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Abstract: Objective: The aim of this study was to find a pre-interventional marker with the capacity to predict in-stent restenosis (ISR). Considering the anti-atherosclerotic role of adiponectin (APO), an adipocytokine with anti-inflammatory, anti-proliferative, anti-oxidative and anti-thrombotic properties, low plasma levels of APO might be correlated with the risk of ISR. We investigated the correlations between the plasma levels of APO and two markers of inflammation: lipoprotein associated phospholipase A2 (Lp-PLA2) and myeloperoxidase (MPO). Design and methods: 80 patients with angiographically significant stenosis underwent percutaneous coronary intervention (PCI) with bare metal stent. Plasma APO concentration and plasma Lp-PLA2 and MPO activities were evaluated immediately before and after PCI, then followed-up at 24, 48, 72 h, and at 1, 3, 6 months, respectively. ISR was evaluated at 6 months after stenting by follow-up coronary angiograms, and it was defined as >50% stenosis of the target lesion. Results: ISR was present in 33.75% of patients. Baseline APO plasma concentration, measured before PCI, was lower in ISR patients than those without ISR [3.97 (±1.05) vs 6.65 (±2.95) μg/mL respectively, p <0.001]. The patients with APO values less than 4.9 μg/mL at discharge were more susceptible to develop ISR (odd ratio, 4.27; 95% CI, 1.56–11.72, p <0.001). ISR rate was independent of inflammation markers Lp-PLA2 and MPO baseline values, measured before PCI. Conclusions: The persistence of a low APO plasma level at discharge and 6 months afterwards may be used as a clinically useful marker for ISR prediction in patients undergoing PCI. [Copyright &y& Elsevier]

Background: The prediction error (PE) hypothesized by the temporal difference model has been shown to correlate with the phasic activity of dopamine neurons during reward learning and the blood-oxygen level dependent (BOLD) response during reward and aversive conditioning tasks. We hypothesized that dopamine would modulate the PE related signal in aversive conditioning and that haloperidol would reduce PE related activity, while an acute dose of amphetamine would increase PE related activity in the ventral striatum. Methods: Healthy participants took an acute dose of amphetamine, haloperidol, or placebo. We used functional magnetic resonance imaging (fMRI) to measure the BOLD signal while they carried out an aversive conditioning task, using cutaneous electrical stimulation as the unconditioned stimulus (US) and yellow and blue circles as conditioned stimulus (CS+ and CS−, respectively). Results: Prediction error related BOLD activity was seen only in the ventral striatum in the placebo subjects. The subjects given amphetamine showed a wider network of PE related BOLD activity, including the ventral striatum, globus pallidus, putamen, insula, anterior cingulate, and substantia nigra/ventral tegmental area. Haloperidol subjects did not show PE related activity in any of these regions. Conclusions: Our results provide the first demonstration that the modulation of dopamine transmission affects both the physiological correlates and PE related BOLD activity during aversive learning. [Copyright &y& Elsevier]

Abstract: Manual drawing of regions of interest (ROIs) on brain positron emission tomography (PET) images is labour intensive and subject to intra- and inter-individual variations. To standardize analysis and improve the reproducibility of PET measures, we have developed image analysis software for automated quantification of PET data. The method is based on the individualization of a set of standard ROIs using a magnetic resonance (MR) image co-registered with the PET image. To evaluate the performance of this automated method, the software-based quantification has been compared with conventional manual quantification of PET images obtained using three different PET radiotracers: [11C]-WAY 100635, [11C]-raclopride and [11C]-DASB. Our results show that binding potential estimates obtained using the automated method correlate highly with those obtained by trained raters using manual delineation of ROIs for frontal and temporal cortex, thalamus, and striatum (global intraclass correlation coefficient >0.8). For the three radioligands, the software yields time–activity data that are similar (within 8%) to those obtained by manual quantification, eliminates investigator-dependent variability, considerably shortens the time required for analysis and thus provides an alternative method for accurate quantification of PET data. [Copyright &y& Elsevier]