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Antonella Potalivo,1,* Jonathan Montomoli,1,* Francesca Facondini,1 Gianfranco Sanson,2 Luigi Arcangelo Lazzari Agli,3,4 Tiziana Perin,5 Francesco Cristini,6 Enrico Cavagna,7 Raffaella De Giovanni,8 Carlo Biagetti,6 Ilaria Panzini,9 Cinzia Ravaioli,10 Maria Maddalena Bitondo,1 Daniela Guerra,1 Giovanni Giuliani,1 Elena Mosconi,1 Sonia Guarino,1 Elisa Marchionni,6 Gianfilippo Gangitano,5 Ilaria Valentini,3,4 Luca Giampaolo,8 Francesco Muratore,7 Giuseppe Nardi1 1Department of Anaesthesia and Intensive Care, Infermi Hospital, AUSL della Romagna, Rimini, Italy; 2Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy; 3Department of Pneumology, Infermi Hospital, Rimini, Italy; 4Ceccarini Hospital, AUSL della Romagna, Riccione, Italy; 5Department of Emergency Medicine, Infermi Hospital, AUSL Della Romagna, Rimini, Italy; 6Department of Infectious Diseases, Infermi Hospital, AUSL della Romagna, Rimini,Italy; 7Department of Radiology, Infermi Hospital, AUSL della Romagna, Rimini, Italy; 8Department of Internal Medicine, Cervesi Hospital, AUSL della Romagna, Cattolica, Italy; 9Department of Clinical Research, AUSL della Romagna, Ravenna, Italy; 10Ausl della Romagna Health Care Service Direction, Ravenna, Italy*These authors contributed equally to this workCorrespondence: Giuseppe NardiDepartment of Anaesthesia and Intensive Care, Infermi Hospital, AUSL della Romagna, Viale Settembrini 2, Rimini 47921, ItalyTel +39 0541-705254Fax +39 0541 705886Email 4doctornardi@gmail.comPurpose: Although the decision of which ventilation strategy to adopt in COVID-19 patients is crucial, yet the most appropriate means of carrying out this undertaking is not supported by strong evidence. We therefore described the organization of a province-level healthcare system during the occurrence of the COVID-19 epidemic and the 60-day outcomes of the hospitalized COVID-19 patients according to the respiratory strategy adopted given the limited available resources.Patients and Methods: All COVID-19 patients (26/02/2020– 18/04/2020) in the Rimini Province of Italy were included in this population-based cohort study. The hospitalized patients were classified according to the maximum level of respiratory support: oxygen supplementation (Oxygen group), non-invasive ventilation (NIV-only group), invasive mechanical ventilation (IMV-only group), and IMV after an NIV trial (IMV-after-NIV group). Sixty-day mortality risk was estimated with a Cox proportional hazard analysis adjusted by age, sex, and administration of steroids, canakinumab, and tocilizumab.Results: We identified a total of 1,424 symptomatic patients: 520 (36.5%) were hospitalized, while 904 (63.5%) were treated at home with no 60-day deaths. Based on the respiratory support, 408 (78.5%) were assigned to the Oxygen group, 46 (8.8%) to the NIV-only group, 25 (4.8%) to the IMV-after-NIV group, and 41 (7.9%) to the IMV-only group. There was no significant difference in the PaO2/FiO2 at IMV inception in the IMV-after-NIV and IMV-only groups (p=0.9). Overall 60-day mortality was 24.2% (Oxygen: 23.0%; NIV-only: 19.6%; IMV-after-NIV: 32.0%; IMV-only: 36.6%; p=0.165). Compared with the Oxygen group, the adjusted 60-day mortality risk significantly increased in the IMV-after-NIV (HR 2.776; p=0.024) and IMV-only groups (HR 2.966; p=0.001).Conclusion: This study provided a population-based estimate of the impact of the COVID-19 outbreak in a severely affected Italian province. A similar 60-day mortality risk was found for patients undergoing immediate IMV and those intubated after an NIV trial with favorable outcomes after prolonged IMV.Keywords: COVID-19, mechanical ventilation, mortality, noninvasive ventilation, multidisciplinary team approach, ARDS

Proton magnetic resonance spectroscopy (MRS) is a sensitive method for investigating the biochemical compounds in a tissue. The interpretation of the data relies on the quantification algorithms applied to MR spectra. Each of these algorithms has certain underlying assumptions and may allow one to incorporate prior knowledge, which could influence the quality of the fit. The most commonly considered types of prior knowledge include the line-shape model (Lorentzian, Gaussian, Voigt), knowledge of the resonating frequencies, modeling of the baseline, constraints on the damping factors and phase, etc. In this article, we study whether the statistical outcome of a biological investigation can be influenced by the quantification method used. We chose to study lipid signals because of their emerging role in the investigation of metabolic disorders. Lipid spectra, in particular, are characterized by peaks that are in most cases not Lorentzian, because measurements are often performed in difficult body locations, e.g. in visceral fats close to peristaltic movements in humans or very small areas close to different tissues in animals. This leads to spectra with several peak distortions. Linear combination of Model spectra (LCModel), Advanced Method for Accurate Robust and Efficient Spectral fitting (AMARES), quantitation based on QUantum ESTimation (QUEST), Automated Quantification of Short Echo-time MRS (AQSES)-Lineshape and Integration were applied to simulated spectra, and area under the curve (AUC) values, which are proportional to the quantity of the resonating molecules in the tissue, were compared with true values. A comparison between techniques was also carried out on lipid signals from obese and lean Zucker rats, for which the polyunsaturation value expressed in white adipose tissue should be statistically different, as confirmed by high-resolution NMR measurements (considered the gold standard) on the same animals. LCModel, AQSES-Lineshape, QUEST and Integration gave the best results in at least one of the considered groups of simulated or in vivo lipid signals. These outcomes highlight the fact that quantification methods can influence the final result and its statistical significance. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

BackgroundThe diagnosis and management of bipolar disorder are limited by the absence of available biomarkers. Patients with bipolar disorder frequently present with mood instability even during remission, which is likely associated with the risk of relapse, impaired functioning, and suicidal behavior, indicating that the illness is active. ObjectiveThis research protocol aimed to investigate the correlations between clinically rated mood symptoms and mood/behavioral data automatically collected using the Toi Même app in patients with bipolar disorder presenting with different mood episodes. This study also aimed to assess the feasibility of this app for self-monitoring subjective and objective mood/behavior parameters in those patients. MethodsThis open-label, nonrandomized trial will enroll 93 (31 depressive, 31 euthymic, and 31 hypomanic) adults diagnosed with bipolar disorder type I/II (Diagnostic and Statistical Manual of Mental Disorders, 5th edition criteria) and owning an iPhone. Clinical evaluations will be performed by psychiatrists at the baseline and after 2 weeks, 1 month, 2 months, and 3 months during the follow-up. Rather than only accessing the daily mood symptoms, the Toi Même app also integrates ecological momentary assessments through 2 gamified tests to assess cognition speed (QUiCKBRAIN) and affective responses (PLAYiMOTIONS) in real-life contexts, continuously measures daily motor activities (eg, number of steps, distance) using the smartphone’s motion sensors, and performs a comprehensive weekly assessment. ResultsRecruitment began in April 2018 and the completion of the study is estimated to be in December 2021. As of April 2019, 25 participants were enrolled in the study. The first results are expected to be submitted for publication in 2020. This project has been funded by the Perception and Memory Unit of the Pasteur Institute (Paris) and it has received the final ethical/research approvals in April 2018 (ID-RCB: 2017-A02450-53). ConclusionsOur results will add to the evidence of exploring other alternatives toward a more integrated approach in the management of bipolar disorder, including digital phenotyping, to develop an ethical and clinically meaningful framework for investigating, diagnosing, and treating individuals at risk of developing bipolar disorder or currently experiencing bipolar disorder. Further prospective studies on the validity of automatically generated smartphone data are needed for better understanding the longitudinal pattern of mood instability in bipolar disorder as well as to establish the reliability, efficacy, and cost-effectiveness of such an app intervention for patients with bipolar disorder. Trial RegistrationClinicalTrials.gov NCT03508427; https://clinicaltrials.gov/ct2/show/NCT03508427 International Registered Report Identifier (IRRID)DERR1-10.2196/18818

Despite the impressive photovoltaic performances with power conversion efficiency beyond 22%, perovskite solar cells are poorly stable under operation, failing by far the market requirements. Various technological approaches have been proposed to overcome the instability problem, which, while delivering appreciable incremental improvements, are still far from a market-proof solution. Here we show one-year stable perovskite devices by engineering an ultra-stable 2D/3D (HOOC(CH2)4NH3)2PbI4/CH3NH3PbI3 perovskite junction. The 2D/3D forms an exceptional gradually-organized multi-dimensional interface that yields up to 12.9% efficiency in a carbon-based architecture, and 14.6% in standard mesoporous solar cells. To demonstrate the up-scale potential of our technology, we fabricate 10 × 10 cm2 solar modules by a fully printable industrial-scale process, delivering 11.2% efficiency stable for >10,000 h with zero loss in performances measured under controlled standard conditions. This innovative stable and low-cost architecture will enable the timely commercialization of perovskite solar cells. [ABSTRACT FROM AUTHOR]

We aimed to evaluate the correlations among event-related evoked potentials (ERPs), neuropsychological and neuroradiological parameters in multiple sclerosis (MS) patients. We studied 10 patients with definite MS (6 males, 4 females, average age 43.6, SD = 11.3), and moderate disability (EDSS 2.85, SD = 1.45; range: 1.0–6.0). All patients underwent standardized neuropsychological tests, P300 evoked potentials study, and MRI. Registration of ERPs (P300) was performed by random double auditory discrimination task paradigm, recorded through scalp electrodes placed at Fz, Cz and Pz and linked to the referred ears. Pearson bivariate correlation test was used to evaluate correlations among latency and amplitude of P300, neuropsychological tests, clinical (age, EDSS, illness length, relapses), and MRI (cortical atrophy, Apparent Diffusion Coefficient – ADC-maps) parameters. In our small series, latency of P300 was related to ADC of corticospinal tracts ( p = 0.001) and illness length ( p = 0.001), while no clear correlation between P300 and neuropsychological or other clinical parameters was found. We suggest that P300 and MRI ADC maps could be combined to give a numerical indirect parameter of disease progression. [ABSTRACT FROM AUTHOR]