SENSING THE LAND SUBSIDENCE IN THE VENICE LAGOON BY INTERFEROMETRIC POINT TARGET ANALYSIS

Land subsidence is a severe geologic hazard threading the lowlying coastal areas worldwide. Monitoring land subsidence has been significantly improved over the last few years by space borne earth observation techniques based on SAR (Synthetic Aperture Radar) Interferometry. Within the INLET Project, funded by Magistrato alle Acque di Venezia – Venice Water Authority (VWA) and Consorzio Venezia Nuova (CVN), we have used the Interferometric Point Target Analysis (IPTA) to characterize the ground displacements within the Venice Lagoon. IPTA measures the movement of backscattering objects (point targets, PT) at the ground surface which persistently reflect radar signal emitted by the SAR antenna. For this study 80 ERS-1/2 and 44 ENVISAT scenes recorded from 1992 to 2005 and from 2003 to 2007, respectively, have been processed by IPTA. High reliable land subsidence data have been detected for thousands of PT located on the lagoon margins, along the littorals, in major and small islands, and on single anthropogenic structures scattered within the lagoon. On the average, land subsidence ranges from less than 1 mm/year to 5 mm/year, with some PT that exhibit values also larger than 10 mm/year depending on both the local geologic conditions and anthropogenic activities. A network of few tens of artificial square trihedral corner reflectors (TCR) has been established before summer 2007 to monitor land subsidence in the inner lagoon areas where natural reflectors completely lack (e.g., on the salt marshes). The first interferometric results on the TCR appear very promising

Imaging a large coronal loop using type U solar radio burst interferometry

Solar radio U-bursts are generated by electron beams traveling along closed magnetic loops in the solar corona. Low-frequency ($<$ 100 MHz) U-bursts serve as powerful diagnostic tools for studying large-sized coronal loops that extend into the middle corona. However, the positive frequency drift component (descending leg) of U-bursts has received less attention in previous studies, as the descending radio flux is weak. In this study, we utilized LOFAR interferometric solar imaging data from a U-burst that has a significant descending leg component, observed between 10 to 90 MHz on June 5th, 2020. By analyzing the radio source centroid positions, we determined the beam velocities and physical parameters of a large coronal magnetic loop that reached just about 1.3 $\rm{R_{\odot}}$ in altitude. At this altitude, we found the plasma temperature to be around 1.1 MK, the plasma pressure around 0.20 $\rm{mdyn,cm^{-2}}$, and the minimum magnetic field strength around 0.07 G. The similarity in physical properties determined from the image suggests a symmetric loop. The average electron beam velocity on the ascending leg was found to be 0.21 c, while it was 0.14 c on the descending leg. This apparent deceleration is attributed to a decrease in the range of electron energies that resonate with Langmuir waves, likely due to the positive background plasma density gradient along the downward loop leg

Analyzing artificial intelligence systems for the prediction of atrial fibrillation from sinus-rhythm ECGs including demographics and feature visualization

Atrial fibrillation (AF) is an abnormal heart rhythm, asymptomatic in many cases, that causes several health problems and mortality in population. This retrospective study evaluates the ability of different AI-based models to predict future episodes of AF from electrocardiograms (ECGs) recorded during normal sinus rhythm. Patients are divided into two classes according to AF occurrence or sinus rhythm permanence along their several ECGs registry. In the constrained scenario of balancing the age distributions between classes, our best AI model predicts future episodes of AF with area under the curve (AUC) 0.79 (0.72–0.86). Multiple scenarios and age-sex-specific groups of patients are considered, achieving best performance of prediction for males older than 70 years. These results point out the importance of considering different demographic groups in the analysis of AF prediction, showing considerable performance gaps among them. In addition to the demographic analysis, we apply feature visualization techniques to identify the most important portions of the ECG signals in the task of AF prediction, improving this way the interpretability and understanding of the AI models. These results and the simplicity of recording ECGs during check-ups add feasibility to clinical applications of AI-based modelsGJO, AS-G, LJJ-B received a research grant from the Carlos III Institute of Health under the health Strategy action 2020-2022 with reference PI20/00792. Tis study is also supported partially by projects TRESPASS-ETN (H2020-MSCAITN-2019-860813), PRIMA (H2020-MSCA-ITN-2019-860315), IDEA-FAST (IMI2-2018-15-853981), BIBECA (RTI2018-101248-B-I00 MINECO/FEDER

Prediction of atrial fibrillation from sinus-rhythm electrocardiograms based on deep neural networks: Analysis of time intervals and longitudinal study

Objective: Artificial Intelligence (AI) in electrocardiogram (ECG) analysis helps to identify persons at risk of developing atrial fibrillation (AF) and reduces the risk for severe complications. Our aim is to investigate the performance of AI-based methods predicting future AF from sinus rhythm (SR) ECGs, according to different characteristics of patients, time intervals for prediction, and longitudinal measures. Methods: We designed a retrospective, prognostic study to predict AF occurrence in patients from 12-lead SR ECGs. We classified patients in two groups, according to their ECGs: 3,761 developed AF and 22,896 presented only SR ECGs. We assessed the impact of age on the overall performance of deep neural network (DNN)-based systems, which consist in a variation of Residual Networks for time series. Then, we analysed how much in advance our system can predict AF from SR ECGs and the performance for different categories of patients with AUC and other metrics. Results: After balancing the age distribution between the two groups of patients, our model achieves AUC of 0.79 (0.72-0.86) without additional constraints, 0.83 (0.76-0.89) for ECGs recorded in the last six months before AF, and 0.87 (0.81-0.93) for patients with stable AF risk measures over time, with sensitivity of 90.62% (80.70-96.48) and diagnostic odd ratio of 20.49 (8.56-49.09). Conclusion: This study shows the ability of DNNs to predict new onsets of AF from SR ECGs, with the best performance achieved for patients with stable AF risk score over time. The introduction of this time-based score opens new possibilities for AF prediction, thanks to the analysis of long-span time intervals and score stabilityEuropean Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No860813 – TReSPAsS-ETNTRESPASS-ET

Diagnostic yield and predictive value on left ventricular remodelling of genetic testing in dilated cardiomyopathy

Aims: We assessed the diagnostic yield of genetic testing and the relationship of left ventricular (LV) reverse remodelling (LVRR) with the presence of DNA pathogenic (P) or likely pathogenic (LP) variants in patients with dilated cardiomyopathy (DCM). Methods and results: From 680 outpatients followed at the Heart Failure Outpatient Clinic of our institution, we selected subjects with a diagnosis of DCM as defined by LV ejection fraction (LVEF) ≤40% and LV dilatation not explained by coronary artery disease or other causes. All patients were offered genetic investigation of 42 disease-associated DCM genes with next-generation sequencing. Seventy patients fulfilled the definition of DCM and 66 underwent genetic investigation. We identified 18 P/LP variants in 16 patients, with a diagnostic yield of 24%. The most common variants were truncating TTN variants (n = 7), followed by LMNA (n = 3), cytoskeleton Z-disc (n = 3), ion channel (n = 2), motor sarcomeric (n = 2), and desmosomal (n = 1) genes. After a median follow-up of 53 months (inter-quartile range 20-111), patients without P/LP variants exhibited higher systolic and diastolic blood pressure, lower plasma brain natriuretic peptide levels, and a larger extent of LVRR, as reflected by the increase in LVEF (+14% vs. +1%, P = 0.0008) and decrease in indexed LV end-diastolic diameter (-6.5 vs. -2 mm/m2 , P = 0.03) compared with patients with P/LP variants. Conclusions: Our results confirm the high diagnostic yield of genetic testing in selected DCM patients and suggest that identification of P/LP variants in DCM portends poorer LVRR in response to guideline-directed medical therapy

Brain perfusion patterns: consistency and similarity with fMRI resting state networks and arterial vascular territories

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Feasibility of high-frequency percussions in people with severe acquired brain injury and tracheostomy: an observational study

People with severe acquired brain injury (pwSABI) frequently experience pulmonary complications. Among these, atelectasis can occur as a result of pneumonia, thus increasing the chance of developing acute respiratory failure. Respiratory physiotherapy contribution to the management of atelectasis in pwSABI is yet poorly understood. We conducted a retrospective analysis on 15 non-cooperative pwSABI with tracheostomy and spontaneously breathing, hospitalized and treated with high-frequency percussion physiotherapy between September 2018 and February 2021 at the Neurological Rehabilitation Unit of the IRCCS “S.Maria Nascente - Fondazione Don Gnocchi”, Milan. Our primary aim was to investigate the feasibility of such a physiotherapy intervention method. Then, we assessed changes in respiratory measures (arterial blood gas analysis and peripheral night-time oxygen saturation) and high-resolution computed tomography lung images, evaluated before and after the physiotherapy treatment. The radiological measures were a modified radiological atelectasis score (mRAS) assigned by two radiologists, and an opacity score automatically provided by the software CT Pneumonia Analysis® that identifies the regions of abnormal lung patterns. Treatment diaries showed that all treatments were completed, and no adverse events during treatment were registered. Among the 15 pwSABI analyzed, 8 were treated with IPV® and 7 with MetaNeb®. After a median of 14 (I-III quartile=12.5-14.5) days of treatment, we observed a statistical improvement in various arterial blood gas measures and peripheral night-time oxygen saturation measures. We also found radiological improvement or stability in more than 80% of pwSABI. In conclusion, our physiotherapy approach was feasible, and we observed respiratory parameters and radiological improvements. Using technology to assess abnormal tomographic patterns could be of interest to disentangle the short-term effects of respiratory physiotherapy on non-collaborating people

Relationship between cerebrovascular reactivity and age in multiple sclerosis

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Extracellular Vesicles Mediate Mesenchymal Stromal Cell-Dependent Regulation of B Cell PI3K-AKT Signaling Pathway and Actin Cytoskeleton

Mesenchymal stromal cells (MSCs) are adult, multipotent cells of mesodermal origin representing the progenitors of all stromal tissues. MSCs possess significant and broad immunomodulatory functions affecting both adaptive and innate immune responses once MSCs are primed by the inflammatory microenvironment. Recently, the role of extracellular vesicles (EVs) in mediating the therapeutic effects of MSCs has been recognized. Nevertheless, the molecular mechanisms responsible for the immunomodulatory properties of MSC-derived EVs (MSC-EVs) are still poorly characterized. Therefore, we carried out a molecular characterization of MSC-EV content by high-throughput approaches. We analyzed miRNA and protein expression profile in cellular and vesicular compartments both in normal and inflammatory conditions. We found several proteins and miRNAs involved in immunological processes, such as MOES, LG3BP, PTX3, and S10A6 proteins, miR-155-5p, and miR-497-5p. Different in silico approaches were also performed to correlate miRNA and protein expression profile and then to evaluate the putative molecules or pathways involved in immunoregulatory properties mediated by MSC-EVs. PI3K-AKT signaling pathway and the regulation of actin cytoskeleton were identified and functionally validated in vitro as key mediators of MSC/B cell communication mediated by MSC-EVs. In conclusion, we identified different molecules and pathways responsible for immunoregulatory properties mediated by MSC-EVs, thus identifying novel therapeutic targets as safer and more useful alternatives to cell or EV-based therapeutic approaches

Determinants of Disability in Multiple Sclerosis: An Immunological and MRI Study

Multiple sclerosis (MS) is characterized by a wide interpatient clinical variability and available biomarkers of disease severity still have suboptimal reliability. We aimed to assess immunological and MRI-derived measures of brain tissue damage in patients with different motor impairment degrees, for in vivo investigating the pathogenesis of MS-related disability. Twenty-two benign (B), 26 secondary progressive (SP), and 11 early, nondisabled relapsing-remitting (RR) MS patients and 37 healthy controls (HC) underwent conventional and diffusion tensor brain MRI and, as regards MS patients, immunophenotypic and functional analysis of stimulated peripheral blood mononuclear cells (PBMC). Corticospinal tract (CST) fractional anisotropy and grey matter volume were lower and CST diffusivity was higher in SPMS compared to RRMS and BMS patients. CD14+IL6+ and CD4+IL25+ cell percentages were higher in BMS than in SPMS patients. A multivariable model having EDSS as the dependent variable retained the following independent predictors: grey matter volume, CD14+IL6+ and CD4+IL25+ cell percentages. In patients without motor impairment after long-lasting MS, the grey matter and CST damage degree seem to remain as low as in the earlier disease stages and an immunological pattern suggestive of balanced pro- and anti-inflammatory activity is observed. MRI-derived and immunological measures might be used as complementary biomarkers of MS severity