The Odonata are considered among the most endangered freshwater faunal taxa. Their DNA‐based monitoring relies on validated reference data sets that are often lacking or do not cover important ...biogeographical centres of diversification. This study presents the results of a DNA barcoding campaign on Odonata, based on the standard 658‐bp 5′ end region of the mitochondrial COI gene, involving the collection of 812 specimens (409 of which barcoded) from peninsular Italy and its main islands (328 localities), belonging to all the 88 species (31 Zygoptera and 57 Anisoptera) known from the country. Additional BOLD and GenBank data from Holarctic samples expanded the data set to 1,294 DNA barcodes. A multi‐approach species delimitation analysis involving two distance (OT and ABGD) and four tree‐based (PTP, MPTP, GMYC and bGMYC) methods was used to explore these data. Of the 88 investigated morphospecies, 75 (85%) unequivocally corresponded to distinct molecular operational units, whereas the remaining ones were classified as ‘warnings’ (i.e. showing a mismatch between morphospecies assignment and DNA‐based species delimitation). These results are in contrast with other DNA barcoding studies on Odonata showing up to 95% of identification success. The species causing warnings were grouped into three categories depending on if they showed low, high or mixed genetic divergence patterns. The analysis of haplotype networks revealed unexpected intraspecific complexity at the Italian, Palearctic and Holarctic scale, possibly indicating the occurrence of cryptic species. Overall, this study provides new insights into the taxonomy of odonates and a valuable basis for future DNA and eDNA‐based monitoring studies.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
•Automated downstream of multi-temporal interferometric data.•PCA applied to Time Series for dimensionality reduction and feature extraction.•Unsupervised clustering for spatial and temporal ...detection of ground displacements.•InSAR data fusion for the retrieval of horizontal and vertical Time Series.
The need for implementing efficient value-adding tools able to optimise Earth Observation data usage, compels the scientific community to find innovative solutions for the downstream of Earth Observation information. In this paper we present an unsupervised and automated approach based on Principal Component Analysis (PCA) and K-means clustering to detect patterns of natural or anthropogenic ground deformation from Interferometric Synthetic Aperture Radar (InSAR) Time Series. For our proof-of-concept, we focus on the Valle d’Aosta region (Northwest Italy) where mass wasting processes frequently occurs, interacting with human activities and infrastructures. The large volumes of Sentinel-1 data produced allows for retrieving horizontal and vertical Time Series from multi-geometry data fusion of Line-of-Sight (LOS) InSAR measurements. The added benefit of combining ascending/descending InSAR data and interpolating displacements in time at different time steps is here explored prior to data dimensionality reduction and feature extraction through PCA. The retrieved principal components serve as a continuous solution for cluster membership indicators in the K-means clustering method, allowing to define spatially and temporally coherent displacement phenomena. The signal of the ground deformation clusters is then deconstructed into the underlying trend and seasonality components to enhance the interpretability of the classified satellite InSAR features. Using InSAR Time series data spanning 2014–2020, the proposed approach detects several slope movements and anthropogenic deformations with both linear and seasonal displacement behaviours. The results demonstrate the potential applicability of our transferable approach to the development of automated ground motion analysis systems.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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•The efficiency of Sentinel-1 based continuous monitoring services was demonstrated.•Anomalies, i.e., changes in the deformation trend, are coupled with several factors.•1788, 598 and ...3665 anomalies for Tuscany, VdA and Veneto had a cause assigned.•The highest percentage of anomalies identified is due to slope instability.•Different distribution of the anomalies is linked to different regional settings.
In Italy, three different operational continuous monitoring experiences based on the exploitation of Multi Temporal Synthetic Aperture Radar data (MTInSAR) Sentinel-1 data are here depicted, and the results obtained in one year have been analysed. Tuscany region (Central Italy) has been the first region to implement such service, followed by Valle d’Aosta and Veneto regions (North-West and North-East Italy, respectively). In detail, the services benefit from regularly updated deformation maps (every 12 days) to promptly detect anomalies of deformation, i.e., trend variations in the time series of displacement. In this work, anomalies detected between September 2019 and September 2020 are thus correlated with several types of factors, either related to the environment, intrinsic of the data or derived from ancillary data. A statistical analysis has been performed on the three regions, and are discretized into five macro-areas, namely: i) spatial and temporal statistics, related to the geographic setting and the temporal distribution of the anomalies; ii) parametric, i.e., related to the interferometric processing; iii) triggering factors; iv) environmental and geological factors; v) urban setting. The results derived from the analysis of this work show the obvious differences between the three regions, highlighting distinct distributions of the anomalies according to the different settings of each study area. Furthermore, results were analyzed, to provide a summary of the main findings obtained, giving a first evaluation of the services and hypothesizing future further improvements and applications.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Aims: TOMM40 single nucleotide polymorphism (SNP) rs2075650 consists of allelic variation c.275-31A > G and it has been linked to Alzheimer disease, apolipoprotein and cholesterol levels and other ...risk factors. However, data on its role in cardiovascular disorders are lacking. The first aim of the study is to evaluate mortality according to TOMM40 genotype in a cohort of selected patients affected by advanced atherosclerosis. Second aim was to investigate the relationship between Xg and AA alleles and the presence of conduction disorders and implantation of defibrillator (ICD) or pacemaker (PM) in our cohort. Materials and Methods: We enrolled 276 patients (mean age 70.16 ± 7.96 years) affected by hemodynamic significant carotid stenosis and/or ischemia of the lower limbs of II or III stadium Fontaine. We divided the population into two groups according to the genotype (Xg and AA carriers). We evaluated several electrocardiographic and echocardiographic parameters, including heart rate, rhythm, presence of right and left bundle branch block (LBBB and RBBB), PR interval, QRS duration and morphology, QTc interval, and left ventricular ejection fraction (LVEF). We clinically followed these patients for 82.53 ± 30.02 months and we evaluated the incidence of cardiovascular events, number of deaths and PM/ICD implantations. Results: We did not find a difference in total mortality between Xg and AA carriers (16.3 % vs. 19.4%; p = 0.62). However, we found a higher mortality for fatal cardiovascular events in Xg carriers (8.2% vs. 4.4%; HR = 4.53, 95% CI 1.179–17.367; p = 0.04) with respect to AA carriers. We noted a higher percentage of LBBB in Xg carriers (10.2% vs. 3.1%, p = 0.027), which was statistically significant. Presence of right bundle branch block (RBBB) was also higher in Xg (10.2% vs. 4.4%, p = 0.10), but without reaching statistically significant difference compared to AA patients. We did not observe significant differences in heart rate, presence of sinus rhythm, number of device implantations, PR and QTc intervals, QRS duration and LVEF between the two groups. At the time of enrolment, we observed a tendency for device implant in Xg carriers at a younger age compared to AA carriers (58.50 ± 0.71 y vs. 72.14 ± 11.11 y, p = 0.10). During the follow-up, we noted no statistical difference for new device implantations in Xg respect to AA carriers (8.2% vs. 3.5%; HR = 2.384, 95% CI 0.718–7.922; p = 0.156). The tendency to implant Xg at a younger age compared to AA patients was confirmed during follow-up, but without reaching a significant difference(69.50 ± 2.89 y vs. 75.63 ± 8.35 y, p = 0.074). Finally, we pointed out that Xg carriers underwent device implantation 7.27 ± 4.43 years before AA (65.83 ± 6.11 years vs. 73.10 ± 10.39 years) and that difference reached a statistically significant difference (p = 0.049) when we considered all patients, from enrollment to follow-up. Conclusions: In our study we observed that TOMM40 Xg patients affected by advanced atherosclerosis have a higher incidence of developing fatal cardiovascular events, higher incidence of LBBB and an earlier age of PM or ICD implantations, as compared to AA carriers. Further studies will be needed to evaluate the genomic contribution of TOMM40 SNPs to cardiovascular deaths and cardiac conduction diseases.
In this cohort study, the general population of an Italian Province was followed for three years after the start of the pandemic, in order to identify the predictors of SARS-CoV-2 infection and ...severe or lethal COVID-19. All the National Healthcare System information on biographical records, vaccinations, SARS-CoV-2 swabs, COVID-19 cases, hospitalizations and co-pay exemptions were extracted from 25 February 2020 to 15 February 2023. Cox proportional hazard analysis was used to compute the relative hazards of infection and severe or lethal COVID-19, adjusting for age, gender, vaccine status, hypertension, diabetes, major cardiovascular diseases (CVD), chronic obstructive pulmonary disease (COPD), kidney disease or cancer. Among the 300,079 residents or domiciled citizens, 41.5% had ≥1 positive swabs during the follow-up (which lasted a mean of 932 days). A total of 3.67% of the infected individuals experienced severe COVID-19 (n = 4574) and 1.76% died (n = 2190). Females, the elderly and subjects with diabetes, CVD, COPD, kidney disease and cancer showed a significantly higher risk of SARS-CoV-2 infection. The likelihood of severe or lethal COVID-19 was >90% lower among the youngest, and all comorbidities were independently associated with a higher risk (ranging from +28% to +214%) of both outcomes. Two years after the start of the immunization campaign, the individuals who received ≥2 doses of COVID-19 vaccines still showed a significantly lower likelihood of severe or lethal disease, with the lowest risk observed among subjects who received at least one booster dose.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
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The rising availability of satellite-based multi-temporal interferometric datasets covering large areas of the Earth surface constitutes a huge asset in the context of operational ...workflows aimed at improving land risk assessment and management. In order to cost-effectively handle huge amount of data, we design a semi-automatic procedure to quickly identify, map and inventory ground and infrastructures displacements by means of spatial clustering performed over very large-scale Differential Synthetic Aperture Radar Interferometry (DInSAR) datasets. The detected deforming areas are then evaluated against the Line of Sight (LOS) velocity vector decomposition and the accessible ancillary layers for a preliminary classification of the triggering factors. We apply our methodology to the mean ascending and descending deformation maps covering the whole Italian territory resulting from 3294 and 2868 Sentinel-1 (S1) acquisitions respectively, spanning from March 2015 to December 2018 and processed through the Parallel Small BAseline Subset (P-SBAS) technique. By setting a displacement rate threshold of ± 1 cm/year, a total number of 14,638 areas resulting from both geometries are found to suffer from instability phenomena, the origin of which are in turn preliminary sorted in 11 classes split between natural causes and man-made activities. With 2 degrees of confidence, we classified landslide and subsidence events as the main causes of deformation within the Italian territory, constituting respectively 31% and 27% of the total unstable areas, followed by volcanic-related processes (22%). Lastly, we provide a complete overview of the deformation phenomena which have recently occurred on the Italian Peninsula starting from national scale statistical analysis and ending up with local scale investigations according to the deformation patterns visible through the vertical and East-West components of motion.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Wide-area ground motion monitoring is nowadays achievable via advanced Differential Interferometry SAR (A-DInSAR) techniques which benefit from the availability of large sets of Copernicus Sentinel-1 ...images. However, it is of primary importance to implement automated solutions aimed at performing integrated analysis of large amounts of interferometric data. To effectively detect high-displacement areas and classify ground motion sources, here we explore the feasibility of a machine learning-based approach. This is achieved by applying the random forest (RF) technique to large-scale deformation maps spanning 2015-2018. Focusing on the northern part of Italy, we train the model to identify landslide, subsidence, and mining-related ground motion with which to construct a balanced training dataset. The presence of noisy signals and other sources of deformation is also tackled within the model construction. The proposed approach relies on the use of explanatory variables extracted from the A-DInSAR datasets and from freely accessible informative layers such as Digital Elevation Model (DEM), land cover maps, and geohazard inventories. In general, the model performance is very promising as we achieved an overall accuracy of 0.97, a true positive rate of 0.94 and an F1-Score of 0.93. The obtained outcomes demonstrate that such transferable and automated approach may constitute an asset for stakeholders in the framework of geohazards risk management.
The redaction of landslide inventory is a fundamental task for risk management and territorial planning activities. The availability of synthetic aperture radar imagery, especially after the launch ...of Sentinel-1 mission, enables to systematically update landslide inventories covering wide areas in a reduced time frame and at different scales of analysis. In this work, SAR data processed from the fully automatic P-SBAS pipeline have been adopted to update the Italian national landslide database. Specifically, a matrix has been introduced by comparing past landslide state of activity obtained with Envisat data (2003–2010) and that computed with Sentinel-1 (2014–2018). The state of activity was defined by obtaining the projected velocity along the slope dip direction. The analysis involved about 56,000 landslides which showed at least one Sentinel-1 measurement point, of which 74% were classified as dormant, having annual average velocity < 7 mm/year (considering a value of two times the standard deviation) and 26% as active (mean velocity > 7 mm/year). Furthermore, a landslide reliability matrix was introduced on the landslide inventory updated with S1 data, using the measurement point (MP) density within each landslide and the standard deviation of the mean V
slope
value of each landslide. In this case, the analysis revealed that more than 80% of landslides has values of reliability from average to very high. Finally, the 2D horizontal and vertical components were computed to characterize magnitude and direction of every type of landslides included in this work, showing that spreadings, deep-seated gravitation slope deformations, and slow flows showed a main horizontal movement, while complex and translational/rotational slides had more heterogeneity in terms of deformation direction. Hence, the work demonstrated that the application of fast and automatically nationwide Sentinel-1 MTInSAR (multi-temporal interferometry SAR) may provide a fundamental aid for landslide inventory update.
Sudden cardiac death (SCD) is a potentially fatal event usually caused by a cardiac arrhythmia, which is often the result of coronary artery disease (CAD). Up to 80% of patients suffering from SCD ...have concomitant CAD. Arrhythmic complications may occur in patients with acute coronary syndrome (ACS) before admission, during revascularization procedures, and in hospital intensive care monitoring. In addition, about 20% of patients who survive cardiac arrest develop a transmural myocardial infarction (MI). Prevention of ACS can be evaluated in selected patients using cardiac computed tomography angiography (CCTA), while diagnosis can be depicted using electrocardiography (ECG), and complications can be evaluated with cardiac magnetic resonance (CMR) and echocardiography. CCTA can evaluate plaque, burden of disease, stenosis, and adverse plaque characteristics, in patients with chest pain. ECG and echocardiography are the first-line tests for ACS and are affordable and useful for diagnosis. CMR can evaluate function and the presence of complications after ACS, such as development of ventricular thrombus and presence of myocardial tissue characterization abnormalities that can be the substrate of ventricular arrhythmias.
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