Search Results (2,359)

The paper presents a GIS plugin, named Bridge Assessment System via MTInSAR (BAS-MTInSAR), aimed at assessing deformations in existing simply supported concrete girder bridges through Multi-Temporal Interferometry Synthetic Aperture Radar (MTInSAR). Existing bridges require continuous maintenance to ensure functionality toward external effects undermining the safety of these structures, such as aging, material degradation, and environmental factors. Although effective and standardized methodologies exist (e.g., structural monitoring, periodic onsite inspections), new emerging technologies could be employed to provide time- and cost-effective information on the current state of structures and to drive prompt interventions to mitigate risk. One example is represented by MTInSAR data, which can provide near-continuous information about structural displacements over time. To easily manage these data, the paper presents BAS-MTInSAR. The tool allows users to insert information of the focused bridge (displacement time series, structural information, temperature data) and, through a user-friendly GUI, observe the occurrence of abnormal deformations. In addition, the tool implements a procedure of multisource data management and defines proper thresholds to assess bridge behavior against current code prescriptions. BAS-MTInSAR is fully described throughout the text and was tested on a real case study, showing the main potentialities of the tool in managing bridge portfolios. Full article

The urgent need for an effective COVID-19 therapy has propelled the exploration of innovative strategies to combat the fast-mutating SARS-CoV-2 virus. This study attempted to develop nanobodies (Nbs) against the SARS-CoV-2 Omicron variants by redirecting the 1.29 neutralizing Nb, a receptor-binding domain (RBD)-specific Nb that can protect against various SARS-CoV-2 variants other than Omicron, to target SARS-CoV-2 Omicron subvariant BA.5, the variant used for the development of the bivalent vaccine. Error-prone libraries of the 1.29 Nb were constructed. Following two rounds of selection using the functional ligand-binding identification by Tat-based recognition of associating proteins (FLI-TRAP) technique, we rapidly identified two Nbs, namely, C11 and K9, that could target the RBD of the Omicron subvariant BA.5, XBB.1.5, and XBB.1.16 subvariants. Molecular docking provided insights into how these Nbs interact with the RBD of the BA.5 and JN.1 variants. The application of directed evolution via utilization of error-prone PCR and the synthetic E. coli applied in the FLI-TRAP selection method may be a powerful tool for facilitating simple, fast and economical selection to redirect existing antibodies and to generate antibody fragments to target proteins susceptible to autonomous mutation, not only for viral infection but also other diseases, such as cancer. Full article

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza, and respiratory syncytial virus (RSV) are significant global health threats. The need for low-cost, easily synthesized oral drugs for rapid deployment during outbreaks is crucial. Broad-spectrum therapeutics, or pan-antivirals, are designed to target multiple viral pathogens simultaneously by focusing on shared molecular features, such as common metal cofactors or conserved residues in viral catalytic domains. This study introduces a new generation of potent sartans, known as bisartans, engineered in our laboratories with negative charges from carboxylate or tetrazolate groups. These anionic tetrazoles interact strongly with cationic arginine residues or metal cations (e.g., Zn²⁺) within viral and host target sites, including the SARS-CoV-2 ACE2 receptor, influenza H1N1 neuraminidases, and the RSV fusion protein. Using virtual ligand docking and molecular dynamics, we investigated how bisartans and their analogs bind to these viral receptors, potentially blocking infection through a pan-antiviral mechanism. Bisartan, ACC519TT, demonstrated stable and high-affinity docking to key catalytic domains of the SARS-CoV-2 NSP3, H1N1 neuraminidase, and RSV fusion protein, outperforming FDA-approved drugs like Paxlovid and oseltamivir. It also showed strong binding to the arginine-rich furin cleavage sites S1/S2 and S2′, suggesting interference with SARS-CoV-2’s spike protein cleavage. The results highlight the potential of tetrazole-based bisartans as promising candidates for developing broad-spectrum antiviral therapies. Full article

In this study, we present a novel face mask engineered for the collection of exhaled breath condensate (EBC) and its application and performance in a clinical study of COVID-19 infection status assessment versus the gold standard polymerase chain reaction (PCR) nasopharyngeal swab testing. EBC was collected within a clinical trial of COVID-19-infected and non-infected patients and analyzed by reverse transcription quantitative (RT-q) PCR, with the results being compared with nasopharyngeal sampling of the same patient. The cycle threshold (Ct) values of the nasopharyngeal samples were generally lower than those of EBC, with viral loads in EBC ranging from 1.2 × 10⁴ to 5 × 10⁸ viral particles mL⁻¹ with 5 min of breathing. From the 60 clinical patients’ samples collected, 30 showed a confirmed SARS-CoV-2 infection. Of these 30 individuals, 22 (73%) had Ct values < 40 (representing the threshold for SARS-CoV-2 infectivity) using both amplification of ORF1a/b and the E-gene. The 30 EBC samples from non-infected participants were all identified as negative, indicating a 100% specificity. These first results encourage the use of the face mask as a noninvasive sampling method for patients with lung-related diseases, especially with a view to equipping the face mask with miniaturized sensing devices, representing a true point-of-care solution in the future. Full article

Ground subsidence in urban areas is mainly due to natural or anthropogenic activities, and it seriously threatens the healthy and sustainable development of the city and the security of individuals’ lives and assets. Shanghai is a megacity of China, and it has a long history of ground subsidence due to the overexploitation of groundwater and urban expansion. Time Series Synthetic Aperture Radar Interferometry (TS-InSAR) is a highly effective and widely used approach for monitoring urban ground deformation. However, it is difficult to obtain long-term (such as over 10 years) deformation results using single-platform SAR satellite in general. To acquire long-term surface deformation monitoring results, it is necessary to integrate data from multi-platform SAR satellites. Furthermore, the deformations are the result of multiple factors that are superimposed, and relevant studies that quantitatively separate the contributions from different driving factors to subsidence are rare. Moreover, the time series cumulative deformation results of massive measurement points also bring difficulties to the deformation interpretation. In this study, we have proposed a long-term surface deformation monitoring and quantitative interpretation method that integrates multi-platform TS-InSAR, PCA, and K-means clustering. SAR images from three SAR datasets, i.e., 19 L-band ALOS-1 PALSAR, 22 C-band ENVISAT ASAR, and 20 C-band Sentinel-1A, were used to retrieve annual deformation rates and time series deformations in Shanghai from 2007 to 2018. The monitoring results indicate that there is serious uneven settlement in Shanghai, with a spatial pattern of stability in the northwest and settlement in the southeast of the study area. Then, we selected Pudong International Airport as the area of interest and quantitatively analyzed the driving factors of land subsidence in this area by using PCA results, combining groundwater exploitation and groundwater level change, precipitation, temperature, and engineering geological and human activities. Finally, the study area was divided into four sub-regions with similar time series deformation patterns using the K-means clustering. This study helps to understand the spatiotemporal evolution of surface deformation and its driving factors in Shanghai, and provides a scientific basis for the formulation and implementation of precise prevention and control strategies for land subsidence disasters, and it can also provide reference for monitoring in other urban areas. Full article

This manuscript explores the development of sustainable biopolymer composites using suberin extraction waste, specifically suberinic acid residues (SAR), as a 10% (w/w) reinforcing additive in polylactide (PLA) and thermoplastic starch–polylactide blends (M30). The materials were subjected to a detailed analysis using thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), and dynamic mechanical analysis (DMA) to assess their thermal, mechanical, and structural properties. The study confirmed the amorphous nature of the biopolymers and highlighted how SAR significantly influences their degradation behavior and thermal stability. M30 exhibited a multi-step degradation process with an initial decomposition temperature (T5%) of 207.2 °C, while PLA showed a higher thermal resistance with decomposition starting at 263.1 °C. Mechanical performance was assessed through storage modulus (E′) measurements, showing reductions with increasing temperature for both materials. The research provides insights into the potential application of SAR-enriched biopolymers in sustainable material development, aligning with circular economy principles. These findings not only suggest that SAR incorporation could enhance the mechanical and thermal properties of biopolymers, but also confirm the effectiveness of the research in reassurance of the audience. Full article

Objectives: SARS-CoV-2 caused the COVID-19 pandemic, which overwhelmed global healthcare systems. Over 776 million COVID-19 cases and more than 7 million deaths were reported by WHO in September 2024. COVID-19 vaccination is crucial for preventing infection and controlling the pandemic. Here, we describe the design and development of a next-generation multi-epitope vaccine for SARS-CoV-2, consisting of T cell epitopes. Methods: Immunoinformatic methods were used to derive models for the selection of MHC binders specific for the mouse strain used in this study among a set of human SARS-CoV-2 T cell epitopes identified in convalescent patients with COVID-19. The immunogenicity of the vaccine prototype was tested on humanized-ACE2 transgenic B6.Cg-Tg(K18-ACE2)2Prlmn/J mice by in vitro, in vivo, and ex vivo immunoassays. Results: Eleven binders (two from the Envelope (E) protein; two from the Membrane (M) protein; three from the Spike (S) protein; and four from the Nucleocapsid (N) protein) were synthesized and included in a multi-epitope vaccine prototype. The animals were immunized with a mix of predicted MHC-I, MHC-II, or MHC-I/MHC-II peptide epitopes in Complete Freund’s Adjuvant, and boosted with peptides in Incomplete Freund’s Adjuvant. Immunization with SARS-CoV-2 epitopes remodeled the lymphocyte profile. A weak humoral response and the significant production of IL-4 and IFN-γ from T cells were found after the vaccination of the animals. Conclusions: The multi-epitope vaccine prototype presented in this study demonstrates immunogenicity in mice and shows potential for human vaccine construction. Full article

Adenoviruses are important human pathogens that are widespread and mainly associated with respiratory and gastrointestinal infections. In a previous study on human adenovirus (HAdV) seroprevalence, we observed reduced binding antibody levels against a range of HAdV types in sera collected from students in 2021 compared to sera collected before the SARS-CoV-2 pandemic. In this follow-up study, we wanted to verify this observation in a cohort of regular blood donors for whom serial samples were available. Therefore, HAdV-specific binding antibody levels were analyzed in sera collected over a 5-year period from 2018 to 2022 in a cohort of 60 regular donors to the blood bank of the University Hospital in Greifswald, Germany. Using ELISA-based assays, we quantified the binding antibody responses against 39 HAdV types. On the cohort level, we found largely stable antibody levels over the analyzed time period, with the highest antibody responses against HAdV-C1, -D25, -D26, -E4, -D10, -D27, -C5, -D75, -C2, and -C6. Only minor but significant reductions in comparison to the first serum samples from 2018 were detected for antibody levels in 2021 and 2022 against the low-prevalent types HAdV-A31, -D8, -D20, -D37, -D65, and -D69. On the other hand, we detected fluctuations in antibody levels on the individual level, with strong increases in antibody levels indicative of novel antigen contact. Interestingly, we frequently found simultaneous changes in antibody responses against multiple HAdV types, resulting in strong correlations of antibody responses against distinct clusters of HAdVs suggesting extensive cross-reactivity of HAdV-specific antibodies. To our knowledge, this is the first study of antibodies against a broad range of HAdV types in serum samples collected from a cohort of individuals over a prolonged period, and our data provide important insight into the long-term stability of HAdV-specific antibody levels. In this cohort of regular blood donors, we did not observe any major impact of the SARS-CoV-2 pandemic on HAdV immunity. Correlations of changes in antibody levels against different types indicate cross-reactivity of HAdV-specific antibodies that are important to consider for HAdV vector development. Our data also reveal possible candidates for future development of HAdV-based vectors. Full article

This study investigates the effect of geological field measurement (offset), global positioning system (GPS), and interferometric synthetic aperture radar (InSAR) data on the estimation of the co-seismic earthquake displacements of the 2002 Denali earthquake. The analysis is conducted using stochastic source modeling. Uncertainties associated with each dataset limit their effectiveness in source model selection and raise questions about the adequate number of datasets and their type for reliable source estimation. To address these questions, stochastic source models with heterogeneous earthquake slip distributions are synthesized using the von Kármán wavenumber spectrum and statistical scaling relationships. The surface displacements of the generated stochastic sources are obtained using the Okada method. The surface displacements are compared with the available datasets (i.e., offset, GPS, and InSAR) individually and in an integrated form. The results indicate that the performance of stochastic source generation can be significantly improved in the case of using GPS data and in the integrated case. Overall, based on the case study of the 2002 Denali earthquake, the combined use of all available datasets increases the robustness of the stochastic source modeling method in characterizing surface displacement. However, GPS data contribute more than InSAR and offset data in producing reliable source models. Full article

The structure–tissue exposure/selectivity relationship (STR) aids in lead optimization to improve drug candidate selection and balance clinical dose, efficacy, and toxicity. In this work, butyrocholinesterase (BuChE)-targeted cannabidiol (CBD) carbamates were used to study the STR in correlation with observed efficacy/toxicity. CBD carbamates with similar structures and same molecular target showed similar/different pharmacokinetics. L2 and L4 had almost same plasma exposure, which was not correlated with their exposure in the brain, while tissue exposure/selectivity was correlated with efficacy/safety. Structural modifications of CBD carbamates not only changed drug plasma exposure, but also altered drug tissue exposure/selectivity. The secondary amine of carbamate can be metabolized into CBD, while the tertiary amine is more stable. Absorption, distribution, metabolism, excretion, and toxicity (ADMET) parameters can be used to predict STR. Therefore, STR can alter drug tissue exposure/selectivity in normal tissues, impacting efficacy/toxicity. The drug optimization process should balance the structure–activity relationship (SAR) and STR of drug candidates for improving clinical trials. Full article

Seasonal vertical ground movement (SVGM), which refers to the periodic vertical displacement of the Earth’s surface, has significant implications for infrastructure stability, agricultural productivity, and environmental sustainability. Understanding how SVGM correlates with climatic conditions—such as temperatures and drought—is essential in managing risks posed by land subsidence or uplift, particularly in regions prone to extreme weather events and climate variability. The correlation of periodic SVGM with climatic data from Earth observation was investigated in this work. The European Ground Motion Service (EGMS) vertical ground movement measurements, provided from 2018 to 2022, were compared with temperature and precipitation data from MODIS and CHIRP datasets, respectively. Measurement points (MP) from the EGMS over Italy provided a value for ground vertical movement approximately every 6 days. The precipitation and temperature datasets were processed to provide drought code (DC) maps calculated ad hoc for this study at a 1 km spatial resolution and daily temporal resolution. Seasonal patterns were analyzed to assess correlations with Spearman’s rank correlation coefficient (ρ) between this measure and the DCs from the Copernicus Emergency Management Service (DCCEMS), from MODIS + CHIRP (DC1km) and from the temperature. The results over the considered area (Italy) showed that 0.46% of all MPs (32,826 MPs out of 7,193,676 MPs) had a ρ greater than 0.7; 12,142 of these had a positive correlation, and 20,684 had a negative correlation. DC1km was the climatic factor that provided the highest number of correlated MPs, roughly giving +59% more correlated MPs than DCCEMS and +300% than the temperature data. If a ρ greater than 0.8 was considered, the number of MPs dropped by a factor of 10: from 12,142 to 1275 for positive correlations and from 20,684 to 2594 for negative correlations between the DC1km values and SVGM measurements. Correlations that lagged in time resulted in most of the correlated MPs being within a window of ±6 days (a single satellite overpass time). Because the DC and temperature are strongly co-linear, further analysis to assess which was superior in explaining the seasonality of the MPs was carried out, resulting in DC1km significantly explaining more variance in the SVGM than the temperature for the inversely correlated points rather than the directly correlated points. The spatial distribution of the correlated MPs showed that they were unevenly distributed in clusters across the Italian territory. This work will lead to further investigation both at a local scale and at a pan-European scale. An interactive WebGIS application that is open to the public is available for data consultation. This article is a revised and expanded version of a paper entitled “Detection and correlation analysis of seasonal vertical ground movement measured from SAR and drought condition” which was accepted and presented at the ISPRS Mid-Term Symposium, Belem, Brasil, 8–12 November 2024. Data are shared in a public repository for the replication of the method. Full article

Background: Humans cannot avoid plastic exposure due to its ubiquitous presence in the natural environment. The waste generated is poorly biodegradable and exists in the form of MPs, which can enter the human body primarily through the digestive tract, respiratory tract, or damaged skin and accumulate in various tissues by crossing biological membrane barriers. There is an increasing amount of research on the health effects of MPs. Most literature reports focus on the impact of plastics on the respiratory, digestive, reproductive, hormonal, nervous, and immune systems, as well as the metabolic effects of MPs accumulation leading to epidemics of obesity, diabetes, hypertension, and non-alcoholic fatty liver disease. MPs, as xenobiotics, undergo ADMET processes in the body, i.e., absorption, distribution, metabolism, and excretion, which are not fully understood. Of particular concern are the carcinogenic chemicals added to plastics during manufacturing or adsorbed from the environment, such as chlorinated paraffins, phthalates, phenols, and bisphenols, which can be released when absorbed by the body. The continuous increase in NMP exposure has accelerated during the SARS-CoV-2 pandemic when there was a need to use single-use plastic products in daily life. Therefore, there is an urgent need to diagnose problems related to the health effects of MP exposure and detection. Methods: We collected eligible publications mainly from PubMed published between 2017 and 2024. Results: In this review, we summarize the current knowledge on potential sources and routes of exposure, translocation pathways, identification methods, and carcinogenic potential confirmed by in vitro and in vivo studies. Additionally, we discuss the limitations of studies such as contamination during sample preparation and instrumental limitations constraints affecting imaging quality and MPs detection sensitivity. Conclusions: The assessment of MP content in samples should be performed according to the appropriate procedure and analytical technique to ensure Quality and Control (QA/QC). It was confirmed that MPs can be absorbed and accumulated in distant tissues, leading to an inflammatory response and initiation of signaling pathways responsible for malignant transformation. Full article

Although a fourth dose of SARS-CoV-2 vaccine was shown to be effective, the immunogenicity of a fifth dose in immunocompetent individuals had not been well described. This was a prospective observational cohort study of previously vaccinated healthcare workers at a single tertiary hospital in Israel. Individuals were administered up to three booster doses of the BNT162b2 mRNA vaccine (i.e., up to five overall doses), during the period between July 2021 and January 2023. Immunogenicity was assessed using the SARS-CoV-2 IgG (sCOVG) semi-quantitative assay, performed at several time points. The cohort consisted of 162 individuals (median age 69 years, 62% female). Of these, 104 (64%) received four doses and 58 (36%) received five doses. Anti-SARS-CoV-2 antibody levels increased in all cases, regardless of the baseline levels. The fold-change increase in the mean sCOVG index was 29.2 (SD 2.6) after the third vaccine, 3.8 (SD 2.4) after the fourth vaccine, and 3.6 (SD 3.0) after the fifth vaccine. A waning effect over time was seen in 78% and 43% of participants for the third and fourth doses, respectively. Adverse events following the fifth dose were limited and mild. Similar to previous booster vaccines, a fifth dose of BNT162b2 is immunogenic and safe in healthy individuals, although the clinical implications remain unclear. Full article

Convolutional neural network (CNN)-based synthetic aperture radar (SAR) ship detection models operating directly on satellites can reduce transmission latency and improve real-time surveillance capabilities. However, limited satellite platform resources present a significant challenge. Post-training quantization (PTQ) provides an efficient method for pre-training neural networks to effectively reduce memory and computational resources without retraining. Despite this, PTQ faces the challenge of maintaining model accuracy, especially at low-bit quantization (e.g., 4-bit or 2-bit). To address this challenge, we propose a hierarchical mixed-precision post-training quantization (HMPTQ) method for SAR ship detection neural networks to reduce quantization error. This method encompasses a layerwise precision configuration based on reconstruction error and an intra-layer mixed-precision quantization strategy. Specifically, our approach initially utilizes the activation reconstruction error of each layer to gauge the sensitivity necessary for bit allocation, considering the interdependencies among layers, which effectively reduces the complexity of computational sensitivity and achieves more precise quantization allocation. Subsequently, to minimize the quantization error of the layers, an intra-layer mixed-precision quantization strategy based on probability density assigns a greater number of quantization bits to regions where the probability density is low for higher values. Our evaluation on the SSDD, HRSID, and LS-SSDD-v1.0 SAR Ship datasets, using different detection CNN models, shows that the YOLOV9c model with mixed-precision quantization at 4-bit and 2-bit for weights and activations achieves only a 0.28% accuracy loss on the SSDD dataset, while reducing the model size by approximately 80%. Compared to state-of-the-art methods, our approach maintains competitive accuracy, confirming the superior performance of the HMPTQ method over existing quantization techniques. Full article

Deep-Seated Gravitational Slope Deformations (DSGSDs) are common in many geological environments, and due to their common limited displacement rate, they can remain unrecognized for a long time. Among the most significant events in Sicily is the Mt. San Calogero DSGSD. To contribute to a better understanding of its characteristics, including the geologic setting promoting its development, ongoing kinematics, and mechanism, a specific analysis was completed. In this paper, the results of this analysis, based on a three-folded strategy, are provided and interpreted in the context of DSGSD predisposing conditions and controlling factors. Especially, field observations associated to visual interpretation of aerial imagery were used for the identification and mapping of main geological features and landforms, high-resolution X-Band DInSAR data enabled researchers to fully characterize the deformational behavior of the slope, while a reduced complexity slope stability analysis allowed them to reconstruct the deep geometry of the DSGSD. Results from the analysis indicate that the DSGSD of Mt. San Calogero is composed of three blocks corresponding to fault-bounded tectonic elements and characterized by a specific kinematics and sensitivity to external forcing (i.e., rainfall), multiple landslides are associated to the DSGSD in the area and the deep geometry of the DSGSD is concave upward and resemble the characteristics of a rotational slide. The interpretation of the results suggests that the formation and the deformation of the Mt. San Calogero DSGSD are linked with the local and regional fault systems related to the Sicilian orogen, while shallow landslides are triggered, in clayey terrains, mostly by rainfalls. In addition, the integrated approach reveals that active tectonics and rainfalls in the San Calogero massive relief are the main driving forces of its different deformation behavior. Full article