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Importance: The goal of schizophrenia treatment has shifted from symptom reduction and relapse prevention to functional recovery; however, recovery rates remain low. Prospective identification of variables associated with real-life functioning domains is essential for personalized and integrated treatment programs. Objective: To assess whether baseline illness-related variables, personal resources, and context-related factors are associated with work skills, interpersonal relationships, and everyday life skills at 4-year follow-up. Design, Setting, and Participants: This multicenter prospective cohort study was conducted across 24 Italian university psychiatric clinics or mental health departments in which 921 patients enrolled in a cross-sectional study were contacted after 4 years for reassessment. Recruitment of community-dwelling, clinically stable persons with schizophrenia was conducted from March 2016 to December 2017, and data were analyzed from January to May 2020. Main Outcomes and Measures: Psychopathology, social and nonsocial cognition, functional capacity, personal resources, and context-related factors were assessed, with real-life functioning as the main outcome. Structural equation modeling, multiple regression analyses, and latent change score modeling were used to identify variables that were associated with real-life functioning domains at follow-up and with changes from baseline in these domains. Results: In total, 618 participants (427 male [69.1%]; mean [SD] age, 45.1 [10.5] years) were included. Five baseline variables were directly associated with real-life functioning at follow-up: neurocognition with everyday life (β, 0.274; 95% CI, 0.207-0.341; P

BackgroundThe increased use of the MATRICS Consensus Cognitive Battery (MCCB) to investigate cognitive dysfunctions in schizophrenia fostered interest in its sensitivity in the context of family studies. As various measures of the same cognitive domains may have different power to distinguish between unaffected relatives of patients and controls, the relative sensitivity of MCCB tests for relative–control differences has to be established. We compared MCCB scores of 852 outpatients with schizophrenia (SCZ) with those of 342 unaffected relatives (REL) and a normative Italian sample of 774 healthy subjects (HCS). We examined familial aggregation of cognitive impairment by investigating within-family prediction of MCCB scores based on probands’ scores.MethodsMultivariate analysis of variance was used to analyze group differences in adjusted MCCB scores. Weighted least-squares analysis was used to investigate whether probands’ MCCB scores predicted REL neurocognitive performance.ResultsSCZ were significantly impaired on all MCCB domains. REL had intermediate scores between SCZ and HCS, showing a similar pattern of impairment, except for social cognition. Proband's scores significantly predicted REL MCCB scores on all domains except for visual learning.ConclusionsIn a large sample of stable patients with schizophrenia, living in the community, and in their unaffected relatives, MCCB demonstrated sensitivity to cognitive deficits in both groups. Our findings of significant within-family prediction of MCCB scores might reflect disease-related genetic or environmental factors.

Self-reported 'personal recovery' and clinical recovery in schizophrenia (SRPR and CR. respectively) reflect different perspectives in schizophrenia outcome, not necessarily concordant with each other and usually representing the consumer's or the therapist's point of view. By means of a cluster analysis on SRPR related variables, we identified three dusters. The first and third cluster included subjects with the best and the poorest clinical outcome respectively. The second cluster was characterized by better insight, higher levels of depression and stigma, lowest self-esteem and personal strength, and highest emotional coping. The first duster showed positive features of recovery, while the third duster showed negative features. The second cluster, with the most positive insight, showed a more complex pattern, a some-what 'paradoxical' mixture of positive and negative personal and clinical features of recovery. The present results suggest the need for a characterization of persons with schizophrenia along SRPR and CR dimensions to design individualized and integrated treatment programs aimed to improve insight and coping strategies, reduce stigma and shape recovery styles. (C) 2017 Elsevier B.V. All rights reserved.

Background Next-Generation-Sequencing (NGS) enables detection of microorganisms present in biological and other matrices of various origin and nature, allowing not only the identification of known phyla and strains but also the discovery of novel ones. The large amount of metagenomic shotgun data produced by NGS require comprehensive and user-friendly pipelines for data analysis, that speed up the bioinformatics steps, relieving the users from the need to manually perform complex and time-consuming tasks. Results We describe here HOME-BIO (sHOtgun MEtagenomic analysis of BIOlogical entities), an exhaustive pipeline for metagenomics data analysis, comprising three independent analytical modules designed for an inclusive analysis of large NGS datasets. Conclusions HOME-BIO is a powerful and easy-to-use tool that can be run also by users with limited computational expertise. It allows in-depth analyses by removing low-complexity/ problematic reads, integrating the analytical steps that lead to a comprehensive taxonomy profile of each sample by querying different source databases, and it is customizable according to specific users’ needs.

Objectives: Clinically significant pancreatic fistula (POPF) has been established as a well-known risk factor for late and severe postpancreatectomy hemorrhage after pancreaticoduodenectomy (PD) (postpancreatectomy pancreatic fistula–associated hemorrhage [PPFH]). Our aim was to assess whether contrast-enhanced CT scan after PD is an effective tool for early prediction of PPFH. Methods: From a prospectively acquired database, all consecutive patients who underwent PD between January 2013 and May 2019 were identified; within this database, all patients who were evaluated, for clinical suspicion of POPF, with at least one contrast-enhanced CT scan examination, were enrolled in this retrospective study. The selected CT findings included perianastomotic fluid collections and air bubbles; pancreaticojejunostomy (PJ) was analyzed in terms of dehiscence and defect. Results: One hundred seventy-eight out of 953 PD patients (18.7%) suffered from clinically significant POPF; after exclusions, 166 patients were enrolled. Among this subset, 33 patients (19.9%) had at least one PPFH episode. In multivariable analysis, PPFH was associated with postoperative CT evidence of fluid collections (p = 0.046), air bubbles (p = 0.046), and posterior PJ defect (p < 0.001). Based on these findings, a practical 4-point prediction score was developed (AUC: 0.904, Se: 76%, Sp: 93.8%): patients with a score ≥ 3 demonstrated a significantly higher risk of PPFH development (OR = 45.6, 95% CI: 13.0–159.3). Conclusions: Postoperative CT scan permits early stratification of PPFH risk, thus providing an actual aid for patients’ management. Key Points: • Postpancreatectomy hemorrhage (PPH) is a dramatic, clinically unpredictable occurrence. • After pancreaticoduodenectomy (PD), early identification of posterior pancreaticojejunostomy defect, perianastomotic air bubbles, and retroperitoneal fluid collections enables effective PPH risk stratification by means of a practical CT-based 4-point scoring system. • CT scan after PD allows a paradigm shift in the management PPH, from a conventional “wait and see” approach, to a more proactive one that relies on early anticipation and timely prevention.

Cardiovascular diseases are still among the first causes of death worldwide with a huge impact on healthcare systems. Within these conditions, the correct diagnosis of coronary artery disease with the most appropriate imaging-based evaluations is of utmost importance. The sustainability of the healthcare systems, considering the high economic burden of modern cardiac imaging equipments, makes cost-effective analysis an important tool, currently used for weighing different costs and health outcomes, when policy makers have to allocate funds and to prioritize interventions, getting the most out of their financial resources. This review aims at evaluating cost-effective analysis in the more recent literature, focused on the role of Calcium Score, coronary computed tomography angiography and cardiac magnetic resonance.

Purpose: To explore the variation of the discriminative power of CT radiomic features (RF) against image discretization/interpolation in characterizing pancreatic neuro-endocrine (PanNEN) neoplasms. Materials and methods: Thirty-nine PanNEN patients with pre-surgical high contrast CT available were considered. Image interpolation and discretization parameters were intentionally changed, including pixel size (0.73–2.19 mm2), slice thickness (2–5 mm) and binning (32–128 grey levels) and their combination generated 27 parameter's set. The ability of 69 RF in discriminating post-surgically assessed tumor grade (>G1), positive nodes, metastases and vascular invasion was tested: AUC changes when changing the parameters were quantified for selected RF, significantly associated to each end-point. The analysis was repeated for the corresponding images with contrast medium and in a sub-group of 29/39 patients scanned on a single scanner. Results: The median tumor volume was 1.57 cm3 (16%-84% percentiles: 0.62–34.58 cm3). RF variability against discretization/interpolation parameters was large: only 21/69 RF showed %COV < 20%. Despite this variability, AUC changes were limited for all end-points: with typical AUC values around 0.75–0.85, AUC ranges for the 27 parameter's set were on average 0.062 (1SD:0.037) for all end-points with maximum %COV equal to 5.5% (mean:2.3%). Performances significantly improved when excluding the 5 mm thickness case and fixing the binning to 64 (mean AUC range: 0.036, 1SD:0.019). Using contrast images or limiting the population to single-scanner patients had limited impact on AUC variability. Conclusions: The discriminative power of CT RF for panNEN is relatively invariant against image interpolation/discretization within a large range of voxel sizes and binning.

Purpose To report the safety and efficacy of the embolization of splenic artery aneurysms (SAAs) with coils plus ethylene vinyl alcohol copolymer (EVOH) agent. Materials and Methods A single-center retrospective study was conducted from 2016 to 2019 to collect SAAs. Twelve asymptomatic patients (mean age, 59 years) with 15 SAAs (mean size, 23.6 mm; size range, 15–40 mm) were treated with embolization. Embolization was performed with EVOH (Squid 8/34) and fibered detachable coils. Transfemoral embolization was performed with a microcatheter to achieve a splenic artery occlusion embolizing the SAA and its efferent and afferent branches. Follow-up was based on color Doppler ultrasound at 24 hours and on computed tomography (CT) angiography at 1 (n = 12) and 6 months (n = 12) after embolization. Mean number of coils and Squid vials used for each patient, major/minor complications, technical success, 30-day clinical success, cases of revascularization/reintervention, and mortality were assessed. Technical success was defined as complete exclusion of the aneurysmal segment and cessation of blood flow into the sac. Clinical success at 1 month was based on the absence of clinical symptoms and the exclusion of aneurysm revascularization on CT angiography. Results The mean number of coils and Squid vials was 5.75 (standard deviation [SD], 1.58; range, 3–9) and 1.41 (SD, 0.49; range, 1–2), respectively. Both technical and 30-day clinical success were 100%, with no cases of aneurysm revascularization (CT angiography performed in all patients at 1 month and 6 months and in 3 patients at 24 months). No major complications or fatal events were recorded. In terms of minor complications, 2 cases of mild pancreatitis (transient amylases increase) and 1 case of focal splenic ischemia without clinical sequelae were recorded. Conclusions Embolization in SAAs using coils plus EVOH was safe and effective without SAA revascularization

Background: Preoperative evaluation of the number of lymph node metastasis (LNM) is the basis of individual treatment of locally advanced gastric cancer (LAGC). However, the routinely used preoperative determination method is not accurate enough. Patients and methods: We enrolled 730 LAGC patients from five centers in China and one center in Italy, and divided them into one primary cohort, three external validation cohorts, and one international validation cohort. A deep learning radiomic nomogram (DLRN) was built based on the images from multiphase computed tomography (CT) for preoperatively determining the number of LNM in LAGC. We comprehensively tested the DLRN and compared it with three state-of-the-art methods. Moreover, we investigated the value of the DLRN in survival analysis. Results: The DLRN showed good discrimination of the number of LNM on all cohorts [overall C-indexes (95% confidence interval): 0.821 (0.785–0.858) in the primary cohort, 0.797 (0.771–0.823) in the external validation cohorts, and 0.822 (0.756–0.887) in the international validation cohort]. The nomogram performed significantly better than the routinely used clinical N stages, tumor size, and clinical model (P < 0.05). Besides, DLRN was significantly associated with the overall survival of LAGC patients (n = 271). Conclusion: A deep learning-based radiomic nomogram had good predictive value for LNM in LAGC. In staging-oriented treatment of gastric cancer, this preoperative nomogram could provide baseline information for individual treatment of LAGC.

Objective To determine the incidence, predictors, and outcome of pneumothorax (PNX)/pneumomediastinum (PMD) in coronavirus disease 2019 (COVID-19) acute respiratory distress syndrome (ARDS). Design Observational study. Setting Tertiary-care university hospital. Participants One hundred sixteen consecutive critically ill, invasively ventilated patients with COVID-19 ARDS. Interventions The authors collected demographic, mechanical ventilation, imaging, laboratory, and outcome data. Primary outcome was the incidence of PNX/PMD. Multiple logistic regression analyses were performed to identify predictors of PNX/PMD. Measurements and Main Results PNX/PMD occurred in a total of 28 patients (24.1%), with 22 patients developing PNX (19.0%) and 13 developing PMD (11.2%). Mean time to development of PNX/PMD was 14 ± 11 days from intubation. The authors found no significant difference in mechanical ventilation parameters between patients who developed PNX/PMD and those who did not. Mechanical ventilation parameters were within recommended limits for protective ventilation in both groups. Ninety-five percent of patients with PNX/PMD had the Macklin effect (linear collections of air contiguous to the bronchovascular sheaths) on a baseline computed tomography scan, and tended to have a higher lung involvement at intensive care unit (ICU) admission (Radiographic Assessment of Lung Edema score 32.2 ± 13.4 v 18.7 ± 9.8 in patients without PNX/PMD, p = 0.08). Time from symptom onset to intubation and time from total bilirubin on day two after ICU admission were the only independent predictors of PNX/PMD. Mortality was 60.7% in patients who developed PNX/PMD versus 38.6% in those who did not (p = 0.04). Conclusion PNX/PMD occurs frequently in COVID-19 patients with ARDS requiring mechanical ventilation, and is associated with increased mortality. Development of PNX/PMD seems to occur despite use of protective mechanical ventilation and has a radiologic predictor sign.

Background: The aim of this study was to quantify COVID-19 pneumonia features using CT performed at time of admission to emergency department in order to predict patients' hypoxia during the hospitalization and outcome. Methods: Consecutive chest CT performed in the emergency department between March 1st and April 7th 2020 for COVID-19 pneumonia were analyzed. The three features of pneumonia (GGO, semi-consolidation and consolidation) and the percentage of well-aerated lung were quantified using a HU threshold based software. ROC curves identified the optimal cut-off values of CT parameters to predict hypoxia worsening and hospital discharge. Multiple Cox proportional hazards regression was used to analyze the capability of CT quantitative features, demographic and clinical variables to predict the time to hospital discharge. Results: Seventy-seven patients (median age 56-years-old, 51 men) with COVID-19 pneumonia at CT were enrolled. The quantitative features of COVID-19 pneumonia were not associated to age, sex and time-from-symptoms onset, whereas higher number of comorbidities was correlated to lower well-aerated parenchyma ratio (rho = −0.234, p = 0.04) and increased semi-consolidation ratio (rho = −0.303, p = 0.008). Well-aerated lung (≤57%), semi-consolidation (≥17%) and consolidation (≥9%) predicted worst hypoxemia during hospitalization, with moderate areas under curves (AUC 0.76, 0.75, 0.77, respectively). Multiple Cox regression identified younger age (p < 0.01), female sex (p < 0.001), longer time-from-symptoms onset (p = 0.049), semi-consolidation ≤17% (p < 0.01) and consolidation ≤13% (p = 0.03) as independent predictors of shorter time to hospital discharge. Conclusion: Quantification of pneumonia features on admitting chest CT predicted hypoxia worsening during hospitalization and time to hospital discharge in COVID-19 patients.

Purpose: To train and validate a predictive model of mortality for hospitalized COVID-19 patients based on lung densitometry. Methods: Two-hundred-fifty-one patients with respiratory symptoms underwent CT few days after hospitalization. “Aerated” (AV), “consolidated” (CV) and “intermediate” (IV) lung sub-volumes were quantified by an operator-independent method based on individual HU maximum gradient recognition. AV, CV, IV, CV/AV, IV/AV, and HU of the first peak position were extracted. Relevant clinical parameters were prospectively collected. The population was composed by training (n = 166) and validation (n = 85) consecutive cohorts, and backward multi-variate logistic regression was applied on the training group to build a CT_model. Similarly, models including only clinical parameters (CLIN_model) and both CT/clinical parameters (COMB_model) were developed. Model's performances were assessed by goodness-of-fit (H&L-test), calibration and discrimination. Model's performances were tested in the validation group. Results: Forty-three patients died (25/18 in training/validation). CT_model included AVmax (i.e. maximum AV between lungs), CV and CV/AE, while CLIN_model included random glycemia, C-reactive protein and biological drugs (protective). Goodness-of-fit and discrimination were similar (H&L:0.70 vs 0.80; AUC:0.80 vs 0.80). COMB_model including AVmax, CV, CV/AE, random glycemia, biological drugs and active cancer, outperformed both models (H&L:0.91; AUC:0.89, 95%CI:0.82–0.93). All models showed good calibration (R2:0.77–0.97). Despite several patient's characteristics were different between training and validation cohorts, performances in the validation cohort confirmed good calibration (R2:0–70-0.81) and discrimination for CT_model/COMB_model (AUC:0.72/0.76), while CLIN_model performed worse (AUC:0.64). Conclusions: Few automatically extracted densitometry parameters with clear functional meaning predicted mortality of COVID-19 patients. Combined with clinical features, the resulting predictive model showed higher discrimination/calibration.

Objectives During severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, dramatic endothelial cell damage with pulmonary microvascular thrombosis have been was hypothesized to occur. The aim was to assess whether pulmonary vascular thrombosis (PVT) is due to recurrent thromboembolism from peripheral deep vein thrombosis or to local inflammatory endothelial damage, with a superimposed thrombotic late complication. Design Observational study. Setting Medical and intensive care unit wards of a teaching hospital. Participants The authors report a subset of patients included in a prospective institutional study (CovidBiob study) with clinical suspicion of pulmonary vascular thromboembolism. Interventions Computed tomography pulmonary angiography and evaluation of laboratory markers and coagulation profile. Measurements and Main Results Twenty-eight of 55 (50.9%) patients showed PVT, with a median time interval from symptom onset of 17.5 days. Simultaneous multiple PVTs were identified in 22 patients, with bilateral involvement in 16, mostly affecting segmental/subsegmental pulmonary artery branches (67.8% and 96.4%). Patients with PVT had significantly higher ground glass opacity areas (31.7% [22.9-41] v 17.8% [10.8-22.1], p < 0.001) compared with those without PVT. Remarkably, in all 28 patients, ground glass opacities areas and PVT had an almost perfect spatial overlap. D-dimer level at hospital admission was predictive of PVT. Conclusions The findings identified a specific radiologic pattern of coronavirus disease 2019 (COVID-19) pneumonia with a unique spatial distribution of PVT overlapping areas of ground-glass opacities. These findings supported the hypothesis of a pathogenetic relationship between COVID-19 lung inflammation and PVT and challenged the previous definition of pulmonary embolism associated with COVID-19 pneumonia., Graphical abstract Computed Tomography Pulmonary Angiography (CTPA) imaging demonstrating, in three different clinical scenarios, eventual filling defects in branches of the pulmonary arteries (white arrows) and their spatial distribution according to the corresponding ventilation maps (white asterisks indicate normal lung parenchyma). In (a) [non COVID-19 pneumonia] and (c) [non COVID-19 ARDS] filling defects are electively found in the branches of the pulmonary arteries accountable for the vascularization of healthy lung segments. On the contrary, in (b) [COVID-19 pneumonia] there is an almost perfect topographical overlap between filling defects distribution and pneumonia extent.Image, graphical abstract

Objective A large number of studies have highlighted the important role of the gut microbiota in the pathophysiology of neurological disorders, suggesting that its manipulation might serve as a treatment strategy. We hypothesized that the gut microbiota participates in absence seizure development and maintenance in the WAG/Rij rat model and tested this hypothesis by evaluating potential gut microbiota and intestinal alterations in the model, as well as measuring the impact of microbiota manipulation using fecal microbiota transplantation (FMT). Methods Initially, gut microbiota composition and intestinal histology of WAG/Rij rats (a well-recognized genetic model of absence epilepsy) were studied at 1, 4, and 8 months of age in comparison to nonepileptic Wistar rats. Subsequently, in a second set of experiments, at 6 months of age, untreated Wistar or WAG/Rij rats treated with ethosuximide (ETH) were used as gut microbiota donors for FMT in WAG/Rij rats, and electroencephalographic (EEG) recordings were obtained over 4 weeks. At the end of FMT, stool and gut samples were collected, absence seizures were measured on EEG recordings, and microbiota analysis and histopathological examinations were performed. Results Gut microbiota analysis showed differences in beta diversity and specific phylotypes at all ages considered and significant variances in the Bacteroidetes/Firmicutes ratio between Wistar and WAG/Rij rats. FMT, from both Wistar and ETH-treated WAG/Rij donors to WAG/Rij rats, significantly decreased the number and duration of seizures. Histological results indicated that WAG/Rij rats were characterized by intestinal villi disruption and inflammatory infiltrates already at 1 month of age, before seizure occurrence; FMT partially restored intestinal morphology while also significantly modifying gut microbiota and concomitantly reducing absence seizures. Significance Our results demonstrate for the first time that the gut microbiota is modified and contributes to seizure occurrence in a genetic animal model of absence epilepsy and that its manipulation may be a suitable therapeutic target for absence seizure management.

Purpose: To assess the ability of radiomic features (RF) extracted from contrast-enhanced CT images (ceCT) and non-contrast-enhanced (non-ceCT) in discriminating histopathologic characteristics of pancreatic neuroendocrine tumors (panNET). Methods: panNET contours were delineated on pre-surgical ceCT and non-ceCT. First- second- and higher-order RF (adjusted to eliminate redundancy) were extracted and correlated with histological panNET grade (G1 vs G2/G3), metastasis, lymph node invasion, microscopic vascular infiltration. Mann–Whitney with Bonferroni corrected p values assessed differences. Discriminative power of significant RF was calculated for each of the end-points. The performance of conventional-imaged-based-parameters was also compared to RF. Results: Thirty-nine patients were included (mean age 55-years-old; 24 male). Mean diameters of the lesions were 24 × 27mm. Sixty-nine RF were considered. Sphericity could discriminate high grade tumors (AUC = 0.79, p = 0.002). Tumor volume (AUC = 0.79, p = 0.003) and several non-ceCT and ceCT RF were able to identify microscopic vascular infiltration: voxel-alignment, neighborhood intensity-difference and intensity-size-zone families (AUC ≥ 0.75, p < 0.001); voxel-alignment, intensity-size-zone and co-occurrence families (AUC ≥ 0.78, p ≤ 0.002), respectively). Non-ceCT neighborhood-intensity-difference (AUC = 0.75, p = 0.009) and ceCT intensity-size-zone (AUC = 0.73, p = 0.014) identified lymph nodal invasion; several non-ceCT and ceCT voxel-alignment family features were discriminative for metastasis (p < 0.01, AUC = 0.80–0.85). Conventional CT ‘necrosis’ could discriminate for microscopic vascular invasion (AUC = 0.76, p = 0.004) and ‘arterial vascular invasion’ for microscopic metastasis (AUC = 0.86, p = 0.001). No conventional-imaged-based-parameter was significantly associated with grade and lymph node invasion. Conclusions: Radiomic features can discriminate histopathology of panNET, suggesting a role of radiomics as a non-invasive tool for tumor characterization. Trial registration number: NCT03967951, 30/05/2019

Objective To evaluate whether the initial chest X-ray (CXR) severity assessed by an AI system may have prognostic utility in patients with COVID-19. Methods This retrospective single-center study included adult patients presenting to the emergency department (ED) between February 25 and April 9, 2020, with SARS-CoV-2 infection confirmed on real-time reverse transcriptase polymerase chain reaction (RT-PCR). Initial CXRs obtained on ED presentation were evaluated by a deep learning artificial intelligence (AI) system and compared with the Radiographic Assessment of Lung Edema (RALE) score, calculated by two experienced radiologists. Death and critical COVID-19 (admission to intensive care unit (ICU) or deaths occurring before ICU admission) were identified as clinical outcomes. Independent predictors of adverse outcomes were evaluated by multivariate analyses. Results Six hundred ninety-seven 697 patients were included in the study: 465 males (66.7%), median age of 62 years (IQR 52–75). Multivariate analyses adjusting for demographics and comorbidities showed that an AI system-based score ≥ 30 on the initial CXR was an independent predictor both for mortality (HR 2.60 (95% CI 1.69 − 3.99; p < 0.001)) and critical COVID-19 (HR 3.40 (95% CI 2.35–4.94; p < 0.001)). Other independent predictors were RALE score, older age, male sex, coronary artery disease, COPD, and neurodegenerative disease. Conclusion AI- and radiologist-assessed disease severity scores on CXRs obtained on ED presentation were independent and comparable predictors of adverse outcomes in patients with COVID-19. Trial registration ClinicalTrials.gov NCT04318366 (https://clinicaltrials.gov/ct2/show/NCT04318366). Key Points • AI system–based score ≥ 30 and a RALE score ≥ 12 at CXRs performed at ED presentation are independent and comparable predictors of death and/or ICU admission in COVID-19 patients. • Other independent predictors are older age, male sex, coronary artery disease, COPD, and neurodegenerative disease. • The comparable performance of the AI system in relation to a radiologist-assessed score in predicting adverse outcomes may represent a game-changer in resource-constrained settings.

Purpose: Leakage of the gastric remnant after laparoscopic sleeve gastrectomy (LSG) represents an unpredictable, dreadful occurrence. Our aim was to assess whether routine postoperative CT scan is an effective tool for early prediction of leakage after LSG. Materials and Methods: From a prospectively acquired database, all consecutive patients who underwent LSG between January 2015 and December 2018 were identified; within this database, all patients who were evaluated with at least one contrast-enhanced CT scan within 48h from surgery were enrolled in this retrospective study. The selected CT findings included twisting of the gastric remnant, perigastric air bubbles, and hematoma; the antral segment proximal from the pylorus to the first staple firing was also analyzed in terms of distance (StP, stapler to pylorus distance) and linearity (LI, linearity index). Results: After exclusions, 250 patients were included; 10 patients suffered from gastric leakage. Patients with perigastric hematoma and/or twisting of the distal part of the gastric remnant on routine postoperative CT scan were found to be more likely to develop leakage after LSG (p= 0.005 and p< 0.001, respectively). The mean StP was 45 ± 19.1mm; the mean LI was 1.54 ± 0.4. Patients with subsequent development of leakage had significantly lower StP (26.7 ± 12.5mm vs. 45.9 ± 18.9mm; p= 0.001) and LI values (1.16 ± 0.11 vs. 1.55 ± 0.39; p= 0.002). Conclusion: Routine postoperative CT scan after LSG permits early stratification of leakage risk, thus providing an actual aid for patients’ management.

Background: Patients with schizophrenia display experiential anomalies in their feelings and cognitions arising in the domain of their lived body. These abnormal bodily phenomena (ABP) are not part of diagnostic criteria for schizophrenia. One of the reasons is the difficulty to assess specific ABP for schizophrenia spectrum disorders. The present study aimed to explore the presence in patients with schizophrenia of specific ABP. Methods: We used a semistructured interview—the Abnormal Bodily Phenomena questionnaire (ABPq), an instrument devised to detect and measure ABP specific to patients with schizophrenia. Fifty-one outpatients affected by schizophrenia and 28 euthymic outpatients affected by bipolar disorder type I with psychotic features (BD-pf-e) were recruited. Before assessing the specificity for schizophrenia of the observed ABP, we tested the internal consistency and the convergent validity of the ABPq in patients with schizophrenia. Specificity was assessed by examining potential differences in ABPq among the patients with schizophrenia in remission (SCZ-r) and BD-pf-e. Results: The ABPq shows strong internal consistency and convergent validity. As to the specificity, ABP measured by ABPq were more frequent and severe in SCZ-r than in BD-pf-e. In particular, all ABPq dimensions, except “Coherence,” had at least mild severity in over 50% of SCZ-r, while dimensions with at least mild severity were observed in 5–10% of the BD-pf-e. Conclusions: These findings can contribute to establish more precise phenomenal boundaries between schizophrenia and bipolar disorder, to explore the borders between nonpsychotic and psychotic forms of ABP, between ABP and negative and disorganized symptoms, and to enlighten core aspects of schizophrenia.

Davide Palumbo,1 Armida Mucci,1 Giulia Maria Giordano,1 Giuseppe Piegari,1 Carmen Aiello,1 Daria Pietrafesa,1 Nicola Annarumma,1 Marcello Chieffi,1 Matteo Cella,2 Silvana Galderisi1 1Department of Psychiatry, University of Campania Luigi Vanvitelli, Naples, Italy; 2Institute of Psychiatry, Psychology and Neuroscience (ioppn), King’s College London, London, UKCorrespondence: Armida MucciDepartment of Psychiatry, University of Campania Luigi Vanvitelli, L.go Madonna delle Grazie 1, 80138 Naples, ItalyTel +39-81-5665153Email armida.mucci@gmail.comIntroduction: The Computerized Interactive Remediation of Cognition – Training for Schizophrenia (CIRCuiTS) is a form of cognitive remediation therapy developed to target neurocognitive and metacognitive deficits of people with schizophrenia, which have a detrimental impact on real-life functioning. The English version of CIRCuiTS demonstrated good acceptability and feasibility. A recent randomized controlled trial provided evidence that the program improves memory and functioning, and that the impact on functional outcome is mediated by metacognition. The next steps in the development of CIRCuiTS include both: 1) the translation and adaptation of the program in different cultural settings; and 2) the demonstration of feasibility, acceptability and effectiveness of a standardized method to administer CIRCuiTS remotely.Purpose: To implement the CIRCuiTS Italian version and to assess acceptability, feasibility and efficacy of a standardized method to administer CIRCuiTS remotely.Methods: Participants were assessed at baseline and received up to 40 CIRCuiTS therapy sessions, three times a week, for about 1 hr over a three-month period. Participants were reassessed post-treatment.Results: The program demonstrated good feasibility and high acceptability when assessed by the number of dropouts and evaluation of patients’ satisfaction. Participants improved in learning, speed of processing, working memory and executive control. They showed a reduction in disorganization and improvement in self-esteem, functional capacity, and real-life functioning.Conclusion: In this study, a standardized protocol for using CIRCuiTS from home was implemented. The first set of data showed in the paper is encouraging. The proposed procedure could lead to a dropout reduction while maintaining the efficacy of the program.Keywords: cognition, cognitive training, metacognition, real-life functioning

Drug tampering practices, with the aim to increase availability of drug delivery and/or enhance drug effects, are accessible on Internet and are practiced by some portion of recreational drug users. Not rarely, recreational misuse may result in toxic and even fatal results. The aim of the present study was to assess the tampering risk of medicaments containing different formulations of an opioid in combination with paracetamol or dexketoprofen, following the procedures reported in dedicated forums on the web. Tablets and suppositories containing codeine, tramadol and oxycodone were extracted following the reported “Cold water extraction”; dextromethorphan was extracted from cough syrup following the procedure reported as “Acid/base extraction” and fentanyl was extracted from transdermal patches according the procedure reported in Internet. The tampered products and opportunely prepared calibrators in water were analysed by liquid chromatography coupled to tandem mass spectrometry (LC–MS/MS). The separation of the analytes was carried on Agilent ZORBAX Eclipse Plus C18 (RRHT 2.1 mm × 50 mm, 1.8 μm) by the gradient elution of 0.01% formic acid in water and 0.01% formic acid in methanol. Acquisition was by MRM mode considering at least two transitions for compound. Declared recoveries for these home-made extractions claimed to exceed 99% for the opioid and to complete remove paracetamol, often associated to liver toxicity and thus to obtain a “safer” preparation. In this study, the authors demonstrated that rarely the recoveries for the opioid reached 90% and that up to 60% of the paracetamol amount remained in solution. Thus, high risks for health remained both for the potential lethality of the opioid content, but also for the sub-lethal chronic use of these mixtures, which contained still uncontrolled, ignored, but often important amounts of paracetamol.

Comprehension of illicit drug market's features at local level is useful to plan and to correctly set-up specific informative and contrast activities. In this paper we report trends, purities and consumption estimations of illicit substances available on the Florentine territory from 2006 to 2016. These data were obtained by the analysis of 10,451 samples seized by the Law Enforcement Agencies in case of personal use offence. Analytical procedures consisted in targeted and untargeted analyses by gas chromatography-flame ionization detector, gas chromatography–mass spectrometry and liquid chromatography–tandem mass spectrometry. The most detected substances were: cannabis (78.0%; resin: 51.7%; herb: 26.3%), cocaine (10.4%), opiates (6.6%; heroin: 6.5%; morphine: 0.1%), ketamine (1.4%), amphetamines (1.3%; 3,4-methylenedioxymethamphetamine – MDMA –: 0.7%; methamphetamine: 0.6%; amphetamine

DNA methylation is often analyzed by reporting the average methylation degree of each cytosine. In this study, we used a single molecule methylation analysis in order to look at the methylation conformation of individual molecules. Using D-aspartate oxidase as a model gene, we performed an in-depth methylation analysis through the developmental stages of three different mouse tissues (brain, lung, and gut), where this gene undergoes opposite methylation destiny. This approach allowed us to track both methylation and demethylation processes at high resolution. The complexity of these dynamics was markedly simplified by introducing the concept of methylation classes (MCs), defined as the number of methylated cytosines per molecule, irrespective of their position. The MC concept smooths the stochasticity of the system, allowing a more deterministic description. In this framework, we also propose a mathematical model based on the Markov chain. This model aims to identify the transition probability of a molecule from one MC to another during methylation and demethylation processes. The results of our model suggest that: 1) both processes are ruled by a dominant class of phenomena, namely, the gain or loss of one methyl group at a time; and 2) the probability of a single CpG site becoming methylated or demethylated depends on the methylation status of the whole molecule at that time.