Learning about brain physiology and complexity from the study of the epilepsies

The brain is a complex system, which produces emergent properties such as those associated with activity-dependent plasticity in processes of learning and memory. Therefore, understanding the integrated structures and functions of the brain is well beyond the scope of either superficial or extremely reductionistic approaches. Although a combination of zoom-in and zoom-out strategies is desirable when the brain is studied, constructing the appropriate interfaces to connect all levels of analysis is one of the most difficult challenges of contemporary neuroscience. Is it possible to build appropriate models of brain function and dysfunctions with computational tools? Among the best-known brain dysfunctions, epilepsies are neurological syndromes that reach a variety of networks, from widespread anatomical brain circuits to local molecular environments. One logical question would be: are those complex brain networks always producing maladaptive emergent properties compatible with epileptogenic substrates? The present review will deal with this question and will try to answer it by illustrating several points from the literature and from our laboratory data, with examples at the behavioral, electrophysiological, cellular and molecular levels. We conclude that, because the brain is a complex system compatible with the production of emergent properties, including plasticity, its functions should be approached using an integrated view. Concepts such as brain networks, graphics theory, neuroinformatics, and e-neuroscience are discussed as new transdisciplinary approaches dealing with the continuous growth of information about brain physiology and its dysfunctions. The epilepsies are discussed as neurobiological models of complex systems displaying maladaptive plasticity.

Pitfalls in the assessment of murine atherosclerosis

This review provides examples of the fact that different procedures for the measurement of atherosclerosis in mice may lead to interpretation of the extent of atherosclerosis having markedly different biological and clinical significance for humans: 1) aortic cholesterol measurement is highly sensitive for the detection of early and advanced atherosclerosis lesions, but misses the identification of the location and complexity of these lesions that are so critical for humans; 2) the histological analysis of the aortic root lesions in simvastatin-treated and control mice reveals similar lesion morphology in spite of the remarkable simvastatin-induced reduction of the aortic cholesteryl ester content; 3) in histological analyses, chemical fixation and inclusion may extract the tissue fat and also shrink and distort tissue structures. Thus, the method may be less sensitive for the detection of slight differences among the experimental groups, unless a more suitable procedure employing physical fixation with histological sample freezing using optimal cutting temperature and liquid nitrogen is employed. Thus, when measuring experimental atherosclerosis in mice, investigators should be aware of several previously unreported pitfalls regarding the extent, location and complexity of the arterial lesion that may not be suitable for extrapolation to human pathology.

Early detection of metabolic and energy disorders by thermal time series stochastic complexity analysis

Maintenance of thermal homeostasis in rats fed a high-fat diet (HFD) is associated with changes in their thermal balance. The thermodynamic relationship between heat dissipation and energy storage is altered by the ingestion of high-energy diet content. Observation of thermal registers of core temperature behavior, in humans and rodents, permits identification of some characteristics of time series, such as autoreference and stationarity that fit adequately to a stochastic analysis. To identify this change, we used, for the first time, a stochastic autoregressive model, the concepts of which match those associated with physiological systems involved and applied in male HFD rats compared with their appropriate standard food intake age-matched male controls (n=7 per group). By analyzing a recorded temperature time series, we were able to identify when thermal homeostasis would be affected by a new diet. The autoregressive time series model (AR model) was used to predict the occurrence of thermal homeostasis, and this model proved to be very effective in distinguishing such a physiological disorder. Thus, we infer from the results of our study that maximum entropy distribution as a means for stochastic characterization of temperature time series registers may be established as an important and early tool to aid in the diagnosis and prevention of metabolic diseases due to their ability to detect small variations in thermal profile.

Physicochemical analyses indicated to the quality control of royal jelly with honey

Royal jelly (RJ) is used as a revitalizing tonic. In order to avoid rejection to its acid taste, it is added to honey. There are regulations for honey and for royal jelly separately but not for the mixture. The objective of this work is, therefore, to verify if the same methods used for pure honey quality control can be used for honey mixed with royal jelly and also the presence of RJ through 10-HDA determination. The methods used were: moisture, reducing sugars, apparent sucrose, ash, hydroxymethylfurfural, insoluble solids, diastase activity, acidity and 10-HDA. Samples were prepared by adding 0-100% of RJ in honey. The results showed that the ash method was the only suitable one to all the samples. The acidity analysis (direct titration) was suitable to 0-30%RJ samples; the reducing sugar analysis was suitable to 0-20% RJ samples. Concerning moisture analysis the refractometric method is suitable to 0-10% RJ and the Infra Red method is suggested to be used for samples with more than 10% RJ. The methods for diastase activity, HMF, apparent sucrose and insoluble solids were inadequate for all samples with RJ. The presence of RJ in the samples was confirmed by the 10-HDA analyses.

Processing, physicochemical, and sensory analyses of ostrich meat hamburger

The objective of this study was to assess the potential utilization of ostrich meat trimming in hamburger preparation, as well as its physicochemical and sensory characterization. Using ostrich meat trimmings from the legs and neck, four different formulations were prepared with varied amounts of bacon and textured soybean protein. Physical analysis of yield, shrinkage percentage, and water retention capacity and chemical analysis of proximate composition, cholesterol levels, and calories were performed. The formulations underwent sensory analysis by 52 potential ostrich meat consumers, who evaluated tenderness, juiciness, flavor, and purchase intent. The formulations containing textured soybean protein showed the highest yield, lowest shrinkage percentage, and highest water retention capacity. Lipid content varied from 0.58 to 4.99%; protein from 17.08 to 21.37%; ash from 3.00 to 3.62%; moisture from 73.87 to 76.27%; cholesterol from 22.54 to 32.11 mg.100 g-1; and calorie from 87.22 to 163.42 kcal.100 g-1. All formulations showed low cholesterol and calorie levels, even that containing 10% bacon and 3.5% textured soybean protein, which achieved the best scores and acceptance by the panelists.

Non-parametric stability analyses of dough properties in wheat

AbstractLiterature has unveiled that a paper has not been published yet on using non-parametric stability statistics (NPSSs) for evaluating genotypic stability in dough properties of wheat. Accordingly, the effects of genotype (G), environment (E) and GE interaction (GEI) on alveograph parameters, i.e. dough baking strength (W) and its tenacity (P)/extensibility (L), of 18 wheat (T. aestivum L.) genotypes were studied under irrigated field conditions in an 8-year trial (2006-2014) in central Turkey. Furthermore, genotypic stability for W and P/L was determined using 8 NPSSs viz. RM-Rank mean, RSD-Rank’s standard deviation, RS-Rank Sum, TOP-Ranking, Si(1), Si(2), Si(3) and Si(6) rank statistics. The ANOVA revealed that W and P/L were primarily controlled by E, although G and GEI also had significant effects. Among the 8 NPSSs, only RM, RS and TOP statistics were suitable for detecting the genotypes with high stable and bread making quality (e.g. G1 and G17). In conclusion, using RM, RS and TOP statistics is advisable to select for dough quality in wheat under multi-environment trials (METs).