The role of self-reported impulsivity and reward sensitivity versus neurocognitive measures of disinhibition and decision making in the prediction of relapse in pathological gamblers

Background: Disinhibition and decision-making skills play an important role in theories on the cause and outcome of addictive behaviors such as substance use disorders and pathological gambling. In recent studies, both disinhibition and disadvantageous decision-making strategies, as measured by neurocognitive tests, have been found to influence the course of substance use disorders. Research on factors affecting relapse in pathological gambling is scarce. Method: This study investigated the effect of both self-reported impulsivity and reward sensitivity, and neurocognitively assessed disinhibition and decision-making under conflicting contingencies, on relapse in a group of 46 pathological gamblers. Results: Logistic regression analysis indicated that longer duration of the disorder and neurocognitive indicators of disinhibition (Stop Signal Reaction Time) and decision-making (Card Playing Task) were significant predictors of relapse (explaining 53% of the variance in relapse), whereas self-reported impulsivity and reward sensitivity did not significantly predict relapse. Overall classification accuracy was 76%, with a positive classification accuracy of 76% and a negative classification accuracy of 75%. Conclusions: Duration of the disorder and neurocognitive measures of disinhibition and decision-making are powerful predictors of relapse in pathological gambling. The results suggest that endophenotypical neurocognitive characteristics are more promising in the prediction of relapse in pathological gambling than phenotypical personality characteristics. Neurocognitive predictors may be useful to guide treatment planning of follow-up contacts and booster sessions. © 2007 Cambridge University Press

Microbial Communities on Plastic Polymers in the Mediterranean Sea

Plastic particles in the ocean are typically covered with microbial biofilms, but it remains unclear whether distinct microbial communities colonize different polymer types. In this study, we analyzed microbial communities forming biofilms on floating microplastics in a bay of the island of Elba in the Mediterranean Sea. Raman spectroscopy revealed that the plastic particles mainly comprised polyethylene (PE), polypropylene (PP), and polystyrene (PS) of which polyethylene and polypropylene particles were typically brittle and featured cracks. Fluorescence in situ hybridization and imaging by high-resolution microscopy revealed dense microbial biofilms on the polymer surfaces. Amplicon sequencing of the 16S rRNA gene showed that the bacterial communities on all plastic types consisted mainly of the orders Flavobacteriales, Rhodobacterales, Cytophagales, Rickettsiales, Alteromonadales, Chitinophagales, and Oceanospirillales. We found significant differences in the biofilm community composition on PE compared with PP and PS (on OTU and order level), which shows that different microbial communities colonize specific polymer types. Furthermore, the sequencing data also revealed a higher relative abundance of archaeal sequences on PS in comparison with PE or PP. We furthermore found a high occurrence, up to 17% of all sequences, of different hydrocarbon-degrading bacteria on all investigated plastic types. However, their functioning in the plastic-associated biofilm and potential role in plastic degradation needs further assessment

Orbitofrontal and caudate volumes in cannabis users: a multi-site mega-analysis comparing dependent versus non-dependent users.

Cannabis (CB) use and dependence are associated with regionally specific alterations to brain circuitry and substantial psychosocial impairment.The objective of this study was to investigate the association between CB use and dependence, and the volumes of brain regions critically involved in goal-directed learning and behaviour-the orbitofrontal cortex (OFC) and caudate.In the largest multi-site structural imaging study of CB users vs healthy controls (HC), 140 CB users and 121 HC were recruited from four research sites. Group differences in OFC and caudate volumes were investigated between HC and CB users and between 70 dependent (CB-dep) and 50 non-dependent (CB-nondep) users. The relationship between quantity of CB use and age of onset of use and caudate and OFC volumes was explored.CB users (consisting of CB-dep and CB-nondep) did not significantly differ from HC in OFC or caudate volume. CB-dep compared to CB-nondep users exhibited significantly smaller volume in the medial and the lateral OFC. Lateral OFC volume was particularly smaller in CB-dep females, and reduced volume in the CB-dep group was associated with higher monthly cannabis dosage.Smaller medial OFC volume may be driven by CB dependence-related mechanisms, while smaller lateral OFC volume may be due to ongoing exposure to cannabinoid compounds. The results highlight a distinction between cannabis use and dependence and warrant examination of gender-specific effects in studies of CB dependence

Prediction of drop-out and outcome in integrated cognitive behavioral therapy for ADHD and SUD:Results from a randomized clinical trial

Background: Patients with substance use disorder (SUD) or Attention Deficit Hyperactivity Disorder (ADHD) have a high risk of drop out from treatment. Few studies have investigated predictors of therapy drop out and outcome in SUD patients with comorbid ADHD. Recently, integrated cognitive behavioral therapy (CBT/Integrated) was shown to be more effective than standard CBT (CBT/SUD) in the treatment of SUD + ADHD. Objective: To investigate the association of demographic, clinical and neurocognitive variables with drop-out and treatment outcome, and to examine which of these variables are suitable for patient-treatment matching. Methods: We performed an RCT in which 119 patients were allocated to CBT/Integrated (n = 60) or CBT/SUD (n = 59). In addition, 55 patients had dropped out before randomization. Demographic variables, clinical characteristics and measures of cognitive functioning (Stroop, Tower of London (ToL) and Balloon Analogue Risk Task (BART)) were included as predictors. Outcome measures were: early treatment drop-out, ADHD symptom severity, and substance use severity at end of treatment and follow up. Results: Primary substance of abuse (drugs as opposed to alcohol only) and lower accuracy scores on the ToL were significant predictors of early treatment drop-out. Having more depression and anxiety symptoms and using ADHD medication at baseline significantly predicted more ADHD symptoms at end of treatment, and higher accuracy scores on the ToL significantly predicted higher substance use at end of treatment. No significant predictor-by-treatment interactions were found. Conclusion: The results add to the existing realization that also relatively mild cognitive deficits are a risk factor for treatment drop-out in these patients