Psychometric evaluation of the Disordered Eating Attitude Scale (DEAS). English version

Eating attitudes are defined as beliefs, thoughts, feelings, behaviors and relationship with food They could influence people`s food choices and their health status Objective This study aimed to adapt from Portuguese to English the Disordered Eating Attitude Scale (DEAS) and evaluate its validity and reliability. The original scale in Portuguese was translated and adapted into English and was applied to female university students of University of Minnesota USA (n = 224). Internal consistency was determined (Cronbach`s Alpha). Convergent validity was assessed by correlations between Eating Attitude Test-26 (EAT-26) and Restrain Scale (RS). Reliability was evaluated applying twice the scale to a sub-sample (n = 30). The scale was back translated into Portuguese and compared with the original version and discrepancies were not found. The internal consistency was .76 The DEAS total score was significantly associated with EAT-26 (r = 0.65) and RS (r = 0 69) scores The correlation between test-retest was r = 09 The English version of DEAS showed appropriate internal consistency, convergent validity and test-retest reliability and will be useful to assess eating attitudes in different population groups in English spoken countries. (C) 2010 Elsevier Ltd. All rights reserved

Negative anticipatory contrast: Does it involve anticipation of an impending reward?

Negative anticipatory contrast (NAC) corresponds to the suppression in consumption of a first rewarding substance (e.g., saccharin 0.15%) when it is followed daily by a second preferred substance (e.g., sucrose 32%). The NAC has been interpreted as resulting from anticipation of the impending preferred reward and its comparison with the currently available first reward [Flaherty, CF., Rowan, G.A., 1985. Anticipatory contrast: within-subjects analysis. Anim. Learn. Behav. 13, 2-5]. In this context, one should expect that devaluation of the preferred substance after the establishment of the NAC would either reduce or abolish the contrast effect. However, contrary to this prediction, the results of the present study show that the NAC is insensitive to devaluation of the second, preferred, substance. This allows one to question that interpretation. The results reported in this study support the view that the NAC effect is controlled by memory of the relative value of the first solution, which is updated daily by means of both a gustatory and/or post-ingestive comparison of the first and second solutions, and memory of past pairings. (C) 2010 Elsevier B.V. All rights reserved.

Prolonged consumption of soy or fish-oil-enriched diets differentially affects the pattern of hypothalamic neuronal activation induced by refeeding in rats

We used c-Fos immunoreactivity to estimate neuronal activation in hypothalamic feeding-regulatory areas of 3-month-old rats fed control or oil-enriched diets (soy or fish) since weaning. While no diet effect was observed in c-Fos immunoreactivity of 24-h fasted animals, the acute response to refeeding was modified by both hyperlipidic diets but with different patterns. Upon refeeding, control-diet rats had significantly increased c-Fos immunoreactivity only in the paraventricular hypothalamic nucleus (PVH, 142%). In soy-diet rats, refeeding with the soy diet increased c-Fos immunoreactivity in dorsomedial hypothalamic nucleus (DMH, 271%) and lateral hypothalamic area (LH, 303%). Refeeding fish-diet rats with the fish diet increased c-Fos immunoreactivity in PVH (161%), DMH (177%), VMH (81%), and ARC (127%). Compared to the fish-diet, c-Fos immunoreactivity was increased in LH by the soy-diet while it was decreased in ventromedial hypothalamic nucleus (VMH) and arcuate hypothalamic nucleus (ARC). Based on the known roles of the activated nuclei, it is suggested that, unlike the fish-diet, the soy-diet induced a potentially obesogenic profile, with high LH and low VMH/PVH activation after refeeding.

Metabolic recovery of adipose tissue is associated with improvement in insulin resistance in a model of experimental diabetes

Obesity and insulin resistance are highly correlated with metabolic disturbances. Both the excess and lack of adipose tissue can lead to severe insulin resistance and diabetes. Adipose tissue plays an active role in energy homeostasis, hormone secretion, and other proteins that affect insulin sensitivity, appetite, energy balance, and lipid metabolism. Rats with streptozotocin-induced diabetes during the neonatal period develop the classic diabetic picture of hyperglycemia, hypoinsulinemia, and insulin resistance in adulthood. Low body weight and reduced epididymal (EP) fit mass were also seen in this model. The am) of this study was to investigate the glucose homeostasis and metabolic repercussions on the adipose tissue following chronic treatment with antidiabetic drugs in these animals. In the 4th week post birth, diabetic animals started an 8-week treatment with pioglitazone, metformin, or insulin.

RUMOR PROCESSES ON N

We study four discrete-time stochastic systems on N, modeling processes of rumor spreading. The involved individuals can either have an active or a passive role, speaking up or asking for the rumor. The appetite for spreading or hearing the rumor is represented by a set of random variables whose distributions may depend on the individuals. Our goal is to understand-based on the distribution of the random variables-whether the probability of having an infinite set of individuals knowing the rumor is positive or not.

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.