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Alcohol use disorder is characterised by disrupted reward learning, underpinned by dysfunctional cortico-striatal reward pathways, although relatively little is known about the biology of reward processing in populations who engage in risky alcohol use. Cues that trigger reward anticipation can be categorized according to their learnt valence (i.e., positive vs. negative outcomes) and motivational salience (i.e., incentive vs. neutral cues). Separating EEG signals associated with these dimensions is challenging because of their inherent collinearity, but the recent application of machine learning methods to single EEG trials affords a solution. Here, the Alcohol Use Disorders Identification Test (AUDIT) was used to quantify risky alcohol use, with participants split into high alcohol (HA) (n = 22, mean AUDIT score: 13.82) and low alcohol (LA) (n = 22, mean AUDIT score: 5.77) groups. We applied machine learning multivariate single-trial classification to the electroencephalography (EEG) data collected during reward anticipation. The LA group demonstrated significant valence discrimination in the early stages of reward anticipation within the cue-P3 time window (400-550 ms), whereas the HA group was insensitive to valence within this time window. Notably, the LA, but not the HA group demonstrated a relationship between single-trial variability in the early valence component and reaction times for gain and loss trials. This study evidences disrupted hypoactive valence sensitivity in the HA group, revealing potential neurophysiological markers for risky drinking behaviours which place individuals at-risk of adverse health events. [ABSTRACT FROM AUTHOR]

Background: The Lieber–DeCarli alcoholic liquid diet is a classical method for establishing animal models of alcoholic cardiomyopathy (ACM). No study has reported whether the AIN‐93 diet, which is widely used as a standard diet for both long‐term and short‐term studies with laboratory animals, could be used to construct the ACM animal model. The present study intended to investigate whether the AIN‐93 diet could be used to establish a mouse ACM model. Methods: Twenty‐four C57BL/6 male mice were randomly divided into 4 equally sized groups. In ethanol (EtOH)‐fed groups, mice were fed a 4%‐EtOH (w/v, 28% of total calories) alcoholic liquid diet of Lieber–DeCarli or the AIN‐93 diet for chronic alcohol exposure for 180 days. In control‐fed groups, mice were fed with non‐EtOH liquid diets with the same calories as EtOH‐fed groups. Morphological observations of the hearts and molecular investigation of the brain natriuretic peptide (BNP) were carried out by echocardiography, hematoxylin and eosin (H&E) and immunohistochemistry (IHC) staining, real‐time quantitative polymerase chain reaction (qPCR), and enzyme‐linked immunosorbent assay. Results: Echocardiography showed that mice fed with either the 4%‐EtOH Lieber–DeCarli diet or the 4%‐EtOH AIN‐93 diet had dilated ventricles and poor cardiac function. IHC staining of BNP, qPCR of BNP mRNA, and plasma concentration of BNP showed an up‐regulated expression in mice fed with both the 4%‐EtOH Lieber–DeCarli and 4%‐EtOH AIN‐93 diets. Less fatty liver was also observed in mice fed the AIN‐93 alcoholic diet than those fed the Lieber–DeCarli alcoholic diet. Conclusions: The AIN‐93 alcoholic liquid diet can be used to establish ACM animal models, as with the conventional Lieber–DeCarli alcoholic liquid diet. [ABSTRACT FROM AUTHOR]