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.

Maternal serum progesterone, estradiol and estriol levels in successful dinoprostone-induced labor

Hormone-mediated quiescence involves the maintenance of a decreased inflammatory responsiveness. However, no study has investigated whether labor induction with prostanoids is associated with changes in the levels of maternal serum hormones. The objective of this study was to determine whether labor induction with dinoprostone is associated with changes in maternal serum progesterone, estradiol, and estriol levels. Blood samples were obtained from 81 pregnant women at term. Sixteen patients had vaginal birth after spontaneous labor, 12 required cesarean section after spontaneous labor and 16 underwent elective cesarean. Thirty-seven patients had labor induction with dinoprostone. Eligible patients received a vaginal insert of dinoprostone (10 mg) and were followed until delivery. Serum progesterone (P4), estradiol (E2) and estriol (E3) levels and changes in P4/E2, P4/E3 and E3/E2 ratios were monitored from admission to immediately before birth, and the association of these measures with the resulting clinical classification outcome (route of delivery and induction responsiveness) was assessed. Progesterone levels decreased from admission to birth in patients who underwent successful labor induction with dinoprostone [vaginal and cesarean birth after induced labor: 23% (P < 0.001) and 18% (P < 0.025) decrease, respectively], but not in those whose induction failed (6.4% decrease, P > 0.05). Estriol and estradiol levels, P4/E2, P4/E3 and E3/E2 ratios did not differ between groups. Successful dinoprostone-induced labor was associated with reduced maternal progesterone levels from induction to birth. While a causal relationship between progesterone decrease and effective dinoprostone-induced labor cannot be established, it is tempting to propose that dinoprostone may contribute to progesterone withdrawal and favor labor induction in humans.

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.

Economic growth, labor and productivity in Brazil and the United States: a comparative analysis

The aim of this paper is to analyze the relation between economic growth and labor market dynamics in Brazil between 1981 and 2009, making a comparison with the United States. Among the findings, one can mention that economic growth in Brazil has been related to a massive incorporation of labor force in labor intensive activities, whereas, in the United States, to a substantial improvement of labor productivity in high-technology activities. Despite the favorable economic context in the 2000s, huge inequalities between these countries have widened since the structure of the Brazilian labor market remained with few or no changes.