erythrocytary zinc is influenced by biomarkers of the metabolic syndrome, presenting an inverse relationship with the waist circumference and body mass index.

Artificial Neural Networks and the Study of the Psychoactivity of Cannabinoid Compounds

Cannabinoid compounds have widely been employed because of its medicinal and psychotropic properties. These compounds are isolated from Cannabis sativa (or marijuana) and are used in several medical treatments, such as glaucoma, nausea associated to chemotherapy, pain and many other situations. More recently, its use as appetite stimulant has been indicated in patients with cachexia or AIDS. In this work, the influence of several molecular descriptors on the psychoactivity of 50 cannabinoid compounds is analyzed aiming one obtain a model able to predict the psychoactivity of new cannabinoids. For this purpose, initially, the selection of descriptors was carried out using the Fisher`s weight, the correlation matrix among the calculated variables and principal component analysis. From these analyses, the following descriptors have been considered more relevant: E(LUMO) (energy of the lowest unoccupied molecular orbital), Log P (logarithm of the partition coefficient), VC4 (volume of the substituent at the C4 position) and LP1 (Lovasz-Pelikan index, a molecular branching index). To follow, two neural network models were used to construct a more adequate model for classifying new cannabinoid compounds. The first model employed was multi-layer perceptrons, with algorithm back-propagation, and the second model used was the Kohonen network. The results obtained from both networks were compared and showed that both techniques presented a high percentage of correctness to discriminate psychoactive and psychoinactive compounds. However, the Kohonen network was superior to multi-layer perceptrons.

Characterization of subgraph relationships and distribution in complex networks

A network can be analyzed at different topological scales, ranging from single nodes to motifs, communities, up to the complete structure. We propose a novel approach which extends from single nodes to the whole network level by considering non-overlapping subgraphs (i.e. connected components) and their interrelationships and distribution through the network. Though such subgraphs can be completely general, our methodology focuses on the cases in which the nodes of these subgraphs share some special feature, such as being critical for the proper operation of the network. The methodology of subgraph characterization involves two main aspects: (i) the generation of histograms of subgraph sizes and distances between subgraphs and (ii) a merging algorithm, developed to assess the relevance of nodes outside subgraphs by progressively merging subgraphs until the whole network is covered. The latter procedure complements the histograms by taking into account the nodes lying between subgraphs, as well as the relevance of these nodes to the overall subgraph interconnectivity. Experiments were carried out using four types of network models and five instances of real-world networks, in order to illustrate how subgraph characterization can help complementing complex network-based studies.

Modularity and robustness of bone networks

Cortical bones, essential for mechanical support and structure in many animals, involve a large number of canals organized in intricate fashion. By using state-of-the art image analysis and computer graphics, the 3D reconstruction of a whole bone (phalange) of a young chicken was obtained and represented in terms of a complex network where each canal was associated to an edge and every confluence of three or more canals yielded a respective node. The representation of the bone canal structure as a complex network has allowed several methods to be applied in order to characterize and analyze the canal system organization and the robustness. First, the distribution of the node degrees (i.e. the number of canals connected to each node) confirmed previous indications that bone canal networks follow a power law, and therefore present some highly connected nodes (hubs). The bone network was also found to be partitioned into communities or modules, i.e. groups of nodes which are more intensely connected to one another than with the rest of the network. We verified that each community exhibited distinct topological properties that are possibly linked with their specific function. In order to better understand the organization of the bone network, its resilience to two types of failures (random attack and cascaded failures) was also quantified comparatively to randomized and regular counterparts. The results indicate that the modular structure improves the robustness of the bone network when compared to a regular network with the same average degree and number of nodes. The effects of disease processes (e. g., osteoporosis) and mutations in genes (e.g., BMP4) that occur at the molecular level can now be investigated at the mesoscopic level by using network based approaches.

Complex networks: the key to systems biology

Though introduced recently, complex networks research has grown steadily because of its potential to represent, characterize and model a wide range of intricate natural systems and phenomena. Because of the intrinsic complexity and systemic organization of life, complex networks provide a specially promising framework for systems biology investigation. The current article is an up-to-date review of the major developments related to the application of complex networks in biology, with special attention focused on the more recent literature. The main concepts and models of complex networks are presented and illustrated in an accessible fashion. Three main types of networks are covered: transcriptional regulatory networks, protein-protein interaction networks and metabolic networks. The key role of complex networks for systems biology is extensively illustrated by several of the papers reviewed.

The impact of obstructive sleep apnea on metabolic and inflammatory markers in consecutive patients with metabolic syndrome

Background: Obstructive Sleep Apnea (OSA) is tightly linked to some components of Metabolic Syndrome (MetS). However, most of the evidence evaluated individual components of the MetS or patients with a diagnosis of OSA that were referred for sleep studies due to sleep complaints. Therefore, it is not clear whether OSA exacerbates the metabolic abnormalities in a representative sample of patients with MetS. Methodology/Principal Findings: We studied 152 consecutive patients (age 48 +/- 9 years, body mass index 32.3 +/- 3.4 Kg/m(2)) newly diagnosed with MetS (Adult Treatment Panel III). All participants underwent standard polysomnography irrespective of sleep complaints, and laboratory measurements (glucose, lipid profile, uric acid and C-reactive protein). The prevalence of OSA (apnea-hypopnea index >= 15 events per hour of sleep) was 60.5%. Patients with OSA exhibited significantly higher levels of blood pressure, glucose, triglycerides, cholesterol, LDL, cholesterol/HDL ratio, triglycerides/HDL ratio, uric acid and C-reactive protein than patients without OSA. OSA was independently associated with 2 MetS criteria: triglycerides: OR: 3.26 (1.47-7.21) and glucose: OR: 2.31 (1.12-4.80). OSA was also independently associated with increased cholesterol/HDL ratio: OR: 2.38 (1.08-5.24), uric acid: OR: 4.19 (1.70-10.35) and C-reactive protein: OR: 6.10 (2.64-14.11). Indices of sleep apnea severity, apnea-hypopnea index and minimum oxygen saturation, were independently associated with increased levels of triglycerides, glucose as well as cholesterol/HDL ratio, uric acid and C-reactive protein. Excessive daytime sleepiness had no effect on the metabolic and inflammatory parameters. Conclusions/Significance: Unrecognized OSA is common in consecutive patients with MetS. OSA may contribute to metabolic dysregulation and systemic inflammation in patients with MetS, regardless of symptoms of daytime sleepiness.

Construct and Compare Gene Coexpression Networks with DAPfinder and DAPview

Background: DAPfinder and DAPview are novel BRB-ArrayTools plug-ins to construct gene coexpression networks and identify significant differences in pairwise gene-gene coexpression between two phenotypes. Results: Each significant difference in gene-gene association represents a Differentially Associated Pair (DAP). Our tools include several choices of filtering methods, gene-gene association metrics, statistical testing methods and multiple comparison adjustments. Network results are easily displayed in Cytoscape. Analyses of glioma experiments and microarray simulations demonstrate the utility of these tools. Conclusions: DAPfinder is a new friendly-user tool for reconstruction and comparison of biological networks.

Hepatic Steatosis, Obesity, and the Metabolic Syndrome Are Independently and Additively Associated With Increased Systemic Inflammation

Objective-The goal of this study was to assess the independent and collective associations of hepatic steatosis, obesity, and the metabolic syndrome with elevated high-sensitivity C-reactive protein (hs-CRP) levels. Methods and Results-We evaluated 2388 individuals without clinical cardiovascular disease between December 2004 and December 2006. Hepatic steatosis was diagnosed by ultrasound, and the metabolic syndrome was defined using National Heart, Lung, and Blood Institute criteria. The cut point of >= 3 mg/L was used to define high hs-CRP. Multivariate logistic regression was used to assess the independent and collective associations of hepatic steatosis, obesity, and the metabolic syndrome with high hs-CRP. Steatosis was detected in 32% of participants, 23% met criteria for metabolic syndrome, and 17% were obese. After multivariate regression, hepatic steatosis (odds ratio [OR] 2.07; 95% CI 1.68 to 2.56), obesity (OR 3.00; 95% CI 2.39 to 3.80), and the metabolic syndrome (2.39; 95% CI 1.88 to 3.04) were all independently associated with high hs-CRP. Combinations of these factors were associated with an additive increase in the odds of high hs-CRP, with individuals with 1, 2, and 3 factors having ORs for high hs-CRP of 1.92 (1.49 to 2.48), 3.38 (2.50 to 4.57), and 4.53 (3.23 to 6.35), respectively. Conclusion-Hepatic steatosis, obesity, and the metabolic syndrome are independently and additively associated with increased odds of high hs-CRP levels. (Arterioscler Thromb Vasc Biol. 2011; 31: 1927-1932.)

Effects of Perilipin (PLIN) Gene Variation on Metabolic Syndrome Risk and Weight Loss in Obese Children and Adolescents

Context: Genetic polymorphisms at the perilipin (PLIN) locus have been investigated for their potential utility as markers for obesity and metabolic syndrome (MS). We examined in obese children and adolescents (OCA) aged 7-14 yr the association of single-nucleotide polymorphisms (SNP) at the PLIN locus with anthropometric, metabolic traits, and weight loss after 20-wk multi-disciplinary behavioral and nutritional treatment without medication. Design: A total of 234 OCA [body mass index (BMI = 30.4 +/- 4.4 kg/m(2); BMI Z-score = 2.31 +/- 0.4) were evaluated at baseline and after intervention. We genotyped four SNPs (PLIN1 6209T -> C, PLIN4 11482G -> A, PLIN5 13041A -> G, and PLIN6 14995A -> T). Results: Allele frequencies were similar to other populations, PLIN1 and PLIN4 were in linkage disequilibrium (D` = 0.999; P < 0.001). At baseline, no anthropometric differences were observed, but minor allele A at PLIN4 was associated with higher triglycerides (111 +/- 49 vs. 94 +/- 42 mg/dl; P = 0.003), lower high-density lipoprotein cholesterol (40 +/- 9 vs. 44 +/- 10 mg/dl; P = 0.003) and higher homeostasis model assessment for insulin resistance (4.0 +/- 2.3 vs. 3.5 +/- 2.1; P +/- 0.015). Minor allele A at PLIN4 was associated with MS risk (age and sex adjusted) hazard ratio 2.4 (95% confidence interval = 1.1-4.9) for genotype GA and 3.5 (95% confidence interval = 1.2-9.9) for AA. After intervention, subjects carrying minor allele T at PLIN6 had increased weight loss (3.3 +/- 3.7 vs. 1.9 +/- 3.4 kg; P = 0.002) and increased loss of the BMI Z-score (0.23 +/- 0.18 vs. 0.18 +/- 0.15; P +/- 0.003). Due to group size, risk of by-chance findings cannot be excluded. Conclusion: The minor A allele at PLIN4 was associated with higher risk of MS at baseline, whereas the PLIN6 SNP was associated with better weight loss, suggesting that these polymorphisms may predict outcome strategies based on multidisciplinary treatment for OCA. (J Clin Endocrinol Metab 93: 4933-4940, 2008)

Upper trunk fat assessment and its relationship with metabolic and biochemical variables and body fat in polycystic ovary syndrome

Background: Fat accumulation in the upper region of the body is common in polycystic ovary syndrome (PCOS) and is associated with metabolic complications. The present study aimed to assess the relationship between trunk circumference, metabolic indicators, and abdominal and visceral fat in obese PCOS women. Methods: The weight, fat mass, and subcutaneous arm fat (SAF) of 30 obese PCOS women and 15 healthy controls matched for age and body mass index were evaluated by bioelectrical impedance analysis. Trunk (TrC), neck (NC) and hip circumferences were measured, and the trunk/hip (Tr/H) ratio was determined. Total abdominal fat (TAF), visceral fat (VF) and trunk fat (TrF) were determined by computed tomography. Biochemical evaluation included glycaemia, insulinaemia, testosterone and lipid profile, insulin resistance (IR) was assessed by the QUICKI index. Results: In the PCOS group, there were positive correlations between NC and TAF (r = 0.49, P < 0.0006), TrC and VF (r = 0.62, P = 0.01), and NC and VF (r = 0.70, P < 0.0002). There was good correlation between TrC and TrF (r = 0.69, P = 0.003). TrF correlated with triglycerides levels positively (r = 0.44, P = 0.02). Women with PCOS and IR had a larger quantity of VF and TrF, but a smaller amount of SAF. Within the PCOS group, women with Tr/H ratio above the median had higher basal insulin levels and lower QUICKI indices compared to women presenting a Tr/H ratio below the median. Conclusions: TrC is associated with important metabolic variables in PCOS, proving to be a valuable and innovative tool for assessment of body adiposity distribution in obese PCOS women.

The modularity of seed dispersal: differences in structure and robustness between bat- and bird-fruit networks

In networks of plant-animal mutualisms, different animal groups interact preferentially with different plants, thus forming distinct modules responsible for different parts of the service. However, what we currently know about seed dispersal networks is based only on birds. Therefore, we wished to fill this gap by studying bat-fruit networks and testing how they differ from bird-fruit networks. As dietary overlap of Neotropical bats and birds is low, they should form distinct mutualistic modules within local networks. Furthermore, since frugivory evolved only once among Neotropical bats, but several times independently among Neotropical birds, greater dietary overlap is expected among bats, and thus connectance and nestedness should be higher in bat-fruit networks. If bat-fruit networks have higher nestedness and connectance, they should be more robust to extinctions. We analyzed 1 mixed network of both bats and birds and 20 networks that consisted exclusively of either bats (11) or birds (9). As expected, the structure of the mixed network was both modular (M = 0.45) and nested (NODF = 0.31); one module contained only birds and two only bats. In 20 datasets with only one disperser group, bat-fruit networks (NODF = 0.53 +/- A 0.09, C = 0.30 +/- A 0.11) were more nested and had a higher connectance than bird-fruit networks (NODF = 0.42 +/- A 0.07, C = 0.22 +/- A 0.09). Unexpectedly, robustness to extinction of animal species was higher in bird-fruit networks (R = 0.60 +/- A 0.13) than in bat-fruit networks (R = 0.54 +/- A 0.09), and differences were explained mainly by species richness. These findings suggest that a modular structure also occurs in seed dispersal networks, similar to pollination networks. The higher nestedness and connectance observed in bat-fruit networks compared with bird-fruit networks may be explained by the monophyletic evolution of frugivory in Neotropical bats, among which the diets of specialists seem to have evolved from the pool of fruits consumed by generalists.

Mecanismos de ação de compostos bioativos dos alimentos no contexto de processos inflamatórios relacionados à obesidade

É indiscutível o papel da dieta e dos alimentos na manutenção da saúde e na redução do risco de DCNT. Estudos epidemiológicos mostram que o aumento do consumo de alimentos de origem vegetal influencia positivamente a saúde, enquanto estudos in vitro e in vivo em modelo animal elucidam os mecanismos pelos quais compostos bioativos não nutrientes, presentes nos alimentos, atuam na manutenção da saúde e na redução do risco de doenças. A modulação da expressão de genes que codificam proteínas envolvidas em vias de sinalização celular ativadas em DCNT é um dos mecanismos de ação dos compostos bioativos, sugerindo que estes possam ser essenciais à manutenção da saúde. A biodisponibilidade dos compostos bioativos de alimentos, as suas rotas metabólicas e o modo de ação de seus metabólitos são importantes fatores no seu efeito nas DCNT. Todos esses aspectos são temas de investigações recentes, cujos resultados contribuem para a compreensão da ocorrência e desenvolvimento das DCNT e da sua relação com a dieta. Essa revisão visou discutir alguns dos mecanismos envolvidos na resposta inflamatória induzida pela obesidade, apresentar os compostos bioativos de alimentos que modulam essa resposta inflamatória e sua relação com o metabolismo desses compostos.