Reward devaluation disrupts latent inhibition in fear conditioning

Three experiments explored the link between reward shifts and latent inhibition (LI). Using consummatory procedures, rewards were either downshifted from 32% to 4% sucrose (Experiments 1–2), or upshifted from 4% to 32% sucrose (Experiment 3). In both cases, appropriate unshifted controls were also included. LI was implemented in terms of fear conditioning involving a single tone-shock pairing after extensive tone-only preexposure. Nonpreexposed controls were also included. Experiment 1 demonstrated a typical LI effect (i.e., disruption of fear conditioning after preexposure to the tone) in animals previously exposed only to 4% sucrose. However, the LI effect was eliminated by preexposure to a 32%-to-4% sucrose devaluation. Experiment 2 replicated this effect when the LI protocol was administered immediately after the reward devaluation event. However, LI was restored when preexposure was administered after a 60- min retention interval. Finally, Experiment 3 showed that a reward upshift did not affect LI. These results point to a significant role of negative emotion related to reward devaluation in the enhancement of stimulus processing despite extensive nonreinforced preexposure experience

A case study evaluation of competitors undertaking an antarctic ultra-endurance event: nutrition, hydration and body composition variables

Background: The nutritional demands of ultra-endurance racing are well documented. However, the relationship between nutritional consumption and performance measures are less obvious for athletes competing in Polar conditions. Therefore, the aim of this study was to evaluate dietary intake, hydration status, body composition and performance times throughout an 800-km Antarctic race. Methods: The event organisers declared that 17 competitors would participate in the South Pole race. Of the 17 competitors, pre-race data were collected from 13 participants (12 males and 1 female (M±SD): age: 40.1±8.9 years; weight 83.9±10.3kg; and body fat percentage: 21.9±3.8%). Dietary recall, body composition and urinary osmolarity were assessed pre-race, midway checkpoint and end race. Data were compared on the basis of fast finishers (the Norwegian team (n=3) who won in a record of 14 day) and slower finishers (the remaining teams (n=10) reaching the South Pole between 22 and 28 days). Results: The percentage contribution of macronutrients to daily energy intake for all participants was as follows: carbohydrate (CHO) - 23.7% (221±82 g.day-1), fat = 60.6% (251±127g.day-1) and protein = 15.7% (117±52g.day-1). Energy demands were closer met by faster finishers compared to slower finishers (5,332±469 vs. 3,048±1,140kcal.day-1, p=0.02). Average reduction in body mass throughout the race was 8.3±5.5kg, with an average loss of lean mass of 2.0±4.1kg. There as a significant negative correlation between changes in lean mass and protein intake (p=0.03), and lean mass and energy intake (p=0.03). End-race urinary osmolarity was significantly elevated for faster finishers compared to slower finishers and control volunteers (faster finishers: 933±157mOsmol.L-1; slower finishers: 543±92mOsmol.L-1; control: 515±165mOsmol.L-1, p+0.04). Conclusions: Throughout the race, both groups were subjected to a negative change in energy balance which partly explained reduced body mass. Carbohydrate availability was limited inferring a greater reliance on fat and protein metabolism. Consequently, loss in fat-free mass was more prevalent with insufficient protein and caloric intake, which may relate to performance

Identification of Antifungal Compounds Active against Candida albicans Using an Improved High-Throughput Caenorhabditis elegans Assay

Candida albicans, the most common human pathogenic fungus, can establish a persistent lethal infection in the intestine of the microscopic nematode Caenorhabditis elegans. The C. elegans–C. albicans infection model was previously adapted to screen for antifungal compounds. Modifications to this screen have been made to facilitate a high-throughput assay including co-inoculation of nematodes with C. albicans and instrumentation allowing precise dispensing of worms into assay wells, eliminating two labor-intensive steps. This high-throughput method was utilized to screen a library of 3,228 compounds represented by 1,948 bioactive compounds and 1,280 small molecules derived via diversity-oriented synthesis. Nineteen compounds were identified that conferred an increase in C. elegans survival, including most known antifungal compounds within the chemical library. In addition to seven clinically used antifungal compounds, twelve compounds were identified which are not primarily used as antifungal agents, including three immunosuppressive drugs. This assay also allowed the assessment of the relative minimal inhibitory concentration, the effective concentration in vivo, and the toxicity of the compound in a single assay

Computational Models of Classical Conditioning guest editors’ introduction

In the present special issue, the performance of current computational models of classical conditioning was evaluated under three requirements: (1) Models were to be tested against a list of previously agreed-upon phenomena; (2) the parameters were fixed across simulations; and (3) the simulations used to test the models had to be made available. These requirements resulted in three major products: (a) a list of fundamental classical-conditioning results for which there is a consensus about their reliability; (b) the necessary information to evaluate each of the models on the basis of its ordinal successes in accounting for the experimental data; and (c) a repository of computational models ready to generate simulations. We believe that the contents of this issue represent the 2012 state of the art in computational modeling of classical conditioning and provide a way to find promising avenues for future model development

Measuring participant rurality in Web-based interventions

<p>Abstract</p> <p>Background</p> <p>Web-based health behavior change programs can reach large groups of disparate participants and thus they provide promise of becoming important public health tools. Data on participant rurality can complement other demographic measures to deepen our understanding of the success of these programs. Specifically, analysis of participant rurality can inform recruitment and social marketing efforts, and facilitate the targeting and tailoring of program content. Rurality analysis can also help evaluate the effectiveness of interventions across population groupings.</p> <p>Methods</p> <p>We describe how the RUCAs (Rural-Urban Commuting Area Codes) methodology can be used to examine results from two Randomized Controlled Trials of Web-based tobacco cessation programs: the ChewFree.com project for smokeless tobacco cessation and the Smokers' Health Improvement Program (SHIP) project for smoking cessation.</p> <p>Results</p> <p>Using RUCAs methodology helped to highlight the extent to which both Web-based interventions reached a substantial percentage of rural participants. The ChewFree program was found to have more rural participation which is consistent with the greater prevalence of smokeless tobacco use in rural settings as well as ChewFree's multifaceted recruitment program that specifically targeted rural settings.</p> <p>Conclusion</p> <p>Researchers of Web-based health behavior change programs targeted to the US should routinely include RUCAs as a part of analyzing participant demographics. Researchers in other countries should examine rurality indices germane to their country.</p