Ethanol-induced sensitization depends preferentially on D(1) rather than D(2) dopamine receptors

Behavioral sensitization, defined as a progressive increase in the locomotor stimulant effects elicited by repeated exposure to drugs of abuse, has been used as an animal model for drug craving in humans. The mesoaccumbens dopaminergic system has been proposed to be critically involved in this phenomenon; however, few studies have been designed to systematically investigate the effects of dopaminergic antagonists on development and expression of behavioral sensitization to ethanol in Swiss mice. We first tested the effects of D(1) antagonist SCH-23390 (0-0.03 mg/kg) or D(2) antagonist Sulpiride (0-30 mg/kg) on the locomotor responses to an acute injection of ethanol (2.0 g/kg). Results showed that all tested doses of the antagonists were effective in blocking ethanol`s stimulant effects. In another set of experiments, mice were pretreated intraperitoneally with SCH-23390 (0.01 mg/kg) or Sulpiride (10 mg/kg) 30 min before saline or ethanol injection, for 21 days. Locomotor activity was measured weekly for 20 min. Four days following this pretreatment, all mice were challenged with ethanol. Both antagonists attenuated the development of ethanol sensitization, but only SCH-23390 blocked the expression of ethanol sensitization according to this protocol. When we tested a single dose (30 min before tests) of either antagonist in mice treated chronically with ethanol, both antagonists attenuated ethanol-induced effects. The present findings demonstrate that the concomitant administration of ethanol with D(1) but not D(2) antagonist prevented the expression of ethanol sensitization, suggesting that the neuroadaptations underlying ethanol behavioral sensitization depend preferentially on D(1) receptor actions. (C) 2010 Elsevier Inc. All rights reserved.

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.