Stress Abolishes the Effect of Previous Chronic Ethanol Consumption on Drug Place Preference and on the Mesocorticolimbic Brain Pathway

BackgroundConditioned place preference (CPP) to ethanol (EtOH) is an important addiction-related alteration thought to be mediated by changed neurotransmission in the mesocorticolimbic brain pathway. Stress is a factor of major importance for the initiation, maintenance, and reinstatement of drug abuse and modulates the neurochemical outcomes of drugs. Thus, the aim of this study was to investigate the effects of concomitant exposure to chronic EtOH and stress on CPP to this drug and alterations of dopaminergic and serotonergic neurotransmission in mice.MethodsMale Swiss mice were chronically treated with EtOH via a liquid diet and were exposed to forced swimming stress. After treatment, animals were evaluated for conditioning, extinction, and reinstatement of CPP to EtOH. Also, mice exposed to the same treatment protocol had their prefrontal cortex (PFC), nucleus accumbens (NAc), and amygdala dissected for the quantitation of dopamine, serotonin, and their metabolites content.ResultsData showed that previous chronic exposure to EtOH potentiated EtOH conditioning and increased dopaminergic turnover in PFC. Exposure to stress potentiated EtOH conditioning and decreased dopaminergic turnover in the NAc. However, animals exposed to both chronic EtOH and stress did not display alterations of CPP and showed an elevated content of dopamine in amygdala. No treatment yielded serotonergic changes.ConclusionsThe present study indicates that previous EtOH consumption as well as stress exposure induces increased EtOH conditioning, which can be related to dopaminergic alterations in the PFC or NAc. Interestingly, concomitant exposure to both stimuli abolished each other's effect on conditioning and PFC or NAc alterations. This protective outcome can be related to the dopaminergic increase in the amygdala.

Brazil's new national policy on solid waste: challenges and opportunities

Brazil, one of the world's largest developing countries, has recently introduced a new solid waste management regulatory policy. This new regulatory policy will have implications for a wide variety of stakeholders and sets the stage for opportunities and lessons to be learned. These issues are discussed in this article. © 2013 Springer-Verlag Berlin Heidelberg.

Classification of histological images based on the stationary wavelet transform

Non-Hodgkin lymphomas are of many distinct types, and different classification systems make it difficult to diagnose them correctly. Many of these systems classify lymphomas only based on what they look like under a microscope. In 2008 the World Health Organisation (WHO) introduced the most recent system, which also considers the chromosome features of the lymphoma cells and the presence of certain proteins on their surface. The WHO system is the one that we apply in this work. Herewith we present an automatic method to classify histological images of three types of non-Hodgkin lymphoma. Our method is based on the Stationary Wavelet Transform (SWT), and it consists of three steps: 1) extracting sub-bands from the histological image through SWT, 2) applying Analysis of Variance (ANOVA) to clean noise and select the most relevant information, 3) classifying it by the Support Vector Machine (SVM) algorithm. The kernel types Linear, RBF and Polynomial were evaluated with our method applied to 210 images of lymphoma from the National Institute on Aging. We concluded that the following combination led to the most relevant results: detail sub-band, ANOVA and SVM with Linear and RBF kernels.